OCS Study

MMS 2001-082

Proceedings:

Twentieth Annual Gulf of Mexico

Information Transfer Meeting

December 2000

U.S. Department of the Interior

Minerals Management Service

Gulf of Mexico OCS Region
U.S. Department of the Interior

Minerals Management Service

Gulf of Mexico OCS Region

OCS Study

MMS 2001-082

Proceedings:

Twentieth Annual Gulf of Mexico

Information Transfer Meeting

December 2000

Editors

Melanie McKay

Copy Editor

Judith Nides

Production Editor

Debra Vigil

Editor

Prepared under MMS Contract

1435-00-01-CA-31060

by

University of New Orleans

Office of Conference Services

New Orleans, Louisiana 70814

Published by

New Orleans

October 2001
iii

DISCLAIMER

This report was prepared under contract between the Minerals Management Service (MMS) and the

University of New Orleans, Office of Conference Services. This report has been technically

reviewed by the MMS and approved for publication. Approval does not signify that contents

necessarily reflect the views and policies of the Service, nor does mention of trade names or

commercial products constitute endorsement or recommendation for use. It is, however, exempt

from review and compliance with MMS editorial standards.

REPORT AVAILABILITY

Extra copies of this report may be obtained from the Public Information Office (Mail Stop 5034)

at the following address:

U.S. Department of the Interior

Minerals Management Service

Gulf of Mexico OCS Region

Public Information Office (MS 5034)

1201 Elmwood Park Boulevard

New Orleans, Louisiana 70123-2394

Telephone Numbers: (504) 736-2519

1-800-200-GULF

CITATION

This study should be cited as:

McKay, M., J. Nides, and D. Vigil, eds. 2001. Proceedings: Twentieth annual Gulf of Mexico

information transfer meeting, December 2000. U.S. Dept. of the Interior, Minerals Management

Service, Gulf of Mexico OCS Region, New Orleans, La. OCS Study MMS 2001-082. 464 pp.
v

TABLE OF CONTENTS

Page

LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii

ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix

SESSION 1A: MISSISSIPPI-ALABAMA MARINE ECOSYSTEM

MONITORING PROGRAM

Co-Chairs: Dr. Gary Brewer and Dr. Robert Rogers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

SESSION 1B: AIR QUALITY

Chair: Dr. Chester Huang; Co-Chair: Ms. Terry Scholten . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

SESSION 1C: GAS HYDRATES IN THE GULF OF MEXICO

Chair: Dr. Mary Boatman; Co-Chair: Mr. Jesse Hunt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

SESSION 2A: DEEPWATER SESSION

Co-Chairs: Mr. G. Ed Richardson and Mr. James Regg . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

SESSION 2B: AIR QUALITY (continued)

Chair: Dr. Chester Huang; Co-Chair: Ms. Terry Scholten . . . . . . . . . . . . . . . . . . . . . . . . . . 135

SESSION 2C: ARCHAEOLOGY

Chair: Dr. Richard Anuskiewicz; Co-Chair: Mr. David Bull . . . . . . . . . . . . . . . . . . . . . . . 159

SESSION 1D: NORTHERN GULF OF MEXICO CONTINENTAL SLOPE

HABITATS AND BENTHIC ECOLOGY STUDY, “DGoMB”

Co-Chairs: Dr. Robert Avent and Mr. Greg Boland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

SESSION 1E: IMPROVEMENTS IN MODELING OF OIL SPILLS

Chair: Ms. Gail Rainey; Co-Chair: Dr. Walter Johnson . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

SESSION 1F: BEYOND OIL AND GAS: THE HUMAN EXPERIENCE—

SOCIAL SCIENCE IN THE GULF OF MEXICO REGION

Co-Chairs: Dr. Claudia Rogers and Dr. Harry Luton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
vi

TABLE OF CONTENTS

(continued)

Page

SESSION 2D: STABILITY AND CHANGE IN GULF OF MEXICO

CHEMOSYNTHETIC COMMUNITIES: “CHEMO II”

Co-Chairs: Dr. Robert Avent and Dr. Mary Boatman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279

SESSION 2E: NEW INITIATIVES IN MODELING OF OIL SPILLS

Chair: Ms. Gail Rainey; Co-Chair: Dr. Walter Johnson . . . . . . . . . . . . . . . . . . . . . . . . . . . 299

SESSION 2F: SOCIOECONOMIC MODELING

Chairs: Ms. Stephanie Gambino and Ms. Vicki Zatarain . . . . . . . . . . . . . . . . . . . . . . . . . . 339

SESSION 1G: ENVIRONMENTAL SCIENCES

Chair: Mr. Greg Boland; Co-Chair: Ms. Debra Vigil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379

SESSION 1H: MMS SPONSORED OIL SPILL RESEARCH

Chair: Ms. Darice Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409

INDEX TO AUTHORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443

ATTENDEES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449
vii

LIST OF FIGURES

No. Page

1A.1. Locations of final monitoring sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1A.2. Composite side-scan image of Sites 1 and 3 with locations of current meter

moorings noted. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

1A.3. For Froude number (U/Nh) a) F = 0.2 and b) F = 4. Derived center-plane streamline

(top) and surface shear-stress patterns (bottom). From Hunt and Snyder (1980). . . . . . . 12

1A.4. Side-scan sonar mosaic of the Garden Banks survey site. Dark areas represent

seafloor with high acoustic backscatter whereas light areas represent low-backscatter

seafloor. Most of the dark areas are seep-affected zones along faults. Several

subcircular features are mud volcanoes. Linear downslope-trending features are

sediment flows. Vertical lines are the ship track locations. . . . . . . . . . . . . . . . . . . . . . . . 18

1A.5. Side-scan sonar mosaic of the seafloor in the shallow Green Canyon survey

area. Conventions as in Figure 1A.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

1A.6. Side-scan sonar mosaic of the seafloor in the deep Green Canyon survey

area. Conventions as in Figure 1A.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1A.7. Location of monitoring sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

1A.8. Rank-frequency relationship for all fish taxa observed in video transects across

study Sites 1 through 9 for Cruises 1C, M2, M3, and M4. . . . . . . . . . . . . . . . . . . . . . . . 28

1A.9. Total fish taxa observed in video transects across study Sites 1 through 9 for

Cruises 1C, M2, M3, and M4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

1A.10. Sample scores from correspondence analysis of a taxa-by-samples matrix based on

video transects plotted on Axes 1 and 2. The scores are labeled 1 through 9 to

represent the monitoring sites. Sites 1, 5, and 7 are high relief; Sites 2. 4, and 8 are

medium relief; and sites 3, 6, and 9 are low relief. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

1A.11. Food Web model of the Pinnacles Reef Fish Community. Lower trophic groups

follow Christensen (1995). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

1A.12. Zooplankton abundance estimated at near surface (2m), midwater, and near-reef

water depths during March 2000. Samples were collected using stationary, 0.5m

diameter, 335μ mesh opening-closing plankton nets. Values given are number of

zooplankters collected per 10-minute sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
viii

LIST OF FIGURES

(continued)

No. Page

1A.13. Zooplankton abundance estimated at near surface (2m), midwater, and near-reef

water depths during May/June 2000. Samples were collected using stationary, 0.5 m

diameter, 335μ mesh opening-closing plankton nets. Values given are number of

zooplankters collected per 10 minute sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

1A.14. Planktonic prey availability to deep reef zooplanktivores. . . . . . . . . . . . . . . . . . . . . . . . 35

1B.1. Meteorological Stations in the MMS Gulf of Mexico Study domain. . . . . . . . . . . . . . . . 47

1B.2. Project schedule, 1998 – 2003. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

1C.1. The Gulf of Mexico continental slope off the state of Louisiana as portrayed by

computer enhanced multibeam bathymetry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

1C.2. This figure summarizes the spectrum of seafloor responses associated with rapid

fluid and gas venting (mud-prone) to slow seepage (mineral-prone). . . . . . . . . . . . . . . . 69

1C.3. A high resolution subbottom profile across an active mud volcano in Green Canyon

143. Rapid venting of fluidized sediment, other fluids (including crude oil) and

gases have created this cone-like buildup and its downslope mudflow deposits. . . . . . . 71

1C.4. A north-south high resolution seismic profile (15 in3

 water gun) across the mound in

Green Canyon 185 (Bush Hill) which contains gas hydrate deposits at the surface and

in the shallow subsurface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

1C.5. An outcropping of gas hydrate at apex of the Green Canyon 185 mound. This

outcrop was orange in color covered with gray mud on which orange Beggiatoa

mats occurred. The field of view is about 2 m across. . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

1C.6. A high resolution seismic profile across a part of the dome in Green Canyon 140.

Note the irregular surface made up of authigenic carbonate mounds that appear to

have developed in a slow seepage environment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

1C.7. Sketch map showing distribution of known gas hydrate sites, seeps with

chemosynthetic communities, and oil and gas fields in the Gulf of Mexico. Note

study areas (GC 185, GC 234, MC 853, AT 425) and closely associated oil fields

(Jolliet, Mars, Ursa). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
ix

LIST OF FIGURES

(continued)

No. Page

1C.8. Sketch showing main elements of a typical gas hydrate mound (1-3 m across)

formed around thermogenic gas vents in a chemosynthetic community. (From

Sassen et al. 1999b.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

1C.9. Sketch showing modeled subsurface distribution of gas hydrate at the GC 185 site.

Note that much gas hydrate is thought to be deeply buried and stable in sediments

where thermogenic hydrocarbon flux from the Jolliet Field faults is continuous for

meaningful spans of time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

2A.1. Alternatives in FPSO EIS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

2A.2. The FPSO EIS Decision Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

2A.3. What is expected to happen after the EIS process and the comparative risk

assessment is completed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

2A.4. An example of the result format expected from the CRA study. . . . . . . . . . . . . . . . . . . 115

2A.5. Cost verses concept for an offshore-based approach compared to a

shipping-based approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

2A.6. A 40m by 20m L&B. It has 4x2 MW horizontal thrusters and 4x1 MW vertical

thrusters. The system is powered by a high-voltage cable/umbilical. . . . . . . . . . . . . . . 122

2A.7. A shuttle tanker, one example of a GOM crude oil shuttle vessel alternative. . . . . . . . 122

2A.8. A sea-going articulated barge, another example of a GOM crude oil shuttle

vessel alternative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

2A.9. A depiction of a coselle CNG carrier from Cran and Tenning Technology, Inc.,

of Calgary, Canada. The carrier is a 60,000 DWT ship with 108 coselles capable

of transporting 300 mmscf of natural gas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

2A.10. A depiction of natural gas storage in coselles on a CNG carrier. . . . . . . . . . . . . . . . . . 124

2A.11. Components of DeepStar’s Phase V cooperative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

2B.1. A verification of Eq. (4a) for unstable conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

2B.2. A verification of Eq. (4b) for stable conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
x

LIST OF FIGURES

(continued)

No. Page

2B.3. A comparison of the shear velocity u* based on Eqs. (3), (6), and (7) using buoy

#42040 during 15 and 16 November 1996 in the northeast Gulf of Mexico (Hsu

et al. 2000). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

2C.1. The 1977 High-Probability Shipwreck “Yes/No” Line. . . . . . . . . . . . . . . . . . . . . . . . . 163

2C.2. The 1989 High-Probability Shipwreck Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

2C.3. The Josephine (Photo courtesy of the Mariner’s Museum, Newport News, VA.) . . . . 169

2C.4. Sidescan image of the Josephine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

2C.5. Side-scan image of the SS Robert E. Lee. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

1D.1. Part 1 of a dynamic time-dependent model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

1D.2. Part 2 of a dynamic time-dependent model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187

1D.3. Part 3 of a dynamic time-dependent model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

1D.4. Positions of 193 stations throughout the southern Gulf of Mexico. . . . . . . . . . . . . . . . 191

1D.5. Macrofaunal biomass seasonal (mixed vs. stratified year 1997: ANOVA F 3,15;

p= 0.02) variability in the transition zone). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193

1D.6. Yearly macrofaunal biomass by depth zones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194

1D.7. Dive sites and dive numbers for the 14 dives completed during 16-31 October 2000,

northern Gulf of Mexico. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

1E.1. The surface current output grid of the PDOM applied to the Gulf of Mexico. A

current map was generated every 3 hours over the 9 years, 1986-1994. This grid is

also the OSRA model input grid for both ocean currents and winds. . . . . . . . . . . . . . . 214

1E.2. The boundaries of a few of the offshore natural resources analyzed by the OSRA

model in oil-spill contact simulations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215

1F.1. Two distances with the same point of origin that people might cover on a daily

basis. The first would be a short distance from A to B to meet daily needs, and

the second a long distance from A to C to gain employment. . . . . . . . . . . . . . . . . . . . . 271
xi

LIST OF FIGURES

(continued)

No. Page

1F.2. Using the latitude and longitude coordinates of the geographic center of the CDP

(provided by the U.S. Census Department) as the center of the road network, the

aggregation included the census block groups whose centers fell within the tenminute travel time network of the CDP center, creating the first ten-minute place. . . . 273

1F.3. Of the original 324 CDPs, 296 were identified as incorporated, ten-minute places.. . . 274

2D.1. Map of the northern Gulf of Mexico showing locations of program study sites

(triangles) and mega-sites for geophysical survey (stippled boxes). . . . . . . . . . . . . . . . 297

2E.1. The model for the formation of methane hydrates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327

2E.2 An example of the equilibrium solution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

2E.3. Model and field data on the Exxon Valdez oil spill. . . . . . . . . . . . . . . . . . . . . . . . . . . . 334

2E.4. Sample worst-case scenario map from chemical spill. . . . . . . . . . . . . . . . . . . . . . . . . . 336

2F.1. MMS Gulf of Mexico coastal areas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347

2F.2. Sample view of Microsoft Access model for Gulf of Mexico. . . . . . . . . . . . . . . . . . . . 356

2F.3. Actual and predicted number of platforms installed. . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

2F.4. Actual and predicted number of platforms removed. . . . . . . . . . . . . . . . . . . . . . . . . . . 366

2F.5. Actual and predicted number of operating platforms. . . . . . . . . . . . . . . . . . . . . . . . . . . 367

2F.6. Forecasted number of operating platforms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 370

1G.1 Location map of the East and West Flower Garden Banks in relation to the

continental shelf and other topographic features of the northwestern Gulf of

Mexico, (from Gittings et al. 1992). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382

1G.2. Biotic zonation and topography of East Flower Garden Bank. The dark area depicts

the high diversity coral reef zone (from Rezak et al. 1985). . . . . . . . . . . . . . . . . . . . . . 383

1G.3. Biotic zonation and topography of the West Flower Garden Bank. The darkest area

depicts the high-diversity coral reef zone (from Rezak et al. 1983). . . . . . . . . . . . . . . . 384
xii

LIST OF FIGURES

(continued)

No. Page

1G.4. Deepwater production systems in the Gulf of Mexico. . . . . . . . . . . . . . . . . . . . . . . . . . 403

1G.5. Spatial distribution of surface longline sets made in the Gulf of Mexico during 1998

(Source: National Marine Fisheries Service longline logbook data 1999). . . . . . . . . . . 404

1H.1. Plants in tank at different elevations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 420

1H.2. Plants exposed to in-situ burning of diesel/crude oil. . . . . . . . . . . . . . . . . . . . . . . . . . . 421

1H.3a. Soil evaluation + 10 cm 400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 422

1H.3b. Soil evaluation + 10 cm 1,400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 422

1H.4a. Soil evaluation 0 cm 400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423

1H.4b. Soil evaluation 0 cm 1,400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423

1H.5a. Soil evaluation -2 cm 400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424

1H.5b. Soil evaluation -2 cm 1,400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424

1H.6a. Soil evaluation -10 cm 400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425

1H.6b. Soil evaluation -10 cm 1,400 s burn exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425

1H.7. Effect of oil-to-dispersant ratio on neat and dilute dispersants. . . . . . . . . . . . . . . . . . . . 440

1H.8. Dispersing efficiency neat vs. dilute: Corexit 9527. . . . . . . . . . . . . . . . . . . . . . . . . . . . 441

1H.9. Dispersing efficiency near vs. dilute: Corexit 9500. . . . . . . . . . . . . . . . . . . . . . . . . . . . 442
xiii

LIST OF TABLES

No. Page

1A.1. Results of statistical analyses for currents observed at 16 mab at Mooring 1A. . . . . . . . . 9

1A.2. Summary of results of Principal Axis Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1A.3. Percent occurrence of Froude Number (U/Nh) at 16 mab at each of the four sites

with currents meters based on the Joint Frequency Distribution Tables (e.g. Table

1A.1.). The upper limit of the speed bin was used for U; a value of 0.01 rad/s was

assumed for N; and the measured mound height was used for h. . . . . . . . . . . . . . . . . . . 14

1A.4. Chemosynthetic community site indicators. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

1B.1. Total Gulf of Mexico emissions by source. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

1C.1. Green Canyon 185 molecular and isotopic compositions of gas hydrate samples. . . . . . 74

2A.1. FPSO EIS process timeline. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

2A.2. Locations of public hearing on the Draft EIS held in September 2000. . . . . . . . . . . . . 111

2A.3. Phases and status of the CRA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

2A.4. Risk measures of the CRA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

2A.5. Event types and outcomes considered in the CRA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

2A.6. DeepStar technical committees. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

2A.7. DeepStar phase expenditures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

2A.8. Maximum noise limits for new facilities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132

2B.1. Summary of Equipment Inventory Data (Number of Components) by Skid Type . . . . 142

2B.2. Speciation weight fractions for total hydrocarbon (THC) emissions by stream type . . 143

2B.3. EPA Average Emission Factors for Total Hydrocarbon Emissions from Oil and Gas

Production Operations (lb/component-day)a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143

2C.1. Discovered vessels in deep water. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
xiv

LIST OF TABLES

(continued)

No. Page

2C.2. Reported shipwrecks in deep water. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

1D.1. Infauna sampling effort in the SW Gulf of Mexico. Zonation according to

Pequegnat (1983). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192

1D.2. Summary of dives, sites visited, and scientific divers during cruise. . . . . . . . . . . . . . . 198

1F.1. Means and standard deviations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243

1F.2. Correlations among dependent measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243

1F.3. Unstandardized OLS regression coefficients predicting measures of employment

volatility. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

1F.4. Limitations of county business patterns data on mining (SIC = 13). . . . . . . . . . . . . . . . 246

1F.5. Sample of data collected for Port Fourchon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262

2D.1. Calculated approximate H2S fluxes for sampling events in 1997 and 1998. A *

indicates an apparent small influx of sulfide due to storage problems. Fluxes at

these sites can generally be expected to be small. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293

2E.1. Rise velocities and times from 890 m depth for various size oil droplets. Droplets

are assumed to have the Foinaven crude specific gravity of 0.902 in seawater with

a specific gravity of 1.026. Rise velocities are computed using the Stokes formula

with a dynamic viscosity of 1.8 x10-6 (m2/s). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329

2F.1. Offshore expenditure categories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345

2F.2. Expenditure profiles for development drilling by water depth. . . . . . . . . . . . . . . . . . . . 346

2F.3. Estimated economic impacts for exploratory drilling, LA-2 Region. . . . . . . . . . . . . . . 349

2F.4. Water depth of fixed offshore structures operating on the Gulf of Mexico OCS

as of 31 December 1997. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360

2F.5. OLS estimates of the platform installation model (t-statistics in parenthesis). . . . . . . . 363

2F.6. Estimated values of model variables and parameters used to forecast the number

of platforms installed from 1998 – 2023. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 368
xv

LIST OF TABLES

(continued)

No. Page

2F.7. Forecasts of the number of platforms to be installed, removed, and operated on

the Gulf of Mexico OCS, 1999 - 2023 – Reference Case. . . . . . . . . . . . . . . . . . . . . . . . 369

2F.8. A results panel following a recent run for the Draft Proposed Program. . . . . . . . . . . . . 375

2F.9. The oil submodel at a single point in time, 2010. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376

2F.10. Sample summary sheet, part 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377

2F.11. Sample summary sheet, part 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378

1H.1. GOMR crude oils that have undergone spill-related testing (1 of 2 pages). . . . . . . . . . 428

1H.2 GOMR spill scenarios. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431

1H.3. Influence of dilution on effectiveness of dispersant on ANS crude oil. . . . . . . . . . . . . 439

1H.4. Target DORs as determined in pre-mixed tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441
xvii

ACKNOWLEDGMENTS

The Minerals Management Service thanks all ITM participants. Recognition goes to the speakers

whose timely individual and panel presentations stimulated discussions and exchange of

information. Authors are listed by name with their articles and again in an index at the back of this

publication.

We are grateful to the chairs and co-chairs for the many hours spent in organizing and chairing the

sessions and for spending time gathering presentation summaries. They are listed by name in the

table of contents as well as at the beginning of each session.

The University of New Orleans, Office of Conference Services, was the contractor responsible for

the meeting. The dedicated staff and subcontractors play an integral role in the execution of this

meeting and the completion of the proceedings. Their tireless efforts are greatly appreciated.

The staff of the Airport Hilton were personable and accommodating to our countless requests.
xix

INTRODUCTION

Ms. Debra L. Vigil

Environmental Sciences Section

Minerals Management Service

The primary purposes of the ITM are (1) to provide a forum for interchange on topics of current

interest relative to environmental assessments in support of offshore oil and gas activities in the Gulf

of Mexico OCS Region; (2) to present the accomplishments of the MMS Environmental Studies

Program for the Gulf of Mexico and of other research programs or study projects; and (3) to foster

an exchange of information of regional interest among scientists, staff members, and decisionmakers from MMS, other Federal or State governmental agencies, regionally important industries,

and academia and to encourage opportunities for these attendees to meet and nurture professional

acquaintances and peer contacts.

The ITM agenda is planned and coordinated by the MMS staff of the Gulf of Mexico OCS Regional

Office around the three themes mentioned above—issues of current interest to the Region or MMS

oil and gas program; accomplishments of the agency; and regional information exchange.

Presentations are by invitation through personal contacts between session chairpersons and speakers

who have demonstrated knowledge or expertise on the subject.

The ITM is considered a meeting of regional importance and is one of the Region’s primary

outreach efforts. Attendance in recent years has been 250-300 people, including scientists, managers,

and laypersons from government, academia, industry, environmental groups, and the general public.

Support funding is provided through the MMS Environmental Studies Program. Logistical support

for the ITM is provided by a contractor and subcontractors selected through the Federal procurement

process. A proceedings volume is prepared for each ITM based on summaries of brief technical

papers submitted by each speaker and on each session chair’s added comments.
1

 SESSION 1A

MISSISSIPPI-ALABAMA MARINE ECOSYSTEM MONITORING PROGRAM

Co-Chairs: Dr. Gary Brewer, USGA Biological Resources Division

Dr. Robert Rogers, Minerals Management Service

Date: December 5, 2000

Presentation Author/Affiliation

Study Overview Dr. Neal W. Phillips

Continental Shelf Associates, Inc.

Jupiter, Florida

Northeastern Gulf of Mexico Coastal and

Marine Ecosystem Program: Ecosystem

Monitoring–Physical Oceanography and

Hydrography in the Mississippi/Alabama

Pinnacle Trend Area During May 1997

Through April 1999

Mr. F. J. Kelly

Conrad Blucher Institute for Surveying

and Science

Texas A&M University-Corpus Christi

Dr. Les C. Bender

Dr. Norman L. Guinasso, Jr.

Geochemical and Environmental

Research Group

Texas A&M University

Geophysical Detection and Characterization

of Chemosynthetic Organism Sites

Dr. William W. Sager

Dr. Ian R. MacDonald

Texas A&M University

Northeast Gulf of Mexico Pinnacles Study

Hard-Bottom Communities

Mr. Dane D. Hardin

Applied Marine Sciences, Inc.

Mr. Keith D. Spring

Mr. Stephen T. Viada

Dr. Alan D. Hart

Mr. Bruce D. Graham

Continental Shelf Associates

Mr. Michael B. Peccini

Texas A&M University

Fish Assemblages Mr. David B. Snyder

Continental Shelf Associates, Inc.

(continued on next page)
2

Presentation Author/Affiliation

Trophic Subsidies in the Twilight Zone:

Zooplankton Availability and Food Web

Structure of Deep Reef Fishes along the

Mississippi-Alabama Outer Continental Shelf

Mr. Douglas C. Weaver

Dr. Kenneth J. Sulak

USGS Biological Resources Division
3

STUDY OVERVIEW

Dr. Neal W. Phillips

Continental Shelf Associates, Inc.

INTRODUCTION

This presentation summarizes the synthesis phase of the Northeastern Gulf of Mexico Coastal and

Marine Ecosystems Program: Ecosystem Monitoring, Mississippi/Alabama Shelf. The project was

sponsored by the U.S. Geological Survey, Biological Resources Division. The project team includes

Continental Shelf Associates, Inc. (CSA), the Geochemical and Environmental Research Group of

Texas A&M University (GERG), Applied Marine Sciences, Inc., and independent consultants.

PROGRAM GOALS

The overall goal of the program was to characterize and monitor biological communities and

environmental conditions at carbonate mounds along the Mississippi-Alabama (Outer Continental

Shelf) OCS. Specific objectives were as follows:

• To describe and monitor seasonal and interannual changes in community structure and

zonation and relate these to changes in environmental conditions (i.e., dissolved oxygen,

turbidity, temperature, salinity, etc.); and

• To characterize the geological, chemical, and physical environment of the mounds as an aid

in understanding their origin, evolution, present-day dynamics, and long-term fate.

STUDY AREA

The study area was located in the pinnacle trend area along the OCS off Mississippi and Alabama

(Figure 1A.1). This area has been the subject of two previous MMS-sponsored studies: the

Mississippi-Alabama Marine Ecosystems Study and the Mississippi-Alabama Pinnacle Trend

Habitat Mapping Study. Based on previous studies, five megasites were selected for detailed

geophysical reconnaissance. Within these megasites, nine sites were ultimately selected for

monitoring. The sites were stratified into three relief categories (high, medium, and low) and three

location categories (western, central, and eastern). Water depths ranged from about 60 to 120 m.

SAMPLING SCHEDULE

The program consisted of four phases, each lasting approximately 12 months:

• Phase 1 included two reconnaissance cruises (Cruise 1A, November 1996; and Cruise 1B,

March 1997) followed by final site selection (April 1997) and the initiation of monitoring

and companion studies on Cruise 1C (May 1997).
4

Figure 1A.1. Locations of final monitoring sites.

• Phase 2 included two monitoring cruises, M2 (October 1997) and M3 (April-May and

August 1998). In addition, mooring service cruises were conducted in July 1997, January

1998, and July 1998.

• Phase 3 concluded the field sampling program with two additional mooring service cruises

(October 1998 and January-February 1999) and one final monitoring cruise (M4, April and

July-August 1999).

• Phase 4 did not include any new field work. During this phase, investigators analyzed and

synthesized data from the entire program. Preliminary results have been discussed in three

previous Annual Interim Reports.

Essentially, after reconnaissance and site selection, there were two full field years of monitoring at

the nine sites.

PROGRAM COMPONENTS

Four components formed the core of the program. These are geology, physical oceanography/

hydrography, hard-bottom communities, and fish communities.
5

Geology

The geology component included three subtasks: geologic characterization, geochemistry, and

sediment dynamics. Principal investigators for the geologic characterization were William W. Sager

and William Schroeder. This task attempted to derive as detailed a physical picture of the mounds

as possible with conventional geophysical and geologic data. Target areas were mapped using highresolution side-scan sonar images, high-frequency subbottom profiles, grab samples, and video

observations. Results are summarized in Dr. Sager’s presentation.

The principal investigator for geochemistry was M.C. Kennicutt II. This subtask included a

combination of hydrocarbon, metal, grain size, total organic carbon, and total inorganic carbon

measurements in sediments and sediment trap materials. Grab samples were collected on all four

monitoring cruises and analyzed for total organic carbon and total inorganic carbon. Samples from

the first monitoring cruise also analyzed for hydrocarbons and selected metals (barium, cadmium,

chromium, iron, lead, mercury, and zinc). Results essentially showed little or no elevation of

hydrocarbon or metal concentrations in the study area.

The sediment dynamics subtask, conducted by Ian D. Walsh, included monitoring of nepheloid layer

dynamics. Sediment traps were deployed at three heights above bottom (2.5 m, 7 m, 15 m) at four

monitoring sites during eight trapping periods. Transmissometer profiles were conducted on all

cruises, with data calibrated against measured particle concentrations. Optical backscatter sensors

were included on current meter moorings, but did not produce useful data. Both the water column

particulate measurements and the sediment trap data indicated high spatial and temporal variability

in resuspension and nepheloid layer dynamics among sites. A benthic nepheloid layer was present

at all sites during all casts, though with a wide range in concentrations; it was most persistent at

Sites 5 and 9. Two hurricanes that passed near the study area in September 1998 caused extreme

responses in sedimentation rates at all sites.

Physical Oceanography and Hydrography

Physical oceanographic and hydrographic data were collected to help understand the geological and

biological processes of the carbonate mounds. Data from moored instrument arrays, hydrographic

profiles conducted on all cruises, and collateral sources provided a basis for characterizing regional

and local current dynamics and understanding the dynamics of environmental parameters such as

temperature, salinity, dissolved oxygen, and turbidity. Instrument moorings were deployed at four

sites (1, 4, 5, and 9) throughout the program, with two additional moorings at Site 1 during the first

year, and relocated to Site 5 in the second year. Current meters were located at 4 m and 16 m above

bottom. The instruments also recorded temperature, conductivity, and dissolved oxygen. Principal

investigators for this component were F.J. Kelly and Norman L. Guinasso, Jr., with Les C. Bender

also contributing to the synthesis report. Results are summarized in Dr. Kelly’s presentation.

Hard-Bottom Communities

Hard-bottom community monitoring consisted mainly of video and photographic sampling at each

site. These included both random photography and video transects, as well as repetitive photography
6

of fixed stations. The nine sites were visited by a remotely operated vehicle (ROV) on each of four

monitoring cruises. In general, 100 random photographs were taken per site on each cruise. Random

photographs were used to estimate the abundances of sessile and motile epibiota. Video observations

(recorded along the ROV’s path between random photograph points) were used to quantify larger

and more widely dispersed organisms and to broadly characterize substrates and species

composition. Fixed video/photoquadrats (five per site) were used to study temporal changes related

to growth, recruitment, competition, and mortality. Voucher specimens were also collected.

Principal investigators for the hard-bottom community component were Dane D. Hardin, Keith D.

Spring, Stephen T. Viada, Alan D. Hart, Bruce D. Graham, and Michael B. Peccini. Results are

summarized in Mr. Hardin’s presentation.

Fish Communities

There was no dedicated fish sampling during this program. Instead, random photographs and video

recorded during the hard-bottom community study were analyzed to evaluate fish distribution. In

addition to standard descriptive analysis of the fish communities associated with the mounds, habitat

use by 17 common fish species was assessed at three spatial scales ranging from tens of kilometers

to a few centimeters. The principal investigator for fish communities was David B. Snyder. Results

are summarized in Mr. Snyder’s presentation.

Microhabitat Studies

This component focused on octocoral orientation in relation to currents at five sites and octocoral

and antipatharian distribution in relation to microhabitat variables (e.g., small and medium scale

roughness, sediment veneer) at four sites. The microhabitat studies also included development of

a geographic information system (GIS) incorporating much of the data collected during this program

(e.g., bathymetry, side-scan sonar mosaics, grab sampling and photo locations, substrate types).

Principal investigators were Ian R. MacDonald and Michael B. Peccini.

Epibiont Recruitment

In this component, settlement plates were deployed on moored arrays to document the process of

larval settlement, growth, and community development. The study focused on hypotheses about

variations with time and space, height above bottom, and orientation of settling surface, as well as

effects of disturbance and small-scale turbulence. Biomoorings with settling plates were deployed

at four sites throughout the program. A spatial study compared settlement among sites. A temporal

study at a single site assessed the effect of duration of exposure. Principal investigators for the

recruitment study were Paul A. Montagna and Tara J. Holmberg.

Dr. Neal W. Phillips is a senior scientist with CSA, with 18 years of experience in environmental

data analysis, interpretation, and impact assessment. He received a Ph.D. in ecology from the

University of Georgia and an M.S. in marine studies from the University of Delaware. His

background is in benthic ecology.
7

NORTHEASTERN GULF OF MEXICO COASTAL AND MARINE ECOSYSTEM

PROGRAM: ECOSYSTEM MONITORING — PHYSICAL OCEANOGRAPHY AND

HYDROGRAPHY IN THE MISSISSIPPI/ALABAMA PINNACLE TREND AREA

DURING MAY 1997 THROUGH APRIL 1999

Mr. F. J. Kelly

Conrad Blucher Institute for Surveying and Science

Texas A&M University – Corpus Christi

Dr. Les C. Bender

Dr. Norman L. Guinasso, Jr.

Geochemical and Environmental Research Group

Texas A&M University

INTRODUCTION

This component of the program monitored oceanographic conditions (i.e., currents, temperature,

salinity, turbidity, dissolved oxygen, etc.) at topographic features along the Mississippi-Alabama

Outer Continental Shelf (OCS) during May 1997 through April 1998. Specific objectives of this

component are (1) to characterize the regional and local currents in the study area; (2) to determine

the dynamics of important oceanographic parameters; and, (3) in concert with the other project

components, to define the relationship of the currents and oceanographic conditions to the geological

and biological process. The hard-bottom features of interest are flow obstacles that extend up to

13 m above the 70-120 m bottom depth. The topic of this paper is the variability induced in the nearbottom flow as it passes over and around the mounds, which is an important subject for some of the

other project components. 

METHODS

One mooring was placed at each of four of the nine study sites. (See Sager et al. 2001 (this volume))

for site maps. These four mooring locations were permanent and maintained throughout the two-year

field program to provide long-term time-series data. The fifth and sixth moorings were re-locatable.

During the first year, they were placed at Site 1 to form, in conjunction with the permanent mooring,

a triangular pattern (Figure 1A.2). They were moved to Site 5 in May 1998. The moorings’ sensors

recorded current velocity, temperature, conductivity and other parameters at 4 meters above bottom

(mab) and at 16 mab. A detailed description of the mooring design is given in the Proceedings of

the 18th Annual Gulf of Mexico ITM (Kelly et al. 2000). CTD casts were taken during the

monitoring and servicing cruises to provide details about the vertical structure. 

For this discussion, tables of the joint frequency distribution (JFD) of speed and direction (tabular

version of the current rose), as well as basic statistics and principal axis analysis are used to provide

a compact method of summarizing the large volume of observations. The results for Site 1 at 16 mab

are shown in Table 1A.1, as an example. These analysis techniques also provide a method of

detecting possible topographic effects on the near-bottom flow. The direction octants of the JFD are
8

Figure 1A.2. Composite side-scan image of Sites 1 and 3 with locations of current meter

moorings noted.
9

Table 1A.1. Results of statistical analyses for currents observed at 16 mab at Mooring 1A.

a) Table of the Joint Frequency Distribution (JFD) of speed and direction in percent occurrence.

RANGE (CM / S) N NE E SE S SW W NW ROW TOT

<=5 2.56 3.38 3.42 2.12 2.11 3.18 4.46 3.09 24.32

>5 <=10 3.14 4.96 5.12 2.69 3.14 4.57 5.52 3.74 32.87

>10 <=15 1.51 2.81 3.69 1.40 1.85 2.29 2.59 1.96 18.10

>15 <=20 0.52 2.31 3.48 0.70 0.80 1.80 1.34 0.66 11.59

>20 <=25 0.20 1.81 3.07 0.36 0.15 1.86 0.88 0.22 8.55

>25 <=30 0.04 0.48 0.98 0.04 0.04 0.93 0.39 0.09 3.01

>30 <=35 0.00 0.16 0.35 0.00 0.01 0.34 0.11 0.01 0.99

>35 <=40 0.00 0.03 0.05 0.00 0.01 0.14 0.01 0.00 0.25

>40 0.00 0.00 0.01 0.00 0.00 0.31 0.01 0.00 0.33

COL TOTALS 7.97 15.95 20.17 7.32 8.11 15.41 15.30 9.77 100.00

b) Principal Axis Analysis

Mean Current Vector: 0.9 cm/s at 91.8° True

Principal Axis Orientation = 66.2°

Major Axis = 11.5 cm/s Minor Axis = 6.5 cm/s

c) Basic statistics

Basic Stats Min. Max. Mean Std. No. Obs.

SPEED: 1.1 96.7 10.6 7.8 29351

U (East): -69.1 40.0 0.9 10.8 29351

V (North): -73.5 29.9 -0.0 7.5 29351

T (Deg. C): 15.4 27.4 20.6 1.6 29351

Salinity: 35.0 37.0 36.2 0.3 29351
10

abbreviated to E for east, NE for northeast, etc. The oceanographic convention for direction is used,

i.e., towards which the current flows. Results from the CTD casts are used to compute the stability

(buoyancy frequency) of the water column.

RESULTS

Flow at 16 mab

The current meters at 16 mab measure the mesoscale flow just above the pinnacles. At this height,

there is substantial similarity across the entire pinnacle study region in the observed flow

characteristics. Site 1, a high-relief site, and Site 9, a low-relief site, span the east-west extent of the

study region and provide the maximum contrast in mound height. At both sites (e.g., Table 1A.1),

the most frequent direction octant is E (20% at Site 1 and 25 % at Site 9). The NE, S and SW octants

are the next most frequent at about 15% each. This reflects the generally NE/SW nature of the flow

at the 16 mab level, which is above the bottom Ekman layer. The most frequent speed range is 5-10

cm/s, (33% at Site 1 and 28% at Site 9), and the overall scalar mean speeds are similar at 11-12

cm/s. Strong currents, i.e., greater than 40 cm/s, are most frequently directed SW or W, particularly

during Hurricane Georges (92 cm/s at Site 1 and 98 cm/s at Site 2). The results at Site 5, located

about midway across the study region, are very similar to those at the each end. The depths at all

three sites are similar (78-92 m). At Site 4, located farther out on the shelf in deeper water (112 m),

the distribution and statistics of speed at 16 mab are similar to the other three sites, with 5-10 cm/s

being most frequent (33%). Because of the greater depth at this site, the maximum speed, recorded

during Hurricane Georges, is only 66 cm/s. The distribution of direction at Site 4 has a slight

southwesterly bias compared to the other three sites, as the most frequent direction octant is SW

(26%). It is followed closely by E (24%), which is the most frequent octant at the other sites. The

SW bias is a result of speeds greater than 20 cm/s, which are most frequently in the SW octant. 

Flow at 4 mab

Compared with the flow at 16 mab, the near-bottom flow is more site-specific. Bottom friction and

the local topography influence the flow, particularly at Site 1. A comparison is again made between

Sites 1 and 9, the high-relief eastern site versus the low-relief western site. The most frequent speed

range at Site 9 is a virtual tie between the 5-10 cm/s range and the 10-15 cm/s range, at 26% each.

At Site 1, on the other hand, the most frequent range is 0-5 cm/s (44%). The overall mean speed is

also lower at Site 1, i.e., 6.3 cm/s compared to 10.3 cm/s at Site 9. Observations of direction also

differ significantly between the two sites. The most frequent direction octant is SW at Site 9 but S

at Site 1, and the angles of the principal axes are 60.7/ (NE/SW) versus 20.3/ (N/S), respectively.

At Sites 4 and 5, the flow statistics at 4 mab are similar to those at Site 9. 

Vertical Comparison of Principal Axes

A difference between the two levels is clearly revealed by the principal axis analysis (Table 1A.2).

At 16 mab, there is a slight clockwise (CW) rotation, going from east to west, in the orientation of

the major axes, i.e., 66.2/ at Site 1 to 75.5/ at Site 9. This trend is probably related to the large-scale

trend of the bathymetry, rather than the mesoscale-scale topography near each site. At 4 mab at Sites
11

Table 1A.2. Summary of results of Principal Axis Analysis.

Mooring I.D. and

height above bottom

of current meter

Major Axis Angle

°( CW from N)

and dir. octant

Major Axis

Amplitude

(cm/s)

Minor Axis

Amplitude

(cm/s)

Rotation (°)

4mab relative

to 16mab

Sense of

rotation

16mab

C1A 66.2 (NE) 11.5 6.5 - -

C4A 70.4 (E) 11.8 4.5 - -

C5A 74.4 (E) 10.5 5.4 - -

C9A 75.5 (E) 13.2 6.3 - -

4mab

C1A 20.3 (N) 5.8 4.7 45.9 CCW

C4A 50.6 (NE) 9.9 5.9 19.8 CCW

C5A 55.8 (NE) 9.0 5.4 18.6 CCW

C9A 60.7 (NE) 9.7 7.2 14.8 CCW

4, 5, and 9 the axes are rotated 15-20/ counterclockwise (CCW) from those at 16 mab, i.e., to the

left, looking down. This is what one would expect because of friction in the bottom Ekman layer.

At Site 1, the vertical difference in angles is 45.9/, considerably larger that at the other three sites,

which may indicate some local influence by the topography of Site 1.

Mooring 1A is located about one “mound” diameter northeast of Site 1. Because this site is the

tallest and the topographic surveys found a steep slope on the east and northeast sides of the mound,

it is the site most likely to create measurable flow disturbances at 4 mab. Compared to the other

three sites, the 4-mab currents at Site 1 have a lower mean speed, greater percentage of near stagnant

conditions, and a much larger CCW rotation of the principal axis. We conclude that the extent of

the flow disturbance created by the topography of Site 1 extends at least the distance to Mooring 1A.

Flow Structure over Generalized Mounds

The observations from the deployed current meters provide a good, quantitative description of the

mesoscale flow conditions between the bottom and 16 m above the bottom in the study region. The

results also indicate some possible flow perturbation at Site 1 and possibly at Site 5 at distance of

one “mound” diameter. A detailed observational study of the flow on the sides and tops of the sites

was beyond the scope of the study. However, a qualitative picture of what such flow might look like

can be inferred from the results of laboratory studies of three-dimensional, stratified, non-rotating

flow over small obstacles. The non-rotational assumption applies because the features of interest in

this study have small horizontal extent (L ~ 200 m). Even for very weak flow (U ~ 10 cm/s), the

Rossby number (U/fL) at the mounds is greater than one, and a typical time scale is less than one

hour. Therefore, the effect of the earth’s rotation, i.e., the Coriolis acceleration on the flow, can be

ignored. (Thus, studies and models of flow around larger scale obstacles such as seamounts are not

applicable to mounds or pinnacles of this study.)
12

Baines (1995) reviews the current state of the theoretical and laboratory models of non-rotating,

stratified flow over small obstacles. Much of Baines’ discussion of three-dimensional flow is based

on the experiments of Hunt and Snyder (1980). The most important non-dimensional parameter in

this field of study is the internal Froude number, F = U/Nh, where h is the height above bottom of

the obstacle, U a characteristic upstream speed at the level of h, and N is the buoyancy frequency

(also called the Brunt-Väisälä frequency) in radians per second. The value of F indicates, based on

experiments and models, whether streamlines from upstream impinge on the hill, go around it, or

go over the top. It also indicates, as a function of stratification, where to expect the locations of

internal hydraulic jumps and their size, and the region of separated or recirculating flow in the lee

of the hill. 

Hunt and Snyder (1980) conducted a set of laboratory experiments to observe the flow structure over

a bell-shaped hill at values of F from 0.1 to 1.7 and at F = 4. Two examples of their results are

reproduced in Figure 1A.3a (for F = 0.2) and Figure 1A.3b (for F = 4). To relate their observed

laboratory flow patterns to specific sites of this study, one must make assumptions about the

frequency of occurrence of various ranges of the value of N. Based on smoothed profiles of N

computed from all the CTD casts, a reasonable assumption would seem to be that N $ 0.01 much

of the time. Lower values obtain when a very homogeneous bottom water mass advects through a

site or when very strong turbulent vertical mixing occurs, such as during a hurricane.

Because of the ranges of the values of h and U used to compute the buoyancy frequency, the 16 mab

values of the Froude number cover at least two orders of magnitude. The values of F near 1.0 are

of particular interest because near this critical value the flow changes from a hill-hugging lee flow

a) F = 0.2 b) F = 4

Figure 1A.3. For Froude number (U/Nh) a) F = 0.2 and b) F = 4. Derived center-plane streamline

(top) and surface shear-stress patterns (bottom). From Hunt and Snyder (1980).
13

to a separated lee flow. For a 15-m hill and N = 0.025 rad/s (strong stratification), the Froude

number is subcritical (less than 1.0) for speeds up to 37.5 cm/s. At N = 0.001 rad/s (very weak

stratification), the flow is subcritical only for the weakest currents, i.e., for speeds less than 1.5 cm/s.

At Site 1, assuming N $ 0.01 rad/s most of the time and h = 13 m, the frequency occurrence of

values of F can be estimated from the JFD tables (e.g., Table 1A.1). The flow will be subcritical

(F < 1.0) for speeds up to 13 cm/s, which occurs almost 75% of the time. In this case, the flow

pattern over the site probably looks something like Figure 1A.3a. As F ÷ 1.0, the flow has more

energy to move in the vertical direction; the region where the flow goes over the top of the hill

broadens; a plume (dye) emanating from an upstream point near the base would spread thinly to

cover a greater portion of the hill; and a strong hydraulic jump develops downstream of the lee

separation point. Downstream, a symmetric pair of vertically oriented vortices causes an upstream

flow on the centerline. However, they become smaller and move closer to the base of the hill as

F ÷ 1.0. 

Near 13 cm/s (F ~ 1.0), the flow begins separating from the top of the lee side of the hill. At the

maximum observed speed of 96.7 cm/s (F = 7.4), the flow in Figure 1A.3b is probably a reasonable

depiction, especially because turbulent mixing would decrease the value of N below the assumed

value of 0.01, making F even larger. Now the flow separates on or before the top of the hill, and a

large recirculating region develops on the leeward slope. The pair of vortices disappears and a

horseshoe pattern develops.

Over the much lower relief feature at Site 9, where the height is only a few meters, the Froude

number is higher to begin with. Assuming N $ 0.01 rad/s and h = 3 m, the flow will be subcritical

only at speeds less than 3 cm/s. More than about 80% of the time, the flow will be supercritical, and

Figure 1A.3b would be appropriate flow model. The maximum observed speed of 91.7 cm/s yields

a Froude number of 30.6, but the turbulent mixing would probably create near neutral flow (F = 4).

SUMMARY

The current meters at 16 mab measure the mesoscale flow just above the pinnacles, and it is similar

across the entire study region (Table 1A.4). There is measurable flow disturbance at 4 mab at Site

1. Compared to the other three sites, the 4-mab currents at Site 1A (northeast side of the mound)

have:

A) a lower mean speed,

B) a greater percentage of near stagnant conditions, and

C) a much larger CCW rotation of the principal axis.

Laboratory studies of 3-D, stratified, non-rotating flow over small obstacles may give a qualitative

picture of flow over the study mounds, when scaled by the Froude Number. At Site 1 the flow is

probably subcritical (F < 1.0) up to 13 cm/s, which occurs ~ 75% of the time.
14

Table 1A.3. Percent occurrence of Froude Number (U/Nh) at 16 mab at each of the four sites

with currents meters based on the Joint Frequency Distribution Tables (e.g. Table

1A.1.). The upper limit of the speed bin was used for U; a value of 0.01 rad/s was

assumed for N; and the measured mound height was used for h.

 Speed Bin Upper Limit

(5 cm/s bins) ÷ 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0

Site 1A F 0.4 0.8 1.2 1.5 1.9 2.3 2.7 3.1

% Occurrence 24.3 32.9 18.1 11.6 8.6 3.0 1.0 0.3

Site 4A F 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

% Occurrence 19.9 35.8 19.5 13.7 9.1 1.7 0.3 0.1

Site 5A F 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

% Occurrence 26.6 33.4 19.5 11.9 6.0 1.9 0.4 0.1

Site 9A F 1.7 3.3 5.0 6.7 8.3 10.0 11.7 13.3

% Occurrence 23.4 27.9 16.7 12.7 10.9 5.9 1.8 0.3

REFERENCES

Baines, P.G. 1995. Topographic Effects in Stratified Flows. New York: Cambridge University Press.

Hunt, J.C.R., and W.H. Snyder. 1980. Experiments on stably and neutrally stratified flow over a

model three-dimensional hill. J. Fluid Mech. 96, 671-704.

Kelly, F.J., N.L. Guinasso, Jr. and L.L. Lee III. 2000. Northeastern Gulf of Mexico coastal and

marine ecosystem program: Ecosystem monitoring—physical oceanography and hydrography

in the Mississippi/Alabama pinnacle trend area during May 1997 through April 1998 and during

September 1998. In Proceedings: Eighteenth Annual Gulf of Mexico Information Transfer

Meeting, December 1998. U.S. Dept. of the Interior, Minerals Mgmt. Service, Gulf of Mexico

OCS Region, New Orleans, La. OCS Study MMS 2000-030. pp 331-340.

Sager et al. This session

Mr. F.J. Kelly is an Associate Research Scientist and the Director of Operations at the Conrad

Blucher Institute for Surveying and Science at Texas A&M University – Corpus Christi. Mr. Kelly

received his B.A. in physics from the University of California, Berkeley, and M.S. in oceanography

from Texas A&M University. He has been investigating the physical oceanography of the Gulf of

Mexico and its continental shelves for more than twenty-five years. He was the Principal

Investigator for the Texas Automated Buoy System (TABS) from its inception through 1999. He
15

has served as Principal Investigator for the physical oceanography component of numerous projects,

including the Mississippi-Alabama Marine Ecosystem Study (MAMES) conducted for the MMS

in 1987-1989. 

Dr. Leslie C. Bender III is an Assistant Research Scientist with the Ocean Sciences section at the

Geochemical and Environmental Research Group at Texas A&M University. Dr. Bender has a B.S.

and M.S. in chemical engineering and a Ph.D. in oceanography. Prior to earning his Ph.D., he spent

nearly five years in the U.S. Navy’s Naval Nuclear Propulsion Program as a member of the

engineering staff. Prior to joining GERG in August 2000, Dr. Bender was the senior research

scientist for Powerware Solutions, Inc for 36 months and was a research scientist with the LATEX

program before joining Powerware. His current interests are in data analysis, circulation modeling,

wind-wave generation, and wave-current interaction. Current projects include support of the Texas

Automated Buoy System.

Dr. Norman Guinasso, Jr. is Deputy Director for Ocean Sciences at the Geochemical and

Environmental Research Group, an element of the College of Geosciences at Texas A&M

University. He received his B.A. in physics in 1966 from San Jose State College and the Ph.D. in

oceanography from Texas A&M in 1984. He serves as Program Manager at Texas A&M for the

Texas Automated Buoy System and is a Principal Investigator on several MMS-sponsored programs

concerned with the oceanography of the Gulf of Mexico.
16

GEOPHYSICAL DETECTION AND CHARACTERIZATION

OF CHEMOSYNTHETIC ORGANISM SITES

Dr. William W. Sager

Dr. Ian R. MacDonald

Texas A&M University

OVERVIEW AND RATIONALE

Owing to their small size and the deep ocean depths that they inhabit, chemosynthetic organisms

cannot be detected directly by remote sensing methods from the sea surface. This poses a problem

for offshore industries and management entities who must determine whether a given site has been

colonized by these organisms. Furthermore, much of our knowledge of Gulf of Mexico (GOM)

chemosynthetic organisms comes from a few intensely-studied sites, raising the question of whether

these sites are representative and whether these organisms are abundant or rare.

Although chemosynthetic organisms themselves are difficult to detect from a distance, they inhabit

hydrocarbon seeps, which can be imaged by acoustic techniques. This occurs because seeps alter

the physical properties of the seafloor and near surface sediments, thus changing the acoustic

reflection character (e.g., Roberts et al. 1990; Sager et al. 1999). In this study, our goal was to

compare and contrast geophysical acoustic methods of detecting and characterizing hydrocarbon

seep sites inhabited by chemosynthetic organisms. In general, this is a broad task, far beyond the

limited scope of time and resources available to this study, so our approach was to survey the

literature, talk with industry geophysicists, and focus on the geophysical signatures of the area

surrounding several chemosynthetic organism sites that have been the object of study for a decade

or more. Because of this focus, we ran the risk of provincialism, that the small number of sites

studied is not entirely representative of all chemosynthetic organism sites. Furthermore, because of

the small number of sites, we could not make statistically significant tests of hypotheses concerning

relations to particular geophysical signatures. Nevertheless, the results of this study are consistent

with what is known about seeps and chemosynthetic organisms. Our overarching conclusion is that

there is no one method of detecting chemosynthetic organism sites that is always accurate.

Ultimately, confirmation depends on actually seeing the organisms by submersible, deep-camera

platform, or recovery of recently live specimens in trawl or core. Defining areas of the seafloor that

have been affected by seepage is more straightforward and can limit the area of seafloor that may

be considered inhabited by chemosynthetic organisms to a fraction of the deep slope.

DATA AND METHODS

Although three-dimensional multichannel seismic (3D MCS) data are the geophysical data most

commonly used to image the seafloor and subsurface by the energy industry, such data are expensive

and therefore not readily available to us for study. In contrast, side-scan sonar can make an acoustic

image of the seafloor rapidly and at low cost; consequently, we used a long-range side-scan sonar

to image the seafloor in three areas of known seeps on the Louisiana continental slope. Side-scan

sonar responds to the physical properties of the seafloor, making a high-resolution acoustic image
17

akin to an aerial photograph (e.g., Johnson and Helferty 1990). The three areas that were surveyed

totaled about 2400 km2 and included a 12 x 13 km site centered on an active mud volcano at the

border of Garden Banks leaseblocks 424 and 425, a 21 x 41 km rectangle on the upper slope in the

Green Canyon leaseblock area, and a 30 x 41 km rectangle on the middle slope, also in the Green

Canyon leaseblock area. The upper slope study site includes water depths of 300 to 1050 m. It

contains several chemosynthetic organism sites that have been routinely studied (Bush Hill, Brine

Pool NR-1, GC234). The deeper site contains depths ranging from 1,000 to 2,250 m; owing to its

depth, relatively little is known about its specific geology or biology.

To aid interpretation, we collected several types of ground-truth data and compared the side-scan

sonar images to other geophysical data. During the program, we collected 33 piston and gravity

cores, mainly from the shallow Green Canyon site. The cores were targeted at anomalous features

in the side-scan images that appeared to be seep-related. Stratigraphy and physical properties of the

cores were examined for evidence of seepage or chemosynthetic organisms and for an understanding

the response of the side-scan sonar. In addition, 3.5 kflz echo-sounder profiles were collected at the

sea surface along all sonar tracks, and near-bottom visual observations and chirp sonar (2-12 kHz

frequency) were collected using the submarine NR-1 at 17 sonar target features in the shallow Green

Canyon survey area. These data were combined with prior submersible dive information from

several sites (Bush Hill, Bush Lite, Green Canyon 139-140, Green Canyon 272, Brine Pool NR-1,

and Green Canyon 234) to better understand how the geology of seeps is imaged by the side-scan

sonar. The sonar images were also compared with maps of seafloor acoustic character constructed

from prior 3.5 kHz echo-sounder surveys (Behrens 1988) and with industry 3D MCS data from six

leaseblocks.

RESULTS & DISCUSSION

 Side-scan sonar images display variations in the amount of acoustic energy scattered back from the

seafloor to the sonar (“backscatter”). In general, the muddy seafloor of the Louisiana slope gives low

backscatter but is punctuated by areas of high backscatter. In the shallow survey areas, the high

backscatter areas correspond mainly to spots where the hydrocarbon seepage has changed the

surface and near surface physical properties of the sediments. In the Garden Banks survey area

Figure 1A.4), a number of linear features are seen. Correlation to 3.5 kflz echo-sounder profiles

shows them to be the surface expressions of faults caused by salt movement in the sedimentary

cover. In places, the faults, are visible by either strong backscatter off a fault scarp facing the sonar

or shadows caused by a scarp facing away. More often, the faults are visible as curvilinear highbackscatter features, evidently where seepage has occurred and modified the sediments around the

fault. Large areas of irregular high backscatter are seen along the faults and cores from these areas

typically display some sort of seep-related anomaly: oil, gas, gas expansion cracks and voids,

carbonate nodules, crusts, or carbonate mudstone gravels, chemosynthetic bivalve shells, and layers

that are anomalously dense or overconsolidated. Because evidence of gas is widespread, we believe

that the strong backscatter areas are primarily caused by gas, but potentially in association with other

introduced materials or sedimentary changes. Several subcircular and elliptical high-backscatter

areas, several hundreds of meters in diameter, correspond to mud mounds likely formed by the

expulsion of formation fluids containing mud (i.e., “mud volcanoes”). One circular high-backscatter

feature appears to be a crater (as judged by its bathymetric profile) with a floor filled with gas
18

Figure 1A.4. Side-scan sonar mosaic of the Garden Banks survey site. Dark areas represent

seafloor with high acoustic backscatter whereas light areas represent low-backscatter

seafloor. Most of the dark areas are seep-affected zones along faults. Several

subcircular features are mud volcanoes. Linear downslope-trending features are

sediment flows. Vertical lines are the ship track locations.

charged sediments. Several linear high-backscatter features that trend downslope appear to be

sediment flows as judged by their shape.

In the Shallow Green Canyon survey area Figure 1A.5), similar features are seen, i.e., fault traces,

curvilinear high-backscatter features, irregular high-backscatter zones along the fault zones,
19

Figure 1A.5. Side-scan sonar mosaic of the seafloor in the shallow Green Canyon survey area.

Conventions as in Figure 1A.4.

subcircular and elliptical high-backscatter features corresponding to mud mounds, and linear, downslope trending high-backscatter features probably caused by sediment flows. In addition, many

subcircular, rough-looking mound features are observed in Green Canyon 139 and 140, atop a salt

dome. These are likely mounds consisting of authigenic carbonate reported in that area (Roberts and

Ahron 1994). In addition, two large, fan-shaped high-backscatter features, several square kilometers

in area, appear in Green Canyon 272 and 233. Both have the appearance of complex, multiple

sediment flows erupted from effusive mud volcanoes.

The deep Green Canyon survey area has a markedly different appearance from the shallow survey

areas. This survey covers an area of salt highs and intrasalt basin, in contrast to the gentler, less

tectonically-disturbed upper slope survey areas. The sonar mosaic (Figure 1A.6) shows many areas

of high-backscatter and an overall more chaotic appearance. Irregular backscatter zones (with both

high and low backscatter features) occur on salt flanks where faulting has produced rough zones.

In addition, mass wasting has caused slumps and sediment flows, which appear as high backscatter
20

Figure 1A.6. Side-scan sonar mosaic of the seafloor in the deep Green Canyon survey area.

Conventions as in Figure 1A.4.

features on the intrasalt basin floors. High backscatter spots, like those observed in the shallow areas

also occur, implying the existence of hydrocarbon seeps and seep alteration, but in this survey area

they are harder to define owing to the background of tectonic features.

Comparison of known chemosynthetic organism sites with side-scan sonar and other data types

highlights the difficulty in attempting to find a diagnostic geophysical signature that will flag

inhabited seep sites. Several sites are characterized by large mud volcanoes. Several are highly

active, such as the Garden Banks 425 site, the Bush Lite site, and the TAMU-6 and TAMLJ-17 sites

discovered in Green Canyon leaseblocks 191 and 233 during the NR-1 cruise. Bush Hill, in contrast,

is continuously active, venting gas, but shows no evidence of recent sediment or fluid expulsion as

do the others. In contrast, the GC 234 and Brine Pool NR-1 sites are ones that are not obvious in

either the side-scan sonar or MCS data. Both occur in areas of high acoustic backscatter, but the

locations of the chemosynthetic communities do not stand out against the complex anomalies

located along fault zones in the vicinity.

Interestingly, several different types of mound character were noted in the geophysical data. The

side-scan sonar data show three types: (1) nearly homogeneous high backscatter, (2) highbackscatter

center with a halo of lesser backscatter (“bulls-eye”), and (3) high backscatter with a “dead spot”

from which the sonar receives no return (“dead-eye”). Bush Hill is an example of type 1, and this
21

Table 1A.4. Chemosynthetic community site indicators.

Indicator Data type Likelihood*

Deep rooted fault Multichannel 2D or 3D seismic data M

Acoustic wipeout High-frequency echosounder profiles M

Strong amplitude anomaly Multichannel 2D or 3D seismic data M

Mound along fault Swath bathymetry; 3D multichannel

seismics, geohazard survey

M

Confluence of regional faults Multichannel 2D or 3D seismic data H

Sea surface oil slick Aerial photography; space

photography; synthetic-aperature

radar

H

Gas stream in water column High-frequency echosounder profiles H

High backscatter along fault Side-scan sonar H

Chimney-shaped acoustic wipeout Multichannel 2D or 3D seismic data H

Strong amplitude anomaly along fault Multichannel 2D or 3D seismic data

coincident with mound

H

High backscatter along fault

coincident with mound

Side-scan sonar VH

Strong amplitude anomaly along

fault, negative reflection coefficient,

coincident with mound

Multichannel 2D or 3D seismic data VH

Presence of small mounds Near bottom high-frequency

echosounder profiles

VH

Presence of small mounds Near bottom side-scan sonar swaths VH

Oil, gas Cores VH

Chemosynthetic shell debris Cores C

Images of chemosynthetic organisms ROY video, camera sled,

submersible

C

*Likelihood of chemosynthetic community code: M=moderate; R=high; YR=very high; C=confirmed
22

appears to be a result of a mound charged with gas and gas hydrate but without an obvious fluid

expulsion vent. Type 2, the bulls-eye mound, were found in the chirp sonar surveys to have a central

hard-bottom surrounded by a region of acoustic wipeout likely caused by gas-charged sediments.

These mounds were not inhabited by chemosynthetic organisms and appeared to be senescent or

dormant. The dead-eye mounds (type 3) were all highly active mud volcanoes with brine pools or

brine vents. We speculate that the dead spots are caused by specular reflection of the sonar signal

away from the sonar (i.e., no backscatter) or nearly complete absorption of the sonar signal by an

extremely gas-charged, sediment/fluid slurry in the vent region.

Comparison with MCS data shows that the seafloor amplitude anomaly associated with the known

chemosynthetic sites and mounds is variable. Bush Hill has a negative reflection coefficient,

implying a reduction of seismic velocity within the mound and a reversal of the signal polarity,

probably as a result of gas-charged sediments. In contrast, the Garden Banks 425 mound shows a

ring of slightly greater reflection around the mound perimeter, with the mound center showing no

anomaly. This type of signature was noted on several other mounds. The TAMU-17 mound, a highly

active mud volcano with abundant tube worm clusters, displays a positive amplitude anomaly. The

Brine Pool NR-1 and GC234 sites are also difficult to detect with MCS amplitude anomaly data.

In all, it appears that there is no one characteristic geophysical signature that will allow an

interpreter to find all of the known chemosynthetic organism sites in our study areas. Instead, the

geophysical data can be used to define areas affected by seepage, and these generally make up only

a small fraction (about 11%) of the total survey area (although the percentage can be much higher

within a localized area, such as a single leaseblock). Whether chemosynthetic organisms inhabit a

given locality can probably only be determined by direct observations, such as submersible

observations, camera sled or ROV photos, or specimens recovered in core or trawl. However, the

likelihood of chemosynthetic organism occurrence can be inferred by using a number of geologic

and geophysical observations to build a case for their occurrence or absence (Table 1A.4).

REFERENCES

Behrens, E. W. 1988. Geology of a continental slope oil seep, northern Gulf of Mexico. American

Association of Petroleum Geologists Bulletin 72:105-114.

Johnson, H.P., and M. Helferty. 1990. The geological interpretation of side-scan sonar. Reviews of

Geophysics 28:357-380.

Roberts, H.H., and P. Aharon. 1994. Hydrocarbon-derived carbonate buildups of the northern Gulf

of Mexico continental slope: A review of submersible investigations. Geo-Marine Letters

14:135-148.

Roberts, H. H., P. Aharon, R. Carney, J. Larkin, and R. Sassen. 1990. Sea floor responses to

hydrocarbon seeps, Louisiana continental slope. Geo-Marine Letters 10:232-243.
23

Sager, W.W., C.S. Lee, I.R. Macdonald, and W.W. Schroeder. 1999. High-frequency nearbottom

acoustic reflection signatures of hydrocarbon seeps on the northern Gulf of Mexico continental

slope. Geo-Marine Letters 18: 267-276.

Dr. William W. Sager is a professor of oceanography in the Department of Oceanography at Texas

A&M University. His research interests include marine geology and geophysics, plate tectonics,

paleomagnetism, environmental magnetism, and seafloor mapping. He received a B.S. degree in

physics from Duke University (1976) and M.S. and Ph. D. degrees in marine geophysics from the

University of Hawaii (1979 and 1983).

Dr. Ian R. MacDonald is an associate research scientist in the Geochemical and Environmental

Research Group at Texas A&M University. His research interests include the geology and ecology

of hydrocarbon seeps, gas hydrates, deep sea currents, seafloor imaging and GIS applications to

seafloor mapping. He received his B.A. degree from The Friends World College (1976), an M.S.

degree in fisheries science from Texas A&M University (1983), and a Ph.D. degree oceanography

from Texas A&M University (1990).
24

NORTHEAST GULF OF MEXICO PINNACLES STUDY HARD-BOTTOM

COMMUNITIES

Mr. Dane D. Hardin

Applied Marine Sciences, Inc.

Mr. Keith D. Spring

Mr. Stephen T. Viada

Dr. Alan D. Hart

Mr. Bruce D. Graham

Continental Shelf Associates

Mr. Michael B. Peccini

Texas A&M University

Abstract

Hard-bottom communities were sampled at nine sites in the northeastern Gulf of Mexico during four

cruises from May 1997 to August 1999. The sites fell into three categories of vertical relief (i.e.,

low, medium, and high) and three categories of region (i.e., east, central, and west). Low-relief sites

averaged 3 m in vertical relief, medium-relief sites averaged 5-7 m in vertical relief, and high-relief

sites averaged 10-12 m in vertical relief. Sites in the east, central, and west regions ranged from 143-

147 km, 108-125 km, and 70-71 km from Main Pass in the Mississippi River delta, respectively.

The communities were sampled photographically, with approximately 100 random and five fixed

photographic samples being collected at each site in each cruise. Photographs were analyzed with

a random-point contact method to estimate percent cover and density of each taxon. Statistical

analyses focused on the 40 taxa with the highest average percent cover over all sites and times.

These 40 taxa accounted for 90% of the total average biological cover at the sites. Ahermatypic

corals, octocorals, and antipatharians dominated the biological cover data, while octocorals and

poriferans had the most taxa.

Analysis of variance tests for the effects of habitat relief, region, and time (i.e., cruise) indicated that

90% of the taxa differed among relief categories, 80% varied among regions, and 70% differed

among cruises. Interpretation of these main effects was complicated by a high number of significant

interactions; all taxa had at least one significant interaction and 57.5% of taxa had significant

interactions for all possible two-way and three-way combinations.Using these ANOVA results only

as a guide to roughly assign taxa to habitat preferences, 23 taxa preferred medium-relief or highrelief habitat and 12 preferred low-relief habitat, and five had no habitat relief preference.

Construction of linear models using all random samples to test for the effects of 11 environmental

variables revealed that distance from the Mississippi River and cruise affected 75-100% of taxa,

regardless of habitat preference. Because distance from the Mississippi River was estimated from

the center of each site, a single value was associated with all samples from a given site.
25

Consequently, distance from the Mississippi River functioned as a surrogate for site in this analysis,

limiting its value as a descriptor of environmental effects on hard-bottom communities. Moreover,

not all sites were sampled in each cruise, which may account for the high numbers of taxa exhibiting

significant cruise effects. Among the other nine environmental variables, depth, sediment veneer,

and medium-scale habitat roughness affected much higher percentages of taxa that preferred

medium-high relief habitat when all sites were included, as compared to analyses that included only

medium or high-relief sites. This suggests that these variables are important determinants in the

higher abundances of many taxa in medium or high-relief habitat.

Location on feature and fluxes of suspended sediments also affected substantial numbers of taxa that

preferred medium to high-relief habitat. Several medium-high relief taxa varied according to the

bearing from the center of rock features and were significantly correlated with estimated food flux

and kinetic energy in currents. Canonical correspondence analysis also indicated that a strong effect

of sediment veneer on many taxa that preferred medium or high-relief habitat, with strong negative

correlations. Chi-square analysis of data from fixed photographs indicated observed frequencies of

sediment accumulation were significantly higher than expected before two hurricanes passed over

the study area, whereas samples from shortly after the hurricanes passed indicated no differences

between observed and expected frequencies of sediment accumulation. The effects of depth,

sediment veneer, medium-scale habitat roughness, location on feature and flux of suspended

sediments on hard-bottom communities can all be related to flux and accumulation of sediment.

We suggest that sedimentological processes are important regulators of hard-bottom communities

in the study area and that hurricanes may be important in limiting the effects of sediment

accumulation on these communities.
26

FISH ASSEMBLAGES

Mr. David B. Snyder

Continental Shelf Associates, Inc.

INTRODUCTION

Along the Mississippi-Alabama Outer Continental Shelf (OCS), numerous carbonate mounds

ranging from less than a few meters to nearly a kilometer in diameter form a trend in water depths

of 60 to 100 m. Although these deep reef features represent complex hard-bottom habitats for fishes

and invertebrates, little is known concerning the existing biotic assemblages. In an effort to provide

basic information, the U.S. Geological Survey (USGS), Biological Resources Division and the

Minerals Management Service sponsored a multidisciplinary program entitled “Northeastern Gulf

of Mexico Coastal and Marine Ecosystems Program: Ecosystem Monitoring, Mississippi/Alabama

Shelf.” The primary focus of this program (conducted by Continental Shelf Associates, Inc. and

Texas A&M University, Geochemical and Environmental Research Group) was to describe and

monitor epibiotal communities and gain an understanding of the dominant environmental processes

that control or influence the distribution, establishment, and development of these communities. A

secondary biological component was to assess the fish assemblages associated with the study sites

using video footage and still photographs collected during the epibiotal surveys as a data source.

This report provides a preliminary account of the fish assessment component of the program.

STUDY OBJECTIVES

The objectives of this study were

1) to describe the fish assemblage structure and dynamics at nine study sites; 

2) to examine the effect of relief (high, medium, and low) and location (east, west, and central)

on assemblage composition; and

3) to examine multi-scale habitat associations for common species.

This report provides results from the first two objectives.

MATERIALS AND METHODS

Hard-bottom assemblages were sampled at nine sites using a remotely operated vehicle (ROV).

Sampling sites were chosen to fall within three categories of relief (i.e., low, medium, and high) in

three regions from east to west (Figure 1A.7). Site selection was based on data from geophysical

surveys and ROV reconnaissance surveys. At each site, random photographs were taken and random

video transects were surveyed during each monitoring cruise. Video images were used to assess the

occurrence and composition of fishes and broadly to characterize substrates. Two videocameras

simultaneously recorded the path taken by the ROV during its operations; one was forward-viewing
27

50 m

90 m

70 m

90 m

70 m

50 m

N

WESTERN

CENTRAL

EASTERN

1

2

3

4 5

2 13

4

6

8

5

9

7

 Legend:

=Megasite

=Site

1

1

Figure 1A.7. Location of monitoring sites.

for piloting the ROV, while the other was downward-viewing, perpendicular to the substrate, for

recording quantitative benthic photographs. Random photographs were collected within eight sectors

of a single circular plot located within each site. The paths recorded on video by the ROV as it

moved from photograph to photograph provided the best data available for characterizing the fish

taxa present at each site. These paths represented random, non-overlapping transects through each

of eight sectors at all sites. Fish assemblages associated with the study sites were described from the

available video and still photographic data collected during four monitoring surveys, conducted in

April 1997 (1C), October 1997 (M2), April 1998 (M3), and August 1998 (M4).

RESULTS AND DISCUSSION

Analysis of 244 video transects from four cruises yielded 73 fish taxa in 32 families. The most

speciose families observed were sea basses (Serranidae), squirrelfishes (Holocentridae), lizardfishes

(Synodontidae), jacks (Carangidae), wrasses (Labridae), and butterflyfishes (Chaetodontidae). The

most frequently occurring taxa in the videotapes were roughtongue bass (Pronotogrammus

martinicensis), short bigeye (Pristigenys alta), bank butterflyfish (Chaetodon aya), red barbier

(Hemanthias vivanus), and tattler (Serranus phoebe). Figure 1A.8 illustrates the rank speciesfrequency relationship for all transects combined.

Although pelagic (e.g., sharks, jacks, bluefish, and king mackerel) and demersal (flounders) fishes

also were observed, the ichthyofauna consisted primarily of reef fishes. Commonly seen species
28

Rank

0 10 20 30 40 50 60 70 80

Frequency

0

20

40

60

80

100

120

140

160

180

200

220

240

Roughtongue bass

Short bigeye

Bank butterflyfish

Red barbier

Scamp

Yellowtail reeffish

Tattler

Scorpionfish (Scorpaena sp.)

Blue angelfish 

 Wrasse bass

Figure 1A.8. Rank-frequency relationship for all fish taxa observed in video transects across study

Sites 1 through 9 for Cruises 1C, M2, M3, and M4.

represent the deep reef fish assemblage reported for water depths of 50 to 300m in the western

Atlantic. Similar species have been reported by previous investigations of the pinnacle features, off

the southeastern U.S. (Parker and Mays 1998), within the lower portion of the topographic features

in the northwestern Gulf of Mexico (GOM) (Dennis and Bright 1988), and near the head of De Soto

Canyon (Shipp and Hopkins 1978). The total number of taxa represents about half of the fish fauna

known from the hard banks and reefs of the northern GOM.

Taxonomic richness recorded from videotapes for each cruise varied across all sites and cruises

(Figure 1A.9). During Cruise 1C, the number of taxa observed ranged from 5 at Site 9 to 22 at Site 7

and averaged 15.3 taxa per site. Cruise M2 yielded an average of 20.7 taxa per site, ranging from

13 taxa at Site 6 to 30 taxa at Site 1. Cruise M3 yielded an average of 28.1 taxa per transect, ranging

from 37 taxa at Site 1 to 19 taxa at Site 8. Transects during Cruise M4 averaged 15.2 taxa per

transect, ranging from 23 taxa at Site 1 to 9 taxa at Site 3. 
29

Study Site

0123456789

Number of Taxa

0

5

10

15

20

25

30

35

40

Cruise 1C

Cruise M2

Cruise M3

Cruise M4

Figure 1A.9. Total fish taxa observed in video transects across study Sites 1 through 9 for

Cruises 1C, M2, M3, and M4.

The influence of relief category (high, medium, and low relief), location (east, central, west), water

depth, and distance from the Mississippi River mouth on fish assemblage composition was examined

by correspondence analysis (Figure 1A.10). Overall, there were no strong, consistent relationships.

Site 1 had the most distinct species composition and supported the highest richness of reef species.

Site 1 is in the high-relief category, is the farthest from the Mississippi River mouth, and more

importantly, is the shallowest of the study sites. Many fishes observed here, but not at other sites,

commonly occur in shallow waters. These include sand tilefish (Malacanthus plumieri), honeycomb

cowfish (Lactophrys polygonia), rock beauty (Holacanthus tricolor), squirrelfish (Holocentrus

adscensionis), and sharpnose puffer (Canthigaster rostrata). The different species composition and

richness at Site 1 may be due simply to shallow water depth or other unmeasured correlates of

shallow water depth rather than distance from the Mississippi River mouth or relief category.

REFERENCES

Parker, R.O. and R.W. Mays. 1998. Southeastern United States deepwater reef fish assemblages,

habitat characteristics, catches, and life history summaries. NOAA Tech. Rep. 138. 41 pp.
30

CA Axis 1

-2 -1 0 1 2 3

CA Axis 2

-4

-3

-2

-1

0

1

2

3

4

1 

1 

2 2 1 1 2 2 3 

3 

3 

3 

4 

4 

4 

4 

5 5 

5 

6 

6 

7 

7 

7 

7 

8 

8 

8 

8 

9 

9 

9 

9 

Figure 1A.10. Sample scores from correspondence analysis of a taxa-by-samples matrix based

on video transects plotted on Axes 1 and 2. The scores are labeled 1 through 9 to

represent the monitoring sites. Sites 1, 5, and 7 are high relief; Sites 2. 4, and 8

are medium relief; and sites 3, 6, and 9 are low relief.

Shipp, R.L. and T.S. Hopkins. 1978. Physical and biological observations of the northern rim of the

De Soto Canyon made from a research submersible. Northeast Gulf Sci. 2(2):113-121.

Mr. David B. Snyder is a senior staff scientist with Continental Shelf Associates, Inc. He has

18 years of experience with aquatic environmental assessment and research programs for federal,

state, and industrial clients. He has participated as Research or Chief Scientist on over 50 scientific

cruises conducted in domestic and international waters. Mr. Snyder has managed several fisheryrelated projects including bycatch studies, life history studies, and ichthyofaunal assessments in a

variety of marine and freshwater habitats. Mr. Snyder received his B.S. in zoology from the

University of Florida in 1978 and his M.S. in ichthyology/marine biology from Florida Atlantic

University in 1984.
31

TROPHIC SUBSIDIES IN THE TWILIGHT ZONE: ZOOPLANKTON AVAILABILITY

AND FOOD WEB STRUCTURE OF DEEP REEF FISHES ALONG

 THE MISSISSIPPI-ALABAMA OUTER CONTINENTAL SHELF

Mr. Douglas C. Weaver

Dr. Kenneth J. Sulak

USGS Biological Resources Division

ABSTRACT

The food web structure and pelagic prey encounter rates of deep (50-110m) reef fishes in the

northeastern Gulf of Mexico was examined. Fish communities on high-profile topographic features

at the edge of the continental shelf are numerically dominated by two species of streamer basses

(Serranidae: Anthiinae): the roughtongue bass, Pronotogrammus martinicensis, and the red barbier,

Hemanthias vivanus. Stomach content analysis revealed that calanoid copepods, pelagic tunicates,

pteropods, and invertebrate larvae dominate the diets of both species, and that these small

planktivores serve as primary prey for many larger reef predators. To compare diets of reef fishes

with pelagic prey availability and encounter rates, stationary plankton tows (0.5m diameter, 335m

mesh conical nets) were made in the water column at near-surface (2m), midwater (35m) and nearreef (60-70m) depths. Preliminary results indicate high flow rates (3.7-24.5 cm/sec,

mean=15.6cm/sec) and high prey availability (estimated at 1.5 million zooplankters per day per

meter) in the vicinity of deep reef features. Estimates of the relative abundance of fishes indicate that

90 to 99% by number are small planktivores, and 65-90% of their diets are calanoid copepods,

forming the main link from the benthos to water column productivity and the primary source of prey

for the demersal reef fish community.

INTRODUCTION

Feeding habits, food web structure, and prey availability for reef fishes occurring along the

Mississippi-Alabama outer continental shelf were surveyed. Trophic pathways are important for

understanding the ecological framework in the reef fish community, including the role of resident

reef fishes in the diet of large predatory fishes, predator-prey relationships among fishes and

invertebrates, and the role of fishes in supplying nutrients to the benthic invertebrate community.

Identification of trophic pathways can also identify functional links of organismal abundance to

geological/ oceanographic processes and trophic links to off-reef benthic and pelagic communities.

From a bioenergetic standpoint, dietary analysis and identification of prey consumption rates also

can identify energy availability for growth and reproduction.

MATERIALS AND METHODS

Fishes were collected by hook-and-line angling during four research cruises along the Pinnacles

Reef Tract of the Mississippi-Alabama Outer Continental Shelf from August 1997 to October 1998.

During each cruise, a variety of artificial and natural baits were used to sample fishes over a wide

range of body sizes, and specimens were placed on ice and frozen or immediately preserved in 10%
32

Figure 1A.11. Food Web model of the Pinnacles Reef Fish Community. Lower trophic groups

follow Christensen (1995).

buffered formalin in the field. Fishes were dissected in the laboratory to remove gastrointestinal

tracts, and stomach contents were removed for identification. Prey items were examined under a

dissecting microscope and identified to the lowest possible taxon. Numerical abundance of prey was

calculated to estimate relative importance of individual prey taxa in the diet of each species of reef

fish. Diets of the common reef fishes were incorporated into a working food web model following

the methods of Winemiller (1990) to identify the dominant trophic pathways in the deep reef fish

community.

To identify prey availability for planktivorous reef fishes, stationary plankton samples were made

using 0.5m diameter, 335m mesh opening-closing plankton nets equipped with mechanical

flowmeters while the vessel was anchored over study reefs. Plankton samples were made at the

surface (2m depth), midwater (35m depth), and near-reef (60-70m) to identify patterns in

zooplankton densities throughout the water column, and availability of pelagic prey to the demersal

fish community. Estimates of zooplankton availability to the deep reef community was estimated

based on plankton densities, foraging range of planktivores, and length of day (feeding period).

RESULTS

Reef fishes of the deep reef community occupy a wide range of trophic pathways, and prey on a

diverse array of planktonic and benthic organisms (Figure 1A.11). Calanoid copepods, gelatinous
33

Figure 1A.12. Zooplankton abundance estimated at near surface (2m), midwater, and near-reef

water depths during March 2000. Samples were collected using stationary, 0.5m

diameter, 335μ mesh opening-closing plankton nets. Values given are number of

zooplankters collected per 10-minute sample.

zooplankton and crustacean larvae dominate the diets of streamer basses, vermilion snapper, and

short bigeye, respectively. Streamer basses are found in stomach contents of red snapper, jacks,

tattler, and other carnivores. Benthic carnivores include red porgy, greenband wrasse, and tattler.

These fishes prey on a variety of benthic invertebrates that are associated with soft-bottom

sediments.

Estimates of zooplankton abundance and prey availability reveal a decline in zooplankton abundance

from surface waters to near reef depths (Figures 1A.12 and 1A.13). Samples taken in March 2000

reveal an average of 2,600 zooplankters per 10-minute tow at 2m, 2,210 at 35m, and approximately
34

Figure 1A.13. Zooplankton abundance estimated at near surface (2m), midwater, and near-reef

water depths during May/June 2000. Samples were collected using stationary,

0.5 m diameter, 335μ mesh opening-closing plankton nets. Values given are

number of zooplankters collected per 10 minute sample.

950 zooplankters collected at near-reef water depths. Calanoid copepods dominated zooplankton

samples at all depths during the March sampling period. Zooplankton abundance increased

dramatically during May/June samples, ranging from 34,000 zooplankters at near surface waters per

sample to 1,500 at near-reef water depths. Surface and midwater samples were dominated by the

sergestid shrimp, Acetes faxoni or the pelagic tunicate Salpa, while near-reef samples were

dominated by calanoid copepods. Measurements of current speed made during plankton tows ranged

from near zero to 54 cm/sec, with a mean speed of 19.5cm/sec at 2m, 13.2 cm/sec at 35m and 15.6

cm/sec at near-reef depths. These values are similar to those reported by Kelly and Bender (2000).

Rough estimates of prey availability to the deep reef community were calculated based upon

zooplankton densities present in the March 2000 samples, for conservative predictions of

planktivore densities that could be sustained by incoming prey resources (Figure 1A.14). Initial

estimates of 1,000 zooplankters per sample, collected during a 10-minute sampling period and with

a net opening of .196 m2

 , equals approximately 5,000 zooplankters per meter square per 10 minutes.

Using an estimate of a 10-hour feeding/daylight period and a 5m foraging range for demersal

planktivores (based on observations made from ROV videotapes, and K. Rademacher, NMFSPascagoula pers. comm.), an estimated 1.5 million zooplankters would be available to planktivores

along a one-meter wide swath in the water column that passes over the reef community.
35

Figure 1A.14. Planktonic prey availability to deep reef zooplanktivores.

If each planktivore consumed an average of 100 zooplankters per day, zooplankton availability

would enable approximately 15,000 planktivorous fish to occupy each meter-wide swath of reef

habitat, based on water-column prey resources alone. On large flat-topped reefs that may reach a

diameter of up to 500m, planktonic prey resources would support up to 30 individual planktivores

per square meter, along a meter-wide transect across the reef. Estimates of availability of planktonic

prey would be supplemented by emergent zooplankton that occur in sediments within or adjacent

to the reef community (Porter and Porter 1977), including nocturnally-active zooplankton that would

support nocturnal predators (such as short bigeye).

DISCUSSION

Direct feeding on pelagic plankton dominates the trophic pathways of the deep reef community, and

estimates of zooplankton abundance indicate high prey availability for resident planktivorous reef

fishes of the shelf-edge community at the Pinnacles Reef Tract. Estimates of number of planktonic

prey availability to the deep reef community are higher than values given for shallow reef fishes at

Davies Reef on the Great Barrier Reef (Approximately one million over a twelve-hour period,
36

Hamner et al. 1988). Local oceanographic conditions in this region, including intrusion of freshwater input from the Mississippi and other rivers to the outer shelf (Kelly and Bender 2000), may

contribute to the high densities of planktonic prey occuring in this study. 

ACKNOWLEDGMENTS

This study was funded by the Outer Continental Shelf Ecosystem Program of the U.S. Geological

Survey- Biological Resources Division, K. Sulak, Principal Investigator.

REFERENCES

Christensen, V. 1995. A model of trophic interactions in the North Sea in 1981, the Year of the

Stomach. Dana 11(1):1-28

Kelley, F. J. and L. C. Bender. 2000. Chapter 6: Physical Oceanography/Hydrography. In

Continental Shelf Associates and Texas A&M University. Northeastern Gulf of Mexico Coastal

and Marine Ecosystem Program: Ecosystem monitoring, Mississippi/Alabama shelf; Final

Synthesis Report. U.S. Department of the Interior, U.S. Geological Survey, Biological Resources

Division and Minerals Mgmt. Service, Gulf of Mexico OCS Region, New Orleans, LA.

Hamner, W. M., M. S. Jones, J. H. Carleton, I. R. Hauri and D. McB. Williams. 1988. Zooplankton,

planktivorous fish, and water currents on a windward reef face: Great Barrier Reef, Australia.

Bulletin of Marine Science 42(3):459-479.

Porter, J. W. and K. G. Porter. 1977. Quantitative sampling of demersal plankton migrating from

different coral reef substrates. Limnology and Oceanography 22(3):553-556.

Winemiller, K. O. 1991. Spatial and temporal variation in tropical fish trophic networks. Ecological

Monographs 60(3):331-367.
37

SESSION 1B

AIR QUALITY

Chair: Dr. Chester Huang, Minerals Management Service

Co-Chair: Ms. Terry Scholten, Minerals Management Service

Date: December 5, 2000

Presentation Author/Affiliation

Observation of the Atmospheric Boundary

Layer in the Western and Central Gulf of

Mexico

Mr. Gary S. Zeigler

URS Corporation

(Radian International LLC)

Boundary Layer Study in the Western and

Central Gulf of Mexico

Dr. Paul T. Roberts

Mr. Clinton P. MacDonald

Mr. Timothy S. Dye

Sonoma Technology, Inc.

Dr. Steven R. Hanna

AMS Certified Consulting Meteorologist

IMPROVE: The Visibility Monitoring

Network

Ms. Kristi Morris

U.S. Fish and Wildlife Service

Development of Gridded Source Emissions

Inventories (Mobile and Stationary)for OCSRelated Activities in the Gulf of Mexico in

1977 and 1988

Mr. Lyle Chinkin

Ms. Dana Coe

Sonoma Technology, Inc.

Dr. Mark Yocke

ENVIRON International Corp.

Mr. David Scalfano

Northlake Engineers, Inc.
39

OBSERVATION OF THE ATMOSPHERIC BOUNDARY LAYER IN THE WESTERN

AND CENTRAL GULF OF MEXICO

Mr. Gary S. Zeigler

URS Corporation

(Radian International LLC)

This meteorological measurements project was initiated by MMS in late 1997. A planned three-year

data collection period began as of 3 June 1998 and has run continuously since that date. This paper

briefly summarizes project implementation actions and provides the status of the data collection

effort as of the end of fiscal year 2000.

PROJECT OBJECTIVES

For the Gulf of Mexico (GOM), data sets from automated weather stations and observational

satellites poorly represent how temperature, winds, and mixing heights vary vertically over the

atmospheric boundary layer and free troposphere. Because data from these sources do not accurately

or precisely measure a range of altitudes, empirical constants and relationships are used to

approximate vertical variations in boundary layer properties. For instance, MMS applies estimated

winds, temperature, and mixing heights in several ways when assessing changes in air quality from

oil and gas production. The MMS assessments use conceptual models of pollutant transport through

the marine boundary layer and theoretical analysis on the marine boundary layer. The MMS,

therefore, has interest in collecting actual field measurement of the vertical structure of the marine

boundary layer because such observations would reduce uncertainties in environmental assessments.

To help address the need for meteorological measurements in the GOM, the MMS initiated the

“Observation of the Atmospheric Boundary Layer in the Western and Central Gulf of Mexico”

project with the following objectives:

• Accurately collect, record, and report meteorological observations for three years.

• Collect surface data measurements, which include air and sea surface temperatures, pressure,

wind, and humidity. Collect upper air data to include temperature and wind profiles.

• Perform quality control checks on the data and strive for a data capture rate of 90% or

higher. 

PROJECT IMPLEMENTATION

Management

The project is carried out by personnel from Radian International LLC (“Radian”) and Sonoma

Technology Inc (“STI”) under the direction of the MMS staff. Radian is responsible for program

management and the installation and operation of the equipment. STI is responsible for the data
40

collection, processing and archiving tasks. Radian and STI share the quality assurance and quality

control functions.

Measurement Equipment

Upper air wind and virtual temperature profiles are measured by a LAP®-3000 boundary layer wind

profiler at each site. Standard surface meteorological sensors are mounted on a small tower at each

site: anemometer, wind vane, air pressure sensor, and relative humidity sensor. In addition, an

infrared sea surface temperature sensor is installed at each site.

Measurement Sites

Two oil platforms were selected as measurement sites in the GOM, one in relatively shallow water,

approximately 30km off-shore, and the other in relatively deep water, approximately 130km offshore. 

• Shallow Water Site: Vermillion 22D at 29.4o

N, 92.5oW, owned by ERT.

• Deep Water Site: South Marsh Island 160A at 28.1o

N/91.9oW, owned by Newfield

Exploration.

Measurement Configurations

All data are reported as hourly averages referenced to central standard time (CST). The radar profiler

uses 5 minutes of each hour in the virtual temperature measurement mode and the remaining 55

minutes of each hour in the wind measurement mode. The profiler measures winds from about 130

to 4,900 meters above antenna level, and virtual temperatures to about 1,300 meters above antenna

level. The surface meteorological sensors are mounted on the small tower at platform level.

Data Communications

Surface meteorological data are collected at each site on a Campbell Scientific data logger and are

transferred hourly from there to the radar profiler’s “Gateway” Computer. Also on an hourly basis,

the Gateway Computer collects upper air wind and temperature data from the site’s Radar

Computer, builds a consolidated, compressed data packet, and sends it to the site’s Synergetics

GOES Data Collection Platform (GOES DCP). At times authorized by NOAA, the GOES DCP

transmits the surface and upper air data packet each hour. Each data packet is then relayed by the

GOES satellite to the NESDIS facility in Wallops Island, VA, where STI accesses it hourly via an

internet connection. After quality checks, the processed data are sent to MMS in monthly

increments. Separately, NOAA’s Forecast System Laboratory can access the hourly data directly

from NESDIS. A telephone modem installed at each site provides a backup means for site status

checks and data retrieval.
41

Data Collection Period

After receipt of GOES transmit time allocations from NOAA, the project’s planned three year data

collection period began on 3 June 1998.

PROJECT FISCAL YEAR 2000 ACTIVITIES

Data Collection Completed

As of the end of FY00 on 30 September 2000, the project had successfully completed 28 consecutive

months of the planned 36-month data collection period, with data collection and reporting operations

continuing in progress. Overall data capture rate for the project as of the end of FY00 was 91%. For

the FY00 portion of the project, the data capture rate was slightly lower at 87%. Data losses during

FY00 were due to a variety of equipment and communications issues that were addressed during site

visits and by remote telephone access.

Site Visits

Three site visits were completed during FY00, as summarized below:

• 12-17 January 2000, Unscheduled Visit. On 1 January 2000, the radar profiler at each site

ceased collecting data. All other data flow from both sites continued normally via GOES.

Trouble-shooting efforts by phone with operator personnel at both platforms failed to

identify the cause of the problem or to successfully restore radar operations. However,

separate from this project, it was determined that deployed radar profilers on other (nonMMS) projects were experiencing similar interrupts due to a configuration problem causing

the installed Global Positioning System (GPS) clock updates to be giving the radar profiler

computers the wrong year (i.e., 1900 instead of 2000). Troubleshooting on the other projects

identified the specific cause of the GPS problem. Platform visits were subsequently

performed in January 2000, during which system configuration changes were implemented

that restored normal data collection by both radar profilers and transmission of the data via

GOES. Equipment audits were also performed at both sites during these site visits.

• 24-26 March 2000, Unscheduled Visit. On 26 February 2000, the Vermillion 22D site

stopped transmitting meteorological data. Attempts to resolve the situation remotely were

not successful, thus requiring an unscheduled maintenance visit. During this trip, a failed

power supply in the charger for the data logger was discovered to be the cause. The power

supply was replaced, after which data transmissions successfully resumed on 24 March

2000. During this visit, a Y2K leap year software fix to the GOES transmission software was

also installed at both the Vermillion 22D and the South Marsh Island 160A sites. 

• 13-17 June 2000, Scheduled Visit. Semi-annual audits of all upper air and surface

meteorological equipment were conducted during this scheduled visit to both sites. A

Windows-95 operating system software fix was also installed at both sites to keep the data

time stamps at Central Standard Time (CST) all year. At the start of Daylight Savings Time
42

(DST) in April 2000, the data time stamps changed from CST to DST, even though the

Windows-95 software had been set to stay on CST. After some research, a problem fix was

obtained from Microsoft and was successfully implemented at both sites. 

Potential Site Relocation Problem

On 11 February 2000, Newfield Exploration announced their tentative planning to soon begin

drilling operations on their South Marsh Island 160A platform. They specified that the MMS

project’s measurement equipment would need to be removed before the new drilling could begin.

In response, MMS authorized additional site survey work to identify other suitable platforms in the

area for siting the measurement equipment in case it had to be moved from South Marsh Island

160A. The additional survey work was successfully completed and contingency relocation plans

were formulated. Fortunately, on 20 May 2000, Newfield Exploration further announced that their

drilling plans had been placed on hold and that the MMS project’s measurement equipment could

remain in place until further notice. This status continued throughout the remainder of 2000, and

will, it is hoped, hold through the completion of the project’s full data collection period. 

SUMMARY OF PROJECT STATUS

The MMS project to collect a three-year database of surface and upper air meteorological

measurements at two platform sites in the Gulf of Mexico continues in progress. Data collection

began as of 3 June 1998. Since that time, all monthly data reports and annual project summary

reports have been delivered to MMS on schedule. During FY00 operations, the data capture rate was

somewhat below average at 87% due to an assortment of equipment and communications issues that

were corrected as they arose. For the project-to-date period through the end of FY00, the data

capture rate achieved was 91%, meeting the project’s data capture rate objective of 90% or greater.
43

BOUNDARY LAYER STUDY IN THE WESTERN AND CENTRAL GULF OF MEXICO

Dr. Paul T. Roberts

Mr. Clinton P. MacDonald

Mr. Timothy S. Dye

Sonoma Technology, Inc.

Dr. Steven R. Hanna

AMS Certified Consulting Meteorologist

This four-year project began in late 1998. The Study Plan was approved in 1999 and technical work

has begun. This talk presents a summary of the plan for the project, plus several examples of data

analysis results. Further updates on the project will occur at future ITM meetings.

PROJECT OBJECTIVES

The purpose of this study is to provide the MMS with a description and analysis of the atmospheric

boundary layer and to explain how its structure influences the dispersion and transport of pollutants

in the western and central Gulf of Mexico (GOM). The results of this study will be used by the

MMS to support techniques for evaluating the effects of oil and gas exploration, development, and

production activities in the Outer Continental Shelf (OCS) on air quality over coastal areas. To

complete this study, we will conduct a number of technical tasks including the following: 

• Produce a data inventory for synthesizing the characteristics of the Atmospheric Boundary

Layer (ABL) and its dispersion properties in the western and central GOM, based on 1998

to 2001 observations and modeling results.

• Evaluate annual, seasonal, and diurnal variations in the ABL’s structure.

• Describe the processes governing variations in the ABL’s structure.

• Evaluate transport and mixing characteristics that govern pollutant dispersion over diurnal

and multi-day scales.

• Provide conceptual model summary of processes that influence the ABL’s structure and

variability and pollutant transport and dispersion.

KEY TECHNICAL ISSUES 

There has always been great uncertainty concerning the vertical and horizontal variability of the

atmospheric boundary layer in the GOM. For example, the depth of the boundary layer and its

vertical stability and wind and turbulence structure can vary greatly in OCS zones due to horizontal

variations in sea surface temperature and the overlying air mass. We are fortunate that the MMS

now has available the following new boundary layer observations in the GOM–two meteorological
44

stations collecting observations of the atmospheric boundary layer for three years (1998-2001) by

using 915 MHz radar wind profilers (RWP), 2 KHz Radio Acoustic Sounding Systems (RASS), and

surface meteorology units. The profilers measure winds and virtual temperatures between the

surface and heights of a few kilometers, and the surface stations measure sea surface temperature

as well as wind speed, wind direction, air temperature, and mixing ratio. 

The two most important meteorological parameters for use in transport and dispersion models are

wind velocity and vertical stability. These parameters are needed over the full depth of the overwater

boundary layer (i.e., up to heights of 1 or 2 kilometers), to better account for variations in transport

speed, transport direction, turbulent dispersion, and stability over the depth of the pollutant plume.

Over travel times of several hours to a few days, or travel distances of several kilometers to a few

hundred kilometers, such pollutant plumes can disperse upwards to the top of the boundary layer,

can shear off in several directions, and can be subjected to layering during the transition and

nighttime hours. The previous practice of using estimates of stability based on the difference

between sea surface and air temperature, and single wind speed observations was often

unsatisfactory.

The new data are being analyzed to investigate the following technical issues:

• The overwater surface energy balances are being studied using the near-surface observations

for both steady-state horizontally-homogeneous conditions and for conditions variable in

time and space. A climatology of latent heat versus sensible heat fluxes are being developed

for both situations, and parameterizations will be developed for use in situations when only

degraded data are available. Our research on this topic has greatly benefited from the results

of the so-called Tropical Ocean-Global Atmosphere Coupled-Ocean Atmosphere Response

Experiment (TOGA COARE). Many researchers participated in TOGA-COARE, which

made use of the most advanced state-of-the-art instrumentation. A major output of TOGACOARE is the COARE computer program, which allows surface fluxes over the ocean to

be accurately parameterized using routine observations (Fairall et al. 1996). The basic

structure is an outgrowth of the Liu-Katsaros-Businger (Liu et al. 1979) method, sometimes

referred to as the LKB method. This program allows fundamental boundary layer scaling

parameters such as the surface roughness length, zo, the friction velocity, u*, the scaling

temperature, T*, the scaling water vapor mixing ratio, q*, and the Monin-Obukhov length,

L, to be estimated. From these parameters, the mixing depth, h, and the vertical profiles of

wind speed, temperature, and water vapor mixing ratio can be estimated.

• Given the surface energy balance components, the vertical profiles of wind and temperature

will be studied to develop climatologies and parameterizations. In particular, it is desirable

to be able to estimate the full vertical profiles of wind and temperature based only on nearsurface measurements of air-water temperature differences and wind speeds.

• The extensive vertical temperature profiles are being studied to estimate the mixing depths

and to prepare empirical formulas to parameterize these observations.
45

• The frequency of occurrence of very stable conditions near the surface and in layers aloft are

being investigated due to the importance of these layers for defining worst-case conditions

for the dispersion of air pollutants.

• The horizontal spatial variability of wind speed and direction are being studied to identify

the fraction of time that wind directions and speeds persist over several hours in the Gulf of

Mexico, thus causing direct straight-line transport of pollutants toward receptors on the

shoreline.

• Estimates of the scaling velocity (u*) and scaling temperature (T*) derived from the

observational data are being made using the COARE algorithm. Since turbulent velocities

(important to dispersion) are directly proportional to u*, it should be possible to derive

improved parameterizations for the dispersion coefficients sy and sz. Perhaps the single most

important technical issue for understanding over-water air quality dispersion is the ability

to properly assess the mixing depth. Mixing height, zI

, or the height of the surface inversion,

h, can be estimated from either the radar profiler refractive index structure parameter (Cn

2

);

RASS virtual temperature data from MMS profiler stations combined with surface

temperature; or other upper-air data sources on land that are augmented by profiles included

in observed Eta fields, and buoyancy flux as described in Hsu 1997.

• Radar profiler mixing depth estimates have been demonstrated to relate well to other

fundamental mixing depth estimation techniques using rawinsonde temperature profiles and

aircraft data. Estimating hourly mixing depths from profiler data is relatively

straightforward. Using a technique developed by STI, we will estimate mixing depths from

the profiler’s reflectivity measurements and RASS’s virtual temperature profiles. The

refractive index structure parameter (Cn

2

) is computed from the profiler’s reflectivity

measurements. Maximum values of Cn

2

 have been theoretically and observationally linked

to the top of the mixed layer. RASS virtual temperature profiles coupled with surface virtual

temperature measurements can estimate the height of the mixed layer by using stability

analysis (Parcel Method).

ESTIMATION OF FLUXES AND OTHER ABL PARAMETERS PRELIMINARY 

This section describes the implementation of the TOGA COARE algorithm, which uses

observational data to develop boundary layer parameters that characterize the Atmospheric

Boundary Layer (ABL). The results of this work will be used to characterize the ABL, evaluate

annual, seasonal, and diurnal variations in ABL structure, and describe processes that influence ABL

structure and variations. The overall objective of this work is to provide the MMS with a description

and analysis of the atmospheric boundary layer in the western and central GOM. 

The COARE algorithm is designed to estimate surface fluxes and scaling parameters over the deep

ocean in tropical regions. The COARE algorithm requires wind speed, air temperature, and relative

humidity (RH) within the surface layer; sea surface skin temperature (Ts) or sea temperature near

the surface; and mixing height. We used a mixing height of 600 m. If the near-surface sea temperature is used, then solar and downwelling longwave irradiance data are required to correct this
46

temperature to a skin temperature. Precipitation data is not required, but if available, COARE will

estimate the precipitation contribution to the latent heat. Site time and position data are required. 

• Data collected at offshore buoys and at the VRM and SMI platforms meet the COARE data

requirements. 

• CMAN stations monitored all the required data, but these sites are not located in deep water.

The COARE algorithm is not tuned to handle the sea-state at shallow-water sites such as

CMAN stations. However, based on discussions with Scientific Review Board members and

Chris Fairall from NOAA, we concluded that the error produced by inaccurate representation

of the sea-state was acceptable for transport and dispersion analysis; therefore, data from

CMAN stations were used in the analysis. 

• The offshore buoy sites did not have skin temperature measurements or solar and

downwelling longwave irradiance data; thus, we were unable accurately to correct the .5 m

underwater temperature to skin temperature. Because the temperature corrections from near

surface temperature to skin temperature are typically within tenths of a degree Celsius, Chris

Fairall, a COARE algorithm author, suggested that in the absence of radiation information,

it would probably be safe to assume that the .5 m temperature equals skin temperature. We

could estimate radiation fluxes from cloud and sun elevation information but felt that the

errors from these estimates could be larger than the errors from assuming that the underwater

temperature equals the Ts. By not correcting the underwater temperature for the warm layer

effect, we underestimate Ts when the sun is out and the wind is light and, therefore, we

underestimate both the sensible and latent heat fluxes. However, under sunny and light wind

conditions the evaporative cool skin effect is also greatest and should somewhat offset the

warm layer effect. Also note that the Ts measured by the radiometer may be slightly cooler

than the skin temperature away from the platforms due to turbulence in the water created by

wave and currents moving around the platforms. 

Based upon the data requirements, we obtained and processed 1998 and 1999 offshore buoy data

from seven sites, CMAN station data from five sites, and data collected on the VRM and SMI

platforms. Figure 1B.1 shows the locations of the offshore buoys, the CMAN stations, and the

platforms. Of the seven offshore sites and five CMAN sites only Offshore Buoy sites 42035 and

42040 and CMAN site GDIL had complete enough data to estimate the boundary layer parameters

that characterize the ABL.

COARE OUTPUT 

Using the hourly meteorological data from sites 42035, 42040, GDIL1, SMI, and VRM we

calculated hourly sensible heat flux, latent heat flux, surface stress, frictional velocity, temperature,

and relative humidity scaling parameters, zr/L, and roughness length. These data are contained in

a working MS Access database. Note that the averages derived from buoy and CMAN stations are

for January to December of 1998 and that the averages derived from the platforms are from June of

1998 to June of 1999. Further work will include expanding this data set to include 1999 and 2000

data as the data become available.
47

42007

42019

42035 42040

BURL1

DPIA1

GDIL1

SRST2

-97.00 -96.00 -95.00 -94.00 -93.00 -92.00 -91.00 -90.00 -89.00 -88.00 -87.00

Longitude (degrees)

27.00

28.00

29.00

30.00

31.00

32.00

33.00

Latitude (degrees)

= Operational 915 MHz Wind Profiler = BAMP 915 MHz Wind Profilers

= Surface

= NEXRAD

= Offshore Buoy 

VRM

SMI

= CMAN

Figure 1B.1. Meteorological Stations in the MMS Gulf of Mexico Study domain.

We calculated monthly and hourly averages by month for selected parameters at each site. For the

zr

 /L stability parameter we calculated the median instead of the average because L approaches zero

under neutral conditions resulting in infinite zr

/L. Case study time series of selected meteorological

and derived ABL parameters were also created. Monthly averages were not computed if more than

80% of the data in a given month were missing.

RESULTS FROM MONTHLY PLOTS 

• The fluxes and scalar parameters calculated by the COARE algorithm seem physically

consistent with our conceptual expectations and were similar to results from TOGA.

Sensible heat flux of 10 w/m2 is typical of other non-Gulf over-water sites. Sensible heat flux

at most sites are about 5 to 30 w/m2. In November and December 1998 the sensible heat

fluxes were 40 to 55 w/m2, respectively. Latent heat fluxes of 50 to 100 w/m2 is typical of

other over-water sites and similar values were calculated for the Gulf sites.

• The sensible heat flux at VRM, SMI, and 42040 were generally within a factor of 2 of one

another. In August and September 1998 the sensible heat fluxes at these sites were within

20% of one another. There are slightly higher sensible heat fluxes in winter, possibly due to
48

warm water and cold air, with the reverse in late spring and early summer. This agrees with

annual variation of Ts.

• The greatest monthly average sensible heat flux of about 55 w/m2

 occurred at VRM in

December 1998, and the flux was nearly double the typical monthly average. The high

average sensible heat flux at VRM in December was a result of a skin temperature minus

theta difference of 5 degrees Celsius, about double the typical monthly average. It seems as

if the air temperature in December is erroneous.

• Discarding GDIL1, there is a factor of 2 or less variability among the three sites. February

and March have very good agreement. The magnitudes roughly follow the Ts (and hence qsat)

annual trend, with higher values in late summer, and lower values in late winter, although

the variation is not strong.

• Sensible heat fluxes were about 1/5 of the latent heat fluxes and were generally greatest in

the winter and early spring at all sites with the exception of GDIL1, which had no distinct

yearly cycle.

• The monthly average latent heat fluxes are generally greater in the summer and fall months.

This is due to higher air temperatures at those times. The latent heat fluxes range from about

40 w/m2 in January at VRM to about 190 W/m2 at GDIL1 in September. The shallow-water

site of GDIL1 generally had the greatest latent heat flux of all the sites during the spring and

summer months and it also had the highest water temperature of all the sites during these

months.

• The total heat flux is in good agreement (within a factor of 2) between sites. Magnitude

generally follows Ts annual variation, since latent heat flux is larger than sensible heat flux.

• Frictional velocity, u*, is in great agreement among sites and well within a factor of 2 and

often 20%. This is important because u* is the key scaling velocity for estimating transport

speeds and dispersion rates. u* is slightly less from May through August and peaks in

September, probably due to hurricanes.

• Temperature scaling, T*, is in good agreement among sites other than GDIL1. T* tends to

be smaller in April and May when Ts is still cool and the air is warming up due to changing

seasons.

• The humidity scaling parameter, q*, is in good agreement among sites and is within a factor

of 2 between sites. It is highest in late summer, when Ts and hence qsat are highest.

• Air temperatures are in good agreement among sites. The temperatures are warmest in July

and August and coolest in the winter. The December temperature at VRM appears to be

erroneously low by about 5 degrees Celsius. This possible error needs to be investigated.
49

• Sea surface temperatures are in good agreement among sites. The temperatures are warmest

in July and August and coolest in the winter. The December temperature at VRM appears

to be erroneously low by about 5 degrees Celsius. This possible error needs to be

investigated.

• Ts minus theta temperature differences are on the order of +1 to +3 degrees Celsius at most

sites all year. There are larger temperature differences at buoy 42040 and VRM in November

and December, respectively. We suspect that there might be a problem with the data during

November and December at these two sites and will investigate.

• Surface wind speed, U, shows good agreement among sites. The lowest speeds occur in July

and August and the highest in September and October. Review of weather maps indicates

that the high wind speeds in September are a result of tropical storms and the high wind

speeds in October are a result of strong continental winds or Bermuda Highs.

• RH is in good agreement among sites and is around 80 percent during all months. 

RESULTS FOR MIXING HEIGHTS

We derived hourly mixing heights and inversion heights, respectively, using the VRM and SMI

RASS virtual temperature data coupled with the platform surface data for May through November

1998. The platform temperature was used instead of the sea surface temperature because the

platform temperature likely better represents the temperature of the parcel. The RASS-derived

mixing heights and inversion heights are stored in an MS Access database. Review of the data

indicates that the mixed layer was convective 98% of the time. From this point forward we use the

term “mixing height” to imply both the mixing heights and the inversion height. Mixing heights

using Cn

2

 data or buoyancy flux methods are not complete.

Preliminary mixing height observations include:

• Ninety-eight percent of the time the surface temperature was warmer than the aloft

temperature and, therefore, the height of the mixed layer was estimated using stability

analysis. This means that only 2% of the time, the reported mixing height is actually the

inversion height capping a stable layer. Under this stable layer condition, the reported

inversion height is likely a gross overestimate of the actual mixing height. However, because

these conditions occurred infrequently during the study period, they do not strongly

influence the monthly average diurnal profiles.

• The average mixing heights at VRM and SRI show similar diurnal profiles, and the profiles

for each month were similar at the two sites. The highest mixing heights occur in July and

August at both sites and the lowest mixing heights occur in November. In July, the nighttime

mixing heights are about 600 m at both sites and increase to about 900 m during the midday

hours before decreasing to about 600 m by evening. In November, the mixing heights at

VRM are about 200 to 300 m all day. At SMI the mixing heights in November range from

200 m at night to about 400 m during the day. Note that the lowest observable mixing height
50

Figure 1B.2. Project schedule, 1998 – 2003.

is 140 m for SMI and 160 m for VRM; the actual mixing heights could, at times, be lower

than 140 m or 160 m.

• The standard deviation of hourly mixing heights by month is large, ranging from about 50

m on November nights to about 400 m on August days. 

• The standard deviation at SMI has a diurnal profile similar to the mixing heights with high

standard deviations during the day and low standard deviations at night. The standard

deviation at VRM has no obvious diurnal cycle.

CONCEPTUAL MODEL DEVELOPMENT 

We will develop a conceptual model of ABL characteristics and variability (as part of Task 3) and

of pollutant transport and dispersion (as part of Task 4) in the offshore and coastal environment of

the western and central Gulf of Mexico. The conceptual model will describe and illustrate the major

meteorological phenomena that control the ABL structure and variability (Task 3) and that control

pollutant transport and dispersion (Task 4). The purpose of developing a conceptual model is to

summarize the current state of knowledge, to provide a basis for testing and evaluating specific

hypotheses, to focus continuing analysis efforts on the most important issues, and to identify those

processes which must be represented in models.

Figure 1B.2 shows a schedule for the project.

Dr. Paul T. Roberts, STI Vice President, designs and manages air quality field, data management,

and data analysis projects. Most of these projects have involved the use of field data and analysis

methods to understand important meteorological and air quality phenomena, and to develop, apply,

and evaluate meteorological and photochemical models. Specific projects during which boundarylayer processes over water and shoreline environments were important components include the

MMS-sponsored Gulf of Mexico Air Quality Study (southeast Texas and Louisiana and offshore),

the Southern California Air Quality Study (SCAQS) and several subsequent data analysis efforts in

and around the South Coast Air Basin (SoCAB), the Lake Michigan Ozone Study, and the

NARSTO-Northeast Air Quality Study (covering Virginia to Maine, including offshore).
51

Mr. Clinton P. MacDonald, a Senior Meteorological Analysis at STI, has performed meteorological

and air quality data analyses in coastal and inland environments throughout the U.S. He has made

extensive use of radar wind profiler and RASS virtual temperature upper-air meteorological data to

understand the phenomena occurring in the atmospheric boundary layer. Mr. MacDonald has

developed and implemented several computer software tools to process and interpret upper-air and

surface meteorological data.

Mr. Timothy S. Dye, STI’s Manager of Meteorological Programs, has operated, quality-controlled,

and analyzed radar wind profiler wind and temperature data for over 11 years. Mr. Dye has

extensively used these upper-air data to conduct analyses of pollutant formation, transport, and

dispersion. He developed algorithms to estimate mixing height from radar profiler reflectivity and

temperature data and has used this technique to understand marine and overland boundary layer

structure and evolution in such programs as the Lake Michigan Ozone Study, the Gulf of Mexico

Air Quality Study, and the NARSTO-Northeast Air Quality Study. Mr. Dye is co-author of the new

EPA guidelines for collecting, quality controlling, and managing the upper-air data from radar

profiler/RASS, sodar, and rawinsonde systems and has designed several methods for conducting

Level 2 data validation of upper-air data.

Dr. Steven R. Hanna is a specialist in atmospheric turbulence and dispersion, in the analysis of

meteorological and aerometric data, and in the development, evaluation, and application of air

quality models. He is an AMS Certified Consulting Meteorologist with over 30 years of experience.

He has led several research and development projects involving, for example, the statistical

evaluations of hazardous gas dispersion models and regional ozone models; the development of

models for the dispersion of emissions from tall power plant stacks and from offshore oil platforms;

and the analysis of data from large regional field experiments in the Santa Barbara area, in the Lake

Michigan region, in the Gulf of Mexico, and in the northeastern United States. He led the

development of the OCD Model. From 1988-1997, Dr. Hanna was Chief Editor of the Journal of

Applied Meteorology, and has published over 100 articles in peer-reviewed journals, six chapters

in books, and four books in which he is the primary author.
52

IMPROVE: THE VISIBILITY MONITORING NETWORK

Ms. Kristi Morris

U.S. Fish and Wildlife Service

The 1999 Regional Haze Rule requires monitoring representative of each of the 156 visibility

protected federal Class I areas (CIAs), beginning in January 2000 to track progress toward the

national visibility goal. The deciview index calculated from ambient particle chemical speciation

data was selected to track haze levels. This tracking entails particle sampling and analysis of the

major aerosol components using methods patterned after those utilized since 1987 by the IMPROVE

Network and consistent with the aerosol monitoring portion of the 1999 Visibility Monitoring

Guidance document issued by EPA.

The Interagency Monitoring of Protected Visual Environments (IMPROVE) program is a

cooperative measurement effort designed

(1) to establish current visibility and aerosol conditions in mandatory CIAs;

(2) to identify chemical species and emission sources responsible for existing man-made

visibility impairment;

(3) to document long-term trends for assessing progress towards the national visibility goal; and

(4) with the enactment of the Regional Haze Rule, to provide regional haze monitoring

representing all visibility-protected federal CIAs where practical.

The program is managed by the IMPROVE Steering Committee that consists of representatives from

the U.S. Environmental Protection Agency (EPA), the four Federal Land Managers (FLMs-National

Park Service, Forest Service, Fish and Wildlife Service, and Bureau of Land Management), the

National Oceanic and Atmospheric Administration, four organizations representing state air quality

organizations (State and Territorial Air Pollution Program Administrators/Association of Local Air

Pollution Control Officials, Western States Air Resources Council, Northeast States for Coordinated

Air Use Management, and Mid-Atlantic Regional Air Management Association), and an Associate

Member, the State of Arizona Department of Environmental Quality.

In 1999, the IMPROVE Network consisted of 30 monitoring sites in CIAs, 20 of which began

operation in 1987 with the others starting in the early 1990s. Each monitoring site includes PM2.5

sampling on a twice per week schedule with subsequent analysis for the fine particle mass and major

aerosol species as well as PM10 sampling and mass analysis. Many of the sites also include optical

monitoring with a nephelometer or a transmissometer, and color photography to document scenic

appearance. In addition, approximately 40 sites, most in remote areas, that use the same

instrumentation and monitoring and analysis protocols (called IMPROVE Protocol sites) were

operated individually by federal or state organizations in recent years. 
53

Beginning in 1998, EPA provided supplemental support to IMPROVE to expand the network to

provide representative particle speciation monitoring that would be needed for the then anticipated

Regional Haze Rule for all of the visibility-protected CIAs where it was practical. With the

exception of ~10 sites, all IMPROVE and Protocol sites have been installed. The remaining sites

will be installed in the near future. In making the decision to support the expansion of the

IMPROVE Network, EPA also considered the value of the PM2.5 mass and speciation data in

remote areas for use by states in their implementation of the PM2.5 regulation. Provisions were

made in those regulations so that states could elect to use IMPROVE monitoring data to meet their

requirements for regional background and transport monitoring sites.

EPA requested IMPROVE change some aspects of its monitoring protocol to increase the

comparability of the monitoring to that required of states at their PM2.5 compliance and speciation

monitoring sites. The IMPROVE Steering Committee agreed to change the twice-weekly sampling

schedule to the national every third day sampling, to add routinely operated collocated instruments

at 10% of the sites to generate quality assurance data, and to provide all of the monitoring data to

the Aerometric Information Retrieval System (AIRS) database. To accommodate these changes, a

new version of the IMPROVE sampler was developed that provides for more flexible sample

schedule control and continuous monitoring of sample flow and temperature, while maintaining the

same sample collection characteristics of the original version of the sampler.

The IMPROVE sampler was designed for the IMPROVE Network and has been operated

extensively in the network and during field studies since the winter of 1987. The IMPROVE sampler

consists of four independent modules. Each module incorporates a separate inlet, filter pack, and

pump assembly; however, all modules are controlled by a singular timing mechanism. It is

convenient to consider a particular module, its associated filter, and the parameters measured from

the filter as a channel of measurement (i.e., module A). Modules A, B, and C are equipped with a

2.5 :m cyclone. The module A Teflon filter is analyzed for fine mass (PM2.5) gravimetrically,

nearly all elements with atomic mass number =11 (which is Na) and =82 (which is Pb) by proton

induced x-ray emission (PIXE) and by x-ray florescence (XRF), elemental hydrogen by proton

elastic scattering analysis (PESA), and for light absorption.

Fine aerosol concentrations are highest in the eastern United States (in the Appalachian Mountains,

Mid-South, Mid-Atlantic, and Washington, D.C. regions). Concentrations are also relatively high

in the Southern California region. The lowest concentrations occur in the Great Basin in Nevada,

the Colorado Plateau in the Four Corners states, Wyoming, and Alaska. 

The largest single component of the fine aerosol in the East is sulfate at 60-65% of the mass; in the

Pacific Northwest it is organics; and in southern California it is nitrates. In general, the largest mass

fractions of the fine aerosol are sulfates, organics and soil/dust. Of the 21 regions in the IMPROVE

Network, carbon (organic plus light-absorbing carbon) is the largest single component in ten regions, primarily in the West. Sulfate is the largest single component of fine aerosol in ten regions,

primarily in the East, and nitrates are slightly greater than carbon in the Southern California region.

The light-extinction coefficient (bext) is calculated from the measured aerosol species’

concentrations by multiplying the concentration of a given species by its light-extinction efficiency
54

and summing over all species. Since sulfates and nitrates are assumed to be hygroscopic, their lightextinction efficiencies increase with relative humidity; therefore, extinction efficiencies for soluble

species must be adjusted according to average relative humidity at each site. 

To show the effect on visibility of aerosol extinction, the deciview (dv) scale is applied to the total

(Rayleigh included) reconstructed aerosol extinction. By utilizing the dv scale, the effect of light

extinction on visibility is portrayed in a way that is approximately linear with respect to perceived

visual air quality. Because higher extinction coefficients lead to higher dv numbers, the geographic

trends in visibility follow the trends in reconstructed extinction. Pristine or Rayleigh conditions

correspond to a dv of zero.

Deciview and reconstructed light extinction varies throughout the United States in a way analogous

to fine aerosol concentrations. The greatest light extinction occurs in the eastern United States and

in southern California, while the least light extinction occurs in the relatively nonurban west and in

Alaska. However, because relative humidity (and therefore the light-scattering efficiency of sulfate

and nitrate) is higher in the East than in the West, the difference between eastern and western light

extinction is even more pronounced than the difference in aerosol concentrations.

The smallest dv value or best visibility is reported at Denali National Park with 7 dv. A broad

region, which includes the Great Basin, most of the Colorado Plateau, and portions of the Central

Rockies, has visibility impairment of less than 10 dv. Moving in any direction from this region

generally results in increasing dv values. The highest annual dv values, greater than or equal to 26

dv, occurring in the eastern United States in the general region of the Ohio River and Tennessee

Valleys. 

The summer months have the highest fine mass loadings at 19 of the 20 monitoring regions. With

few exceptions, sulfate, organic carbon, and light-absorbing carbon components of fine mass are

highest in summer as well. In the Pacific Coastal Mountains region, fine mass concentrations are

nearly the same in the summer and autumn seasons, while the West Texas fine mass loadings are

nearly the same in spring and summer. In the Northern Rocky Mountains region, fine mass loadings

are greatest during the autumn season primarily because of increased organic mass concentration.

East of the Mississippi sulfates make up about 60-70% of the fine mass in all seasons, while in much

of the inner-mountain west, fine mass concentrations are somewhat evenly split between sulfates,

carbon, and soil/dust mass concentrations.

The goal of the Regional Haze Rule is to remedy existing and prevent any future man-made

impairment in the 156 mandatory class I areas. The Rule requires visibility to improve on the 20%

haziest days and to ensure that no degradation will occur on the 20% clearest days. Five Regional

Planning Organizations (RPOs) have formed across the U.S. to ensure state compliance with the

Regional Haze Rule. These organizations will use IMPROVE data to determine current conditions

and the slope of the glide path necessary to achieve natural conditions in 60 years. State and Tribal

Implementation Plans are due in 2003 or 2008.

For more information on the IMPROVE Network and data analysis, the IMPROVE web site

(http://yampa.cira.colostate.edu/improve) was made available to the public in January 2001.
55

DEVELOPMENT OF GRIDDED SOURCE EMISSIONS INVENTORIES

(MOBILE AND STATIONARY)FOR OCS-RELATED ACTIVITIES

IN THE GULF OF MEXICO IN 1977 AND 1988

Mr. Lyle Chinkin

Ms. Dana Coe

Sonoma Technology, Inc.

Dr. Mark Yocke

ENVIRON International Corp.

Mr. David Scalfano

Northlake Engineers, Inc.

This report summarizes the approach to and results of the development of gridded emissions

inventories for mobile and stationary sources operating in the Outer Continental Shelf (OCS) areas

of the Gulf of Mexico (GOM). The subjects of this study were only those sources related to oil and

gas exploration and production activities in the OCS and included:

• crew and supply boats,

• pipeline laying ships,

• research and exploration vessels, 

• crew and supply helicopters,

• drilling ships/rigs, and

• platforms

The data sources and methods for estimating emissions from the source categories were somewhat

different. Therefore, we present a section discussing the methodologies and results for each source

category. First, we discuss issues common to more than one category.

GENERAL ISSUES 

Emissions totals for the entire GOM OCS have been prepared by source category for each pollutant

species for 1977 and 1988 (Table 1B.1). In addition, emissions were spatially allocated to a 45 (west

to east) by 26 (south to north) grid, as shown in the attached figures. Grid squares are roughly 20

km by 20 km; the grid origin (southwest corner) is located at coordinates 26 degrees North latitude

and 97.2 degrees East longitude.

We used ARC/INFO (a common GIS software package) to digitize this grid and then “intersect” the

grid cells with the geographical locations of active OCS platforms. This was done to facilitate the

allocation of estimated emissions from some source categories where the number of active platforms

in each grid served as the spatial surrogate.
56

Table 1B.1. Total Gulf of Mexico emissions by source.

1977 Annual Total Emissions (kg)

THC VOC CO NOx SOx TSP PM10 PM2.5

Helicopters 541 487 6893 24130 3334 3315 1833 1293

Crew & Supply Boats 128947 128947 1355115 12073949 2185342 300237 300237 276218

Exploration Ships 16603 16603 161539 1240136 572835 30981 30981 28502

Drill Ships 23089 23089 290017 3660733 1643671 90349 90349 83121

Pipe Laying Ships 10303 10303 100238 769528 355455 19224 19224 17686

TOTAL 179483 179429 1913803 17768475 4760638 444107 442625 406821

1988 Annual Total Emissions (kg)

THC VOC CO NOx SOx TSP PM10 PM2.5

Helicopters 966 870 12316 43113 5956 5923 3276 2310

Crew & Supply Boats 230390 230390 2421180 21572492 3904545 536433 536433 493519

Exploration Ships 16603 16603 161539 1240136 572835 30981 30981 28502

Drill Ships 41616 41616 513400 6480364 2909687 159939 159939 147144

Pipe Laying Ships 12522 12522 121837 935343 432047 23366 23366 21497

TOTAL 302098 302001 3230272 30271446 7825072 756643 753996 692973

Because some of the spatial data used provide vessel operations by lease tract, we also needed to

identify in which tract(s) each grid cell lies. This was done by manually intersecting the boundaries

of the lease tracts in the GOM OCS against grid square boundaries. Thus, each grid cell was

assigned wholly or partially to one or more tracts.

The 1993 MMS Offshore Activity Data Bases (MOADS) contains data pertaining to the numbers,

activities, fuel consumption, and engine sizes of platforms, crew and supply boats and helicopters.

These data provide 1993 emissions totals, which serve as basis for back-casting and gridding of

emissions for some of these sources categories. In addition, MMS recently published a series of data

CDs entitled “50 Year Anniversary Offshore Oil and Gas CD Collection.” Data from this 4-CD set,

and additional data downloaded from MMS Internet Website, were used to estimate the numbers

of active platforms, production levels, and drilling and pipe-laying activities and locations in 1977

and 1988. The ship vessel registration and characteristics data maintained by the US Coast Guard

(USCG) were accessed and used to characterize the size and propulsion units on research vessels.

A private data source (Offshore Data Services [ODS]) provided historical information about pipelaying and drill ship activities. For each mobile source category, specific emission factors were

obtained from the USEPA databases (AP42 and/or NONROAD) for THC, CO, NOx, SOx, and TSP.
57

VOC factors were expressed as fractions of THC emissions, and PM10 and PM2.5 factors were

expressed as fractions of TSP emissions.

The inventory for stationary sources is not complete, and no results are available at this time. The

following section focuses on the methodology being used in the stationary source emissions while

the last section reports the preliminary results of the mobile source categories.

STATIONARY SOURCES

Production Platforms

Activity Data Source: Several methods of activity data sources were explored before the one

described below was chosen.

First, MMS historical records were reviewed in the Information Technology Department (ITD) to

determine if records of actual platform equipment and/or fuel consumption were available. This

included review of inspectors’ records and safe charts. Data on actual equipment, etc. from 1977 and

1988 were not available in the MMS records. Archived safe charts were not retained; only current,

up-to-date versions were on file. Inspectors’ reports from 1977 and 1988 did not include equipment

lists. 

Second, we contacted some oil companies to determine whether records from 1977 and 1988 were

available. Most did not have access to record documents that would describe equipment or activity

from 1977 and 1988. A couple of companies did provide a list of equipment from 1988 or

schematics from 1977 on three to five platforms, but without certain data—such a horsepower

ratings— it was difficult to calculate estimated emissions. Also, such a small representation of those

platforms from 1977 and 1988, if extrapolated on the basis of production, could introduce larger

discrepancies in the final database. 

Finally, it was decided to use the 1993 MOADS database of emissions as related to production rates.

Production rates from 1977, 1988, and 1992/3 are readily available from the MMS. Once

determined, these emissions/production rates would be applied production rates and platform

locations as per records from MMS from 1977 and 1988. 

Gas reported vented or flared in 1993 MOADS database will be used to establish a ratio of gas

vented / flared vs. production rates. MMS records from 1977 and 1988 for gas vented and/or flared

is available from OGAR B reports. These reports do not differentiate between venting and flaring.

Once the gas vented/flared rate vs. production from 1977 and 1988 is established, then the

appropriate emissions can be adjusted to represent the variation in venting/flaring in 1993 to 1977

and 1988. 

For construction activities, i.e. platform installations, the list of platforms installed in 1977 and 1988

is available from the MMS. At these locations, a estimate of installation time, derrick barge spread

and fuel consumed and emissions generated will be added to this platform location. 
58

Emissions Factors: By default, i. e. using the 1993 MOADS emissions as related to production rates,

the emission factors used in the 1993 MOADS database will be the same used in the 1977 and 1988

emissions. These factors were predominately AP-42 for the following sources:

1. Crude and Diesel Storage Tanks,

2. Natural Gas and Diesel Reciprocating Internal Combustion Engines,

3. Line/Process Heaters,

4 Turbines,

5. Flares and Vents,

6. Fugitives,

7. Gas Sweetening, and 

8. Gas Dehydration.

A complete description of the emission factors is available in MMS report 95-0040 Gulf of Mexico

Air Quality Study, Final Report.

Emissions Calculations: The emission calculations are going to be a direct reflection of those in the

1993 MOADS database except for a slight modifications for changes in flaring and venting and

platform installation activities. 

Once the venting and flaring rates vs. production rate from 1993 is determined, then the combined

vent/ flare rate vs. production rates for 1977 and 1988 will be determined. The portion of emissions

due to venting and flaring in 1993 will then be adjusted up or down depending on the comparison

from 1993, 1977, and 1988.

The emissions for each platform installation will be calculated using a kg/hp-hr emission factor and

the assumed hp and duration.

PM10 and PM2.5 were estimated from TSP using the fractions 1.0 and 0.92, which were taken from

the EPA NONROAD SPECIATE database version 1.5 profile # 32202—Heavy duty diesel. Due to

lack of data, it was assumed that VOC emissions are approximately equal to THC. This assumption

seems reasonable because heavy-duty diesel engines emit little methane or ethane.

Drill Rigs

Activity Data Source: Drill rigs differ from drill ships (see below) in that drill rigs are allocated to

a production platform and not to an exploratory well. Drill rigs could be jack-up, platform, or tender

type rigs. We obtained borehole data from the MMS Website. These data contained detailed

information about the locations and time of installation of boreholes for both 1977 and 1988. To

determine the duration of the drilling for each borehole, the “spud date” was assumed to indicate the

start of drilling, and the “total depth date” the final day. Continuous operation was assumed between

these two dates. The effective drill period was assumed to be the duration between the spud and total

depth dates or 10 days, whichever was longer. Only drilling that occurred within the calendar year

for each year was considered (if drilling lasted from December 1988 to January 1989, only

December was counted).
59

Emissions Factors: Drill ship emission factors were obtained from Table 5-1 of Analysis of

Commercial Marine Vessels Emissions and Fuel Consumption Data (EPA, February 2000,

(http://www.epa.gov/otaq/models/nonrdmdl/c-marine/r00002.pdf). The equation published therein

for calculating PM, NOx, CO, and HC emissions factors is:

Emissions Rate (g/kW-hr) = a (Fractional Load)^(-x) + b

The equation for SO2 is:

Emissions Rate (g/kW-hr) = a (Fuel Sulfur Flow in g/kW-hr) + b

The equation given for fuel consumption is::

Fuel Consumption (g/kW-hr) = 14.12/(Fractional Load) + 205.717

However, since we didn’t have fractional load data, we used an average drill rig fuel usage rate of

2,256 gallons/day, which was published in a April 1995 letter from the Offshore Operators

Committee to Chris Oynes of the MMS.

Marine diesel fuel sulfur levels were obtained from Table 4 of In-Use Marine Diesel Fuel (for EPA

by ICF, August 1999 [http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/dfuelrpt.pdf] as 0.91 %

by weight for DMB [the predominant marine fuel for large engine vessels]. The mass of emissions

per mass of fuel consumed emission factors were converted to kg emissions/ gal fuel using a fuel

density of 2.6kg/gal.

Emission factors were estimated at 100% load.

Emissions Calculations: Emissions were calculated for each drill rig reported in the MMS borehole

database for 1977 and 1988. Platform coordinates were used to allocate emissions to the appropriate

location. Since only a small fraction of the rig time is spent in transit and most borehole locations

in these years were near the coastline, we allocate all emissions to the platforms containing the

borehole (i.e., we did not account for emissions associated with travel to-and-from the borehole

locations).

MOBILE SOURCES

Crew and Supply Helicopters

Activity Data Source: There are approximately thirteen OCS helicopter operating companies

represented in the 1993 MOADS. 1993 helicopter activity levels, areas of operations, as well as

emissions estimates were derived from this data base..

Emissions Factors: Helicopter emission factors used are from AP-42, Table II-1-8. We selected

emissions factors representative of turbine engines in the helicopter fleet operating in the GOM OCS

region.
60

Emissions were estimated for all phases of operation since these helicopters most often operate

within the convective marine mixing layer. Since landings/takeoffs (LTOs) comprise a very small

portion of the total hours of operation and no LTO data are available, they are ignored in this

analysis. Furthermore, since helicopters utilize a relatively constant amount of power for all phases

of operation, a single emission factor was used for all flight modes. Thus, emissions were estimated

as the product of the emission factor and the total hours of flight.

The AP-42 emissions factors, which are expressed in kg of emissions per kg of fuel consumed

(kg/kg fuel), were converted into kg/gal fuel units by assuming a jet fuel density factor of 2.6 kg/gal.

Emissions Calculations: 1988 and 1977 helicopter emissions were estimated by assuming that OCSwide emissions were proportional to the number of platforms operating in those years compared to

1993. The total OCS emissions were then spatially allocated by assuming that emissions in each cell

were proportional to the number of operating platforms in that cell.

PM2.5 and PM10 were estimated from TSP by applying mass fractions of 0.390 and 0.553 taken

from the NONROAD SPECIATE database version 1.5 (profile #34001 - Jet Aircraft). VOC was

estimated as 90% of THC. Based upon the SPECIATE database (Version 3.0, profile 1098 - Aircraft

Landing/Takeoff (LTO) - Commercial), it was assumed that methane and ethane comprise about

10% of total hydrocarbons.

Crew and Supply Boats

Activity Data Source: The MOADS data contains 1993 annual usage data in hours and rated

horsepower for the crew and supply boats by engine type.

Emissions Factors: The crew and supply boat emission factors were derived based on information

given in Table 5-1 of Analysis of Commercial Marine Vessels Emissions and Fuel Consumption

Data (EPA, February 2000, http://www.epa.gov/otaq/models/nonrdmdl/c-marine/r00002.pdf). This

reference presents the following equation for calculating PM, NOx, CO, and HC emissions factors:

Emissions Rate (g/kW-hr) = a (Fractional Load)^(-x) + b

The equation for SO2 is:

Emissions Rate (g/kW-hr) = a (Fuel Sulfur Flow in g/kW-hr) + b

The equation for fuel consumption is:

Fuel Consumption (g/kW-hr) = 14.12/(Fractional Load) + 205.717

Marine diesel fuel sulfur level was obtained from Table 4 of In-Use Marine Diesel Fuel (for EPA

by ICF, August 1999, (http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/dfuelrpt.pdf) as 0.36 %

by weight for DMA, the predominant marine fuel for medium- and small-engine vessels.
61

Emission factors were estimated at 70% load, based upon Table 5-2 in the reference above, and

expressed as mass per horsepower-hour (hp-hr).

Emissions Calculations: The 1977 and 1988 total emissions were estimated by scaling the 1993

emissions by the ratio of platforms operating in 1977 and 1988 to those operating in 1993,

respectively. The total emissions were increased by a factor of 1.56 to account for the fact that only

64% of the crew and supply boat operators responded to the 1993 MOADS activity survey. The

spatial allocation procedures used were the same as for crew and supply helicopters, with each cell

receiving the amount of emissions proportional to the number of platforms present.

PM10 and PM2.5 were estimated from TSP using the fractions 1.0 and 0.92, which were obtained

from the NONROAD SPECIATE database version 1.5 profile # 32202—Heavy duty diesel. For lack

of specific data, it was assumed that VOC emissions are approximately equal to THC. This

assumption seems reasonable in the case of heavy-duty diesel engines since they emit little methane

or ethane.

Drill Ships

Activity Data Source: We obtained borehole data from the MMS Website. These data contained

detailed information about the locations and time of installation of exploratory boreholes for both

1977 and 1988. To determine the duration of the drilling for each borehole, the “spud date” was

assumed to indicate the start of drilling, and the “total depth date” the final day. Continuous

operation was assumed between these two dates. The effective drill period was assumed to be the

duration between the spud and total depth dates or 10 days, whichever was longer. Only drilling that

occurred within the calendar year for each year was considered (if drilling lasted from December

1988 to January 1989, only December was counted.

Emissions Factors: Drill ship emission factors were obtained from Table 5-1 of Analysis of

Commercial Marine Vessels Emissions and Fuel Consumption Data (EPA, February 2000,

(http://www.epa.gov/otaq/models/nonrdmdl/c-marine/r00002.pdf). The equation published therein

for calculating PM, NOx, CO, and HC emissions factors is:

Emissions Rate (g/kW-hr) = a (Fractional Load)^(-x) + b

The equation for SO2 is:

Emissions Rate (g/kW-hr) = a (Fuel Sulfur Flow in g/kW-hr) + b

The equation given for fuel consumption is::

Fuel Consumption (g/kW-hr) = 14.12/(Fractional Load) + 205.717

However, since we did not have fractional load data, we used an average drill ship fuel usage rate

of 2,256 gallons/day, which was published in a April 1995 letter from the Offshore Operators

Committee to Chris Oynes of the MMS.
62

Marine diesel fuel sulfur levels were obtained from Table 4 of In-Use Marine Diesel Fuel (for EPA

by ICF, August 1999 [http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/dfuelrpt.pdf] as 0.91 %

by weight for DMB [the predominant marine fuel for large engine vessels]. The mass of emissions

per mass of fuel consumed emission factors were converted to kg emissions/ gal fuel using a fuel

density of 2.6kg/gal.

Emission factors were estimated at 100% load.

Emissions Calculations: Emissions were calculated for each drill ship voyage reported in the MMS

borehole database for 1977 and 1988. Borehole coordinates were used to allocate emissions to the

appropriate grid cell. Since only a small fraction of the vessel time is spent in transit and most

borehole locations in these years were near the coastline, we allocate all emissions to the cells

containing the borehole (i.e., we did not account for emissions associated with travel to-and-from

the borehole locations).

Exploration Vessels

Activity Data Source: The activities of exploration vessels were estimated using 1988 MMS

exploration and research permit data. 1977 permit data were not available, so we assumed the levels

and locations of exploration vessel activities in 1977 to be the same as 1988. 

The MMS data were arranged by individual ship voyage with a specified time frame and the area

of exploration. We obtained USCG vessel registration data and vessel-specifications for the vessel

lists in the MMS permit archives. If the rated horsepower of a ship’s engines was not available in

this USCG database, horsepower was estimated using a correlation between boat length and

horsepower developed from the available data points. If boat length was also unavailable, an average

value of 3,000hp was used. 

The MMS permit data specified those lease block(s) in which a specific research/exploration vessel

was to operate. We assigned emissions from each voyage uniformly to all grid cells contained within

the listed lease block(s). The records that did not have a block assigned or had inconsistent data were

examined and treated on a case-by-case basis. For example, in the case of voyages that involved

a single ship without an assigned block, emissions were spread over the entire OCS. When a voyage

date for a specific ship overlapped significantly those of a second voyage of the same ship, the

second record was ignored to avoid double-counting. It was also necessary to correct obvious

inconsistencies or errors in the ship registry numbers. 

The number of operating days was estimated and allocated based upon the permit dates and blocks.

Although in some cases the 1988 permits allowed exploration into 1989, the numbers of operating

days were estimated using 31 December 1988 as a cutoff. It was determined through discussions

with operators that the permit periods are often much longer than the actual voyages. Based on these

discussions, the number of operating days per permit was assumed to be two weeks or the total

permit period, whichever was smaller. 
63

Emission Factors: Exploration vessel emission factors were calculated in the same manner as for

crew and supply boats. However, the load factor used was 60% (based on discussions with

operators), and SO2 emissions were estimated assuming 0.91% fuel sulfur content, which is the

average for DMB, the most common distillate fuel for large-engine ocean-going vessels according

to In-Use Marine Diesel Fuel (EPA, Aug 1999).

Emissions Calculations: Horsepower ratings were determined by matching either the ship’s name

or registry number to the available USCG vessel information data. Registry number was used first

and if that did not produce a match, then the name was used. If these two did not produce a match,

then the average of 3,000hp was used -- this occurred in the cases of only four voyage permit

records.

PM10 and PM2.5 were estimated from TSP using the fractions 1.0 and 0.92, which were obtained

from the EPA NONROAD SPECIATE database version 1.5 profile # 32202—Heavy duty diesel.

Due to lack of data, it was assumed that VOC emissions are approximately equal to THC. This

assumption seems reasonable because heavy-duty diesel engines emit little methane or ethane.

Estimated exploration vessel emissions for each voyage were uniformly allocated to those grid cells

within the lease tracts listed in each permit. If there were multiple tracts in any single permit record,

each tract was assumed to have received an equal portion of the emissions, without regard to the size

of the tract. Permit records that covered the entire Gulf had their associated emissions spread evenly

across the entire OCS grid.

Pipe-Laying Ships

Activity Data Source: We obtained information about pipelines installed in the GOM in 1977 and

1988 from Offshore Data Services (ODS). These data included information about the area (tract)

into which the pipe was installed, pipe diameter, and pipeline length. In 1988, a few of the pipelines

started and terminated in different tracts. These cases were examined individually. If the dominant

length of the pipeline extended in one tract, then that tract was assigned the whole length of the pipe.

If the distance in each tract was roughly equal, the pipe length was divided between the tracts. 

The ODS database also included some information on “days-to-complete,” which was assumed to

be equal to the duration of pipe-laying activities in each case. However, this information was

missing from many records. Using data from the records that were complete, two statistical

regression analyses were performed using Excel, one relating pipe length to installation duration,

and the second relating both pipe length and diameter to installation duration. Although the

regression using both pipe length and diameter had fewer complete records, it produced a stronger

regression coefficient. Thus, the second regression was used to estimate the duration of pipe

installations cases with missing completion time records.

All pipeline installations were assumed to have been performed using ships with 3,000 hp engines

at 60% load.
64

Emission Factors: The emission factors for pipe ships were derived in the same manner as for

exploration vessels, using 0.91% sulfur content.

Emissions Calculations: The emissions for each installation were calculated using a kg/hp-hr

emission factor and the assumed hp and duration.

PM10 and PM2.5 were estimated from TSP using the fractions 1.0 and 0.92, which were taken from

the EPA NONROAD SPECIATE database version 1.5 profile # 32202—Heavy duty diesel. Due to

lack of data, it was assumed that VOC emissions are approximately equal to THC. This assumption

seems reasonable because heavy-duty diesel engines emit little methane or ethane.

Spatial allocation of estimated emissions from pipe-laying ships began by totaling the emissions in

each tract. Then, we assumed that pipelines generally extend from one facility or platform to

another. Thus, the emissions total for each tract was allocated to each grid cell in proportion to the

number of active platforms in the cell.

RESULTS

Table 1B.1 summarizes the emissions totals by pollutant species and by source type for 1977 and

1988. Crew and supply boats clearly are the largest contributors to emissions totals in both years.

Since all of the mobile sources are internal combustion engines, NOx, CO, and SOx are the species

with the largest emissions. Consistent with the expansion of exploration and production levels,

estimated emissions in 1988 were roughly 70% larger that those calculated for 1977.

The figures in Table 1B.1show the gridded distribution of estimated emissions totals by pollutant

species in 1977 and 1988. The spatial emissions patterns reflect the geographical distributions of

active platforms in those years. Also shown are the distributions of NOx emissions by mobile source

type for 1977 and 1988. [NOx was selected because it has the largest estimated emission totals of

all species.]
65

SESSION 1C

GAS HYDRATES IN THE GULF OF MEXICO

Chair: Dr. Mary Boatman, Minerals Management Service

Co-Chair: Mr. Jesse Hunt, Minerals Management Service

Date: December 5, 2000

Presentation Author/Affiliation

Gas Hydrates in a Complex Geologic

Province—Northern Gulf of Mexico

Continental Slope

Dr. Harry H. Roberts

Coastal Studies Institute

Louisiana State University

Application of High-Resolution Seismology

to Issues Related to Gas Hydrates in the Gulf

of Mexico

– Document not submitted –

Dr. Joe Gettrust

Naval Research Laboratory, Stennis

Monitoring the Physical and Chemical

Conditions Affecting the Hydrocarbon

System Within the Hydrate Stability Zone of

the Northern Gulf of Mexico

Dr. J. Robert Woolsey, Director

The Center for Marine Resources and

Environmental Technology

The University of Mississippi

Gas hydrates in the Gulf of Mexico: A

Geochemical Perspective

Dr. Roger Sassen

Geochemical and Environmental

Research Group

Texas A&M University
67

GAS HYDRATES IN A COMPLEX GEOLOGIC PROVINCE—

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE

Dr. Harry H. Roberts

Coastal Studies Institute

Louisiana State University

The northern Gulf of Mexico (GOM) slope province exhibits complex structural relationships

resulting from dynamic adjustments between sediments and salt. Numerous faulted pathways exist

for deep subsurface fluids and gases to be transported to the modern seafloor. Seafloor response to

these hydrocarbon-rich fluids and gases is highly variable and dependent largely on rate and duration

of delivery as well as fluid and gas composition. Rapid expulsions of fluids (including fluidized

sediment) and gases generally result in buildups of sediment in the form of cones (mud volcanoes)

that vary from a few meters to several kilometers in diameter and/or sheet-like flows that may

extend tens of kilometers downslope. Slow seepage promotes lithification of the seafloor through

precipitation of a variety of mineral species. Microbial utilization of hydrocarbons encourages the

precipitation of 13C-depleted Ca-Mg carbonates as by-products. These carbonates have δ 13C values

that are light (to –55 % PDB). The 13C-depleted carbonates form mounds and hardgrounds that occur

over the full depth range of the slope. Mounds have relief of up to 30 m, but mounds of 5-10 m relief

are most common at sites thus far investigated. Carbonates comprising the mounds are mixed

mineral phases of aragonite, Mg-calcite, and dolomite with Mg-calcite being the most common.

Other products like barite are precipitated from mineral-rich fluids that arrive at the seafloor in lowto-moderate seep rate settings. However, barite precipitation is not as pervasive as that of 13Cdepleted carbonates. Intermediate flux settings are best described as areas where gas hydrates occur

at the seafloor or in the very shallow subsurface. This environment displays considerable variability

with regard to surficial geology and on a local scale have elements of both rapid and slow flux

settings. Intermediate flux environments appear to have the unique set of conditions necessary to

support and sustain densely populated communities of chemosynthetic organisms. Most of these

areas are associated with faulting at the edges of intraslope basins. At these sites, surficial or shallow

subsurface gas hydrates (accessible by piston coring) are oriented along these faults and not in broad

areas characterized by distinct bottom simulating reflectors (BSRs) as is the case in many simpler

geologic settings. Shallow gas hydrates are composed of a complex mixture of biogenicthermogenic methane and other thermogenic gases. In situ experiments have shown that slight

variations in near-bottom water temperature resulting from a variety of natural oceanographic

processes cause gas hydrate dissociation and out-gassing resulting in the degradation to

disappearance of surficial gas hydrate mounds.

INTRODUCTION

Much of what we know about the geology of the northern Gulf continental slope comes from data

collected in search of hydrocarbons. The northern Gulf slope is the most mature deep-water oil and

gas province in the world. With 3D-seismic and higher resolution acoustic data sets used for

geohazards assessment, a new vision of the slope seafloor is being established. Even though these

data sets are exceptionally revealing regarding the seafloor and probable processes impacting it, they
68

typically cover small areas. These high resolution data sets are site specific and usually separated

by considerable distances. Therefore, the wide variety of bottom features and their links to formative

processes have been difficult to determine. However, multibeam bathymetry and 3D-seismic have

provided a detailed and yet regional view of the slope surface. These two data types have

emphasized the complex surface geology. Mapping surface amplitude anomalies from 3D-seismic

data (Roberts et al. 1992a; Roberts 1996; Hill 1996) has helped identify fluid and gas expulsion

features. Coupled with polarity analysis of the surface reflector, these methodologies can identify

hard-bottom from soft-bottom areas as well as areas charged with gas. Calibrated to “ground-truth”

data provided by piston cores and direct observation and sampling using manned submersibles, it

is now clear that fluid and gas expulsion is an important process affecting both seafloor geology and

biology across the entire depth range of the northern and northwestern GOM continental slope.

Although most calibration data have been acquired from the upper slope (< 1000 m water depth),

3D-seismic amplitude data, piston cores, and a few ROV and manned submersible observations

confirm the importance of fluid and gas expulsion processes to the base of the slope at water depths

of about 2500 m.

On the flanks of intraslope basins, complex faulting and associated salt masses focus the flux of

subsurface fluids and gases to the modern seafloor resulting in a variety of response features

generally superimposed on dome-like regional features supported by underlying salt. Such complex

areas are regionally distinct on the multibeam bathymetry image of Figure 1C.1 from smoothbottom areas representative of the intraslope basins. The small-scale geologic features that mantel

salt-supported domes and other salt-associated areas of the seafloor are partly the products of fluid

and gas expulsion. These intraslope basins formed within large salt masses that were emplaced

during the Oligocene and Miocene (Diegel et al. 1995). Later, Cenozoic deposition of large volumes

of siliciclastic sediments mobilized allochthonous salt masses out of the shelf minibasin and

detachment provinces into the tabular salt and minibasin province (Prather et al. 1998). Subsequent

loading of the salt has formed the complex array of basins and basin-flanking features that shape

today’s slope surface (Figure 1C.1). 

This paper organizes data on surficial geology, and to a lesser extent biology, related to the flux of

fluids and gases to the modern surface of the slope. Even though quantification of flux rate has been

an elusive target, the present database qualitatively suggests a strong relationship between flux rate

and seafloor response. The objective is to explore a qualitative framework for understanding the

links between flux-related processes and geologic-biologic responses at the slope surface. Special

emphasis is placed on gas hydrates and authigenic carbonate mounds. 

FLUID AND GAS EXPULSION FEATURE SPECTRUM

Although a quantitative relationship between fluid–gas expulsion and geologic-biologic response

has yet to be derived, it is clear that qualitatively geologic-biologic response is not only dependent

on fluid and gas type but largely on flux rate and frequency of delivery events (Roberts and Carney

1997), Figure 1C.2. Data on the frequency, composition, and impacts of expulsion events are

essentially nonexistent for the slope. However, repeated observations of expulsion sites on the upper

continental slope of the northern Gulf support the short-term episodic nature of fluid-gas venting

and seepage at a scale still not predicted by numerical simulations of the process.
69

Figure 1C.1. The Gulf of Mexico continental slope off the state of Louisiana as portrayed by

computer enhanced multibeam bathymetry.

Figure 1C.2. This figure summarizes the spectrum of seafloor responses associated with rapid

fluid and gas venting (mud-prone) to slow seepage (mineral-prone).
70

Seafloor features that are the consequence of the fluid-gas expulsion process convey information

about the types of fluid and gases being delivered, the episodic nature of the delivery process, the

duration of expulsion events, and the delivery rate. On both high resolution and lower frequency

exploration-scale seismic profiles, most expulsion features are accompanied by an acoustically

opaque zone (acoustic wipe-out zone) that extends from the seafloor into the subsurface (Figure

1C.1). The general interpretation for this response is the presence of a free gas phase (bubbles) in

surface and near-surface sediments. On seismic records, gas-charged sediments are identified by

high amplitude reflecting horizons and/or acoustic wipe-out zones below (Bryant 1981). Although

an acoustically opaque response on a seismic record can result from a number of surface and

subsurface conditions (Roberts et al. 1999a), expulsion features are associated with free gas as well

as fluids. In most cases, these features are clearly linked to faulting as determined from seismic

records.

Rapid Flux (Mud Prone) Case

The vertical migration of gas and fluids through unconsolidated-to-semiconsolidated sediments may

create a slurry-like mixture of sediment, gas, and water that may be extruded on the seafloor to form

a variety constructional features (Hedberg 1974). Mud volcanoes and extruded mud sheets have

been observed from many different marine geologic settings (Hovland and Judd 1988), ranging from

degassing and dewatering of accretionary prisms during subduction to areas of active salt

deformation like the Gulf (Neurauter and Bryant 1990) to breached anticlines in the Caspian Sea

(Corthay and Aliyev 2000). 

Numerous examples of features produced by rapid flux of fluidized sediment can be found on the

northern GOM continental slope. Most of these features develop into conical mounds of various

dimensions that are collectively referred to as mud volcanoes. Mud volcanoes are generally

accompanied by a vertical pathway of acoustic attenuation (acoustic wipe-out zone) that is

commonly interpreted as an indicator of free gas as well as sediment remolding in a subsurface

feeder system (Figure 1C.3). This interpretation is easy to accept since abundant gas can frequently

be observed escaping from the central vent of active mud-extrusion features.

In the rapid flux setting, exemplified by mud volcano formation, considerable heat is transported

to the modern seafloor along with fluidized sediment. McDonald et al. (2000) have just published

measurements from a mud volcano from the Garden Banks area that reached an absolute

temperature of 48<C on a part of the slope with ambient water temperatures that range between 4-

7<C. This heat flux can preclude the formation of gas hydrate or decompose it if it forms during

periods of mud vent inactivity. The process of rapid vertical flux of fluids and gases suggests that

there is little time for the hydrocarbon fraction of the carrier fluids to be microbially oxidized.

Sassen et al. (1994) note that oil-stained sediments from an active mud volcano in Green Canyon

143 (27<50.14'N, 91<21.93'W) have characteristics (an envelope of n-alkanes and isoprenoids)

suggesting that the oil has not been microbially degraded. In this case, bacterial oxidation is unable

to keep pace with high rates of hydrocarbon venting typical of the rapid flux and mud prone setting.

Fined-grained expulsions, both as suspended sediment and as flows, create environments that are

hostile for benthic fauna. For filter feeders, high suspended sediment loads overwhelm respiratory
71

Figure 1C.3. A high resolution subbottom profile across an active mud volcano in Green Canyon

143. Rapid venting of fluidized sediment, other fluids (including crude oil) and gases

have created this cone-like buildup and its downslope mudflow deposits.

systems, and flows can bury benthic organisms or make life positioning difficult or impossible.

Extruded sediment may derive from sources containing little sulfide. High sediment delivery rates

preclude sulfide-producing anaerobic oxidation of hydrocarbons. Mat-forming bacteria Beggiatoa

may colonize the surface of hydrocarbon-laced fluidized sediments surrounding the venting area or

on recently deposited flows. Once the fluidized mud has been deposited, lucinid-vesycomyid clams

can colonize as biodegradation of incorporated hydrocarbons produces a sufficient sulfide source.

Since expulsion events are episodic, any one flow deposit has a limited hydrocarbon charge and
72

sulfide-producing potential. For this reason infaunal lucinid clam communities establish themselves

and then quickly deplete the available sulfide source. Large surficial accumulations of lucinidvesycomyid clam shells are frequently scattered over the surfaces of extruded muds. Multiple

lucinid-vesycomyid shell layers in piston cores through sediments near active expulsion features

confirm the episodic nature of mud extrusion events.

Moderate Flux Case

Below water depth of ~ 500 m, sites on the upper continental slope of the northern Gulf that fall

within this category commonly display gas hydrate exposures at the seafloor. These sites are

characterized by dense and comparatively diverse chemosynthetic communities consisting of

bacterial mats, lucinid-vesycomyid clams, pogonophoran tube worms, vestimentiferan tube worms,

and bathymodiolid mussels. Only infrequent occurrences of chemosynthetic organisms have been

reported shallower than the gas hydrate “water depth window” which is dictated by termperature,

pressure, and mixture of hydrocarbon gases (Sloan 1990). Association of gas hydrates and

chemosynthetic communities is probably not fortuitous since gas hydrates store the trophic resources

necessary to sustain long-term and diverse chemosynthetic communities. Such communities require

sustainable sources of hydrocarbon gases and sulfide. As Carney (1994) suggests, “solid-phase gas

hydrates of methane and water, which are stable at the pressure and temperature conditions below

400-500 m of water depth in the GOM, may be that unique aspect of deep ocean methane and sulfide

chemistry that allows for chemosynthetic community development.” 

A mound-like feature (“Bush Hill”) in Green Canyon 185 (27°46.97'N; 91°30.47'W) is a site where

gas hydrates are frequently observed as exposures at the seafloor (Figure 1C.4). At this locality,

seismic profiles indicate that vertically oriented acoustically opaque corridors connect with the deep

subsurface. An antithetic fault that connects to a major fault system penetrating deep Pliocene

sediments connects to the GC185 mound (Cook and D’Onfro 1991). Gas analyses of gas hydrate

at the mound crest prove the incorporation of thermogenic hydrocarbons derived from the deep

subsurface (Table 1C.1). On 3D-seismic surface amplitude data the mounds shown in stand out as

high amplitude features of negative polarity, suggesting free gas in near-surface sediments (Roberts

et al. 1992a).

Within a few tens of meters at the GC185 mound top one can move from areas of outcropping gas

hydrate covered with orange Beggiatoa mats (Figure 1C.5) to complex and densely arranged

chemosynthetic communities of mussels and tube worms mixed with small outcrops of authigenic

carbonate. 

It is apparent that in many cases, gas is being vented up faults through the gas hydrate complex and

into the overlying water column. Minor faults and fractures are the probable conduits for free gas

through the hydrate stability zone. It is also apparent through site specific experiments at GC185

(Roberts et al. 1999b) that surficial gas hydrates decompose and out-gas as a product of water

column temperature changes. Out-gassing from an exposure of gas hydrate is strongly coherent with

the water temperature signal (Roberts et al. 1999b). Even though temperature fluctuations are

relatively small during the period when out-gassing and water temperature were simultaneously

measured (maximum variation ~ 1.5°C), much more energetic out-gassing is expected during the
73

Figure 1C.4. A north-south high resolution seismic profile (15 in3 water gun) across the mound

in Green Canyon 185 (Bush Hill) which contains gas hydrate deposits at the surface

and in the shallow subsurface.
74

Figure 1C.5. An outcropping of gas hydrate at apex of the Green Canyon 185 mound. This

outcrop was orange in color covered with gray mud on which orange Beggiatoa mats

occurred. The field of view is about 2 m across.

Table 1C.1. Green Canyon 185 molecular and isotopic compositions of gas hydrate samples.

Sample

δ13C

C1

δD

C1

%C1 δ13C

C2

%C2 δ13C

C3

%C3 δ13C

i - c4

%

i - c4

δ13C

n - C4

%

n - C4

δ13C

i - C5

%

i - C5

δ13C

n - C5

%

n - C5

%

neo-C1

δ13C

CO2

Gas Hydrate -42.9 -163 83.1 -28.6 7.6 -24.9 8.1 -27.2 0.9 -22.1 0.2 -27.8

Gas Hydrate -42.2 -190 71.7 -29.0 10.6 -25.5 12.6 -27.6 2.6 -22.8 1.7 -26.2 0.8 -20.0

Gas Hydrate -43.5 -177 80.2 -29.7 9.4 -25.5 7.3 -27.9 1.6 -23.0 1.2 -24.8 0.3 -23.7

Gas Hydrate -42.5 -193 72.1 -29.2 12.4 -25.7 11.4 -27.8 2.3 -22.7 1.6 -24.7 0.3 -21.6

Gas Hydrate -42.9 -115 85.7 -28.6 6.3 -25.6 6.1 -26.8 1.1 0.8

Gas Hydrate -43.6 -167 72.1 -29.8 10.5 -26.1 12.4 -28.1 2.5 -24.0 1.7 0.7 <0.1 +17.5

Data from Sassen et al. (1999a, 1999b) and Sassen et al. (1998).
75

passage of Loop Current eddies that can elevate water temperatures near the bottom on the upper

slope by 4-6°C in water depth to ~1000 m (Hamilton 1990). Repeated observations of the same sites

over nearly a decade of submersible research suggests that some sites go through cycles of

decomposition and formation at an interannual frequency. 

Slow Flux (Mineral Prone) Case

GOM slope sites that demonstrate slow vertical fluid and gas flux display abundant forms of seafloor lithification but have few macro-scale chemosynthetic organisms. Instead, they are inhabited

by microbial communities of sulfate-reducing bacteria, methanogenic bacteria, sulfide- and

methane-oxidizing bacteria, and bacteria that oxidize thermogenic hydrocarbon gas and crude oil

(Jannasch 1984; Sassen et al. 1993). Microbial communities are critical to carbon cycling in intermediate-to-slow seepage environments and to producing chemical gradients that result in precipitation of calcium-magnesium carbonates (Ritger et al. 1987; Roberts et al. 1992a; Paull et al. 1992),

and mineral phases such as barite (Roberts and Aharon 1994; Fu et al. 1994; Torres et al. 1996).

Authigenic carbonates produced by these bacterially-mediated processes inherit their δ 13C

signatures from a carbon pool comprised of carbon that is converted to dissolved inorganic carbon

(DIC) from crude oil to biogenic methane as well as DIC from sea water. Therefore, it is unlikely

that the carbon in Ca-Mg carbonates is derived from an individual source. However, authigenic

carbonates from areas seeping primarily crude oil have δ 13C values that are close to crude oil value

(-24 o/oo to –34 o/oo PDB), while similar carbonates from methane seeps are more 13C-depleted.

Therefore, the δ 13C values associated with hydrocarbon seep-vent carbonates appear to be a window

into the parent carbon sources and the formative microbial processes that initiated precipitation

sources (Aharon et al. 1990). Carbonates derived from sites of fermentation are much closer to δ

13C values for normal marine biogenic carbonates. The general range of δ 13C values for seep-vent

related authigenic carbonates from the northern GOM slope is from –18 o/oo to –58 o/oo PDB, while

the δ 13C range is about 1.8 o/oo to 5.6 o/oo PDB (Roberts and Aharon 1994). 

Mineralogical complexity of authigenic carbonates from the northern Gulf is greater than

counterparts from the base of the Florida Escarpment (Paull et al. 1992), and all three

phases-aragonite, Mg-calcite, and dolomite occur (Roberts et al. 1992b). Magnesian calcites are the

most commonly encountered authigenic carbonate mineral phase.

Authigenic carbonates are found as nodular masses within surficial sediment, hardgrounds, slabs,

and mound-like buildups of various dimensions. Nodular masses, hardgrounds, and crusts are most

common to the intermediate-to-slow flux rate settings. Mounded carbonates and chimneys are also

found primarily in slow flux rate environments. Cement morphologies and mineralogies associated

with the various authigenic carbonates found in association with seep-vent sites are highly variable.

These morphologies range from microcrystalline dolomites and Mg-calcites to void-filling and

circum-granular acicular and botryoidal aragonites (Roberts et al. 1992b; Roberts and Aharon 1994).

One of the best examples of mounded authigenic carbonates is in Green Canyon 140 (Figure 1C.6).

On the 3D-seismic surface amplitude data, the Green Canyon 140 dome crest provides very high
76

Figure 1C.6. A high resolution seismic profile across a part of the dome in Green Canyon 140.

Note the irregular surface made up of authigenic carbonate mounds that appear to

have developed in a slow seepage environment.
77

amplitude response because of the high reflective areas of lithified seafloor. The positive polarity

of the 3D-seismic surface reflector suggests a hard-bottom area with limited gas-charge near-surface

sediment (Roberts et al. 1992a). High resolution seismic profiles and side-scan sonar swaths across

the dome crest (water depth ~240-280 m) reveal a mounded seafloor. Individual mounds express

themselves as hard targets with sharp boundaries, irregular surfaces, and average relief above the

surrounding seafloor ranging between 5-10 m (Figure 7). Direct observations and sampling of these

mounds using manned submersibles clearly identify them as hard, rocky structures with very few

attached organisms (e.g., gorgonians). Each mound appears as an accumulation of chaotically tilted

and fractured blocks separated by well-defined crevasses (joints) that apparently result from flexure

of underlying shallow salt. Laboratory analyses on these carbonates (Roberts et al. 1992b) indicate

that they are extremely 13C-depleted (δ13C values to –55o/oo PDB) and have a mineralogy that is

primarily Mg-calcite 1>moleo/oo Mg, with dolomite frequently lining pores and fractures (Roberts

1992b). The range of δ13C values for samples from these mounds suggests a variety of hydrocarbon

sources. The δ13C values range from those associated with crude oil that is found trapped in the

pores of many samples from these mounds to the extremely 13C-depleted carbonate cements

suggesting that methane is the contributor of isotopically light carbon (Roberts and Aharon 1994).

The slow flux of fluids and gases to the modern seafloor in this setting is thought to be related to the

presence of shallow salt and the limited migration pathways provided by faults that originate from

the salt and extend above to the domed ocean floor. These complex fault families do not presently

have direct access to petroleum systems deep within the adjacent sedimentary basin.

Transitional Cases

Not all fluid and gas expulsion features conveniently fit into the rapid flux-to-slow spectrum

discussed in this paper and in Roberts and Carney (1997). Variations from the simple qualitative

relationships illustrated in Figure 1C.2 occur because of (a) differences in the chemistry of fluids

and gases being transported to the seafloor; (b) the frequency of expulsion events; (c) duration of

expulsion events; (d) the strength of these events; and, (e) the number of expulsion sites within a

given area. Through time, sites may shift from one part of the feature spectrum to another, either by

a systematic increase or decrease in the rate that fluids and gases are delivered to the seafloor. For

example, thin but rapidly deposited mudflows from the crest of a salt-cored diapiric mound in

Garden Banks 427 (27<33.59'N; 92<25.53'W) display surface lithification, a slow flux characteristic,

because of the infrequency of expulsion events. This surface lithification (primarily Mg-calcite)

produces a highly reflective seafloor response on 3D-seismic surface amplitude maps. However, the

positive-to-negative polarity shift in the surface seismic reflector suggests the presence of gascharged sediments (Roberts and Doyle 1998). In settings where expulsion events are more frequent

than in the Garden Banks 427 case, such as large and active mud volcanoes, seafloor lithification

does not generally occur over broad areas, but still may be found at localized sites (Roberts and

Doyle 1998).

SUMMARY

Fluid and gas expulsion features of the northern GOM continental slope fall into three general

categories that have rather distinct assemblages of geological features and biologic communities.
78

These categories, originally discussed by Roberts and Carney (1997), have been identified as rapid,

moderate, and slow flux settings. 

Rapid flux of fluids (including fluidized sediment) and gases create mud-prone topographic features

such as mud volcanoes and/or mud flows in the form of broad sheets or stacked sheets. Mud

volcanoes range in scale from local features < 1 m across to large forms with diameters of > 1 km.

Mud flows display the same wide range of scales. Existing evidence suggests that the delivery of

fluidized sediment to create these features is episodic. During rapid flux events, sedimentation rates

are so high that diagenetic processes of mineralization and biogenic processes have little opportunity

to impact the geologic record. These rapid flux, mud-prone deposits contain hydrocarbons that show

little evidence of biodegradation, a conspicuous reduction in hard mineralized surfaces (particularly

authigenic carbonates) and few-to-no remains of chemosynthetic organisms. Rapid sedimentation

buries sessil organisms and smothers those that are filter feeders and provides only a limited trophic

resource for sustaining life for chemotrophic organisms. Bacterial mats (Beggiatoa) and lucinidvesycomyid clams are the only chemosynthetic organisms typical of rapid flux, mud-prone settings.

Moderate flux cases display the most local variability in small-scale geologic features, substrate

types, and biologic communities. The rather constant but moderate flux of hydrocarbon gases and

to a lesser extent fluids (including moderately biodegraded crude oil) to the seafloor within the

hydrate stability zone promotes the formation of gas hydrates at or near the ocean floor (in water

depth below ~500 m). Gas hydrates may not be excluded from more rapid and slower flux settings,

but in the moderate flux case, the hydrocarbon delivery system causes gas hydrate to form in the

subsurface and to the sediment-water interface. In this setting, abundant gas is being fluxed through

the sediments and by-passing the zones of gas hydrate formation to the water column. In the upper

continental slope setting, plumes of gas are commonly documented on echo-sounders above areas

where gas hydrates are exposed on the seafloor. Accompanying surface and shallow subsurface

concentrations of gas hydrates are densely populated and the most diverse and widely distributed

chemosynthetic communities thus far encountered on the northern GOM continental slope. These

communities consist of bacterial mats (Beggiatoa), lucinid-vesycomyid clams, pogonophoran and

vestimentiferan tube worms, bathymodiolid mussels, and a variety of accessory organisms. In

addition to gas hydrates and associated chemosynthetic communities, moderate flux settings can

display localized outcroppings of authigenic carbonate, nodular masses of carbonate in near-surface

sediments, and a variety of small-scale gas-fluid expulsion features (small mud volcanoes, mud

vents, and shallow pockmark-like depressions).

Slow flux environments are mineral-prone. As hydrocarbon-rich fluids and gases are slowly

transported to the modern seafloor, microbial communities oxidize the hydrocarbons. Products of

this process help induce the precipitation of authigenic carbonates (mainly aragonite, Mg-calcite,

and dolomite) as by-products. In some cases, barite is precipitated at the seafloor in a variety of

forms (crusts, small mounds, and chimneys). The carbonates occur as nodular masses within the

sediment, hardgrounds, and lithified slabs, and mound-like buildups that have a wide range of relief

( < 1 m to > 20 m above the surrounding seafloor). The carbonate buildups themselves do not

generally support abundant chemosynthetic organisms. However, small communities consisting of

bacterial mats, pogonophoran tube worms, and lucinid-vesycomyid clams are sometimes found on
79

the mud bottoms surrounding the buildups, in crevasses within the buildups, and adjacent to

hardgrounds and slabs.

Finally, the responses to the rate of fluid and gas flux to the modern seafloor discussed in this paper

are end-member types. However, because of the episodic nature of expulsion events and the

systematic changes in flux rate at a given sites, the seafloor may shift from one part of the feature

spectrum to another given sufficient time. 

ACKNOWLEDGMENTS

I acknowledge the Louisiana Education Quality Support Funds (Contract No. LEQSF (1994-1997)

RD-B-12) and NOAA National Underseas Research Center, University of North Carolina at

Wilmington (Grants NA80AA-8-00081, NA 88AA-D-UR004, and NA 36RU-0060) for dive time

that supported this study. I thank the Minerals Management Service through the Coastal Marine

Institute and the Louisiana State University Cooperative Agreement (Contract No. 14-35-0001-

30660 and 35-01-99-CA-30951) for supporting studies of the northern GOM continental slope,

which involved analysis of 3D-seismic and high resolution acoustic data as well as manned

submersible work in evaluating areas where the full spectrum of fluid and gas expulsion features

have been investigated. Fugro-McClelland Marine Geosciences Inc. is gratefully acknowledged for

providing selected geotechnical data for this study and for participating as partners on two slope

studies sponsored by LEQSF. I thank Ms. Mary Lee Eggart for her excellent help with illustrations

and Ms. April Hawkins and Ms. Jami Donley for clerical and editorial support. Finally, the CSI

Field Support Group is acknowledged for their excellent technical support in all aspects of our slope

research, particularly in designing, building, and helping to sample the bottom and to measure

critical processes affecting the seafloor.

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chimneys and calcarious fauna from hydrocarbon vents on the Gulf of Mexico slope, Geological

Society of American Abstracts with Programs 22:A208.

Bryant, W. R. 1981. Gas charged sediments. In A.H. Bouma, ed. High resolution seismic profiling

and side-scan sonar: United States Geological Survey, Office of Marine Geology.

Carney, R.S. 1994. Consideration of the oasis analogy for chemosynthetic communities at Gulf of

Mexico hydrocarbon vents: Geo-Marine Letters, 14:149-159.

Cook, D. and P.D. D’Onfro. 1991. Joliet field thrust fault structure and stratigraphy-Green Canyon

block 184, offshore Louisiana: Gulf Coast Association of Geological Societies Transactions,

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Fu, B., P. Aharon, G.R. Byerly, and H.H. Roberts. 1994. Barite chimneys on the Gulf of Mexico

slope: Initial report of their petrography and geochemistry: Geo-Marine Letters, 14:81-87.

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Prather, B.E., J.R. Booth, G.S. Steffens, and P.A. Craig. 1998. Classification, lithologic calibration,

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northern Gulf of Mexico continental slope. Economic Geology, v.92, p.863-879.

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amplitude rendering of the “diapiric hill,” Garden Banks 427: Proceedings Offshore Technology

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paradox for interpreting seafloor geologic/geotechnical characteristics (An example for Garden

Banks 161): Proceedings Offshore Technology Conference, OTC Paper 10921, p. 1-12.

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the Louisiana continental slope - Initial results of direct observations and in situ data collection.

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J.M. Brooks. 1994. Organic geochemistry of sediments from chemosynthetic communities, Gulf

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and geochemistry of gas hydrates, central Gulf of Mexico continental slope. Transactions Gulf

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gas hydrates and hydrocarbon gases in complex chemosynthetic communities, Gulf of Mexico

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82

MONITORING THE PHYSICAL AND CHEMICAL CONDITIONS AFFECTING

THE HYDROCARBON SYSTEM WITHIN THE HYDRATE STABILITY ZONE

OF THE NORTHERN GULF OF MEXICO

Dr. J. Robert Woolsey

The Center for Marine Resources and Environmental Technology

The University of Mississippi

INTRODUCTION

A definite need exists to address questions related to the shallow hydrocarbon system within the

hydrate stability zone of the Continental Slope, northern Gulf of Mexico (GOM). The possibility

of designing and developing a remote, multi-sensor monitoring station for long-term investigation

and research of this problematic near-sea floor hydrocarbon system has been discussed for some

years. During 22-26 March 1999, a workshop entitled “New Concepts in Ocean, Atmosphere and

Sea Floor Sensor Technologies for Gas Hydrate Investigations and Research” was held in Biloxi,

Mississippi. It was sponsored primarily by the Center for Marine Resources and Environmental

Technology (CMRET) of the University of Mississippi. It was attended by an international group

of participants that included a delegation from the Russian Academy of Sciences. One day was

devoted to intensive discussion sessions that addressed practical aspects of assembling and

deploying such a station. By June 1999, those and subsequent discussions had led to a written

document describing a project that would produce a station primarily for studying sea floor stability.

That document was well received by government, industry, and academia. The interest it generated

led to further discussions and meetings and the project concept has been revised incrementally to

include a widening spectrum of interests.

As of December 2000, the intention is to assemble a station to monitor physical and chemical

parameters of the sea water and sea floor sediments on a more or less continuous basis over an

extended period of time. The project will initiate collection of a data base for assessing and

modeling the stability of the sea floor and factors associated with the formation and dissociation of

gas hydrates. This data base will also be available for planning hydrate area exploration/delineation

and, eventually, for analyzing the impact of producing hydrates from the ocean floor. It is also

possible to expand the capabilities of the station to include biological monitoring. This expansion

would allow the study of chemosynthetic communities and their potential as a source for natural

products/drug discoveries as well as an assessment of their environmental health and interactions

with geologic processes.

BACKGROUND INFORMATION

The near-sea floor hydrocarbon system of the northern GOM is manifested by a variety of unusual

features. One of the more interesting and perplexing is the occurrence of gas hydrates, an ice-like

mineral composed of natural gases and water. Gas hydrates are stable within a hydrate stability zone

(HSZ) defined by pressure, temperature and gas composition. If the gas is almost pure methane, the

proper conditions typically are found at ocean depths greater than 400m. The vertical extent beneath
83

the sea floor is largely controlled by the geothermal gradient. Gas hydrates commonly form along

faults and intersecting fractures near the sea floor where the hydrocarbon gases that migrate up from

deep reservoirs interact with sea water. Mounds form on the sea floor containing gas hydrates and

various minerals deposited by bacteria feeding on the hydrocarbons. Variations in pore pressure,

temperature distribution, chemical composition of the gas, and gas flow rate combine to determine

whether hydrates within the mounds accumulate or dissociate. Many geoscientists familiar with

recent geologic processes in the GOM think that events that produce changes to the mounds also

trigger episodes of sea floor instability.

Hydrates in direct contact with a large volume of sea water are only marginally stable. This

instability causes parts of the mounds where hydrates outcrop to be more or less ephemeral, capable

of changing greatly within a matter of days. The eddies of warm water that periodically separate

from the Loop Current, a major current that runs northward through the Yucatan Strait and eastward

through the Straits of Florida, are potentially prominent influences on outcropping hydrates because

they can raise bottom temperatures by as much as 2-3 degrees C and thereby impose a quasicyclicity of sea floor hydrate formation and dissociation. Changes in pore pressure, gas composition,

and flow rate may also be major influences but their causes are not well understood. They may relate

to tectonic activity associated with salt movement.

Hydrates contained in sediments are stable when the host sediment is within the HSZ. If

hydrocarbon gases migrating up faults encounter sediments of sufficient permeability within the

HSZ, hydrates can form within pore spaces, along bedding planes, and within fractures. When

hydrates act to cement the sediment grains, the shear modulus, and thereby the bearing capacity, of

the sediment increases. When outside influences, such as thermal distortions due to salt movement,

fluid migration, or drilling activity, act to dissociate the hydrates; the bearing capacity decreases and

the potential for sea floor instability is created.

Common indicators of bearing capacity are the speeds at which compressional (P) and shear (S)

waves propagate below the sea floor and the efficiency of P-to-S conversion (PS) at reflecting

horizons. A comprehensive monitoring station would be capable of measuring these and many other

parameters that are relevant to the formation and dissociation of gas hydrates. 

The degree to which biological factors come into play is the subject of increasing amounts of

research. For example, over time, bacteria consume the hydrocarbon molecules within the hydrate

crystals and precipitate minerals, such as calcium carbonate, which cement sediment particles and

increase bearing capacity.

OVERVIEW OF STATION SYSTEMS

Sea Floor Positioning System

The first system to be installed at the monitoring station site will be a sea floor navigation system

by which the locations of other systems are referenced. It will be a long baseline system that

encompasses an area of about 10 square miles (25 km2

), somewhat larger than that required to

deploy all other systems. It will remain in place throughout the lifetime of the station.
84

Vertical Line Arrays/Sea Floor Probes

The heart of the station will be a net of vertical arrays (VLAs) and sea floor probes (SFPs). The

VLAs will occupy the lower portion of the water column while the SFPs will be placed in shallow

bore holes (10m) in the sea floor close proximity to the anchor points of the VLAs. VLA and SFP

sensors will be selected to monitor dynamic oceanographic and geologic processes acting on the

lower water column and the near-sea floor sedimentary section.

The VLAs and SFPs will be designed with the following general architecture and sensor

compliment:

• a three component ocean bottom accelerometer will be imbedded at hole bottom of the SFP

for measurements of S-waves and seismicity;

• extending upwards, the SFP will consist of a string of interspersed hydrophones for

measurements of P-waves and sound speed; pressure sensors for measurement of pore fluid

pressure; and thermistors - for measurement of pore fluid /host sediment temperature and

heat flow gradients (in the near-sea floor); (in addition to these subbottom sensors, fiber

optic sensors for pore fluid chemistry measurements may also be incorporated on the string);

and

• the VLA will extend into the water column approximately 200m and will be fitted with

interspersed hydrophones for measurement of P-waves and sound speed, and thermistors for

measurement of water temperature (in the lower water column).

The signal from each sensor will be digitized and recorded individually. 

Hydrophones

The set of acoustic signals provided by the hydrophones will be processed by correlation and

matched field processing (MFP) techniques that make use of time and amplitude information to

provide estimates of

• temperature variations in the water column (by travel-time tomography);

• speeds of P-wave propagation in sea floor sediment/hydrate (by MFP); and

• 3-D images of geological structure beneath the sea floor (by MFP).

These estimates will be used to detect changes in the sea floor resulting from a triggering event and

to provide an image of the subbottom geological structure after an event is detected.
85

Ocean Bottom Accelerometers (OBAs)

The three components of OBAs will allow the identification of S-waves and measurement of their

amplitudes, thereby providing subbottom information not available from P-waves alone. During site

calibration, S-wave speeds immediately below the sea floor will be measured by recording signals

from an S-wave generator towed on the sea floor; the PS-waves converted at deeper reflecting

horizons will be generated by sources deployed on the sea surface. Between calibrations, the threecomponent instruments will monitor seismic activity and the noise of passing ships. The complete

set of accelerometer data will be useful for studying the

• approximate delineation and evolution in time of the gas hydrate stability zone;

• underlying free-gas zone associated with the hydrate edifice; and

• configuration of pathways through which gases and liquids migrate.

After the station has been deployed, the site will be calibrated by determining an acoustic model of

the station’s environment using controlled sources towed by ships and fired at known precise

locations and times. The noise of passing ships, i.e. sources of opportunity, will then be traced and

employed to monitor changes to that model on a more or less continuous basis. The site will be

recalibrated as necessary using controlled sources.

An issue to be addressed in consideration of appropriate systems for S-wave measurement is

whether the 3-component instruments should be seismometers or accelerometers. Seismometers are

more traditional but accelerometers can have broader bandwidths and are more shock resistant.

When ocean bottom seismometers (OBSs) are deployed on the surface of sea floor sediment, their

data can be degraded if the coupling between the instruments and the sediment is poor. That is

probable in the GOM where sediments are often very soft. The sea floor earthquake measurement

system (SEMS IV) of the Minerals Management Service reports great success using OBAs pushed

into soft sediments to monitor earthquakes offshore California. An experiment will be conducted

during the site selection phase in which OBSs and OBAs will be pushed into the bottom by a

remotely operated vehicle (ROV). Recordings from each will then be compared to determine

whether OBAs rather than OBSs should be used at surface locations. Regardless of the outcome, the

OBAs will be the only practical sensors for the SFPs.

Thermistors

The thermistors mounted on the sensor string of the SFP will be designed to monitor heat-flow

density from which heat flow gradient estimates may be determined. These data will in turn provide

estimates for the depth dimensions of the HSZ as well as provide a base for mapping heat flow

anomalies relating to localized hydrocarbon fluid flow (primarily gas).

The subbottom thermal measurements will be accompanied by pore-fluid pressure measurements

to provide information pertaining to hydrate dissociation and its effects on the physical/mechanical

properties of the sediments. The results will be described in terms of both absolute pressure (and
86

how it changes due to a small amount of gas release), and load partitioning between sediment matrix

and pore fluid during tidal cycles and meteorological events.

Thermistors mounted on the VLA will add to the thermal study by enabling the monitoring and input

of bottom-water temperature variations. 

Optical Spectroscopy

Using a technique similar to that employed by the Mars Rover, an optical spectrometer will be used

to identify and quantify hydrocarbon gases present in the sea water. Samples will be illuminated by

laser light shining through an optic fiber and the backscattered light collected by other optic fibers.

Spectral analysis of the backscattered light will provide information concerning the chemical

composition of the gas in each sample. Of particular interest is a recent advancement in mid infrared

(MIR) spectroscopy, under development, which utilizes a miniature cryogenic cooler at the sensor

which has been demonstrated in the laboratory to produce very significant analytical results with

mixed hydrocarbon gases. An obvious and very useful application of this technology would be its

incorporation in the sea floor mounted tip bucket, a free gas volume measurement device presently

in use on small gas vent sites. For instance, a sample might be analyzed after a programmed number

of tips of the bucket. A less conventional but equally valuable application would be the installation

of optical sensors on the SFP string for measurement of pore fluid chemistry in situ.

Current Measurements

An acoustic doppler current profiler (ADCP) will be installed on the sea floor to monitor current

flow at several levels within the lower approximate 200m of the water column. These data will also

be processed for backscatter intensity to yield an estimate of suspended particulate mass, a

parameter affected by both sediment resuspension due to water currents and by sediment mass

movements. In addition, a number of three-axis acoustic current meters will be installed near the

VLA to assist in the determination of VLA receiver geometry. Each of these meters will record

temperature, pressure, and optical backscatter as well as current flow.

Underwater Vehicles

A variety of underwater vehicles will be used at various stages of the project: deep-tow and bottomtow devices, tethered ROVs, manned and eventually autonomous underwater vehicles (AUVs). The

latter will carry sensors that are more effective when moved about, thus improving spatial

resolution, while the former group will be vital to reconnaissance and station assembly. The

locations of underwater vehicle activities will be determined in relation to the long baseline

navigation system.

Towed vehicles and ROVs will be deployed from surface ships during site selection and calibration.

Towed vehicles will reconnoiter areas with survey tools such as side scan sonar, seismic/acoustic

subbottom profilers, and the electromagnetic profiler. ROVs and manned vehicles will be used to

survey smaller areas with greater precision and to deploy and service instruments such as OBSs and

OBAs, cameras, conductivity-temperature-density (CTD) probes, pore-water samplers, pH meters,
87

dissolved oxygen (O2) probes, and the optical spectrometer. Together, they will provide close-up

images of the sea floor and measurements to identify hydrate zones, hydrocarbon seeps and

chemosynthetic communities.

A future consideration, not presently factored, will be the use of AUVs. It is anticipated that the

AUV will carry imaging instruments and measuring probes but will be used primarily during periods

when the station is not attended by surface ships. It will be guided by the long baseline navigation

system to carry imaging systems along specific transects or to take measurements at specific

locations. It will be guided by genetic algorithms and other software to search designated sectors

for new targets. Given appropriate development, it will operate from a docking facility near the

monitoring station where data can be downloaded, instructions received, and batteries recharged.

The dock will be connected by fiber optic to a site, probably an oil platform, where the images and

spectral data can be transmitted ashore and instructions received. Electric power for recharging

batteries will also be obtained from that site.

INITIAL EXPERIMENTS

A suite of experiments will be carried out in the spring of 2001 that, taken together, will approximate the operation of a monitoring station. The experimental site is expected to be in Mississippi

Canyon Block 798 where verbal permission, subject to formal request, has been received from the

lease holder. The topography of the bottom is relatively gentle there and the presence of hydrate

mounds has been confirmed. Additional investigation was done using OBS deployments and high

resolution seismic profiling during a June 1998, cruise funded by CMRET, the U.S.Geological

Survey, and the U.S.Department of Energy. The existing data are sufficient to provide a reasonably

detailed understanding of the configuration of the subbottom there.

Systems used in the Block 798 will include an autonomous VLA, several OBSs and OBAs, and

several resistivity and heat flow conventional gravity probes. The instruments will be deployed for

a period of 7-10 days. High resolution seismic profiles will be recorded, using surface-deployed

seismic sources of various energy levels. Signals from these sources also will be recorded by the

VLA, OBSs, and OBAs. In addition, the sounds of ships will be recorded to test the usefulness of

sources of opportunity; probes will be deployed to obtain resistivity and heat flow data; and gas

samples will be collected by an ROV.

For a period of some months commencing in 2002, Conoco has offered to provide facilities in the

Green Canyon area (Marquette and Joliet fields) for the purpose of performing experiments related

to the monitoring station. The offer includes limited access to platforms, electrical power, and

satellite communications. It is expected that one of the first experiments to be performed using these

facilities will be a test of the feasibility of measuring fluid flow rates (from sea floor vents) using

the sound of bubbles and possibly the deployment of a video monitoring system.

VIDEO MONITORING SYSTEM

If the monitoring station has access to sufficient electrical power, several video systems with pan

and tilt capability will be installed for scientific, educational, and public outreach purposes. Not only
88

will the live images be useful to scientists for visual evaluation of sea floor conditions as they

change in response to either experimental or natural stimuli, but they will be made available to K-12

educators for use in classrooms as well. Students at any facility with access to the Internet will be

able, on a predetermined schedule, to pan, tilt, and zoom the cameras, engage different lights, and

compare the images with other data and with images from other, similar systems.

SITE SELECTION

A short list of potential monitoring station sites will be identified on the basis of their geologic

framework and the applicability of available and appropriate technologies tested during the initial

experiments. The final choice will be the responsibility of the project’s board of scientific

supervisors.

The process of selecting a site for the monitoring station will commence with evaluation of

candidate sites for which pertinent information already exists. Many sites have been studied over

a period of years, especially by the Coastal Studies Institute of Louisiana State University and the

Geochemical and Environmental Research Group of Texas A&M University. These sites will have

priority in the selection process. Appropriate physical conditions form only part of the criteria for

a suitable site. Much of the sea floor in the GOM is under lease to private parties and sea floor

instruments cannot be installed in leased areas without permission of the lease holder(s). Another

criterion for site selection is reasonable proximity to a telemetering site and an electrical power

source.

The most efficient method for reconnoitering potential sites is reflection seismic profiling. A

substantial body of exploration seismic data exists, and some of it is available for review. The

resolution of exploration data is generally low, however, and higher resolution data will be required

prior to final site selection. The higher resolution data will make it possible to resolve layers a

fraction of a meter thick near the sea floor while providing somewhat lower resolution up to a

kilometer below the sea floor.

Seismic profiling can provide information concerning reflection coefficients and, to some extent,

speeds of seismic propagation, but other types of geophysical data will be required before a final site

choice can be made. Optical, side scan and swath-bathymetry images as well as shear-wave,

geoelectric and heat-flow measurements will be collected at sites on the short list. Core samples will

also be taken as necessary.

STATION DEVELOPMENT, DEPLOYMENT, AND OPERATION

A period of two years will be required to construct, integrate station systems, and deploy the

VLAs/SFPs, the end of the second year marking the beginning of operations of the initial station on

the sea floor. Probably, a third year will be required to complete the station as presently planned.

A few systems require at least some development before they can be constructed. These include

certain of the SFP sensors and the optical spectrometer.
89

As noted previously, the VLAs and SFPs will represent key components of the monitoring station.

Considering the architecture and economics involved, the VLAs are retrievable systems while the

SFPs, by design and location, must be considered more or less permanent in their placement and

expendable.

Deployment

Following assembly and testing of the SFP, it will be deployed using a modified version of existing

CMRET remote sea floor drilling technology. The present version is designed remotely to emplace

and extract casing of up to 11.4cm (4.5 in.) O.D. by 12m (40 ft.) length to take cores and implant

sensor probes. In the case of the latter, the probe, consisting of a string of various sensor elements,

which may or may not be incased in a gel-filled plastic tube, is emplaced in the delivery casing. To

meet the requirements of the proposed project, a fishtail drill point of greater diameter than the

selected casing will be loosely inserted at the lower end of the casing and provided with a slot to

permit torquing of the casing during the emplanting procedure. The sensor string or tube is attached

to the fishtail drill point such that on extraction of the casing, the sensor string remains in the hole,

anchored to the bottom by the detached drill point.

With this program in mind, the CMRET remote sea floor drill (RSD) design modification plans have

been completed and await implementation, which will permit system operation to 1,000m. Basically,

the modifications involve a battery powered d.c. electric-hydraulic system supplying an existing

bottom mounted semi-rotary (reciprocal) casing drive mechanism fitted with hydraulic cylinders for

pull-down and pull-up. The existing system is operated via a pressure vessel-encased computer

system controlled by a computer on deck. Additional modifications will include the installation of

a locator pinger and a video camera and light to assist in site location. Once modified, the RSD may

be deployed from offshore vessels of opportunity, suspended from a single coaxial communication/suspension cable.

Operation

Initial operation of the VLAs/SFPs will be in an autonomous mode, utilizing battery power (pressure

compensated) and data recording. While recording of thermal, pore pressure, and chemical data can

be recorded for extended periods, the high volume typical in acoustic data collection will require

down loading at three to five day intervals. Since the acoustic source for both P and S wave studies

will be deployed from an appropriate surface vessel, servicing batteries and downloading the

recorders can be accomplished by means of ROVs. It is, however, the long term intent to utilize

power and communication uplink where available at the sea floor. The station will produce many

channels of data on a more or less continuous basis. The total data volume will be large and recovery

is not a trivial problem. Present plans are to digitize each channel on site and transmit the digital

signals via optic-fiber cable to a structure, such as an oil platform, where they can be telemetered

to an onshore processing facility.
90

CONCLUSIONS

Aspects of installing a station to monitor an area of the sea floor near hydrate mounds on the

continental slope of the northern GOM have been discussed in depth by some of the world’s

foremost experts in appropriate fields. Unanimous agreement that not only is the concept feasible

but that most of the necessary components exist and already have been used in deep ocean

applications. A few components still require some development, though initial experiments and site

selection will commence in the spring of 2001.

The monitoring station will commence initial operation by the end of 2003 and will begin collection

on a more or less continuous basis in 2004. Physical and chemical information concerning sea floor

stability and the accretion/dissociation of gas hydrates will be the initial primary focus. If that

information reveals factors as expected, which elicit responses from chemosynthetic communities

residing nearby, the stations’s capabilities could be expanded to include biologic monitoring. This

expansion should provide an excellent means of exploring the interactions between life forms and

physical/chemical stimuli as well as ways of exploring how biologic agents produce or modify

geologic materials and processes.

Transfer of technology and science to industry and government agencies will be regarded as a

primary responsibility. Also, an effort will be made to make activities and results of the monitoring

station available for use in classrooms. The access will be in near-to-real time and, as much as

possible, interactive.

A Cooperative Effort with Support/Participation From

DEPARTMENT OF COMMERCE

National Oceanographic and Atmospheric Administration

National Undersea Research Program

DEPARTMENT OF DEFENSE

Naval Research Laboratory

Naval Oceanographic Office

DEPARTMENT OF ENERGY

Federal Energy Technology Center

DEPARTMENT OF INTERIOR

Minerals Management Service

U.S. Geological Survey

Geological Survey of Canada

Conoco

Marathon

Specialty Devices, Inc.
91

Florida State University

Louisiana State University

Mississippi State University

Texas A&M University

University of Georgia

University of Southern Mississippi

University of Texas, Austin

University of Victoria, British Columbia

Woods Hole Oceanographic Institution

Facilitated by:

The Center for Marine Resources and Environmental Technology

The University of Mississippi
92

GAS HYDRATES IN THE GULF OF MEXICO: A GEOCHEMICAL PERSPECTIVE

Dr. Roger Sassen

Geochemical and Environmental Research Group

Texas A&M University

ABSTRACT

Thermogenic gas hydrate is abundant on the Gulf of Mexico (GOM) continental slope because

hydrocarbon gases from a deep, hot subsurface hydrocarbon system vent prolifically to the sea floor

where regions of low temperatures and high pressures are within the gas hydrate stability zone

(GHSZ). The presence or absence of gas hydrate is controlled by geologic structure, among other

factors. Structure II gas hydrate is commonly encountered and contains mainly C1-C4 hydrocarbons

that crystallize from relatively unaltered vent gases. Structure H hydrate is occasionally found in

association with structure II hydrate and contains abundant isopentane. Most structure II gas hydrate

at sites studied in the ~540-1930 m water depth range appears to be stable, and gas hydrate is

thought to be accumulating to considerable depth in sediment (> 1 km) because of prolific gas

venting. A leaky hydrocarbon system is probably the main contributor of thermogenic greenhouse

gases to the ocean and atmosphere from the GOM, not gas hydrate decomposition. The geology of

gas hydrate in the GOM is particularly favorable for future development as an energy mineral. 

INTRODUCTION

The GOM has possible global significance as a large reservoir of hydrate-bound greenhouse gases.

Gas hydrates are abundant on the Gulf slope because hydrocarbon gases vent to a sea-floor

temperature and pressure regime in which gas hydrates are stable. Larger gas hydrate outcrop sites

have been discovered on the sea floor of the GOM Salt Basin than in any other basin (Sassen et al.

1999a). Intact gas hydrate samples have been recovered from sediments by piston coring and by

research submersibles from >50 localities in the Gulf slope (Figure 1C.7). Gas hydrate localities

form a belt that extends laterally across the Gulf from offshore Texas to the central Gulf offshore

Louisiana over a distance >500 km; near the center of this range, the maximum width of the belt is

>100 km (Figure 1C.7). The minimum observed water depth of occurrence of gas hydrate in the

GOM is ~440 m and the maximum water depth is >2,400 m (Sassen et al. 1999a). The thickness of

the gas hydrate stability zone (GHSZ) increases with water depth, and models suggest that gashydrate bearing sediments could be >1 km thick in 2-3 km deep water (Milkov and Sassen 2000).

Gas hydrates are ice-like crystalline minerals in which hydrocarbon gases and non-hydrocarbon

gases are held within rigid cages of water molecules. Structure I gas hydrate has a body-centered

cubic lattice, structure II gas hydrate has a diamond lattice, and structure H gas hydrate has a

hexagonal lattice (Sloan 1998). Structure I gas hydrate, which occurs in the Gulf and many other

basins, is usually dominated by bacterial methane (Kvenvolden 1995, 1999). Theoretically, Structure

I gas hydrates could contain either thermogenic or bacterial methane, but no examples of

thermogenic methane gas hydrate (structure I) are yet known from the GOM. The δ13C and δD of

bacterial methane from seafloor gas vents sampled by research submarine and from deep-water
93

Figure 1C.7. Sketch map showing distribution of known gas hydrate sites, seeps with

chemosynthetic communities, and oil and gas fields in the Gulf of Mexico. Note

study areas (GC 185, GC 234, MC 853, AT 425) and closely associated oil fields

(Jolliet, Mars, Ursa).

structure I gas hydrates are thus far consistent with an origin from methanogenesis via CO2 reduction

(Sassen et al. 1999a, b). The origin of bacterial (structure I) gas hydrate, which contains only a

single hydrocarbon molecule, thus appears relatively straightforward in the GOM and will not be

discussed in this paper. 

In contrast to simple bacterial methane hydrate, thermogenic gas hydrates preserve complex

information on origin and stability because numerous hydrocarbon molecules of varying properties

are held within crystal lattices. Both structure II and structure H gas hydrates are believed to co-exist

in the Gulf at water depths as shallow as ~540 m (Sassen and MacDonald 1997). Structure II gas

hydrate generally includes C1-C4 hydrocarbons (methane through isobutane), whereas structure H

gas hydrate generally includes C1-C5 hydrocarbons (methane through isopentane) as significant

components (Sloan 1998). 
94

Temperature, pressure, and availability of hydrate-forming gas molecules are fundamental factors,

among others, that control the stability of gas hydrate (Sloan 1998). Thermogenic gas hydrates

(structure II and H) are stable at higher temperatures and lower pressures than structure I gas hydrate

(Sloan 1998; Milkov and Sassen 2000). Roberts et al. (1999) suggest that outcropping structure II

gas hydrates at GC 185 (~540 m) are transiently stable because of natural fluctuations in temperature

of seawater. Variable or decreasing rates of free gas flux also impact gas hydrate stability, especially

of gas hydrate that outcrops on the sea floor (Egorov et al. 1999). Bacterial oxidation of hydratebound methane and of free hydrocarbon gases in adjacent sediments also could decrease stability

of structure II gas hydrate by removing key hydrate-forming hydrocarbons (particularly propane)

necessary to maintain equilibrium (Sassen et al. 1998, 1999b). Less is known about the stability and

composition of thermogenic gas hydrates buried at depth in sediment and in deep water near the

downdip limit of the GOM Salt Basin. 

Massive decomposition of gas hydrate and concomitant release of greenhouse gases including

methane are suggested as an agent of rapid climate change (e.g. MacDonald 1990; Dickens 1995,

1997; Bains et al. 1999; Max et al. 1999). Kvenvolden (1999) believes this climate change

hypothesis is overstated. The volume of free gas from hydrate decomposition is thought, on the basis

of indirect evidence, to be meaningful in some basins, contributing to the formation of sea floor seep

features (e.g. Vogt et al. 1994; Paull et al. 1995), and impacting sediment fabrics (Kennet and

Fackler-Adams 2000). Although the line of reasoning is attractive, direct molecular and isotopic

evidence of significant gas hydrate decomposition is thus far lacking, and other explanations are

possible. Recent piston coring and submersible investigations have given us the opportunity to add

to our GOM database and obtain intact sediment-free samples of thermogenic gas hydrate from new

and deeper-water sites in the GOM. 

The primary objective of the present paper is to review recent work on gas hydrate and associated

sediments from shallow to ultra-deep water within the GHSZ. Secondary objectives are to address

the basic geologic questions of whether there is stable net accumulation or decomposition of gas

hydrate in the GOM. We also consider gas hydrate as a future energy mineral. 

GEOLOGIC SETTING

The main structural features of the northern GOM are salt basins including the large GOM Salt

Basin and a series of smaller interior salt basins that extend from south Texas to Alabama. The

basins formed during Late Triassic rifting and were floored by salt (Louann/Werner formations)

during Middle Jurassic marine incursions. During the Tertiary, when the development of large river

systems to the north provided abundant sediment to the basin. An important effect of the rapid

sediment influx was massive deformation of underlying salt. The GOM continental shelf is now

characterized by numerous salt domes, whereas the continental slope is more affected by large sheetlike salt thrusts that extend from the shelf edge across the continental slope to the Sigsbee

Escarpment, near the edge of the abyssal plain. The Mississippi Fan Foldbelt is a zone of rapid

geologic transition that extends northeast-southwest for ~350 km along the lower continental slope

of the GOM (Weimer and Buffler 1992; Wu 1993; Rowan 1997). Some salt pierced through the

overlying section to form allochthonous salt bodies at shallow depths, providing localized conduits

for migration to the sea floor. The Mississippi Fan Foldbelt represents the downdip limit of the
95

GOM Salt Basin, and undeformed salt-free sediments of the abyssal plain are thought to occur

immediately to the south. 

The geology of the GOM slope is conducive to seepage from deeply buried petroleum systems to

the sea floor because hydrocarbon generation is geologically recent within deep sediment sections

of large salt withdrawal basins (Wenger et al. 1994). Fracture zones associated with moving salt

sheets, as well as active faults, provide efficient migration conduits for fluid flow to the sea floor

including hydrocarbons and brines. The sea floor shows markedly irregular bathymetry from

structural deformation, faulting, fracturing, and slumping (Roberts and Carney 1997). Massive

hydrocarbon seepage manifests itself at the Gulf sea floor as gas hydrate, oil-stained sediments,

authigenic carbonate rock with light δ13C, and unique hydrocarbon-driven chemosynthetic

communities (e.g. Aharon et al.1997; Roberts and Aharon 1994; MacDonald et al. 1989; Roberts

and Carney 1997). Because the fluid flow is structurally focused, gas hydrate accumulations are

concentrated along the rims of salt-withdrawal basins, over salt ridges, and near the faulted and

folded margin of the Sigsbee Escarpment near the downdip limit of the GOM Salt Basin (Sassen et

al. 1999a). Seep-related features such as gas hydrates are only infrequently observed within salt

withdrawal basins themselves because such sediments are less deformed and usually lack major

migration conduits to shallow sediments or the sea floor. 

MAIN STUDY SITES

The GC 185 and 234 sites are on the upper slope of the GOM in ~540 m water depth (Figure 1C.7),

near the upper limit of the GHSZ. The most recent episodes of hydrocarbon venting in this area

appear to have commenced during the late Pleistocene (Aharon et al. 1997). The GC 185 site (Bush

Hill) is a fault-related seep feature (27/ 45.7' N and 91/ 30.5' W). An antithetic fault at GC 185 is

related to nearby Jolliet Field (GC 184). Oil and gas that vent at GC 185 and which occur in

reservoirs at ~2-3 km depth in Jolliet Field correlate (Kennicutt et al. 1988). Composition of gas

venting to the sea is consistent with an origin from the same hydrocarbon source system or from

Jolliet Field itself. Research submersible observation shows that sea-floor gas hydrate mounds are

generally associated with active gas vents (Figure 1C.8). 

Multiple gas hydrate mounds at GC 185 have persisted for >7 years, but mounds show deformation

over a scale of months or years (MacDonald et al. 1994). Vent mounds show typical features (Figure

1C.8). Gas hydrate is capped by thin layer of highly deformed hemipelagic mud that contains

bacterially oxidized crude oil, free gas, dispersed gas hydrate nodules, authigenic carbonate depleted

in 13C, and H2S (Sassen et al. 1993, 1994, 1999a, b). The fabric of the sediment cap is affected by

tubular polychaete burrows that extend down to the gas hydrate, and sediment contains abundant

calcareous fragments of chemosynthetic mussels as well as various bivalves and gastropods (Sassen

et al. 1998). The gas hydrate mounds are covered by bacterial mats (Beggiatoa, which oxidizes

sulfide) and are surrounded by a complex chemosynthetic community including tube worms (Sassen

et al. 1999a, b). 

The GC 234 site (27/ 44.8' N and 91/ 13.3' W) at ~543 m water depth is a fault-related seep area

over shallow salt. When the site was first identified by a research submarine in 1997, a small gas

hydrate vein-filling surface (~1 m) outcropped on the surface of an upthrown fault scarp in
96

Figure 1C.8. Sketch showing main elements of a typical gas hydrate mound (1-3 m across) formed

around thermogenic gas vents in a chemosynthetic community. (From Sassen et al.

1999b.)

association with gas vents. The exposure was actively undercut by vent gas expulsion. The gas

hydrate was unstable in contact with seawater, and exposed gas hydrate had decomposed by 1998

(Sassen et al. 1999b). Bacterial mats (Beggiatoa) covered the sediment surface over the exposed gas

hydrate. A complex chemosynthetic community including tube worms is present at this site (Sassen

et al. 1999b). Maximum depth of stability in sediments of structure II hydrate at the GC 234 site is

~650 m, similar to the GC 185 site (Milkov and Sassen 2000). 

The Mississippi Canyon 853 site (28° 7.4' N, 89° 8.2' W) at ~1060-1070 m water depth is a large

sea-floor mound (~1.5 km across, with ~30-40 m of relief) on the middle Gulf slope (Figure 1C.7).

The mound directly overlies shallow salt on the edge of a large salt withdrawal basin near Ursa and

Mars fields (Figure 1C.7). The mound is believed to contain large volumes of gas hydrate, free gas,

authigenic carbonate, and highly deformed sediments (Sassen et al. 1999a). The MC 853 site is in

close association with Ursa Field and the giant Mars Field (Figure 1C.7). The GC 185, GC 234, and

MC 853 sites show rapid hydrocarbon flux related to maturation and vertical migration from the

same or similar Mesozoic source facies (Wenger et al. 1994) at ~6-10 km burial depth. 

The AT 425 study site is an isolated sea-floor vent feature on the lower GOM slope (27/ 34.1' N and

88/ 29.7' W) at ~1920-1930 m water depth (Figure 1C.7). The site is part of the Mississippi Fan
97

Foldbelt (Weimer and Buffler 1992; Wu 1993; Rowan 1997). The hydrocarbon source system at AT

425 is thought to represent a different Mesozoic source facies than encountered updip in the GOM

Salt Basin at our other study areas. The AT 425 site is characterized by sea-floor seep features

related to faults overlying an allochthonous salt ridge at shallow depth in sediments (Sager and

Kennicutt 2000). Fluids from depth beneath the AT 425 site pierce a thick apron of gently dipping

sediment deposited by transport from the Mississippi Fan Channel. The AT 425 vent is assumed to

be a major fluid flow release site from depth in the Mississippi Fan Foldbelt because no other vent

and gas hydrate sites are known within tens of km (Figure 1C.7). 

OVERVIEW

Vent Gases

The molecular and isotopic properties of gases that vent directly to the water column from gas

hydrate mounds on the sea floor can determine whether the gases are related to ongoing crystallization of associated gas hydrate or whether they are related to gas hydrate decomposition. Thus,

molecular and isotopic data on vent gases from hydrate-bearing sediments are pivotal and should

be an objective focus of future research on gas hydrate stability. The change in phase from vent gas

to solid structure II gas hydrate involves molecular fractionation that favors gases of appropriate

molecular diameter (Sloan 1998). Methane decreases in abundance relative to vent gas and the C2+

hydrate-forming gases (especially ethane and propane) increase in abundance in structure II gas

hydrate (Sloan 1998). Meaningful carbon isotopic fractionation is not thought to occur during gas

hydrate crystallization (Claypool et al. 1985, Brooks et al. 1986; Kennicutt et al. 1988; Sassen and

MacDonald 1997; Sassen et al. 1999a, b). On this basis, vent gas from decomposition of structure

II gas hydrate would be isotopically similar but would display a characteristic molecular distribution

with anomalous percentages of hydrate-forming hydrocarbons (such as ethane, propane, and

butanes). 

Thermogenic gas vents, thus far, have only been sampled overlying hydrate-bearing sediments at

the GC 185 and GC 234 sites on the GOM slope at ~540 m water depth. These vents are near the

upper limit of the GHSZ (Milkov and Sassen 2000). The molecular distributions of gas venting from

gas hydrate mounds show generally decreasing relative abundance of C1-C5 hydrocarbons with

increasing carbon number, as generally observed in relatively unaltered reservoir gases (e.g. James

and Burns 1984). The molecular distributions of vent gas are incompatible with significant flux from

gas hydrate decomposition when compared to flux from the deep subsurface (Sassen et al. 2001).

Instead, the molecular and isotopic properties of vent gases are consistent with direct migration of

relatively unaltered hydrocarbon gases from deeply buried source rocks, or with leakage from

nearby subsurface oil reservoirs (Kennicutt et al. 1988; Sassen et al. 1999; Sassen et al. 1999a, b).

This assessment of vent gas properties over shallow hydrate-bearing sediments in the GOM has

important implications. At gas hydrate study sites in the GOM, rapid flux of thermogenic

greenhouse gas to the water column appears to be dominated by an unusually leaky subsurface

hydrocarbon system that also charges subsurface reservoirs with oil and gas (Sassen et al. 2001).

Similarly, most other large seep features at the GOM sea floor, as well as chemosynthetic

communities, are related to rapid flux from the subsurface hydrocarbon system, and are generally

not related to hydrate decomposition. 
98

Figure 1C.9. Sketch showing modeled subsurface distribution of gas hydrate at the GC 185 site.

Note that much gas hydrate is thought to be deeply buried and stable in sediments

where thermogenic hydrocarbon flux from the Jolliet Field faults is continuous for

meaningful spans of time.

Measurements of filling rates of plastic tubes of known volume during gas hydrate experiments at

the sea floor suggest that the rate of venting from a single bubble stream to the water column at the

GC 185 site is about 60 L/minute (STP). In aggregate, venting rates from large numbers of orifices

at gas hydrate sites could be considerable. The observation that decomposition does not impact vent

gas compositions (Sassen et al. 2001) serves as direct evidence that gas hydrate decomposition is

not quantitatively significant because most gas hydrate is buried and stable at depth in sediments

(Figure 1C.9). It is postulated that the bulk of buried gas hydrate masses at study localities within

the GHSZ are stable or are still accreting because of the relatively rapid flux of gases from the

subsurface (Sassen et al. 2001).
99

Gas Hydrate and Sediment Fabrics

Interpreting observed gas hydrate fabrics and textures helps to address whether net gas hydrate

accumulation or decomposition is occurring in the GOM. Deformed vein-filling gas hydrates and

gas hydrate nodules are observed exposed on the flanks of gas hydrate mounds at the GC 185 and

GC 234 sites (~540 m) in the GOM (Sassen et al. 1998; 1999a). The basic morphology of gas

hydrate recovered from piston cores at the deep-water AT 425 and MC 853 sites consists of vein

fillings and nodules at sediment depths in the 1.8 to 4.4 m range. The fabrics we observe both in

shallow and ultra-deep water are typical of gas hydrate settings with high flux rates of hydrocarbon

gases (Ginsburg 1998; Ginsburg and Soloviev 1998). 

Based on experimental precipitation of thermogenic gas hydrates at natural gas vents at the Gulf sea

floor (Sassen and MacDonald 1997), natural gas hydrate crystallization can occur rapidly (on a scale

or seconds or minutes). The vein fillings observed in cores are postulated to result from sudden

episodic increases in gas pressure that open up tension fractures along sub-horizontal zones of

weakness in hemipelagic muds, mixing gas and water to effect rapid crystallization that holds the

fractures open. The gas hydrate vein-fillings probably further expand during subsequent gas

injections, and as a consequence of pressure of crystallization (Sassen et al. 1999a). Associated

sediments are highly deformed by crystallization of the gas hydrates. One could speculate that, in

the GOM at present, soft sediment deformation from gas hydrate crystallization is more important

than the effects of gas hydrate decomposition. 

Structure II and Structure H Gas Hydrates

Structure II gas hydrate has been identified from oily sediments of the GOM (Brooks et al. 1986)

and from the Caspian Sea (Ginsburg and Soloviev 1998). Gas hydrate samples from the shallow GC

185 and GC 234 sites at ~540 m water depth have C1-C5 hydrocarbon molecular distributions that

are broadly consistent with structure II gas hydrate, in that methane, ethane, propane, and butanes

are significant components (Sloan et al. 1998). The structural assignment (structure II) based on

molecular distribution is confirmed by solid state nuclear magnetic resonance (NMR) of intact gas

hydrate sample from GC 184 (Davidson et al. 1986), and from GC 185 (Sassen and MacDonald

1997). C1-C5 molecular distributions from the AT 425 and MC 853 sites are consistent with structure

II gas hydrates because of their basic molecular similarity to proven structure II gas hydrate at GC

184/185. Structure II gas hydrates from ultra-deep water at AT 425 and MC 853 also appear to have

crystallized from relatively unaltered C1-C5 hydrocarbon gases at or near natural gas vents with high

flux rates. 

Rapid crystallization of gas hydrate appears to affect the molecular distribution of gases in

associated sediments by exclusion of incompatible molecules. Crystallization of structure II gas

hydrate preferentially removes hydrate-forming gases (i.e. methane, ethane, propane) and enriches

residual gases in incompatible hydrocarbons (i.e. pentanes) that are too large to fit within structure

II hydrate cages. Isopentane is present in anomalous abundance in sediment samples that directly

overlie buried structure II gas hydrate at AT 425 (Sassen et al. 2000). Similarly, isopentane is

present in anomalous abundance (as much as 13.8%) in sediments near active gas hydrate mounds

at GC 185 and GC 234 (Sassen et al. 1999b). The free isopentane in hydrate-bearing sediments
100

further contributes to explaining the observed association of structure H gas hydrate, rich in

isopentane, with structure II gas hydrate in the GOM (Sassen and MacDonald 1994). Other novel

crystal structures of gas hydrate are likely to be discovered in the GOM. 

CONCLUSIONS AND SYNTHESIS

The major source of thermogenic greenhouse gases in the GOM is a leaky subsurface hydrocarbon

system that also charges subsurface reservoirs of oil and gas. GOM gas hydrate accumulations are

also a meaningful reservoir of greenhouse gases that may be released from sediments if gas hydrate

decomposition occurred. One basic question is assessment of the relative rates of gas hydrate

accumulation and decomposition in the GOM. Several lines of reasoning suggest that structure II

gas hydrate is forming in the GOM at a significantly greater rate than it is decomposing. Vent gases

over hydrate-bearing sediments and gas hydrate mounds do not show evidence that gas hydrate

decomposition is quantitatively significant. 

All study sites (~540-1930 m water depth) are high-flux settings where hydrocarbon migration

conduits intersect the sea floor deep within the GHSZ. Gas hydrate and sediment fabrics are

consistent with the rapid crystal growth caused by high flux rates of hydrocarbon gases. The C2+

hydrocarbons of gas hydrates are protected from bacterial oxidation when locked within the stable

structure II gas hydrate crystal lattice (Sassen et al. 1998,1999a, b). The abundance of incompatible

isopentane in sediments adjacent to structure II gas hydrate provides additional evidence of recent

or ongoing gas hydrate crystallization, and also contributes to explaining the observed association

of structure II and isopentane-rich (structure H) gas hydrates in the GOM (Sassen and MacDonald

1994). 

The process of generation and migration of oil and gas from source rocks can last as much as

millions of years. We conclude that gas hydrate is sometimes unstable in the GOM, particularly

when exposed to the water column at shallow water depths near the upper limit of the GHSZ, where

water temperatures are most variable. Nevertheless, overall results are consistent with net

accumulation of gas hydrates buried in sediment as a consequence of recent and ongoing

crystallization. Thermogenic gas hydrate crystallization is driven by hydrocarbons from an active

subsurface hydrocarbon system. 

The three-dimensional aspect is important. Maximum thickness of the GHSZ increases with

increasing water depth. Models of stability suggest that thermogenic gas hydrate could accumulate

within sediments at depths >1 km beneath the sea floor of the ultra-deep GOM (Milkov and Sassen

2000). Deeply buried gas hydrates are probably well insulated from the transient effects (such as

temperature changes) that impact gas hydrate at or near the sea floor. Large volumes of gas hydrate

in the GOM are probably buried as stable accumulations in sediments of ultra-deep water where the

maximum thickness of the GHSZ is greatest (Milkov and Sassen 2000). 

The molecular distributions of thermogenic gas vents suggest that the flux of hydrocarbon

greenhouse gases from a leaky subsurface hydrocarbon system is far more significant than from gas

hydrate decomposition in the GOM. Insofar as the GOM is a meaningful analog, it appears prudent

to constrain or modify speculation on the relation between gas hydrate decomposition and global
101

climate change. Other factors, such as coincident maturation of prolific hydrocarbon source rocks

in leaky basins on global continental margins could be more important. Because gas hydrate

crystallization results in net trapping of hydrocarbons before subsurface gases can impact the sea

and atmosphere, stable or accumulating gas hydrates appear likely to buffer the atmosphere by

sequestering some greenhouse gases (Sassen et al. 2001). Thus, massive accumulation of gas

hydrate in leaky basins could contribute to global climate stability over meaningful spans of

geologic time.

The GOM is probably one of the first areas in which economic production of gas hydrate energy will

occur. Instead of being thinly dispersed in pore spaces of sediment, gas hydrate in the GOM often

occurs as thick vein-fillings (as much as 40 cm) in fracture porosity and as nodules. Moreover,

models suggest that gas hydrate is stable and extends to great depth in sediment, perhaps as thick

as a kilometer. Thus, gas hydrate is highly concentrated in the GOM, which is an important factor

in economic assessment. The Department of Energy predicts that conventional supplies of gas will

begin an era of permanent decline in production within 10-20 years, yet demand is projected to

increase at the same time. Alternate sustainable energy resources (e.g. hydrogen-based energy) will

take longer than that to bring on line. Energy from gas hydrate could bridge the gap from

conventional fossil fuels to a sustainable energy future. 

ACKNOWLEDGMENTS

We acknowledge the support provided by ten energy companies and the Minerals Management

Service that participated in Texas A&M University’s Applied Gas Hydrate Research Program, 1999-

2000. The assistance in obtaining piston core samples of gas hydrates in ultra-deep water by the

scientists, graduate students, and crew of the Research Vessel Powell is greatly appreciated. 

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105

SESSION 2A

DEEPWATER SESSION

Co-Chairs: Mr. G. Ed Richardson, Minerals Management Service

Mr. James Regg, Minerals Management Service

Date: December 5, 2000

Presentation Author/Affiliation

Status on the Floating Production, Storage,

and Offloading Environmental Impact

Statement

Ms. Deborah Cranswick

Minerals Management Service

Status of the Comparative Risk Assessment Mr. James Regg

Minerals Management Service

Gulf of Mexico OCS Region

Regulatory Framework for Floating

Production, Storage, and Offloading Systems

Ms. Wanda Parker

WJP Enterprises

Deepwater Oil Transportation: Future Vision Mr. C.G. (Chuck) Stuebe

Conoco Shipping Company

DeepStar Activities, Accomplishments, and

Plans

Mr. Allen J. Verret

DeepStar

Mr. Steve Brooks

ExxonMobil

Update on U.S. Coast Guard OCS Activities LCDR John Cushing

Chief, Outer Continental Shelf Branch

Eighth Coast Guard District
107

STATUS ON THE FLOATING PRODUCTION, STORAGE, AND OFFLOADING

ENVIRONMENTAL IMPACT STATEMENT

Ms. Deborah Cranswick

Minerals Management Service

BACKGROUND

Several projects are underway in the Gulf of Mexico OCS Region to determine the applicability of

placing a floating production, storage, and offloading (FPSO) system in the Gulf of Mexico (GOM).

These include (1) an “outsourced” environmental impact statement (EIS) for FPSO systems, (2) a

comparative risk assessment that compares potential risks associated with FPSOs, tension-leg

platforms, spars, and fixed platforms that serve as “hubs” for other developments, and (3) a

regulatory model to identify potential gaps in regulations regarding FPSOs.

Why was an EIS required for the proposed use of FPSOs in the GOM? FPSO usage in the GOM

is considered to be new and unusual technology. Specifically, FPSO systems involve the on-site

storage of oil, offloading procedures, and transport of OCS-produced oil by surface vessels (shuttle

tankers or barges).

THE ENVIRONMENTAL IMPACT STATEMENT

Map of Study Area

Figure 2A.1 depicts the study area for the FPSO EIS.

Issues in the EIS

The following are issues to be addressed in the FPSO EIS:

• Operational Issues, including

- Oil spill risks and spill response

- Offloading and tankering operations

- Emissions

- Associated gas

• Regulatory Issues (involving jurisdiction and applicable regulations), including
Figure 2A.1. Alternatives in FPSO EIS.
109

- Technical issues

- Unusual technologies verses spill risks

- Mooring

• Socioeconomic Issues.

Alternatives Considered in the Draft EIS

The FPSO EIS contains three alternatives for evaluation. These include

• Alternative A: approval of the general concept of using FPSOs in deepwater areas of the

Western and Central Planning Areas of the GOM

• Alternative B: approval of the general concept of using FPSOs in deepwater areas of the

Western and Central Planning Areas of the GOM with geographic restrictions and

operational conditions

• Alternative C (No Action): the general concept of using FPSOs in the deepwater GOM is

neither approved nor disapproved at this time.

FPSO Configuration

The following is a description of the generic FPSO configuration analyzed in the EIS:

• 1 MM bbls of oil storage

• Processing capabilities of up to 300,000 BOPD and up to 300 MM CFGPD

• Multi-well subsea clusters

• Transport of OCS-produced oil by 500,000 bbl shuttle tankers and 

• Transport of OCS-produced gas by pipeline.

EIS Timelime

Table 2A.1 depicts the timeline for the remaining portions of the FPSO EIS process.

Draft EIS Distribution

The Draft EIS was a popular publication among the MMS external customers. Five hundred copies

of the Draft EIS were printed. The public consumed all of these copies in less than two weeks. An

additional 250 copies were printed. Most of these copies are gone. Customers also used the MMS
110

Table 2A.1. FPSO EIS process timeline.

DATES EVENTS

17 August 2000 Draft EIS is issued

18-21 September 2000 Public Hearings on the Draft EIS

10 October 2000 Public Comment Period on the Draft EIS Ends

19 January 2001 Final EIS is issued

February 2001 Record of Decision is issued

website to gain information about the Draft EIS. During the interval of 13 August to 16 September

2000, the MMS website was visited 1,177 times by 429 visitors who downloaded 1,879 section of

the Draft EIS.

Findings of the Draft EIS

The following is a listing of the finding contained within the Draft EIS document:

• Potential site-specific impacts are essentially the same as for other production systems

• Potential emission impacts to the Breton Wilderness Area occur from potential FPSO

locations in the Viosca Knoll and northern Mississippi Canyon areas

• Comparable oil spill risks – “FPSO and shuttle tanker risk are comparable to the existing

deepwater production structures and oil pipeline risks...the net gain in risk would be

negligible” 

• Potential FPSO-unique spills are 5% of the total spill risk.

Public Hearings

Public hearings on the Draft EIS were held in September 2000 at various locations in the Gulf

States. Table 2A.2 characterizes these public hearings.

The public hearings developed the following comments and issues regarding the Draft EIS:

• Industry supports the use of FPSOs and Alternative A in the EIS

• Transportation issues include

- Piloting of shuttle tankers
111

Table 2A.2. Locations of public hearing on the Draft EIS held in September 2000.

LOCATION NO. OF ATTENDEES NO. OF SPEAKERS

Mobile, AL 28 4

New Orleans, LA 40 2

Houston, TX 79 10

Lake Charles, LA 7 2

- Safe movement from FPSO to ports

- Tankers verses ocean-going articulated tug barges

• Single bottom/double sided verses double hull FPSOs

• FPSOs will create jobs

• The OCS spill record has improved

• Environmental Justice (benefits to minorities)

In addition, the MMS received 37 comment letters or cards regarding the Draft EIS. These

documents raised the following issues.

• Hurricane survivability

• Pilotage of the shuttle tankers in ports

• Reliability and maneuverability of ocean going articulated tub barges

• Oil spills and spill response

• Attendant vessel requirements

• MMS verses U.S. Coast Guard jurisdiction

EIS Decision Model

Figure 2A.2 describes the FPSO EIS Decision Model.
112

Figure 2A.2. The FPSO EIS Decision Model.

What Happens after the EIS and CRA

Figure 2A.3 depicts what is expected to happen after the EIS process and the comparative risk

assessment is completed.

Figure 2A.3. What is expected to happen after the EIS process and the comparative risk

assessment is completed.

Ms. Deborah Cranswick is a Senior Environmental Scientist in the Environmental Assessment

Section in the MMS Gulf of Mexico Region. She is the Contracting Officer’s Technical Representative on the contract for the FPSO Environmental Impact Statement and is also the EIS Coordinator.
113

STATUS OF THE COMPARATIVE RISK ASSESSMENT

Mr. James Regg

Minerals Management Service

Gulf of Mexico OCS Region

BACKGROUND

The purpose of the comparative risk assessment (CRA) is to determine the relative risks of floating

production, storage, and offloading (FPSO) systems compared to the existing deepwater Gulf of

Mexico (GOM) production facilities. Specifically, the CRA would examine the risks associated with

tension-leg platforms (TLPs), spars, and fixed platform “hubs” or “hosts” compared to FPSO

systems.

Table 2A.3 depicts the phases of the CRA and the status of each phase.

Table 2A.3. Phases and status of the CRA.

PHASE PHASE DEFINITION STATUS

I System Definition Completed

II Events and Outcomes Completed

III Preliminary QRA Completed

IV Final Report Review and

Presentation

Project Completion

Projected for January

2001

WHY DO A COMPARATIVE RISK ASSESSMENT

In 1999, Bechtel Corporation conducted a risk assessment of an FPSO in the GOM. However, no

risk acceptance criteria had been established for the GOM. Existing deepwater systems provide

known risks. They comply with existing regulations. They are designed and operated under existing

standards. The current production systems exhibit satisfactory operating experience.
114

COMPARATIVE RISK ASSESSMENT STUDY LIMITS

Study limits had to be established for the CRA. A “field life” definition was established. The interval

starts when oil flows from the first well and ends when all wells are shut in. This definition excludes

pre-drilling, site preparation, and installation of facilities. These events may be common to all

systems under evaluation and therefore provides no differential. The study would include oil and

gas production, drilling and well workovers during production, offshore processing of oil and gas,

and transportation of oil and gas to the shore.

A study scenario and boundaries had to also be established. Table 2A.4 depicts CRA risk measures.

Table 2A.4. Risk measures of the CRA.

RISKS MEASURE UNIT

Human Safety Total Fatalities Number of Fatalities

Environment (Chronic) Total Volume of Oil Release BBLs of Oil

Environment (Acute) Max. Volume of Oil Release

in a Single Event

BBLs of Oil

A table of events and outcomes had to be developed. Table 2A.5 is an example of the type of events

and outcomes considered in the CRA study.

Table 2A.5. Event types and outcomes considered in the CRA.

SYSTEM SUBSYSTEM PHASE EVENT

POSSIBLE

OUTCOME COMMENTS

TLP Riser Production,

Workover

Dropped

Object

Damage to

wells or riser

SCSSV should

prevent major

consequences
115

Risk = ∑(Consequence x Probability)

 A B C D

 System

Risk for

Total Oil

Release

(BBL per

BBL

produced)

Transport

Production

Drilling etc.

Events

Figure 2A.4. An example of the result format expected from the CRA study.

Figure 2A.4 represents an example of the result format expected from the CRA study. Note the A,

B, C, and D representing each bar in the chart would be the production systems; e.g., TLP, spar, etc.

The following steps remain in the study’s timeline:

1. Draft Final Report is prepared

2. MMS review is needed
116

3. Presentation of results to the MMS and the USCG

4. Publication to put information in the public domain

5. Integrate information into the Record of Decision for the FPSO EIS

Mr. Jim Regg is the Chief of the Technical Assessment and Operations Support Section with the

MMS Gulf of Mexico Region, located in New Orleans. His office is responsible for technical,

safety, research, and regulatory issues relating to drilling and production activities in the GOM Outer

Continental Shelf. Jim has offshore experience in drilling and production operations in Alaska and

the Gulf of Mexico, and also experience with the MMS’s offshore inspection program. He has had

numerous papers published, conducted several workshops, and serves on several joint MMSindustry initiatives, including DeepStar. Jim received a B.S. degree in petroleum and natural gas

engineering from the Pennsylvania State University in 1983.
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REGULATORY FRAMEWORK FOR FLOATING PRODUCTION, STORAGE,

AND OFFLOADING SYSTEMS

Ms. Wanda Parker

WJP Enterprises

BACKGROUND

The FPSO regulatory framework investigation was initiated on 22 March 2000 by the MMS. A work

group was formed under the Offshore Operators Committee (OOC). This work group was composed

of 16 industry members, seven MMS representatives, three members from the U.S. Coast Guard

(USCG), 11 participants from the class societies, and one API representative. The goals of the work

group were to (1) review the existing regulations and industry standards covering the design,

construction, and operations of FPSOs in the Gulf of Mexico (GOM) and (2) identify gaps in the

regulations and standards.

THE FPSO REGULATORY FRAMEWORK

To form the basis of the study, several FPSO characteristics were considered. These include the

following:

• U.S. flag or undocumented FPSO

• Ship-shaped configuration

• Permanently moored FPSO

• Focus discussions on systems that are unique to the FPSOs

Several work products were established for the study. These include:

• A table of jurisdictional issues based on the MOU between the MMS and the USCG,

• A table of unique FPSO systems, and

• A summary of conclusions, gaps, and recommendations.

CONCLUSIONS

The study made several conclusions. The following is a listing of these conclusions:

• The USCG’s MSC and Headquarters groups need to be fully engaged in determining

regulations for FPSOs in the GOM.
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• The existing regulatory framework is adequate with some modifications.

• A large number of class society guides and rules as well as API documents exist that cover

FPSO systems designs and operations. Some review and updating of these documents is

needed.

• Regulations for non-ship-shaped FPSOs will need additional consideration.

• Many of the recommendations are applicable to other types of floating facilities.

RECOMMENDATIONS

Recommendations were made for each of the major stakeholders regarding FPSO activities. The

following lists depicts these recommendations on and individual entity basis.

Recommendations to the MMS:

• The MMS’s CVA regulations should be updated for floating systems.

• The MMS should review and adopt API RP 2FPS, RP 2SM, 2SK, 2RD and 17J.

Recommendations to the USCG:

• Specific floating facility regulations should be adopted in Subpart N.

• Marine crew manning and qualification regulations should be codified.

• The API’s RP 500/505 for area classification should be adopted.

• Regulations for fire-fighting systems for production systems should be codified.

• The API’s RP 75 should be recognized as the basis for an acceptable safety management

system.

Joint recommendations were offered for the USCG and the MMS:

• The CVA process should be acceptable to both agencies to review and certify the design of

the turret and mooring systems.

• The jurisdiction of integral hull tanks used as process vessels should belong to the MMS.

The study had recommendations to the industry as well:

• Representatives from the industry should review the overboard discharge regulations of the

U.S. Environmental Protection Agency and the USCG for adequacy for FPSO operations.
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• The industry should develop a strategy for obtaining a formal determination from the U.S.

Department of Customs regarding the acceptability of foreign-flag FPSOs.

• The industry should review the various API documents on mooring and riser design,

composite materials, and RP 14C, RP 14E for adequacy for floating systems.

• Industry representatives need to review and update (as needed) API’s RP 75 for FPSO

operations.

• The industry should confirm appropriate standards for cargo tank cleaning for FPSOs.

The workgroup also had some recommendations to continue its investigation of certain related

matters:

• Operational standards for offloading from FPSOs in the Gulf of Mexico should be

developed.

• A LOC checklist for foreign flagged FPSOs should be developed.

• The integration of the monitoring and safety systems should be addressed.

• It should be determined where specifications break between the MMS and the USCG

regulations should occur.

Ms. Wanda Parker is a private consultant for offshore regulatory issues, specializing in deepwater.

Prior to her consulting, Ms. Parker worked 22 years for Sun and Oryx Energy in various engineering

positions, including 10 years focusing on regulatory and environmental work. Ms. Parker is a

member of the NOSAC Committee and an active participant in various OOC committees as well

as the DeepStar Regulatory Issues Committee. She received a Bachelor of Science in Petroleum

Engineering from Texas A&M University.
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Figure 2A.5. Cost verses concept for an offshore-based approach compared to a shipping-based

approach.

DEEPWATER OIL TRANSPORTATION: FUTURE VISION

Mr. C.G. (Chuck) Stuebe

Conoco Shipping Company

The Gulf of Mexico (GOM) has extensive pipeline infrastructure that supports production on the

continental shelf. Pipelines have begun to reach into deepwater areas of the Gulf; however, resources

have been discovered beyond the reach of these pipeline assets. For future deepwater development,

several alternatives may be viable. Figure 2A.5 depicts cost verses concept for an offshore-based

approach compared to a shipping-based approach.

DEEPWATER FIELD DEVELOPMENT SOLUTIONS

Several options for deepwater field development are available to operators. These include

• FPSOs – provide low-cost “real estate” for processing equipment, but require a rig for well

interventions
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• TLPs – favored when direct vertical access is needed and many wells are required for

optimal recovery of hydrocarbon resources

• Spars and TLPs – lack storage, but minimal storage can be designed into the structures

SHIPPING-APPROACH ALTERNATIVES

Two of the most viable shipping-approach alternatives for deepwater developments are floating

production, storage, and offloading systems (FPSOs) and direct shuttle loading (DSL). The

following is a brief characterization of the two shuttle offtake solutions.

• Floating Production, Storage, and Offloading Systems

- Offtake configuration is usually in tandem

- Offtake occurs from a spread-moored or weather vaning FPSO or FSO

- Field storage of liquid hydrocarbons is an integral part of the system

• Direct Shuttle Loading

- DSL offers a variety of offtake configurations

- Offtake can occur from fixed platform, spar, or TLP

- DSL has minimal or no storage of liquid hydrocarbons in the field

- DSL can accommodate a wide range of production rates

Floating storage works. There are 66 FPSO vessels operating worldwide today. There are 62 floating

storage and offloading (FSO) vessels also operating worldwide. Both of these systems are adaptable

to worldwide sea conditions—from the North Sea to South America. These systems are independent

of infrastructure. There has not been a significant spill in the 20-year operating history of these

systems.

Conoco’s Heidrun direct shuttle loading is an example of the DSL systems available to offshore

operator today. The Heidrun oil offloading system operates off the coast of Norway in the North

Sea. Since its inception in 1995, the Heidrun system has been able to maintain 100 % uptime. It has

had production rates of up to 250,000 barrels of oil per day (BOPD).

There are some DSL concepts for a GOM application. The design would accommodate expected

Gulf sea conditions. It would be capable of operating in four-meter significant wave heights. The

system would be water-depth independent. The Figures 2A.6 through 2A.10 depict a possible DSL

system for the Gulf.

Chuck Steube’s has been Director of Floating Systems Operations for Conoco Shipping Company

since 1997. He has more than 25 years of operations experience with Conoco ranging from onshore,

arctic, offshore field operations, and field developments. He was part of the Project Team that

installed Conoco’s first FPSO in Nigeria and was the Offshore Superintendent for that installation.

Chuck holds a B.A. degree from Texas Tech University and an MBA from Tulane University.
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Figure 2A.6. A 40m by 20m L&B. It has 4x2 MW horizontal thrusters and 4x1 MW vertical

thrusters. The system is powered by a high-voltage cable/umbilical.

Figure 2A.7. A shuttle tanker, one example of a GOM crude oil shuttle vessel alternative.
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Figure 2A.8. A sea-going articulated barge, another example of a GOM crude oil shuttle vessel

alternative.

Figure 2A.9. A depiction of a coselle CNG carrier from Cran and Tenning Technology, Inc., of

Calgary, Canada. The carrier is a 60,000 DWT ship with 108 coselles capable of

transporting 300 mmscf of natural gas.
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Figure 2A.10. A depiction of natural gas storage in coselles on a CNG carrier.
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Management

 Committee

Program Manager Advisory Panel Contributor Advisory

Panel

Admin Staff Systems

 Engineering

Team

Vendors &

 Contractors

Technical

Committees &

 Technical Consultants

Figure 2A.11. Components of DeepStar’s Phase V cooperative.

DEEPSTAR ACTIVITIES, ACCOMPLISHMENTS, AND PLANS

Mr. Allen J. Verret

DeepStar

Mr. Steve Brooks

ExxonMobil

BACKGROUND

DeepStar is an industry-led cooperative effort to develop economically viable, fit-for-purpose

deepwater production technology with global applicability and to support the regulatory acceptance

of this technology. Its initial focus is on the Gulf of Mexico (GOM). DeepStar’s original focus was

on “extended reach subsea tieback concepts.” Over time, its focus evolved and broadened to “how

to develop deepwater technology.” With this change in focus, participation contracts broadened.

Figure 2A.11 depicts the various components of DeepStar’s Phase V cooperative.

The DeepStar cooperative has eight working Technical Committees. Table 2A.6 depicts the

technical groups and the persons (and their company affiliation) that serve as chairs for the

committees.
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Table 2A.6. DeepStar technical committees.

GROUP PERSONS – COMPANY

5100 Regulatory Group Steve Brooks – ExxonMobile

Debra Beaubien – BP-Amoco

Allen Verret – Mark A. Stair & Assoc.

5200 Flow Assurance Harvey Hensley – Phillips

Jim Chitwood – Chitwood Engineers

5300 Controls, Pipelines, & Subsea Otto Granhaug – Oxy USA

Ray Seid – Paragon

Steve Stockman – Texaco

5400 Vessels, Mooring & Risers Paul Devlin – Texaco

5500 Drilling Completions Rod Roberts – Marathon

George Medley – Signa

5600 Project Management Paul R. Hays – Texaco

5700 Reservoir Engineering Walt Bozeman – Vastar

5800 Met-Ocean Tom Mitchell – Texaco

5900 Systems Engineering Denby Morrison – Shell

Jim Chitwood – Chitwood Engineers

The monetary expenditures for the various phases of the DeepStar cooperative are shown in Table

2A.7.

Table 2A.7. DeepStar phase expenditures.

PHASE DOLLARS (U.S.)

I 550,000

II 4,800,000

IIA 9,500,000

III 7,800,000

IV 15,300,000

V 8,000,000

TOTAL VALUE 45,950,000
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DEEPSTAR PHASE V

Phase V of DeepStar was begun in January 2000. It is an $8,000,000, two-year program with 16

paying participants. DeepStar is pursuing other prospective participants to join this phase of the

program. The budget is segmented into specific areas of concentration. They are the following:

• Systems Engineering

• Enhancing existing technology in water depths of up to 6,000 feet

• Enabling new technology in water depths from 6,000 feet to 10,000 feet

• Implementation through standards and regulations, and

• Administration of the program

DeepStar has two primary goals for Phase V. They are to

• Optimize existing tools and processes and

• Deploy technology

The following are examples of deployed technology under DeepStar’s projects:

• For the Gemini Project:

- Multiplexed control system architecture and functional requirements

- Combination metal tube umbilical in lieu of thermo-plastic hose to reduce costs and risks

offering better resistance to collapse and spill prevention

- Fluid compatibility matrix—work done ahead of time that expedited project execution

• For the Arnold and Oyster Projects:

- Pipe-in-pipe insulated flowlines—first 6-inch in 10-inch reeled pipeline (Arnold)

- Round trip piggable flowline system

- Full-life transit analysis of multiphase flow in deepwater pipeline systems

- Designated, retrievable flow cut devices with quick acting control systems

• Other technology deployed by industry:

- Agip and Unocal have already used extended reach blockage hardware in GOM field

applications—more than 10 other deployments have occurred off of GOM platforms

- Feedback has been provided and the Ambar System is continuing to undergo

modifications to be a more effective tool for blockages
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REGULATORY COMMITTEE

The DeepStar’s Regulatory Committee has focused its attention primarily on OCS activities and the

federal agencies that have that jurisdiction. DeepStar was most supportive of the Memorandum of

Understanding (MOU) between the MMS and the U.S. Coast Guard that detailed regulatory

responsibilities on the OCS. The MOU was revised and executed in late 1999.

DeepStar also undertook a major effort in funding an “outsourced” environmental impact statement

(EIS) regarding floating production, storage, and offloading systems (FPSOs). DeepStar’s intent was

to provide accurate technical and environmental information about FPSOs so that the MMS could

determine their applicability in the GOM. The outsourced EIS would help to expedite the MMS’s

decision on FPSOs. The EIS is projected to cost the industry approximately $1.3 million. In

addition, the industry has expended about $750,000 in assistance to the EIS. Possible outcomes from

the EIS include:

• Use of FPSOs with no conditions

• Use of FPSOs with special conditions, or

• No decision on a general basis with reviews done on a case-by-case basis

DeepStar is also involved in a comparative risk assessment (CRA) regarding offshore production

systems. The CRA is an MMS funded and DeepStar-supported effort to compare the risks of

operating tension-leg platforms (TLPs), spars, fixed platforms as “hubs” and FPSOs in the GOM.

The industry has several roles and methods of participation in the CRA. The industry’s input,

experience, and expertise in all the systems are important to the success of the CRA study. The CRA

Study process includes

• Interactive workshops for industry to provide input and share its experiences and expertise

• Interim reports with an opportunity for industry review and comments, and

• A final report with an opportunity for review and comments

Workshop participation was offered both online and offline. Online industry had topical inputs and

discussions. Consistency from workshop to workshop was sought. The workshops also helped

develop a consensus of views. Offline, participants reviewed pre-workshop materials and prepared

for the meeting. Post-workshop actions involved reviewing reports and providing feedback.

Participants also worked with others in the industry to ensure appropriate information was provided

in the workshop. Everyone strove to provide useful information and data. The CRA Study was

programmed to be completed at the same time that the FPSO EIS would be available.
129

Mr. Allen Verret entered service with Texaco after receiving his B.S. in civil engineering at the

University of Louisiana at Lafayette in 1970. He was assigned to the then-new Offshore District

Office in Morgan City. During his career with Texaco, Allen held engineering, management and

advisor positions in field, district, and division offices and worked in engineering, construction, field

operations, production, drilling, and workover operations as well as being active in the marine

technology development needs. Mr. Verret has been active in the DeepStar Project since its

inception and has served as Texaco’s Senior Advisor on the Management Panel as well as being the

Chairman of the Regulatory Committee for Phase I through Phase IV. Allen retired from Texaco in

1999 after 29 years of service in their offshore Gulf of Mexico operations. He is currently the

Technical Advisor to the Regulatory Issues Committee and serves as the Executive Director of the

Offshore Operators Committee in New Orleans, LA.

Mr. Steve Brooks graduated from the University of Tennessee. He has been with Exxon almost 33

years, including time in the U.S. Army. Steve started his career in marketing, but the last 19 years

have been in various engineering and management positions associated with offshore production

operations. Steve is currently responsible for ExxonMobil’s offshore regulatory compliance

activities. He serves as the co-chair for the DeepStar Regulatory Issues Committee, and Chairman

of OOC Technical Subcommittee. Additionally, he is involved with several other industry

committees, most recently chairing the API Recommended Practice 2D - 3rd Edition - committee

and the API RP 14C - 7th edition - committee.
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UPDATE ON U.S. COAST GUARD OCS ACTIVITIES

LCDR John Cushing

Chief, Outer Continental Shelf Branch

Eighth Coast Guard District

INTRODUCTION

The U.S. Coast Guard (USCG) has three major areas of regulatory activities concerning the Outer

Continental Shelf that may be of interest to you. They are

• Revision of Subchapter N (33 CFR 140-147),

• The current USCG position on floating production, storage, and offloading (FPSO) facilities

and applicable regulations, and

• The memorandum of understanding (MOU) between the USCG and the Minerals

Management Service (MMS).

SUBCHAPTER N (33 CFR 140-147)

Subchapter N is being written in “plain English.” The notice of proposed rule making (NPRM) was

published on 7 December 1999. Comments from the public were due on 5 April 2000. The USCG

extended the comment period until 30 November 2000. Major changes were proposed for certain

subparts of Subchapter N.

33 CFR 142, Workplace Safety and Health

Subpart B (Personal Protection Equipment) includes these new requirements (note subsections are

in parentheses to facilitate identification):

• Hearing protection (142.135),

• Electrical safety training (142.145),

• Personal transfer net certification and inspections (142.165),

• Radiation monitoring (142.175 to 142.179),

• Airborne substance exposure limits (142.180 to 142.183), and

• Infectious material exposure training (142.185)
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Subpart C (General Workplace Conditions) also received modifications that contained new

requirements. These are

• Preventing deck obstructions near survival craft (142.207),

• Noise surveys and required singage (142.235 to 142.240),

• Guards for rotating and reciprocating machines (142.245 to 142.250)

• Proper use and maintenance of equipment (142.255)

• Use and maintenance of slings (142.260),

• Use and maintenance of personnel transfer nets (142.265 to 142.280), and

• Warning sign requirements (142.285).

Subpart D (Confined Space Entry) is a new part of the regulations. The following are requirements

contained in this subpart:

• A comprehensive confined space entry program,

• Testing of confined spaces prior to entry,

• Testing be conducted by a

- Certified marine chemist

- Certified industrial hygienist

- Offshore competent person, and

• Presence of “rescue team” during entry.

The subpart also identifies training requirements for an “offshore competent person.”

33 CFR 143, Fixed Facilities

Significant changes were made to the lifesaving equipment requirements of the regulations. These

include

• Lifeboats on all manned OCS facilities (100 % capacity)

• Two lifeboats for facilities with more than 31 persons

• Rescue boat required on facilities with more than 8 persons
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• Lifefloats (vice liferafts) permitted for additional 100 % lifesaving capacity if facility is

within three (3) nautical miles of a “safe haven”

• “New” equipment is required within two years of the effective date of the Final Rule.

Substantial changes were made to the fire-fighting equipment requirements as well. These changes

include

• Comprehensive requirements for portable and semi-portable fire extinguishers

• Manned facilities must have fire main systems (water) for

- Accommodation spaces

- Helicopter decks

• Two fireman’s outfits are required if a facility has more than 8 persons

• The fire-fighting equipment detailed under 33 CFR 143, Subpart K, is required within two

years of the effect date of the Final Rule.

Structural fire protection (SFP) for manned facilities is addressed under Subpart L. These

requirements only apply to new manned facilities.

• Requires accommodation spaces meet SFP requirements of NFPA 101

• Have independent “A-60" fire wall if within 30 meters of platform hydrocarbon source, or

• Meet SFP requirements of 46 CFR 108 (MODU regulations)

Maximum noise limits have been set for new facilities are shown in Table 2A.8.

Table 2A.8. Maximum noise limits for new facilities.

AREAS MAX. NOISE LEVEL (in dbA)

Sleeping rooms 60

Mess rooms 65

Offices 65

Recreation rooms 65

Open recreation areas 75

Galleys 75
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33 CFR 144, Floating OCS Facilities

Comprehensive requirements are proposed for floating units (TLPs, Spars, FPSs, FPSOs, etc.) These

new regulations include:

• Meeting 33 CFR 142, Workplace Safety & Health standards,

• Lifesaving requirements for MODUs (generally)

• Firefighting and structural fire protection for MODUs (generally)

• Design and equipment requirements for MODUs and possibly API RP 2FPS (draft)

Overall Status of Subchapter N

• Significant comments from the industry are on the docket

• Comments are likely to delay the Final Rule

• The USCG has the MMS’s comments, and the USCG is committed to a close partnership

with the MMS

FLOATING PRODUCTION, STORAGE AND OFFLOADING (FPSO) FACILITIES

The current USCG position on FPSO in part is as follows:

• FPSOs are vessels regardless of their shapes

• Oil stored within a FPSO is considered to be “cargo”

• The OPA-90 hull requirements apply

Applicable USCG regulations that apply to FPSOs are

• 33 CFR 144 (being developed): Floating OCS facilities

• 33 CFR 157 (OPA –90): Double hull

• 46 CFR Subchapter D: Tank vessels

MEMORANDUM OF UNDERSTANDING (MOU) BETWEEN THE USCG AND THE MMS

The following is a brief update on the MOU between the two agencies.

• The MMS is to do annual “CG inspection” on fixed platforms
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• Implementation:

- Short term: Training, forms (address in MOU?)

- Long term: MOU, eventually Subchapter N

• The MMS/USCG transition team is working on short- and long-term implementation

• USCG legal department is reviewing authority for MMS to enforce USCG regulations

• Target for short-term implementation is 1 July 2001

Lieutenant Commander John Cushing is the Chief of the Offshore Compliance Branch, Eighth Coast

Guard District, located in New Orleans. Prior to his current assignment, he worked two separate

tours of duty in the Marine Safety Office Portland, Oregon (1986-1990 and 1996-2000), serving as

Marine Inspector, Resident Shipyard Inspector, and Assistant Chief in the Inspections Department.

Between his assignments in Portland, he served four years in the Marine Safety Center in

Washington, DC. His duties in the MSC were Staff Engineer, performing structural & stability plan

reviews, and Chief of the MODU Branch. LCDR Cushing has served on the USCG Cutter Sherman

in 1985-1986 as an Assistant Engineer Officer, and the Cutter Mellon from 1984-1985 as a Student

Engineer. LCDR Cushing graduated from the Coast Guard Academy (Class of 1984) with a B.S. in

civil engineering. He received M.S. degrees in mechanical engineering, and naval architecture and

marine engineering from the Massachusetts Institute of Technology in 1992.
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SESSION 2B

AIR QUALITY (continued)

Chair: Dr. Chester Huang, Minerals Management Service

Co-Chair: Ms. Terry Scholten, Minerals Management Service

Date: December 5, 2000

Presentation Author/Affiliation

Assessment of Air Pollutant Emissions in the

Gulf of Mexico

Ms. Darcy Wilson

Eastern Research Group

Research Triangle Park, NC

Mr. Brian Boyer

COMM Engineering

Lafayette, LA

Recent Advances in Air-Sea Interaction

Studies Applied to Overwater Air Quality

Modelling

Dr. S. A. Hsu

Professor of Marine Meteorology

Louisiana State University
137

ASSESSMENT OF AIR POLLUTANT EMISSIONS IN THE GULF OF MEXICO

Ms. Darcy Wilson

Eastern Research Group

Research Triangle Park, NC

Mr. Brian Boyer

COMM Engineering

Lafayette, LA

ABSTRACT

The Minerals Management Service (MMS) is responsible for determining if air pollutant emissions

from platform and other sources in the Gulf of Mexico (GOM) influence the ozone attainment (and

nonattainment) status of onshore areas. To this end, MMS implemented the Gulfwide Emission

Inventory Study to develop a base year 2000 inventory of criteria pollutant emissions for all oil and

gas production-related sources in the Gulf. MMS will ultimately provide the inventory data to state

agencies for their use in regional modeling.

MMS conducted an initial study of emission sources in the GOM whose results are summarized in

the 1995 report: “Gulf of Mexico Air Quality Study” (MMS 1995). The 1995 study covered many

types of offshore emission sources, focusing on oil and gas production platform emissions. MMS

is working on a project that affects only platforms near the Breton National Wilderness Area in the

Gulf. As a part of this program, MMS developed a Visual Basic program for platform operators to

use to submit activity data on a monthly basis. The Breton Offshore Activities Data System

(BOADS) is being used by affected operators to submit activity data for a number of production

platform emission sources. 

The Gulfwide Emission Inventory Study builds upon these MMS studies with the goal of developing

criteria pollutant and greenhouse gas emission inventories for all oil and gas production-related

sources in the entire GOM. The Gulfwide Offshore Activities Data System (GOADS) is being

developed from the BOADS Visual Basic program, modified to request activity data for additional

emission sources. The 1995 “Gulf of Mexico Air Quality Study” will be used as the starting point

for non-platform sources covered in the Gulfwide Study. 

This paper focuses on the (1) the form emission sources that will be covered in the Gulfwide

Emission Inventory Study that are not covered in the Breton Island study and (2) the methods that

will be used to estimate emissions from these sources. It will also briefly discuss the non-platform

sources covered, and how emissions estimates for these sources will be developed. Lastly, we will

present the proposed schedule for the Gulfwide Emission Inventory Study. 
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INTRODUCTION

MMS published Notice to Lessees and Operators (NTL) 99-G15 to introduce the “Production

Activities Information Collection and Reporting” requirements for lessees and operators of federal

oil, gas, and sulphur leases in the Outer Continental Shelf, Gulf of Mexico OCS Region. A

workshop was held in New Orleans 15 November 1999 to discuss and explain the GOADS

information collection and reporting procedures, the pollutants to be covered in the study, and why

the GOADS study was being undertaken. In addition, information was provided to assist in

submitting activity data needed for GOADS. Much of the information provided is available on the

GOADS website: http://www.gomr.mms.gov/homepg/regulate/environ/airquality/goad.html

Information posted on this website by MMS includes:

• NTL 99-G15

• Frequently Asked Questions (FAQs) and other updates on data collection and reporting

• The BOADS Users Guide (for use until GOADS is available)

• The BOADS Activity Database (for use until GOADS is available)

• Slides and other helpful activity data collection tips from 15 November 1999 workshop

When it is available, the GOADS data collection software will also be posted here. A training course

is planned for 15 March 2001.

In addition to collecting activity data from platform operators, we are modifying an existing

Oracle® program to house the GOADS platform activity data and develop emission estimates. This

Oracle® program will also house activity data and other data needed to calculate emissions for nonplatform sources in the Gulf. Non-platform sources that will be included in GOADS include:

• Drilling vessels

• Pipe laying vessels

• Survey vessels

• Construction barges

• Off-shore tugs

• Crew boats

• Supply boats
139

• Lightering vessels

• Helicopters

• The Louisiana Offshore Oil Port (LOOP)

• Oceangoing barges

• Commercial fishing

• Recreational fishing

• Commercial marine vessels

• Military activities

• Biogenic sources

ACTIVITY DATA NEEDED AND ESTIMATION METHODS

FOR NEW PLATFORM SOURCES

The goal of the Gulfwide Emission Inventory Study is to develop an emission inventory for all

criteria pollutants and greenhouse gases. To this end, activity data are needed for sources that are

not covered in BOADS, particularly sources of volatile organic compounds (VOCs). Listed below

are the new equipment in GOADS (but not in BOADS), and the data needed and methods that will

be used to estimate emissions. Operators will also be asked to provide a sales gas analysis for each

platform.

Pressure/Level Controllers

For pressure and level controllers, we need to estimate emissions associated with the bleed-rate of

each controller. Information needs for pressure and level controllers were discussed at the 15

November 1999 GOADS workshop. Operators will be asked to provide the following information,

but only for controllers that are in natural gas service. Operators should not include units in

compressed air service.

• Service type (pressure control vs. level control)

• Manufacturer and model (with pre-populated lookup tables, or can be added)

• Amount of natural gas consumed in SCF/hr (optional)

• Hours of operation in the reporting period

• Average elevation above mean sea level
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Hydrocarbon emissions for pressure and level controllers will be developed using the following

equation (EIIP 1999):

Lbs/hr = (SCFH) (mole weight of gas, lbs/lb-mole) (1 lb-mole/379 SCF)

Where SCFH = standard cubic feet per hour of natural gas used.

Pneumatic Pumps

For pneumatic pumps, we need to estimate emissions associated with each pump (i.e., chemical

injection, Wilden diaphragm, Texstream chemical and diaphragm, etc.). Information needs for

pneumatic pumps were also discussed at the 15 November 1999 GOADS workshop. Operators will

be asked to provide the following information, but again, only for pumps that are in natural gas

service. Operators should not include pumps in compressed air service.

• Manufacturer and model (with limited pre-populated lookup tables)

• Amount of natural gas consumed in SCF/hr (optional)

• Hours of operation in the reporting period

• Average elevation above mean sea level

• Whether it is vented to a manifold, a flare, or the atmosphere

Hydrocarbon emissions for pneumatic pumps will be developed using the following equation (EIIP

1999):

Lbs/hr = (SCFH) (mole weight of gas, lbs/lb-mole) (1 lb-mole/379 SCF)

Where SCFH = standard cubic feet per hour of natural gas used.

Losses from Flashing

Flash gas is natural gas that is liberated when an oil stream undergoes a pressure drop. BOADS

requests data for flash gas associated with storage tanks. For GOADS, we also need to collect data

associated with separators, heater treaters, and surge tanks. We only need to account for flash gas

that is vented to the atmosphere or burned in a flare. Flash gas that is routed back into the system

(e.g., sales pipeline) should not be reported in GOADS. 

Each point of separation/treatment must be examined as a potential source of flash gas. For example,

oil from a low-pressure separator may be sent to a heater treater, then on to a storage tank. Flash gas

that is vented or flared from each vessel must be accounted for.
141

Flash gas can be vented to the atmosphere or burned in flares from the following equipment: high,

intermediate and low pressure separators; heater treaters; surge tanks; accumulators; and fixed roof

atmospheric storage tanks.

Operators will be asked to report the following parameters for each part of the process:

• API gravity of stored oil

• Operating pressure (psig) of each vessel (i.e., separator, heater treater, surge tank, storage

tank)

• Operating temperature (°F) of each vessel

• Actual throughput of oil for each vessel

• Disposition of flash gas from each vessel – routed to system (e.g., sales pipeline, gas-lift),

vented to atmosphere, or burned in flare

• SCF of flash gas per bbl of oil throughput specific to your source (optional)

Emissions for losses from flashing will be developed using the Vasquez and Beggs Correlation

Equations to estimate tank vapors in standard cubic feet per barrel of oil produced. 

Fugitive Emissions

Fugitive emissions are included in the BOADS software, but operators are not required to report the

information for BOADS. However, fugitives must be reported in the annual report for the GOADS

effort. To report fugitive emissions in GOADS, operators will be required to supply the information

requested for fugitives in the BOADS software. This information includes delineating the stream

type (gas, heavy oil, light oil, or water/oil) and average VOC weight percent of fugitives, and an

equipment inventory (number of components). To facilitate this process, MMS will only require a

one-time submittal of this information—operators will not be required to cut and paste the

equipment inventory data every month. 

Operators are encouraged to prepare an equipment inventory by making direct counts of components

by service type. It may be beneficial to use of the information presented in Table 2B.1 as a starting

point, however. This information was compiled for MMS by the Offshore Operators Committee and

can be adjusted by service type for each component for each part of the production train (i.e., for

each skid type). 

Also note that because there is a large variation in emissions for compressor seals, operators will

also be asked to specify the compressor and seal type as:

• Centrifugal-wet seal
142

Table 2B.1. Summary of Equipment Inventory Data (Number of Components) by Skid Typea

Skid Type

Valves

Pump Seals

Threaded

Flanges

Open Ended LinesCompressor SealsDiaphragmsDrainsDump ArmsHatchesInstrumentsMetersPressure Relief ValvesPolished RodsOther Relief ValvesVents

Separator Skid 34 0 13 73 0 0 0 2 0 0 15 1 1 0 0 0

Heater Treater Skid 98 0 70 114 0 0 0 3 0 0 25 0 3 0 0 0

LACT Charge Pump Skid 21 3 6 47 0 0 0 1 0 0 9 0 0 0 0 0

LACT Skid 62 1 75 69 0 0 0 1 0 0 34 4 6 0 0 0

Pipeline Pumps Skid 39 3 12 78 0 0 0 2 0 0 70 0 3 0 0 0

Pig Launcher/Receiver Skid 13 0 14 16 0 0 0 0 0 0 9 0 1 0 0 0

Compressor Skid 119 0 113 138 0 4 0 1 0 0 69 0 9 4 0 0

Filter/Separator Skid 30 0 25 37 0 0 0 1 0 0 9 0 1 0 0 0

Gas Dehydration Skid 23 0 14 40 0 0 0 1 0 0 12 0 1 0 0 0

Glycol Regeneration Skid 134 0 110 194 0 0 0 4 0 0 45 1 7 6 1 0

Gas Meter 10 0 11 26 0 0 0 1 0 0 21 2 0 0 0 0

Fuel Gas Skid 62 0 47 85 0 0 0 1 0 0 32 1 4 0 0 0

Flotation Cell Skid 41 1 34 70 0 0 1 1 0 15 8 0 2 0 2 0

Scrubber 13 0 13 18 0 0 0 1 0 0 9 0 1 0 0 0

Amine Unit 226 8 166 391 0 0 1 5 0 0 121 2 12 0 1 0

Line Heater 30 0 46 18 0 0 0 1 0 0 10 0 0 0 1 0

Production Manifold 108 0 31 148 0 0 0 1 0 0 43 0 0 7 0 0

Wellhead 15 0 6 19 0 0 0 0 0 0 11 0 0 0 0 0

Import or Export Pipeline 3 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0

a Provided to MMS by the Offshore Operators Committee, August 2000.
143

• Centrifugal- dry seal

• Reciprocating- shaft packing, or

• Other (specify)

The information in Table 2A.2 may also be useful for completing the GOADS fugitive emissions

general information tab.

Table 2B.2. Speciation weight fractions for total hydrocarbon (THC) emissions by stream typea.

THC Fraction Gas

Light Oil

(3 20 API Gravity)

Heavy Oil

(<20 API Gravity) Water/Oilb

Methane 0.687 0.612 0.942 0.612

Non-methane 0.313 0.388 0.058 0.388

VOC 0.171 0.296 0.030 0.296

a

 Source: API. 1996. Calculation Workbook for Oil and Gas Production Equipment Fugitive Emissions.

b

 Water/oil refers to water streams in oil service with a water content greater than 50% from the point of

origin to the point where the water content reaches 99%. For water streams with a water content greater

than 99%, the emission rate is considered negligible.

Emission estimates for fugitives will be developed using the emission factors shown in Table 2B.3.

Table 2B.3. EPA Average Emission Factors for Total Hydrocarbon Emissions from Oil and Gas

Production Operations (lb/component-day)a

Gas

Heavy Oil

(<20 API Gravity)

Light Oil

(3 20 API Gravity) Water/Oil

Connector 1.1E-02 4.0E-04 1.1E-02 5.8E-03

Flange 2.1E-02 2.1E-05 5.8E-03 1.5E-04

Open-end 1.1E-01 7.4E-03 7.4E-02 1.3E-02

Otherb 4.7E-01 1.7E-03 4.0E-01 7.4E-01

Pump 1.3E-01 Not Avail 6.9E-01 1.3E-03

Valve 2.4E-01 4.4E-04 1.3E-01 5.2E-03

a

Source: API, 1996. Calculation Workbook for Oil and Gas Production Equipment Fugitive Emissions.

b Includes compressors, diaphragms, drains, dump arms, hatches, instruments, meters, pressure relief valves,

polished rods, and vents.
144

Mud Degassing

Mud degassing emissions occur when gas that has seeped into the well bore and dissolved or

become entrained in the drilling mud is separated from the mud and vented to the atmosphere (EIIP

1999). In GOADS, operators only need to include information on platform drilling rigs or from jackup rigs adjacent to platforms. For required drilling activity, operators should keep a record of:

• Number of days that drilling operations occurred

• Number of wells drilled

• Depth of each well

• Type of drilling mud used (water-based, synthetic, oil-based)

Hydrocarbon emissions will be estimated using emission factors provided in the 1977 EPA report:

Atmospheric Emissions from Offshore Oil and Gas Development and Production (0.4 Mg/day for

water-based and 0.09 Mg/rig for oil-based muds). 

ACTIVITY DATA NEEDED AND ESTIMATION METHODS

FOR NON-PLATFORM SOURCES

For the non-platform emission sources in the Gulf, we will use the 1995 GOM inventory as the

starting point. For all of the vessels and barges included in this study, emissions will be calculated

using the following information:

• Number of vessels by engine type, horsepower and typical load factors 

• Duration and route of travel 

• Duration of ship hotelling (LOOP) 

• Hours of operation 

• Fuel consumption by vessel 

The appropriate activity data will be combined with the most up-to-date emission factors. Most of

the marine sources are diesel powered, and we will use recently published emission factors from the

EPA’s Marine Diesel Engine Regulatory Program, with spatial, seasonal, and diurnal adjustments

to reflect monthly activity (EPA 2000). For helicopters, emissions will be estimated based on

landing-takeoffs (LTOs) and hours of operation. These data will be combined with the emission

factors used in the 1995 study. 

In addition to emissions associated with fuel combustion, loading and ballasting emissions will be

developed for lightering vessels and the LOOP based on throughput. Mud degassing emissions will
145

be generated using data from the MMS Platform Inspection System. Volatile organic compound

emissions from sub-surface oil and natural gas seeps will be estimated using from the 1995 MMS

report “Northern Gulf of Mexico Chemosynthetic Ecosystems Study” (McDonald et al. 1995). 

SCHEDULE

Operators are encouraged to use the BOADS software until the GOADS software is finalized. It is

important that the operators maintain a copy of every monthly BOADS survey with a unique file

name. The files should be named so that the month can be conveniently identified later from the

filename. These data can then be directly uploaded into the GOADS software when it becomes

available. Operators will then have to enter only data for the new data elements and equipment

discussed in this paper. 

Training on the GOADS software is currently scheduled to take place 15 March 2001 in New

Orleans. Operators will be given the GOADS software and GOADS User’s Guide, and will receive

training on uploading their BOADS files, and entering new data elements and equipment

information unique to GOADS. 

An important new feature of GOADS is the QA Summary Form, which operators will be required

to print out and submit along with their electronic files. The QA Summary Form identifies key

missing or inconsistent data that would prevent calculation of emissions. This form is designed to

identify missing data so they can be corrected before the files are sent to MMS. Otherwise, the

missing data would be identified during MMS’s review of the files, and the operators would be

contacted and asked to submit the missing data. The goal of the QA Summary Form is to make the

GOADS data collection process more efficient and to reduce the burden on both MMS and the

operators.

Following the release of the GOADS software and User’s Guide, and training on its use, the current

schedule proposes that operators submit their GOADS files (with the QA Summary Form printout)

by 15 June 2001.

MMS will complete the QA/QC of the submitted activity data files and take the necessary corrective

actions by 1 December 2001. Draft emission calculations will be prepared by February 2002; final

by July 2002.

REFERENCES

API, 1996. Calculation Workbook for Oil and Gas Production Equipment Fugitive Emissions.

Emission Inventory Improvement Program (EIIP). 1999. Preferred and Alternative Methods for

Estimating Air Emissions from Oil and Gas Field Production and Processing Operations (EIIP

Volume II – Chapter 10).

Minerals Management Service (MMS). 1995. Gulf of Mexico Air Quality Study. U.S. Department

of Interior, Minerals Management Service, Gulf of Mexico OCS Region. MMS 95-0040. 
146

McDonald et al. 1995. Northern Gulf of Mexico Chemosynthetic Ecosystems Study. Prepared by

the Geochemical and Environmental Research Group. U.S. Department of Interior, Minerals

Management Service, Gulf of Mexico OCS Region. MMS 95-0023. 

Offshore Operators Committee. August 2000. Summary of Equipment Inventory Data (Number of

Components) by Skid Type. 

U.S. Environmental Protection Agency (EPA). 1977. Atmospheric Emissions from Offshore Oil and

Gas Development and Production. EPA-450/3-77-026. 

U.S. Environmental Protection Agency (EPA). 2000. Analysis of Commercial Marine Vessels

Emissions and Fuel Consumption Data. Office of Transportation and Air Quality, Ann Arbor,

MI. EPA-420/R-00-002.
147

RECENT ADVANCES IN AIR-SEA INTERACTION STUDIES APPLIED TO

OVERWATER AIR QUALITY MODELLING

Dr. S. A. Hsu

Professor of Marine Meteorology

Louisiana State University

INTRODUCTION

Air pollution meteorology is concerned with the fate of pollutants once they are emitted into the

atmosphere and addresses natural releases, deliberate industrial emissions, and accidental spills.

According to Zannetti (1990), air quality modeling is an essential tool for most air pollution studies.

For more detail about air pollution meteorology and air quality modeling, see, e.g. Hanna et al.

(1982), Zannetti (1990), and Arya (1999).

Overwater dispersion characteristics required in air quality modeling include stability classification,

turbulence intensity, eddy diffusion, and mixing height. The purpose of this review is to synthesize

recent advances in these parameterizations. The most important difference between sea and land is

that the sea surface is in motion while the land surface is fixed. Sea waves and currents will affect

the aerodynamic roughness so that rapid changes in both space and time depend upon the windgenerated wave characteristics. Hence the drag coefficient, which is fixed on land, cannot be treated

as a constant. This in turn affects a host of other overwater characteristics.

DETERMINING THE STABILITY CHARACTERISTICS

For overwater air quality modelling, the Offshore and Coastal Dispersion Model (OCD) (see Hanna

et al. 1985) has recommended for regulatory use by both the U.S. Environmental Protection Agency

(EPA) and the U.S. Minerals Management Service (MMS) for emissions located on the outer

continental shelf (see Zannetti 1990). In this EPA preferred model, the stability parameter z/L is

required, where z is the height above the surface and L is the Monin-Obukhov stability length, which

is defined as (see, e.g., Garratt 1992, p. 38)

(1a)

L

u

g w

v

v

= − *

' '

3 θ

κ θ

or as (e.g., Panofsky and Dutton 1984, p. 132)

L (1b)

u CT

g H B

ph air

= −

+ 



 





*

.

3

1

0 07

ρ

κ
148

where u* is the friction velocity, 2v is the virtual potential temperature, g is the gravitational

acceleration, 6 is the von Karman constant, is the surface buoyancy flux, D is the air density, Cph is

the specific heat of air at constant pressure, Tair is the air temperature, H is the surface layer sensible

heat flux, and B is the Bowen ratio (the ratio of sensible to latent heat flux). Note that Tair should be

Tv, the virtual temperature. However, since Tv = Tair (1 + 0.68q) and q is at most 5% (see, e.g.,

Komen et al. 1994, p. 59), we use Tv – Tair.

Since direct measurements of u* and H are not available routinely, the following parameterization

is employed.

From Eq. 1b and Smith (1980, Eqs. 3 and 4)

(2)

( ) H

C

CU T T

ph

T sea air ρ = − 10

and

(3)

C

u

U d = 



 



 *

10

2

or u*

3

 = U10

3

Cd

3/2, we have for unstable condition (Tsea > Tair)

(4a) ( )

L

TC U

gCT T B

air d

T sea air

= −

− + 



 





3 2

10

2

1

0 07

/

. κ

and for stable condition (Tsea < Tair)

(4b) ( ) L

TC U

gCT T

air d

T sea air

= − −

3 2

10

/ 2

κ

where CT is the heat flux coefficient (= 1.1 x 10-3 for unstable, 1.0 x 10-3 for neutral and 0.83 x 10-3

for stable conditions (see Smith 1980 and 1988)), Cd is the drag coefficient, U10 is the wind speed

at 10 m above the sea surface, and Tsea is the sea surface temperature.

On the basis of thermodynamic conditions, a relationship between B and (Tsea - Tair) under unstable

conditions (i.e., Tsea > Tair) has been proposed by Hsu (1998) that

(5a) B aT T ( ) sea air

b

= −
149

where a and b are to be determined by field experiments. Based on the availability of additional data

sets from tropical oceans and coastal seas, Hsu (1999) found

(5b) B TT = − 0146( ) sea air

0 49

. .

with a high correlation coefficient of 0.94 between B and (Tsea - Tair). This paper will attempt to

verify Eq. (4) by employing this B parameterization along with a proven Cd formulation used

successfully in the third generation wave model (see WAMDI 1988, p. 1784) that

(6) ( ) C

x U ms

U x U ms d = <

+ ≥







− −

− −

12875 10 7 5

08 0 065 10 7 5

3

10

1

10

3

10

1

., .

.. , .

In order to verify Eq. (4), simultaneous measurements of Tair, Tsea, U10, and L are necessary. The data

sets provided in Donelan et al. (1997) supply all of these parameters. We classify z/L # -0.03 as

unstable, |z/L| < 0.03 as near-neutral, and z/L $ 0.03 as stable. In this verification, we set z = 10 m

to correspond to U10 and the Cd formulation used in Eq. (6). Our results are shown in Figures 2B.1

and 2B.2 for unstable and stable conditions, respectively. If one accepts the small RMSE values (.8

to 11 m) for the range of L between zero and approximately 350 m, Eq. (4) is verified. Note that the

term of B, i.e., (1 + 0.07/B) in the denominator of Eq. (4a) was dropped for stable conditions in Eq.

(4b) when Tair is larger than Tsea and therefore no sensible heat is directed from the sea to the air.

DETERMINING OVERWATER FRICTION VELOCITY, u*

The friction (or shear) velocity, u*, can be computed by Eqs. (3) and (6). On the other hand, from

the Wind-Wave Interaction method (Hsu 1995)

(7)

u

U

H

C

U

s

p

*

.

.

. ln

=

− 



 





























0 4

110

10

10

2 6

where Cp = gTp / 2B, is the phase speed of the waves at the spectral peak. Note that the parameter

Cp / U10 is defined as the wave age.

Figure 2B.3 shows the results of our comparison between Eqs. (3), (6), and (7) for the Gulf of

Mexico. Since the root mean square error is only 0.9 cm s-1 for the data range between 20 and 70 cm

s

-1, either Eq. (6) or (7) can be used. Since Eq. (6) is easier to use, it is recommended for operational

computations, although Eq. (7) can be used to explain Eq. (6) based on wind-wave interaction

characteristics. For more detailed discussion, see Hsu et al. 2000.
150

Figure 2B.1. A verification of Eq. (4a) for unstable conditions.
151

Figure 2B.2. A verification of Eq. (4b) for stable conditions.
152

Figure 2B.3. A comparison of the shear velocity u* based on Eqs. (3), (6), and (7) using buoy

#42040 during 15 and 16 November 1996 in the northeast Gulf of Mexico (Hsu et

al. 2000).
153

THE MIXING HEIGHT

Due to potential evaporation, the air over the water is usually moister than that over land, and the

top of the marine boundary layer is oftentimes capped by clouds (see, e.g., Garratt 1992). On the

basis of analysis of vertical soundings by research aircraft, rawinsondings, and radar wind profilers

and Radio Acoustic Sounding Systems (RASS), it has been shown by Garratt (1992) that the mixing

height h = LCL, the lifting condensation level under cumulus cloud conditions (where LCL = cloud

base). The height of the LCL may be estimated by (see Hsu 1998)

(8) H TT LCL air dew = − 125 ( )

where HLCL is in meters and the dewpoint depression at the sea surface in degrees Celsius.

On the eastern and Gulf coasts of the U.S., as well as over the East China Sea, cold air outbreaks are

common in the winter season. Under these conditions, according to Hsu (1997), the mixing height,

Zi

, is convectively unstable that

(9) Z A Bw i v ( )o = + ' ' θ

and from experiments conducted off the U.S. east coast and over the East China Sea, Zi is found to

be

(10) Z w i v = + 369 6004 ( )0 ' ' θ

where Zi is in meters and is the buoyancy flux in meters per second Kelvin.

For operational applications, the buoyancy flux at the sea surface is found to be 

(11) ( ) w CU T T ( ) B v T sea air ' . ' θ

0 10 1

0 07

= −+ 



 





where CT = 1.10 x 10-3 under unstable conditions (Smith 1980) and B is the Bowen ratio which has

been provided in Eq. (5b).

Alternately, if we know the mixing height on land, Hland (in meters), and a barotropic boundary layer

across the coastal zone exists, we may estimate the mixing height over the water, Hsea (in meters)

by applying (Hsu 1988, p. 183)

(12)

H H

C

C

U

U sea land

d sea

d land

sea

land

= 



















 





2
154

where Cd land is the drag coefficient on land, Cd sea is based on Eq. (6), Usea and Uland (both in m s-1) are

the wind speeds at sea and over land, respectively.

If the planetary boundary layer is baroclinic across the coastal zone, i.e., under the land and sea

breeze effects, according to Hsu (1988, p. 204)

(13) HH TT sea land land sea =− − 123 ( )

where Tland and Tsea (both in °C) are the air temperatures over land and sea, respectively.

In certain geographic regions and occasionally elsewhere, the sea surface temperature is less than

the air temperature. Therefore, the boundary layer is said to be stable. The mixing height under

stable conditions, hstable, is (see Garratt 1992)

(14)

h c

u L

f stable = * *

where f is the Coriolis parameter. From limited measurements under stable conditions, the

coefficient c*

 is found to be 0.11. Certainly, more field experiments are needed to further

substantiate Eq. (14) and the value of c*.

STANDARD DEVIATIONS OF THE CROSSWIND (Fy)

AND VERTICAL (Fz) DIRECTIONS

Some dispersion models require Fy and Fz in which Pasquill (1971) suggested that

(15)

σ σ y vy

L

t S

t

T = 



 





(16)

σ σ z wz

L

t S

t

T = 



 





or

(17)

σ

σ

y

v

y U L

x S

t

T = 



 



 



 





10
155

(18)

σ

σ z

w

z U L

x S

t

T = 



 



 



 





10

For overwater applications, the turbulence intensities are found to be (Geernaert et al. 1987)

(19)

σ v

U

U

10

=+ ± 0 0586 0 0012 0 015 10 .. .

and

(20)

σ w

U

U

10

=+ ± 0 0369 0 0010 0 005 10 .. .

All symbols are conventional in air-pollution meteorology (see, e.g., Zannetti 1990).

THE VERTICAL EDDY DIFFUSIVITY

In some K-diffusion models, the vertical eddy diffusivity, Kz, is required, e.g. (Hanna 1984)

(21)

K cu Z

Z

h z = − 



 



 * 1

where u* is the friction velocity and h is the mixing height. For example, the Urban Airshed Model

(UAM), the preferred model of the U.S. Environmental Protection Agency for ozone studies, has

a meteorological preprocessing subroutine which employs the gradient transport (K) modeling

(Zannetti 1990, p. 234). Since in the K-theory, u* is required for the computation of vertical

diffusivity, Kz, and concentration, P, it is recommended that proper formulas to reflect the overwater

variations in aerodynamic roughness length, Z0, and drag coefficient, Cd, be made in light of recent

advances in the air-sea interaction field as discussed previously.

SUMMARY

In air quality modeling, many parameters are required. Therefore, parameterization is needed.

Because the sea surface is mobile due to various wind waves and ocean currents, this review

attempts to synthesize those parameterizations specifically applied to the marine environment for

the determination of stability length, overwater friction velocity, the mixing height, turbulence

intensity, and vertical eddy diffusivity. Many more field experiments are needed in order to further

substantiate these results. The review provided here offers a guide for practical applications since

many in situ air-sea interaction parameters may not be available over vast regions of the ocean.
156

ACKNOWLEDGMENTS

This study was supported in part by the U.S. Minerals Management Service under Contract 14-35-

0001-30660 Task Order 19925.

REFERENCES

Arya, S.P. 1999. Air Pollution Meteorology and Dispersion. Oxford: Oxford University Press.

Donelan, M.A., W.M. Drennan, and K.B. Katsaros. 1997. The Air-Sea Momentum Flux in

Conditions of Wind Sea and Swell, J. Phys. Oceanogr. 27, 2087 - 2099.

Garratt, J.R. 1992. The Atmospheric Boundary Layer. Cambridge: Cambridge University Press.

Geernaert, G.L., S.E. Larsen, and F. Hansen. 1987. Measurements of the Wind Stress, Heat Flux,

and Turbulence Intensity During Storm Conditions Over the North Sea, J. Geophys. Res.

92(C12), 13127 -13139.

Hanna, S.R., G.A. Briggs, and R.P. Hosker, Jr. 1982. Handbook on Atmospheric Diffusion.

Technical Information Center, U.S. Dept. of Energy, DOE/TIC-11223.

Hanna, S.R. 1984. Applications in air pollution modeling. In F.T.M. Nieuwstadt and H. Van Dop,

eds., Atmospheric Turbulence and Air Pollution Modeling. D. Reidel Pub. Co. pp. 275 - 310.

Hanna, S.R., L.L. Schulman, R.J. Paine, J.E. Pleim, and M. Baer. 1985. Development and

Evaluation of the Offshore and Coastal Dispersion Model, J. Air Poll. Contr. Assoc. 35, 1039 -

1047.

Hsu, S.A. 1988. Coastal Meteorology. San Diego, CA : Academic Press.

Hsu, S.A. 1995. A proper wind-stress drag coefficient formulation for computer modelling of seas

and coastal regions. In C.A. Brebbia, L. Traversoni, and L.C. Wrobel, eds., Computer Modelling

of Seas and Coastal Regions II, Computational Mechanics Publications, Boston, pp. 413 - 420.

Hsu, S.A. 1997. Estimating Overwater Convective Boundary Layer Height From Routine

Meteorological Measurements For Diffusion Applications At Sea, J. Appl. Meteor. 36, 1245 -

1248.

Hsu, S.A. 1998. A Relationship Between the Bowen Ratio and Sea-Air Temperature Difference

Under Unstable Conditions at Sea, J. Phys. Oceanogr. 28, 2222 - 2226.

Hsu, S.A. 1999. On the Estimation of Overwater Bowen Ratio from Sea-Air Temperature

Difference, J. Phys. Oceanogr. 29, 1372 - 1373.
157

Hsu, S.A., X. Zhang, and B.W. Blanchard. 2000. An evaluation of nine dimensionless fetch-limited

wind-wave interaction formulas for the northeast Gulf of Mexico. Journal of Coastal Research,

16(4), 1063 -1067. West Palm Beach, Florida. ISSN 0749-0208.

Komen, G.J., L. Cavaleri, M. Donelan, K. Hasselmann, S. Hasselmann, and P.A.E.M. Janssen. 1994.

Dynamics and Modelling of Ocean Waves. Cambridge: Cambridge University Press.

Pasquill, F. 1971. Atmospheric Dispersion of Pollution, Quart. J. Roy. Meteor. Soc. 97, 369 - 395.

Panofsky, H.A. and J.A. Dutton. 1984. Atmospheric Turbulence. New York: Wiley.

Smith, S.D. 1980. Wind Stress and Heat Flux Over the Ocean in Gale Force Winds, J. Phys.

Oceanogr. 10, 709 - 726.

Smith, S.D. 1988. Coefficients for Sea Surface Wind Stress, Heat Flux, and Wind Profiles as a

Function of Wind Speed and Temperature, J. Geophys. Res. 93, 15467 - 15474.

The WAMDI Group. 1988. The WAM Model - A Third Generation Ocean Wave Prediction Model,

J. Phys. Oceanogr. 18, 1775 - 1810.

Zannetti, P. 1990. Air Pollution Modeling. New York: Van Nostrand Reinhold.

Dr. S. A. Hsu received his Ph.D. in meteorology from the University of Texas at Austin. He has

been a professor at Louisiana State University since 1969. His research interests are coastal and

marine meteorology, air-sea interaction, and pollution transport physics. Dr. Hsu has published

extensively, including a textbook entitled Coastal Meteorology.
159

SESSION 2C

ARCHAEOLOGY

Chair: Dr. Richard Anuskiewicz, Minerals Management Service

Co-Chair: Mr. David Bull, Minerals Management Service

Date: December 5, 2000

Presentation Author/Affiliation

Introduction Dr. Richard J. Anuskiewicz

Mr. David A. Ball

Minerals Management Service

Rational for Refining and Revising the Gulf

of Mexico OCS Region High Probability

Model for Historic Shipwrecks

Dr. Richard J. Anuskiewicz

Minerals Management Service

Results of Seafloor Monitoring for Historic

Shipwreck Management

Mr. David A. Ball

Minerals Management Service

Archaeology Under Pressure: Surveying for

Shipwrecks Is a Challenge in Deep Water

Dr. Jack B. Irion

Minerals Management Service
161

INTRODUCTION

Dr. Richard J. Anuskiewicz

Mr. David A. Ball

Minerals Management Service

This session focuses on the mission of the Gulf of Mexico Region’s archaeological resource

management program,“to manage archaeological resources through the pursuit of quality science

while applying a fair, reasonable and consistent management strategy.” To meet the goals articulated

in our mission statement and to manage the workload and technology challenges of the 21st century,

the Gulf of Mexico Region’s archaeology program has had to evolve. Once a program involving

primarily office work, it has expanded to combine office work, fieldwork, and research in the pursuit

of quality science to manage submerged archaeological resources. The three presentations in this

session provide a brief history of the region’s involvement in developing archaeological management strategies, provide a management work-in-progress report, and suggest future possibilities for

management of deepwater submerged archaeological resources for the 21st century.
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RATIONALE FOR REFINING AND REVISING THE GULF OF MEXICO OCS REGION

HIGH-PROBABILITY MODEL FOR HISTORIC SHIPWRECKS

Dr. Richard J. Anuskiewicz

Minerals Management Service

ABSTRACT

After using the present archaeological historic shipwreck model for the past 11 years, the Minerals

Management Service (MMS) Gulf of Mexico (GOM) Region archaeological resource management

program has concluded that model is not effective in finding shipwrecks and is thus flawed. This

paper provides a brief history of the evolution of shipwreck modeling in the MMS GOM Region

from 1977 and then discusses the 1989 shipwreck model and its shortcomings. The paper also

provides insight on a new shipwreck model study presently under way that is expected to be

completed by summer of 2002.

BACKGROUND: THE 1977 SHIPWRECK MODEL

For the past 16 years, the MMS has relied on a shipwreck model as justification to require the oil

and gas industry to conduct remote-sensing surveys on lease blocks before exploration and

development to look for historic shipwrecks. The first shipwreck model to require remote-sensing

surveys was initiated and funded jointly by the National Park Service and the Bureau of Land

Management in 1977 by Coastal Environments, Inc. (CEI). The CEI study recommended conducting

150-m (500 ft) remote-sensing shipwreck survey linespacing for all lease blocks shoreward of a line

that roughly followed the 60 m (200 ft) bathemetric contour line, which encompassed about 2,395

lease blocks in the Western and Central GOM Region. This was called the “yes” or “no” conceptual

model (meaning if a lease block fell shoreward of the model line a remote-sensing survey was

required and if the block fell seaward of the line “no” survey was required) (Figure 2C.1). These

initial surveys cost the lessee about $25,000 to $30,000 per lease block. 

THE 1989 SHIPWRECK MODEL

In 1987 The Gulf of Mexico OCS Region contracted with Texas A & M University to conduct a

study to reevaluate the Region’s 1977 historic shipwreck model and make recommendations, if

necessary, to refine and revise the existing historic shipwreck model (Garrison et al. 1989). The

study was to also determine whether there was a relationship between survey linespacing of

magnetometer readings and side-scan sonar targets and the detection of objects below the sea floor.

Another study task was to investigate whether remote-sensing data gathered during required

archaeological shipwreck surveys in the Gulf could be analyzed to discriminate between historic

shipwrecks and modern marine debris. Still another study goal was to develop, with a high

confidence level, a shipwreck model that would provided the best available information the location

of wrecks in the GOM based on their last known location. The Texas A&M study was completed

in 1989 and provided a totally different shipwreck high-probability model both technically and
163

Figure 2C.1. The 1977 High-Probability Shipwreck “Yes/No” Line.

visually from the 1977 CEI model. The literature search for this study inventoried more than 4,000

shipwrecks throughout the GOM. Over 75% of shipwrecks inventoried occurred near shore and in

state waters with the remainder in the open sea or federal waters. Of the over 4,000 shipwrecks

inventoried less than one-half of one percent have known or verified locations. Therefore,

approximately 99.5 % of the shipwreck locations inventoried during this study are only location

estimates of where they sank. Based on these data and information, the contractor developed and

recommended the following model and remote-sensing instrumentation shipwreck search strategy.

One important factor that led to the development of the1989 shipwreck model was researching the

evolution of navigation technology. Archival shipwreck research indicated the older the wreck, the

less reliable was the wreck location information because of error factors in early navigation maps

and instruments. 

The 1989 study attempted to narrow the search location where wrecks might have sunk by developing the following remote-sensing search guidelines. The remote-sensing search guidelines were

based on using the last known or reported location of a shipwreck and placing that location, if it fell

within federal waters, in federal lease block. Since these locations are only estimates, the contractor
164

Figure 2C.2. The 1989 High-Probability Shipwreck Model.

theorized that the wreck would fall within 4.5-mile radial circle of the wreck’s last known position.

For federal lease blocks, the study recommended using a lease block as the center of a radial point

and then swinging a 4.5-mile radial arc around that point forming a 9-mile circle which

encompassed a nine-lease block square or shipwreck centroid. The nine-block centroid represents

a high-probability area for the occurrence of historic shipwrecks and is the basis for requiring the

oil and gas industry to conduct 50-m remote-sensing surveys for a particular lease block. There are

approximately 1,440 lease blocks within the 1989 high-probability shipwreck model areas requiring

surveys within the Western and Central GOM Region. Of these blocks, 251 (e.g. 28

wrecks/centroids) are in water depths greater than 60-m (200 ft) and only require 300-m survey

linespacing. The remaining 1,189 blocks (e.g. 152 wrecks/centroids) require 50-m survey (Figure

2C.2). These 50-m surveys can cost the lessee upwards of $60,000 per block surveyed; deepwater

surveys cost over $100,000 to $300,000 for a block survey.

PROBLEMS WITH THE 1989 SHIPWRECK MODEL

We simply do not know the precise locations of the nearly 300 historic shipwrecks thought to exist

on the OCS. We have relied on the 1989-shipwreck model to reduce the area where these more

expensive surveys must be conducted by designating certain leases as falling into a “highprobability” area for wrecks. Since the GOM OCS Region first instituted archaeological research

into the lease block review process, over 70 shipwrecks have been discovered on the OCS. Very few

of these shipwrecks have been determined to be historic. Most significantly, almost none of the

historic wrecks were discovered within the “high-probability” zone designated by the 1989 model.
165

How is the 1989 Shipwreck Model Flawed? After eleven years of using this model, the Region’s

archaeologists have determined the model must be updated. A new study must incorporate primary

as well as secondary literature sources, and also sources not considered during the original study

(e.g. hang sites). The new study must also correct errors in the data used to develop the 1989 model.

In addition, many new developments have occurred in marine survey instrument technology in the

last 11 years. Using this new technology would significantly improve our ability to detect potential

shipwrecks if these instruments and methodologies were required by the MMS. At present, our

experience with these older instruments limits our ability to design appropriate survey

methodologies to find shipwrecks. Some of these new instruments promise the ability to conduct

surveys, and gather and interpret data at a much faster rate, which would reduce survey costs while

producing better-quality remote-sensing data.

STUDY OBJECTIVES OF THE NEW SHIPWRECK MODEL

The objectives of this study are to review the existing MMS shipwreck model, to examine new

shipwreck databases, to review old shipwreck data sources to determine specifically where the 1989

study is flawed, and to determine how this model can be improved. This study will also examine the

correlation between existing shipwrecks and hang sites associated with the MMS/NOAA sponsored

“Fisherman’s Contingency Fund” hang site database. Another objective will be to ground-truth, by

archaeological divers, a limited number of “hangs” and develop a new, more refined, shipwreck

model for the GOM OCS Region. This task will serve to verify the presumed correlation between

sea floor hangs and shipwreck sites and establish the validity of the new model. All of this

information will be synthesized and these data then used to develop a new high-probability

shipwreck model. This study will also review, compare, and contrast the state-of-technology transfer

of marine remote-sensing instrumentation that could be used to better fulfill requirements in the

Region’s archaeology NTL.

STUDY METHODS

A three-pronged research approach is being used to refine and revise the Region’s high-probability

shipwreck model. Ongoing now is a primary and secondary source archival search for historic

period shipwrecks that sank within the GOM OCS Region’s jurisdiction. This information is being

compared with the 1989 shipwreck data base and the existing Fisherman’s Contingency Fund along

with other sea floor hang records, as well as existing lease block surveys. This research is being

done to determine whether there are common shipwreck and hang site locations. This information

will be synthesized to select a limited number of shipwrecks and/or underwater hang sites that will

be surveyed by marine remote-sensing instrumentation and then ground-truthed by archaeological

divers. Wrecks discovered during this task and/or two known historic wrecks will be then surveyed

using both the “industry standard” proton precession magnetometer in concert with a 100 kHz sidescan sonar system and using a 50 m survey line spacing. The same wreck sites will be resurveyed

using new cesium magnetometer and a high resolution 500 kHz side-scan sonar system at varying

line space intervals and survey speeds. Next, the contract calls for comparing and contrasting results

of these surveys over the selected shipwrecks sites to determine if present survey requirements are

adequate to detect wrecks or if different survey standards should be required to encourage the use

of more modern technology.
166

ANTICIPATED DELIVERABLES

Based on the results from the study objectives, the contractor will prepare a new revised predictive

model for historic shipwrecks in the GOM and recommend survey instrumentation and strategies

that would be the most effective in locating historic shipwrecks.

BENEFIT TO THE MMS AND OIL AND GAS INDUSTRY OF THE NEW

SHIPWRECK MODEL AND STUDY

We anticipate the new archival study results will provide more accurate shipwreck locations and

reduce the actual number of wrecks that will require the lease block holders to conduct 50-m

linespacing surveys. Ground-truthing hang sites will locate additional shipwreck sites and help to

reduce the number of 50-m survey blocks. We also believe that using the scientific methods to

compare and contrast magnetometer and sonar technologies and strategies will provide significant

technical data and strong justification for considering recommendations to use new instrument

packages and survey strategies to conduct archaeological surveys on the OCS.

REFERENCES

Coastal Environments, Inc. 1977. Cultural Resource Evaluation of the Northern Gulf of Mexico

Continental Shelf. Prepared for Interagency Archaeological Services, Office of Historic

Preservation, National Park Service, Washington D.C. and Bureau of Land Management, New

Orleans. 5 Volumes. 

Garrison, Ervan G., C. P. Giammona, F. J. Kelly, Anthony R. Tripp, and Gary A. Wolf. Historic

Shipwrecks and Magnetic Anomalies of the Northern Gulf of Mexico: Reevaluation of

Archaeological Resource Management Zone 1. Prepared for U. S. Department of the Interior,

Minerals Management Service, OCS Study 89-0023-25. 3 Volumes.

Richard (Rik) J. Anuskiewicz was awarded his B.A. in 1972 and his M.A. in 1974 in Anthropology,

with specialization in archaeology from California State University at Hayward. Rik was employed

with the U.S. Army Corps of Engineer Districts of San Francisco, Savannah, and New England

Division from 1974 to 1984 as a terrestrial and underwater archaeologist. In 1980 he began work

on his doctorate. In 1984 he accepted his present position with Department of the Interior, Minerals

Management Service, Gulf of Mexico Region as a marine archaeologist. Rik received his Ph.D. in

1989 in Anthropology, with specialization in marine remote-sensing and archaeology from the

University of Tennessee at Knoxville. Rik’s current research interest is focused on using remotesensing instrumentation as a tool for middle-range theory building through the correlation of

instrumental signatures to specific observable archaeological indices.
167

RESULTS OF SEAFLOOR MONITORING FOR HISTORIC

SHIPWRECK MANAGEMENT

Mr. David A. Ball

Minerals Management Service

INTRODUCTION

The Minerals Management Service’s Seafloor Monitoring Team was instituted to verify industry

compliance with environmental mitigation measures and to ensure the protection of significant

seafloor habitats and archaeological properties. It was established in 1997 and receives its authority

from the National Environmental Policy Act; MMS legislation 30 CFR 250, which requires

operators to conduct various monitoring programs; and the Government Performance Results Act.

Additionally, the National Historic Preservation Act requires federal agencies to inventory and

protect historic sites and to evaluate these sites for eligibility to the National Register of Historic

Places (Irion and Anuskiewicz 1999).

Currently, the Seafloor Monitoring Team consists of seven divers, including three archaeologists,

two biologists, an engineer, and a geophysicist. Over the last four years, the team has carried out

almost twenty projects; these include assessing industry compliance of resource mitigation,

evaluations of natural reefs and hard-bottom areas, and investigation of almost twenty shipwreck

sites. Of the almost twenty wreck sites that we have examined, five have been identified as historic

shipwrecks, and one of these, the 19th century sidewheel steamship Josephine, has been listed with

the National Register of Historic Places.

As Dr. Anuskiewicz discussed in his paper, the MMS has developed, and is currently revising, the

predictive model for where we expect to find historic shipwrecks in the Gulf of Mexico

(Anuskiewicz 2001). One of the ways that we manage these shipwrecks is with the Seafloor

Monitoring Team. By investigating and ground-truthing reported shipwrecks we are sometimes able

to free up several lease blocks from the more costly 50-meter survey requirements. We are also able

to create an inventory of these wrecks and evaluate their conditions, thus fulfilling our requirements

under the National Historic Preservation Act. 

This paper examines the outcomes from a couple of historic wrecks that the Seafloor Monitoring

Team has inspected over the last four years, the Josephine and the Tulsa. Both of these wrecks are

located in the Mobile Area. The Josephine was originally reported in Mobile Block 810 but was

actually found in Block 766, and two separate reports identified the Tulsa in Block 1000 and 1001.

As a result of the 1989 High Probability Shipwreck study, a nine-block centroid area was set aside

for each of these wrecks requiring 50-meter survey line spacing for each block (Garrison, et al.

1989). 
168

THE TULSA

Historical research has identified the Tulsa as a 607-ton barge schooner that was built in 1909 and

sunk on 11 March. The vessel was owned by the Texas Company at the time of its sinking (U.S.

Treasury Department Bureau of Customs 1944).

Though the 1989 historic shipwrecks predictive model placed the location of the Tulsa in Mobile

Area, Block 1000, a 1985 survey had identified a cluster of magnetic anomalies and sidescan sonar

targets in Block 1001 as the Tulsa (Thornton et al. 1985). In 1999 a new survey was conducted in

the Mobile 1000/1001 area for a right-of-way pipeline. The report from this survey identified a

cluster of magnetic anomalies and sidescan targets in Block 1000 as the remains of the Tulsa

(George et al. 1999).

With the information from these two surveys, the MMS Seafloor Monitoring Team developed a research design to conduct its own investigation to determine which of the two reported locations was

correct and to evaluate both sites for potential eligibility to the National Register of Historic Places.

In July 2000, the MMS Seafloor Monitoring Team conducted a survey in Mobile Area, Blocks 1000

and 1001. Using our 600 kHz sidescan sonar, we identified a large debris scatter in block 1000, near

the 1999 reported location of the Tulsa. The debris field extended over 500 feet long by approximately 100 feet wide and was oriented in a northwest by southeast direction. Once the debris scatter

was identified, divers were sent down to make observations of the wreck. 

During our investigation of the wreck site we located and identified several artifacts specifically

associated with a sailing vessel. Divers were able to identify rigging components such as chain plate

and eyebolts (where the lower standing rigging or “shrouds” were attached to the side of the ship)

and the remains of a deadeye (used for adjusting tension on the lines supporting the mast). We also

observed the remains of a winch, part of a small auxiliary steam engine, and metal trusses for

attaching the yardarms to the masts. However, no remains of the hull of the vessel were observed

during the investigation. The most prominent feature of the site was a large pile of chain surrounding

a Danforth-type stockless anchor. Based on the discovery of component parts of the rigging of an

early twentieth-century sailing ship, we have determined that the shipwreck located in Mobile Area,

Block 1000 is the Tulsa (Anuskiewicz 2000).

The second day of our investigation in the Mobile area focused on the reported wreck in Block 1001.

Divers observed a very large steel vessel several hundred feet long, sheered off below the deck level.

The vessel was determined to be the remains of the lower hold of a “Liberty” ship. Further

investigation of available records for this area of the Gulf indicated that the Liberty Ship Anderson

had been positioned in this area by the Alabama Marine Resources Division in 1973 as part of their

artificial reef program.

THE JOSEPHINE

The sidewheel steamship Josephine was originally reported to be in Mobile Block 810, but was

actually found a couple of miles away in Block 766. The vessel was first brought to the attention of
169

1

 Charles Morgan’s influences are still seen through the south today. For example, Brashear City, LA, was renamed

Morgan City in his honor, and one of his sons-in-law, Charles Whitney, who worked in the Morgan steamship business

for many years, went on to found Whitney Bank.

Figure 2C.3. The Josephine (Photo courtesy of the Mariner’s Museum, Newport News, VA.)

the MMS as a result of a survey performed by Klein and Associates about a decade ago. Though the

ship’s identity had been long forgotten, the location of the wreck had been well known to locals as

a great fishing spot.

With the acquisition of a high-resolution sidescan sonar in 1997, the Seafloor Monitoring Team

developed a research design to test its new sidescan unit on this wreck site. The MMS archaeologists

running the survey were astonished by the excellent state of preservation of what was clearly a

sidewheel steamship with a walking beam engine. Subsequent research, which included the

discovery that the wreck was labeled on an 1883 navigation chart, identified the vessel as the

Josephine (Figure 2C.3), an iron-hulled steamer built in 1867 for the Morgan Line (Irion 2000).

After initial diver investigations of the shipwreck in 1997, historical research was conducted to learn

more about the history of the Josephine and also to determine its potential significance for

nomination to the National Register of Historic Places. Research has found that this vessel was

owned by New York businessman Charles Morgan, one of the foremost figures in the development

of the steamship trade along the Gulf Coast of the United States.1

Construction of the Josephine was completed in 1868 by the Harlan and Hollingsworth Company

of Wilmington, Delaware, which was one of the premier companies to manufacture merchant

steamers in the 19th century. The ship was built specifically for use by Charles Morgan and his
170

Louisiana and Texas Railroad and Steamship Company. Upon her arrival at New Orleans in 1868,

she was immediately assigned to regular weekly service between New Orleans and Galveston.

Early in 1881, the Josephine was transferred to the New Orleans to Havana route. This was to be

her last voyage. On 27 January, the Josephine left New Orleans, and arrived in Havana a few days

later. On 2 February she departed Havana with several passengers and a cargo of tobacco and cigars.

According to one passenger’s account of the foundering, the steamer began her return trip to New

Orleans at 5 p.m. on 2 February. She arrived in Key West the following afternoon and departed for

Cedar Key that evening, arriving on the morning of Friday, 4 February. At Cedar Key the Josephine

picked up several more passengers. Included among the new passengers were 14 members of an

Italian crew that had recently survived the sinking of their lumber ship, originally bound for London

from Pensacola.

The Josephine left Cedar Key around 4 p.m. Friday enroute to New Orleans, evidently sailing

without incident until sometime Sunday, when it was noticed that the vessel was leaking. Passengers

and crew worked to bail water, but could not control the leak. The captain made arrangements to

abandon ship; however, before the captain gave the order, the leak began to subside. Yet not long

after, the seas picked up and the vessel began to take on water once more. On Monday evening the

captain again had the crew prepare to abandon ship. By 3 a.m. Tuesday morning all had escaped,

and the vessel began to heel to one side (Daily Picayune 1881).

The Seafloor Monitoring Team returned to the wreck site in 1999 and made several dives.

Measurements of significant features of the vessel, as well as photo and video documentation and

sidescan sonar images were obtained (Figure 2C.4). Researchers observed that much of the hull of

the wreck remains buried, while the upper hull above the waterline is gone. This observation is

based, in part, on the position of the attachment points for the paddlewheels, which are still intact,

and the iron spokes of the paddlewheels, some of which survived. The bow of the vessel is

completely buried, but the line of the hull may be followed with only short interruptions to the

vessel’s rudder. By measuring the paddlewheel eccentrics, MMS divers were able to derive the

stroke of the engine at 11 feet, the same dimension published for the Josephine’s engine. One of the

most dramatic features of the wreck is the walking beam, the diamond-shaped feature that connected

the engine piston to the eccentric of the paddlewheels, which lies collapsed against the starboard

side. Based on observations made by the MMS seafloor monitoring team, we are confident in

identifying the wreck, which has been assigned Mississippi State Historic site number 22HR843,

as Morgan’s Josephine (Irion and Ball 2000).

NATIONAL REGISTER NOMINATION OF THE JOSEPHINE

With two separate visits by MMS divers to the Josephine, and a good idea of the history of the

vessel, MMS archaeologists next began to evaluate the acquired information to determine if the

vessel were eligible to be listed on the National Register of Historic Places.
171

Figure 2C.4. Sidescan image of the Josephine.

In order for an archaeological site to be listed with the National Register, the site must meet at least

one of four criteria for eligibility. Criterion A evaluates a site based on its association with events

that have made a significant contribution to the broad patterns of our history. Criterion B states that

a site must be associated with the lives of persons significant in our past. Criterion C requires an

assessment based on unique design or construction methods. The final criterion, D, considers a site’s

information potential. In other words, properties may be eligible if they have yielded, or may be

likely to yield, information important in history or prehistory (NRHP website 2000). 

Though an argument could be made that the Josephine qualifies for listing under each of the four

criteria, the vessel was officially nominated, and accepted, under criteria C and D. On 21 September

2000 the Mississippi Department of Archives and History’s National Register Review Board

accepted the steamship Josephine to the National Register of Historic Places. It was posted in the

Federal Register on 6 November 2000.

CONCLUSION

The investigation and evaluation of the reported locations of the shipwrecks Tulsa and Josephine,

located on the Federal OCS, provided valuable information for the MMS Archaeological Resource

Management Program. Based on divers’ observations, video, and photographic documentation, the
172

MMS was able to identify two historic shipwrecks. And through additional historical research and

evaluation of these wrecks, the MMS has fulfilled its obligation under the National Historic

Preservation Act to “assess and inventory” archaeological sites under its control.

We were able to determine that because of the Tulsa’s rapid rate of deterioration since its loss in

1943, and its lack of structural and physical integrity, the vessel most likely does not meet the

necessary eligibility criteria for listing in the National Register of Historic Places. Because of the

excellent preservation of a large portion of the Josephine, this vessel has now been listed, and

therefore will receive protection under the National Register of Historic Places. Additionally,

identification of these vessels will enable the MMS to release several lease blocks from 50-meter

survey requirements, thereby providing significant survey cost savings to the oil and gas industry.

REFERENCES

Anuskiewicz, Richard A. 2000. Trip Report for National Register Evaluation of the Schooner Tulsa,

Mobile Area, July 18-20, 2000. U.S. Government Memorandum, Minerals Management Service,

New Orleans, LA.

Anuskiewicz, Richard A. 2001. This session.

Daily Picayune. 10 February 1881. Microfilm collections, Jefferson Parish Public Library, Metairie,

LA.

Garrision, Ervan G., Charles P. Giammona, Frank J. Kelly, Anthony R. Tripp, and Gary A. Wolff.

1989. Historic shipwrecks and magnetic anomalies of the northern Gulf of Mexico. U.S.

Department of the Interior Minerals Management Service, Gulf of Mexico Region, OCS Study

No. MMS 89-0024.

George, Tony, Robert A. Church, Stephen Fournet, Paul K. Monier, and Daniel J. Warren. 1999.

Archaeological, Engineering and Hazard Report “Buccaneer” Pipeline Project Proposed 36-inch

Pipeline Route. Prepared by C & C Technologies Survey Services, Lafayette, LA.

Irion, Jack. 2000. “MMS Divers Identify Historic Shipwreck.” In The Gulf of Mexico Alligator. US

Department of the Interior Minerals Management Service, Gulf of Mexico Region, New

Orleans, LA.

Irion, Jack B. and Richard J. Anuskiewicz. 1999. MMS Seafloor Monitoring Project: First Annual

Technical Report, 1997 Field Season. U.S. Department of the Interior Minerals Management

Service, Gulf of Mexico Region, OCS Report No. MMS 99-0014.

Irion, Jack B. and David A. Ball. 2000. The New York and the Josephine: two steamships of the

Charles Morgan line. U.S. Department of the Interior Minerals Management Service, Gulf of

Mexico Region. http://www.gomr.mms.gov/homepg/whatsnew/publicat/gomr/Irion_and_Ball.pdf
173

National Register of Historic Places, Listing a Property. http://www.cr.npw.gov/nr/listing.htm . May

2000. (Accessed 13 Dec. 2000).

Thornton, K., I. Preece, D. Price, and D. Stier. 1985. Geohazard, Archaeological and Live-bottom

Survey Report for Viosca Knoll Block 32. Prepared by Comap Geosurveys, Inc., Houston, TX.

U.S. Treasury Department Bureau of Customs. 1944. Merchant Vessels of the U.S. U.S.

Government Printing Office, Washington, DC.

Dave Ball received his Bachelor of Arts degree in anthropology from Sonoma State University in

1992 and his Master of Arts degree, which focused on marine archaeology, from Florida State

University in 1998. He has conducted fieldwork in archaeology for over eight years and has directed

field research on both land and underwater archaeological sites from Florida to Washington State.

Some of the more notable sites that Dave has worked on include an inundated prehistoric site at

Little Salt Spring, Florida, dating back about 10,000 years; a 1533 Spanish shipwreck in the Dry

Tortugas; a Confederate Ironclad in Mobile Bay, Alabama; and the 1686 French shipwreck la Belle,

which wrecked in Matagorda Bay, Texas. Dave has been employed with the MMS as a Marine

Archaeologist since October 1999.
174

ARCHAEOLOGY UNDER PRESSURE: SURVEYING FOR SHIPWRECKS

IS A CHALLENGE IN DEEP WATER

Dr. Jack B. Irion 

Minerals Management Service

ABSTRACT

This paper addresses one of the major challenges facing historic preservation in the 21st century. As

the oil and gas industry moves into the deep water environment, balancing the need to extract

resources with the mandate to protect natural and cultural resources tests the limits of our

resourcefulness. This presentation explores some of these challenges, examines some of the

technology that is now being applied to deepwater surveying, and offers practical solutions for

dealing with these issues

As the oil and gas industry moves its operations farther and farther from shore and into ever-deeper

water, the Minerals Management Service faces new challenges in fulfilling its role as environmental

steward. Not the least of these challenges comes as a result of our responsibility to protect

significant archaeological resources on the seabed. MMS, as a federal agency, is obligated under

Section 106 of the National Historic Preservation Act to consider the effect of its actions, which

includes the granting of exploration and development permits, on properties deemed important

enough to be eligible for the National Register of Historic Places. The MMS estimates that there are

well over 4,000 historic shipwrecks in the Gulf of Mexico (GOM), which, if discovered, could

potentially meet these criteria (Garrison et al. 1989: I-1). The phrase “if discovered” is key. At

present, we have only a vague idea of where most of these shipwrecks lie based on historical

research using old maps, wreck reports, and other primary and secondary sources. As a result, the

only way to locate these properties is to conduct remote sensing surveys of lease blocks before

operations commence.

In an attempt to target these surveys in a way that would optimize the discovery of potential

shipwrecks, the MMS funded a study in 1989 to designate certain “high-probability” blocks for

more intensive survey using instruments that have proven successful for the purpose: the proton

precession magnetometer and the side-scan sonar. The magnetometer measures localized

fluctuations in the earth’s magnetic field caused by the presence of anomalous deposits of ferrous

metal. Anchors, cannon, or the iron hulls of 19th century steamships all cause detectable anomalies.

The side-scan sonar, on the other hand, paints a picture of the surface of the seafloor using reflected

sound. The outline of a ship’s hull, if it protrudes above the seabed, can easily be distinguished from

the surrounding bottom. Over a hundred shipwrecks have been located to date in the Gulf using

these methods, 14 of which are in water depths greater than 1,000 feet (Table 2C.1). Discovered

shipwrecks include such historically important vessels as the New York, the Hatteras, the Josephine,

and nearly a dozen casualties from World War II.

The process on the relatively shallow waters of the shelf has been as follows. In blocks designated

as having a high potential for shipwrecks, the leasee is required to conduct a high-resolution survey
175

Table 2C.1. Discovered vessels in deep water.

Vessel Name Area Wreck Date

Min Depth

(meters)

Max Depth

(meters)

Unknown GC ? 802 965

Unknown MC ? 315 519

Unknown MC ? 572 784

Unknown GB ? 441 592

Unknown GB ? 622 900

Gulf Oil? MC 1942? 1209 1359

Unknown MC ? 1163 1231

Unknown VK ? 1250 1427

Unknown EB ? 1109 1144

Unknown EB ? 967 1224

Unknown GB ? 1062 1146

Gulf Penn? MC 1942? 455 578

Alcoa Puritan MC 1942 1399 1642

Robert E. Lee MC 1942 1399 1642

using a boat-towed magnetometer, a side-scan sonar, a subbottom profiler, and a fathometer. These

surveys differ from normal shallow hazard surveys only in that they are conducted along tracklines

spaced 50 meters (165) apart instead of 300 meters (990 ft) apart. The reduced line spacing is

important because shipwrecks occupy relatively small, defined areas, and 50 meters is determined

to be the widest interval to allow the sensor to detect a wreck on at least three passes. This clustering

of anomalies helps the archaeologist distinguish a possible shipwreck from casually discarded small

debris. At wider line spacing, virtually any detected magnetic anomaly could be a shipwreck. Worse,

at the 300-meter line spacing, something like a 400-year-old Spanish galleon could go completely

undetected by the magnetometer between the survey lines.

The high-probability block model was based on the idea that historic shipwrecks would likely be

found within 10 miles of their historically reported positions. Unfortunately, this has not proven to

be entirely accurate. Over the past ten years, a number of important wrecks have been found many

miles away from their reported position and outside of the 9-block grid designated for their search.

This is due to a number of factors, mostly relating to the general vagueness of historic wreck

reporting, which increases exponentially as one goes farther back in time, and the inherent

inaccuracy in pre-GPS navigation. Many historic wrecks were recorded simply as “lost between

Galveston and New Orleans” or “sunk 35 miles south [of] the Sabine River.” Even the recorded

positions of relatively recent World War II wrecks are woefully inaccurate. The problems associated

with the current shipwreck model and steps that we are taking to correct this problem is the subject

of a paper in this session by Dr. Rik Anuskiewicz. 
176

Many of the wrecks discovered in oil and gas industry surveys were located by side-scan sonar using

standard shallow hazard survey methods despite being outside the archaeological high-probability

survey grid. In fact, the routine use of side-scan for shallow hazard surveys outside of any lease area

designated for archaeological survey has given us something of a comfort factor for those areas

beyond the 60 meter depth contour where archaeological survey was not required. As a result of

industry’s use of the deep-tow sonar, for example, two World War II era wrecks—the Robert E. Lee

and the Alcoa Puritan—were discovered in over 5,000 feet of water in the Mississippi Canyon Area.

Again, these ships lay outside of the two 9-block grids designated for their search from our historical

research.

The difficulties associated with locating shipwrecks become exacerbated as industry moves farther

offshore and into deeper water. Historical estimates of location based on dead reckoning become

exaggerated and the likelihood of survivors to report the wreck decreases. In very deep water, the

drift of the vessel through the water column for a mile or more can result in a large discrepancy

between the reported position when the vessel began sinking on the surface to its final resting place

on the ocean floor. The great uncertainty associated with historic shipwreck positions coupled with

the current trend in the industry to eschew traditional “hi-res” survey instruments in favor of 3-D

seismic imaging is forcing MMS to re-think its approach to Section 106 compliance in the face of

the steady advance into deepwater areas. 

At present, MMS estimates that there are some 35 historic shipwrecks in the GOM in water depths

greater than 1,000 feet (Table 2C.2). These vessels range in date from 1752 to 1942, and include

several merchant ships lost to U-boat attacks such as the Ontario, the Torny, the Ampala, the

Carabelle, the Gulf Penn, and the Gulf Oil. The majority of the reported losses, however, are

schooners ranging from 300 to just over a thousand tons that foundered in the late nineteenth and

early twentieth century.

If industry were routinely conducting high resolution sonar surveys of their lease blocks, we would

have a fair degree of confidence that many of these wrecks would be discovered even if they fell

outside of an “official” archaeological survey area. Sadly, that is no longer the case. Because of the

high cost of conducting high-resolution surveys in deep water, the current trend is to utilize 3-D

seismic data in hazards analyses in areas without complex bottom topography. Unlike highresolution survey instruments, whose sensors must be towed close to the seafloor, 3-D seismic

instrumentation consists of streamers and airgun arrays that are towed just below the surface. A

typical survey boat tows 9 streamers that can be up to 12 km in length. 3-D seismic technology has

proven to be a real boon to the oil and gas in the Gulf, primarily because it permits, for the first time,

accurate definition of reserves beneath salt domes, which act as a barrier to traditional 2-D imaging.

With proper post-processing, 3-D data also have proven useful in mapping surface faults, vents, and

other “geological hazards.” As a result, MMS biologists currently are using these data to predict the

location of chemosynthetic organisms (Roberts et al. 2000).

It would be fortunate if 3-D seismic data could also be used to locate shipwrecks, since these data

are routinely acquired in deepwater lease blocks. Unfortunately, though, this does not appear likely

based upon analysis of two test cases. As discussed earlier, two important wrecks have already been

discovered in Mississippi Canyon Area in over 5,000 feet of water using the deep-tow sonar. Both
177

Table 2C.2. Reported shipwrecks in deep water.

Vessel Name Centroid

Wreck

Date

Min Depth of

Search Area

(meters)

Max Depth of

Search Area

(meters)

Rhoda B. Taylor DC 347 1878 368 439

Marion N. Cobb DC 141 1925 1421 2321

Walter L. Plummer DC 347 1894 282 335

B-1 DC 412 1942 889 1061

James C. Clifford DD 504 1909 258 525

Villa y Hermano DD 984 1905 669 810

Springfield DC 543 1918 1083 1398

Ontario DC 800 1942 2495 2743

C.W. Wells DT 853 1921 770 1006

Northern Eagle EB 199 1908 246 483

Helena E. Russel EL 451 1899 799 1195

William J. Keyser EL 459 1898 296 487

Emma L. Cottingham EL 984 1906 1046 3230

Allegheny HE 287 1921 2985 3051

Torny HE 334 1942 3032 3118

Biscayne HE 345 1913 3159 3219

Rosetta McNeil HE 480 1882 3180 3219

Fred P. Litchfield HE 970 1906 3008 3082

Horace M. Bickford HH 598 1925 3292 3322

Speedwell LL 449 1920 2888 2926

Providencia LL 451 1936 2906 2999

Isaac T. Campbell LL 503 1909 2995 3072

Three Marys LL 755 1920 2792 2890

J.W. Clise LU 168 1940 2637 2762

W.H. Marston LU 344 1927 2601 2787

Ampala LU 453 1942 2825 2918

Carabelle LU 671 1942 2966 3033

Carrie Strong LU 775 1916 2773 2883

Nokomis MC 1008 1905 2220 2579

Western Empire MC 332 1875 978 2171

Gulf Penn (see Table 2C.1) MC 499 1942 426 720

Gulf Oil (see Table 2C.1) MC 795 1942 381 757

Elmer E. Randall VK 826 1906 250 1042

Anona VK 830 1944 378 1321

Bradford C. French VK 957 1916 709 1497

Gulf Oil (see Table 2C.1) MC 795 1942 381 757
178

of these wrecks, believed to be the Robert E. Lee and the Alcoa Puritan, are quite large with

substantial remains showing above the seafloor. The German submarine U-166 torpedoed the

passenger ship SS Robert E. Lee on 30 July 1942, while it was in route from Trinidad to New

Orleans (Figure 2C.5). At the time of her loss, her compliment consisted of 131 crewmembers, 6

Naval Armed Guard, and 270 passengers, most of whom were survivors of other torpedoed

American ships. Ten crewmembers and 15 passengers were lost. The Robert E. Lee was built in

1924 and was 375 ft long with a 54-ft beam and a gross tonnage of 5,184. The side-scan image of

the wreck shows it to be largely intact and upright on the seafloor with a relief off the seabed of over

30 ft.

The vessel Alcoa Puritan, located a short distance away in the same lease block, was in route from

Trinidad to Mobile when it came under fire from the German submarine U-507 on 6 May 1942.

After losing steerage, her crew of 40 abandoned her and the U-507 sunk her with a torpedo

amidships. The side-scan image obtained by industry of this wreck shows a large vessel broken into

at least two pieces. The 6,759-ton Alcoa Puritan’s recorded dimensions were 397 ft long with a

beam of 60 ft.

Both of these steel-hulled wrecks are quite large with substantial remains above the seafloor. The

Robert E. Lee, in particular, appears largely intact in the sonar record. Moreover, accurate

coordinates of both of these wrecks were obtained in 1986. This permitted a line-by-line analysis

of available 3-D data by MMS geophysicists for several hundred feet around both coordinates.

Absolutely nothing was observed in these data that could distinguish either of these two large

vessels from the surrounding seafloor. As a result, we are forced to conclude that 3-D seismic

surveys are completely ineffective for the purpose of locating shipwrecks on the seafloor.

What then are the alternatives? At present, we are forced to continue to rely on boat-towed side-scan

sonars as a search tool. The MMS has, at times, waived this requirement when seafloor impacts were

minimal and the impact areas could be inspected visually by an ROV. Hopefully, continued

advances in technology will make survey using Autonomous Underwater Vehicles (AUVs)

practical. AUVs are currently in use that can conduct high-resolution survey along pre-programmed

routes and store the data on a hard drive until it can be downloaded on the mother ship after the

vehicle is recovered (Chance et al. 2000). Since they are not towed by a boat, but operate

independently, survey time is greatly reduced. In the meantime, more intensive historical research

may help us to refine and improve our model of where shipwrecks are likely to occur in deep water

and which of these wrecks might truly be of National Register significance.

Why does the MMS require industry to go to such effort to locate shipwrecks in deep water? The

National Historic Preservation Act of 1966 was enacted to recognize that the nation is “founded

upon and reflected in its historic heritage” (16 U.S.C. ss. 470 et seq., 470[b][1]). By passing this Act

into law, Congress proclaimed that

The preservation of this irreplaceable heritage is in the public interest so that its vital

legacy of cultural, aesthetic, inspirational, economic, and energy benefits will be

maintained and enriched for future generations. (16 U.S.C. s. 470[b][4]).
179

Figure 2C.5.Side-scan image of the SS Robert E. Lee.
180

Section 106 of the National Historic Preservation Act (NHPA) requires that federal agencies take

into account the effect of any proposed federal, federally assisted, or federally licensed undertaking

on any historic property that is included in, or eligible for inclusion in, the National Register of

Historic Places. The other main provision of the NHPA is section 110(a)(2), which requires federal

agencies to manage historical resources under their jurisdiction and control. Such management

includes the obligation to survey, inventory, and determine the eligibility of historic properties for

nomination to the National Register.

At present, no other historic preservation legislation applies to shipwrecks on the Outer Continental

Shelf (Varmer and Blanco 1999). The Abandoned Shipwreck Act (43 U.S.C. ss. 2101-2106

[effective 28 April 1988]) is applied only to state waters, the National Marine Sanctuary Act (16

U.S.C. s. 1431, et seq.), only protects shipwrecks in National Marine Sanctuaries, and the

Antiquities Act (16 U.S.C. s. 431, et seq.) is limited to marine protected areas, such as national

seashores. This legislative “gap,” however, may soon change. On 12 November 1997, the UNESCO

general conference adopted resolution 29C/6.3 to the effect that “the protection of the underwater

cultural heritage should be regulated at the international level and that the method adopted should

be an international convention.” A Draft Convention on the Protection of the Underwater Cultural

Heritage was circulated to Member States of UNESCO (the U.S. is only an observer to UNESCO)

in April 1998. The UNESCO draft permits nations to regulate and authorize all activities affecting

historic shipwrecks or drowned prehistoric sites in the Exclusive Economic Zone and continental

shelf (Strati 1999). Once the Draft Convention is finalized and becomes an international treaty, and

should the US agree to become a party to the treaty, implementing regulations would have to be

passed by Congress. At present, no one knows what effect this could have, if any, on MMS policy

with respect to archaeological resources. It would seem likely, though, to bring MMS policies under

close scrutiny and to increase pressure on expanding surveys in the deep Gulf.

REFERENCES

Chance, Thomas S., Art A. Kleiner & Jay G. Northcutt. The Autonomous Underwater Vehicle

(AUV): A Cost-Effective Alternative to Deep-Towed Technology, Integrated Coastal Zone

Mgmt., Vol.I, pp. 65-71.

Garrison, E. G., C.P. Giamona, F.J. Kelly, A.R. Tripp, and G.A. Wolf. 1989. Historic Shipwrecks

and Magnetic Anomalies of the Northern Gulf of Mexico. 3 vols. Prepared for the U.S.

Department of the Interior, Minerals Management Service, OCS Study MMS 89-0023.

Roberts, H., J. Coleman, J. Hunt, Jr. and W.W. Shedd. 2000. Improving interpretation of seafloor

geology, biology from remote sensing, Offshore Vol. 60, No. 9, pp. 126-128, 181.

Strati, Anastasia. 1999. Draft Convention on the Protection of Underwater Cultural Heritage: A

Commentary. UNESCO Publication CLT.99/WS/8, 97 p.

Varmer, Ole and Caroline M. Blanco. 1999. United States of America, in Legal Protection of the

Underwater Cultural Heritage: National and International Perspectives, Sarah Dromgoole, ed.
181

Dr. Jack B. Irion is supervisor of the Social Sciences Unit within MMS’s Leasing and Environment

Section. Before joining the MMS in 1995, he worked as a marine archaeologist in private consulting

firms and specialized in conducting remote sensing surveys and diving investigations of historic

shipwrecks. He has directed archaeological investigations at a number of significant sites, including

the C.S.S. Louisiana (1862), the steamships Columbus (1850) and New York (1846), and, most

recently, the S.S. Josephine (1881). Dr. Irion received his Ph.D. from the University of Texas in

1990 and has published over 40 reports and articles on topics dealing with underwater archaeology.
183

SESSION 1D

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITATS

AND BENTHIC ECOLOGY STUDY, “DGoMB”

Co-Chairs: Dr. Robert Avent, Minerals Management Service

Mr. Greg Boland, Minerals Management Service

Date: December 6, 2000

Presentation Author/Affiliation

Deep Gulf of Mexico Benthos Dr. Gilbert T. Rowe

Texas A&M University

Abyssal Macrobenthic Infaunal Biomass in

the Southwestern Gulf of Mexico

Dr. Elva Escobar Briones

Universidad Nacional Autónoma de

México

Biological Findings from DSV Alvin Dives in

the Deep Gulf of Mexico

Dr. Ian R. MacDonald

Geochemical and Environmental

Research Group

Texas A&M University

 Mega-Furrows of the Continental Rises

Seaward of the Sigsbee Escarpment,

Northwest, Gulf of Mexico

Dr. William Bryant

Mr. Dan Bean

Dr. Niall Slowey

Dr. Tim Dellapenna

Department Of Oceanography

Texas A&M University

Mr. Erik Scott

BHP Petroleum (Americas)
185

DEEP GULF OF MEXICO BENTHOS

Dr. Gilbert T. Rowe

Texas A&M University

INTRODUCTION

A new investigation has been initiated of the benthos of the deep Gulf of Mexico (GOM). Increasing

exploitation by industry of fossil hydrocarbon resources offshore has prompted the Minerals

Management Service of the U.S. Department of the Interior to support an investigation of the

structure and function of the communities of organisms that live in association with the sea floor.

Community structure is being used to test hypotheses about what controls the distribution of animal

communities in the deep sea. Community function is being investigated by measuring critical fluxes

in a food-web carbon model that portrays the relationships between carbon input and carbon flow

through the near-bottom biota. The field work covers the entire northern GOM continental slope

from depths of 300 meters on the upper slope out to greater than 3,000 meters seaward of the base

of the Sigsbee and Florida escarpments. Sampling during three separate years will allow the

hypotheses and the models to be revised and re-tested in an iterative fashion in years two and three.

Previous data from the Sigsbee Abyssal Plain based on a joint project with UNAM has been put into

a dynamic time-dependent model to illustrate the approach to be used (Figures 1D.1 through 1D.3).

The study was designed to improve predictions of variations in the structure of animal assemblages

in relation to depth, geographic location, time, and water mass. This predictive capability was

adopted because it was not feasible to investigate every physiographic feature of the gulf. Eight

hypotheses are being tested on the basis of community structure. These hypotheses propose that

community structure will vary as a function of 

1) water depth, 

2) east vs. west geographic extremes, 

3) association with canyons, 

4) association with mid-slope basins, 

5) surface productivity, 

6) proximity to hydrocarbon seeps, 

7) variations in time (seasonal scale), and 

8) association with the base of escarpments. 
186

Figure 1D.1. Part 1 of a dynamic time-dependent model.

The structural characteristics of the communities used in the tests are variations in diversity,

similarities in taxonomic composition between geographic locations (zonation, for example, with

depth), variations in biomass and abundances, and mean size of indivduals within functional size

categories. 

An underlying premise of the eight hypotheses is that deep-sea communities are all food-limited.

This premise leads to the assumption that variations in community structure in time and space,

therefore, are a function of food input to the sea floor. The hypotheses thus test the possibility that

each of the eight variables is related to how and in what quantities organic matter is provided to the

communities. A second assumption is that community dynamics and community structure are

interdependent. It follows that community structure, if it can be used to infer relative flows of
187

Figure 1D.2. Part 2 of a dynamic time-dependent model.

organic matter into the deep ocean ecosystem, can also be used as a qualitative predictor of

community dynamics. This conclusion assumes that community structure and community function

are tightly coupled. While few would doubt this generalization, the evidence for it in the deep sea

is fragmentary at best. 

A conceptual model is being used to represent each of the principal components of the food chain

measured in the survey of standing stocks. The model includes demersal fishes, megafauna,

scavengers, macrofauna, meiofauna and heterotrophic bacteria. This can be linked, as appropriate,

with a simplified model of the seepage of fossil hydrocarbons utilized by chemotrophic organisms,

including large invertebrates that contain symbiotic chemotrophs. The boxes represent standing
188

Figure 1D.3. Part 3 of a dynamic time-dependent model.

stocks which have units of biomass in terms of carbon whereas the arrows represent flows of carbon

between boxes and hence have units of l/time. For consistency the units are mg C m-2 and mg C m2

day-1. 

Data are used to quantify standing stocks in terms of carbon across the entire survey area.

Respiration rates are estimated as a function of size and temperature from previous studies in the

literature. The flows representing transfers between components are calculated by difference to

balance respiratory losses at steady state. Burial loss is sediment organic carbon concentration times

sediment accumulation rate. Input to the bottom is solved by assuming it is equal to the sum of the

respiration and burial losses.

The second field phase of the project is designed to test the model. Measurements of fluxes will be

made that initially had been estimated based on size and temperature. This measurement will be

done on two sequential trips in June of 2001 and 2002. Total community respiration will be

determined using a benthic lander. Total respiration will be partitioned by measuring bacterial

activity aboard ship in pressure chamber incubations at in situ temperatures. Uptake and respiration

will be determined using mixed amino acids labeled with radiocarbon. Sulfate reduction will be

measured using radiolabeled sulfate incubation aboard ship of samples from cores. Lander fluxes

to be measured are oxygen, DIC, inorganic nitrogen compounds, phosphate and silicate. Scavenger
189

domains of occupation will be estimated using baited traps, time-lapse cameras and a current meter

array. Stable isotopes of C and N will be used to confirm food chain linkages. Data from the second

field year will be used to adjust the model parameters. Experiments during the third field year will

be designed to further validate the revised model rates and parameters. 

STATUS OF PHASE 2: PROCESSING SURVEY CRUISE DATA

Four kinds of information were collected at each observational site during the survey cruise on

GYRE, 4 May to 23 June 2000: physical and chemical properties of the water column, geological

characteristics of the sediments, geochemistry of the sediments, and kinds and numbers of organisms

present. The present status of these individual data sets will be described separately in interim

reports as the data emerge, along with some preliminary interpretation of their significance and how

they will affect future directions of continuing research.Through our rather elaborate process of

hypothesis testing and model development, followed by hypothesis revision and model validation

and adjustment, the DGoMB program anticipates significant improvement in our ability to predict

and understand what controls variations in life in the deep sea.

Gilbert T. Rowe has a B.S. in zoology and an M.S. in oceanography from Texas A&M. He obtained

a Ph.D. from Duke in 1968. Following a summer at Florida State, he spent 10 years at the Woods

Hole Oceanographic Institution, followed by 8 years at the Brookhaven National Laboratory, before

returning to Texas A&M in 1987. Last year he was able to work for two months as a Fulbright

Scholar at the University of Concepcion in Chile.
190

ABYSSAL MACROBENTHIC INFAUNAL BIOMASS IN

THE SOUTHWESTERN GULF OF MEXICO

Dr. Elva Escobar-Briones

Universidad Nacional Autónoma de México

INTRODUCTION

The central Gulf of Mexico (GOM) is known among the most oligotrophic basins of the world’s

oceans. Studies in similar impoverished tropical areas have revealed significant correlation between

deep-sea infaunal abundances and those factors indicating food availability (Tselepides &

Eleftheriou 1992; Boetius et al. 1996). These correlations are very low compared to those in

temperate regions (Cosson et al. 1998), which suggests that low densities of macrofauna reflect the

oligotrophic status of tropical seas (Pasternak et al. 1975). The extreme oligotrophy in the GOM is

related to the persistent stratification of the euphotic layer and low production rates related to the

limited availability of nutrients (Escobar-Briones et al. 1999). Long-term records of organic matter

flux in open-ocean areas of the southern GOM are lacking, but several characteristics of the region

probably restrict the organic matter supply to the deep-benthos (max. depth 3,780 m). One example

would be the warmth of the upper and intermediate waters which allow for higher decomposition

rates. The limited food supply to the deep may be expressed in terms of the benthic community

structure, with higher species richness attributed to trophic specialization to the limited organic

matter content in sediment (Thiel 1978) and standing stocks determined by alternate energy sources

and energy fluxes related to regional events (Tselepides & Eleftheriou 1992).

To investigate the distribution of the macrobenthic infauna in the southern GOM, a series of cruises

(R/V Justo Sierra) were conducted from 1993 to 2000. The main objective was to improve the

knowledge of the distribution of benthic invertebrates (micro-, meio-, macro and megafauna) and

its relation to food availability, and to quantify the contribution of the macroinfauna to total benthic

biomass. This short paper presents data on the distribution of macrobenthic infauna in the deep-sea

of the southern GOM and discusses the distribution of biomass.

STUDY SITES AND SAMPLING PROCEDURES

Figure 1D.4 shows the position of 193 stations through the southern GOM. Table 1D.1 illustrates

the sampling effort that occurred from 1993 to 2000. and shows that sampling of benthic

communities in the mesoabyssal (2,275 to 3,200 m) and lower abyssal (>3,225 m) zones started with

a joint UNAM-TAMU cruise to the Sigsbee abyssal plain in 1997. The sediments and benthic

samples were recovered with a 0.25 US-NEL box corer deployed by replicate at each station to

detect the variability in the range of millimeters to centimeters at the sea-floor; the size of the

sampled area was 0.0625 per replicate. The sediments samples included the top 10 cm layer.

Macrofauna (125 μm to 1 mm) were sieved onboard, fixed in ethanol 95%, sorted by each boxcore

replicate and identified to the lowest taxonomic level possible in the laboratory. Every sorted taxon

has been stored in the formal collections in separate vials and fixed in ethanol 70%. Biomass

expressed as organic carbon was determined by weighing each taxonomic group by replicate by 
191

98 96 94 92 90 88

18

20

22

24

26

28

30

3000 m

2000 m

1000 m

200 m

Yucatan

Gulf of Mexico

Figure 1D.4. Positions of 193 stations throughout the southern Gulf of Mexico.

station at each cruise. Grain sizes, organic carbon and nitrogen contents, chloroplastic pigments and

temperature were measured on sediments subsamples from the same cores. Faunal composition ,

density and biomass data were analyzed in a comparative format with the existing data from the

northern GOM according to the depth zones described by Pequegnat (1983): transition zone (300
192

Table 1D.1. Infauna sampling effort in the SW Gulf of Mexico. Zonation according to Pequegnat

(1983).

Cruise/Zone Transition Arquibenthic UpperAbyssal Mesoabyssal LowerAbyssal Total

Month Year 300 to 450 m 460 to 950 m 975 to 2250 m 2275 to 3200 m 3225 to 3850 m

OGMEX.11 Abr/May 93 10 11 21

OGMEX.12 Jul 94 1 3 7 11

OGMEX.13 Jun 95 1 8 13 22

OGMEX.14 Jan 96 1 1

OGMEX.15 Jan/Feb 97 4 7 4 15

SIGSBEE Jun 97 1 3 1 8 13

OGMEX.16 Sep 97 4 6 9 19

ENOS.1 Mar 98 2 9 1 12

ENOS.2 Jun 98 1 4 2 1 8

SIGSBEE.2 Jun 99 1 1 6 4 9 21

PROMEBIO.1 Aug 99 1 3 3 14 21

PROMEBIO.2 Nov 99 1 2 3

PROMEBIO.3 Apr 00 1 4 1 1 7

SIGSBEE.3 May 00 2 4 4 9 19

Sum by zone 23 51 65 27 27 193

to 450 m), archibenthic (460 to 950 m), upper abyssal (975 to 2,250 m), mesoabyssal (2,275 to 3,200

m and lower abyssal (3,225 to 3,850 m) (see Table 1D.1). The analyses were carried out using SAS

General Linear Models nested ANOVA procedure, where the model included terms for depth zones,

stations within zones, and the year/season (starified vs. mixed conditions) for the time at which each

cruise was carried out. Comparisons of depth zones were made against the error terms representing

stations, seasons and years within variances, where stations were samples collected given by the

means of replicated cores. Interaction between depth zones was analyzed for seasons and years using

a replicated measures analysis. 
193

±Std. Dev.

±Std. Err.

Mean

Categorized Plot for Variable: VAR3 

VAR1

VAR3

VAR2: 93

-0,02

0,02

0,06

0,10

0,14

0,18

0,22

Mixed Stratifi

VAR2: 95

Mixed Stratifi

VAR2: 97

-0,02

0,02

0,06

0,10

0,14

0,18

0,22

Mixed Stratifi

Figure 1D.5. Macrofaunal biomass seasonal (mixed vs. stratified year 1997: ANOVA F 3,15;

p= 0.02) variability in the transition zone).

RESULTS

Average macrofaunal biomass values ranged from 0.002 to 0.37 gC.m2 and were surprisingly more

than ten times higher on the lower abyssal plain (average 0.21 gC.m2, n=106) than on the

mesoabyssal zone (average 0.019 gC.m2, n= 78) and to three times higher than other zones

(transition zone 0.060 gC.m2, n= 73; archibenthic zone 0.078 gC.m2, n=150), upper abyssal zone

0.019 gC.m2, n=194). Regionally the largest average biomass values were recorded in the Campeche

Bay, followed by lower values in the Campeche Scarpment; the lowest values were consistently

recorded off the Mexican Ridges. Seasonal differences were recorded between cruises carried out

in the years 1993, 1995 and 1997: ANOVA F 3,15; p= 0.02 with highest values recorded during the

mixed conditions in contrast to the stratified condition (Figure 1D.5).

Average macrofaunal biomass during the stratified condition showed significant differences from

one year to another on the upper abyssal , mesoabyssal, and lower abyssal zones (Figure 1D.6 ). The

three abyssal zones showed similar biomass values in the years 1997 and 1998. Aa significant

decrease in biomass values was observed for the two zones in 1999 that remained equally low in the

year 2000 (Figure 1D.6). In general, the biomass values recorded in 1994 were higher than in 1995

and in 1997, in contrast to 1998 and 1999. 

Differences in macrofaunal taxonomic composition were observed among depth zones. The

polychaetes comprised between 10 and 57 % of the total macrofauna, followed by the crustacea
194

±Std. Dev.

±Std. Err.

Mean

Categorized Plot for Variable: BIOMASS 

YEAR

BIOMASS

-0,02

0,04

0,10

0,16

0,22

0,28

97 98 99

±Std. Dev.

±Std. Err.

Mean

Categorized Plot for Variable: BIOMASS 

YEAR

BIOMASS

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,07

0,08

97 98 99

±Std. Dev.

±Std. Err.

Mean

Categorized Plot for Variable: BIOMASS 

YEAR

BIOMASS

-0,005

0,005

0,015

0,025

0,035

0,045

0,055

0 97 98 99

a Upper abyssal zone b. Mesoabyssal zone

d. Lower abyssal zone

Figure 1D.6. Yearly macrofaunal biomass by depth zones.

from 16 to 50% of the total abundance. At the shallowest sites sampled (<450 m), nematodes,

polychaetes and crustacea were mostly present. Taxa present in the deeper zone sediments included

mainly peracarid crustaceans. Molluscs other than aplacophorans were rare and echinoderms were

conspicuously absent from the abyssal zone sediments.

Macrofaunal taxonomic richness was lowest on the upper abyssal zone (four phyla among 880

ind.m2

), over twice as high on the archibenthic and the abyssal zones (eight phyla among 2,700

ind.m2). A cumulative percent curve by taxon rank shows strong dominance by a few taxa on the

northern abyssal and archibenthal zones and considerably less dominance and higher species

richness at the southern abyssal sites.

DISCUSSION

The shallower and deeper zones had different biological assemblages, which we hypothesize is

partly a response to food supply. This variation is attributed on the slope, upper abyssal zone, to the

presence of a minimum oxygen depth and a differential tolerance to low oxygen, with greater

sensitivity to hipoxia of macrofaunal components as has been reported previously at similar depths

at the same latitude (Levin et al. 1991). Labile organic matter on the sediment and oxygen
195

concentration appear to be good predictors of macrofaunal biomass in the GOM. Patterns of

macrofaunal community structure on the deeper sites were characteristic of many other deep-sea

regions. Macrofaunal zonation patterns associated with oxygen gradients were reported by Sanders

(1969) for Walvis Bay, by Rhoads and Morse (1971) for the Black Sea, Gulf of California, and

southern California Basins, by Thompson et al. 1985) for the central California slope and are

summarized by Thiel (1978) for regions off Chile and Peru. El Niño, which lead to elevated oxygen

concentrations in Peruvian waters, produced increases in macrobenthic density, biomass and

diversity (Tarazona et al. 1988 a, b).

ACKNOWLEDGMENTS

The invaluable assistance of the captain, crews, pilots and scientific participants of cruises of the

R/V Justo Sierra. Support for this research was provided by DGAPA UNAM IN 211200, 217298,

213197, 203894, 208089 and CONACyT 400356-5-050PÑ-1297, G-27777B, 0004V-T,

CONACyT-NSF and CONABIO B072 grants.

REFERENCES

Boetius, A., S. Scheibe, A. Tselepides & H. Thiel. 1996. Microbial biomass and activities in

deep-sea sediments of the eastern Mediterranean: trenches are benthic hotspots. Deep-sea

Research. 43(9):1439-1460.

Cosson, N., M. Sibuet, G.L.J. Paterson, A. Vangriesheim. 1998. Polychaete diversity at tropical

Atlantic deep-sea sites: environmental effects. Marine Ecology Progress Series 165: 173-185.

Escobar, E., M. Signoret & D. Hernandez. 1999. Variation of the macrobenthic infaunal density in

a bathymetric gradient: Western Gulf of Mexico. Ciencias Marinas 25(2): 193-212.

Levin, L.A., C.L. Huggett & K.F. Wishner. 1991. Control of deep-sea benthic community structure

by oxygen and organic matter gradients in the eastern Pacific Ocean. Journal of Marine Research

49:763-800.

Pasternak, F.A., L.I. Moskalev, and N.F. Fedikov. 1975. Some characteristics of the distribution of

the deep-sea benthic fauna of the Caribbean and the Gulf of Mexico. Trudy Instituta Okeanologii

Akademii Nauk SSSR, Vol. 101:52-64.

Sanders, H.L. 1969. Benthic marine diversity and the stability time hypothesis. Brookhaven

symposium in Biology 12:71-81.

Rhoads, D.C. & J.W. Morse. 1971. Evolutionary and ecologica significance of oxygen-deficient

marine basins. Lethaia 4:413-428.

Tarazona, J., H. Salzwedel & W. Arntz. 1988 a. Positive effects of El Niño on macrobenthos

inhabiting hipoxic areas of the Peruvian upwelling system. Oecologia 76:184-190.
196

Tarazona , J., H. Salzwedel & W. Arntz. 1988 b. Oscillations of macrobenthos in shallow waters of

the Pruvian central coast induced by El Niño 1982-1983. Journal of Marine Research

46:593-611.

Thiel, H. 1978. Benthos in upwelling regions. pp. 124-138. In Boje, R. & M. Tomczak, eds.

Upwelling Ecosystems. Springer Verlag. 

Thompson, J.B., H.T. Mullins, C.R. Newton & T.L. Vercoutere.1985. Alternative biofacies model

for dysaerobic communities. Lethaia 18:167-179.

Tselepides, A. & A. Eleftheriou.1992. South Aegean (eastern Mediterranean) continental slope

benthos: macroinfaunal-environmental relationships. pp. 139-156. In Rowe, G.T. & V. Pariente,

eds. Deep-sea food chains and the global carbon cycle. Kluwer Academic Publishers.
197

Figure 1D.7. Dive sites and dive numbers for the 14 dives completed during 16-31 October

2000, northern Gulf of Mexico.

BIOLOGICAL FINDINGS FROM DSV ALVIN DIVES IN THE DEEP GULF OF MEXICO

Dr. Ian R. MacDonald

Geochemical and Environmental Research Group

Texas A&M University

INTRODUCTION

The RV Atlantis (Cruise 3, Leg 58) completed DSV Alvin Dives 3624-3637 at eight sites across the

northern Gulf of Mexico (GOM) (Figure 1D.7) during 16-31 October 2000. The cruise embarked

in Galveston, Texas and demobilized in Key West, Florida. There was an at-sea exchange of 13 scientific personnel on 25 October. In all, thirty-six scientists and observers participated in the cruise.

The cruise was jointly funded by National Oceanographic and Atmospheric Administration

(National Undersea Research Program), Minerals Management Service (Gulf of Mexico Office),

and Dept. of Energy (National Energy Technology Laboratory). The overall objectives of the cruise

were to provide submersible and ship support for research being conducted by four separate projects.

Fourteen dives at eight separate sites were completed. None of the planned dives were cancelled due

to weather or other problems. The Atlantis/Alvin group elected not to dive at one scheduled site,

Bush Hill, because it was situated less than one mile from an energy production platform. Sites,

divers, and localities are summarized in Table 1D.2. 
198

Table 1D.2. Summary of dives, sites visited, and scientific divers during cruise.

Dive # Site Depth Sci-1 Sci-2 Latitude Longitude

3624 Alaminos Canyon 2230 Paul Aharon Sam Bowser 26.35667 -94.50267

3625 Alaminos Canyon 2230 Barun Sen Gupta Joan Bernhard 26.35709 -94.48397

3626 Green Canyon 272 687 Paul Aharon Lorene Smith 27.68644 -91.53670

3627 Green Canyon 272 687 Joan Bernhard Matt Hackworth 27.68401 -91.53703

3628 Farnella Canyon 2930 Ian MacDonald Tom Cole 26.44713 -90.77330

3629 Green Knoll 2457 Bill Bryant Erik Scott 26.92353 -90.21502

3630 Miss. Canyon 853 1079 Ian MacDonald Anthony Tarantino

(PIT)

28.12663 -89.14367

3631 Miss. Canyon 853 1079 Dan Bean Tim Dellapenna 28.12640 -89.14172

3632 Atwater 425 1955 Ian MacDonald Andy Shepard 27.57516 -88.48793

3633 Atwater 425 1955 Joan Bernhard Will Sager 27.57898 -88.51056

3634 N. FL. Escarpment 2873 Ian MacDonald Sarah Fangman 28.03697 -86.55668

3635 S. Fl. Escarpment 3288 Cindy Van Dover Karen Jacobsen 26.03069 -84.91954

3636 S. Fl. Escarpment 3288 Mary Turnipseed Joshua Osterberg 26.03069 -84.91954

3637 S. Fl. Escarpment 3288 Cheryll Jenkins Anthony Tarantino

(PIT)

26.03069 -84.91954

Images taken with video and digital still cameras comprised an important part of the cruise records.

Two high resolution systems were added to Alvin’s standard suite of cameras for selected dives

during the cruise. These were a high definition television (HDTV) camera provided by the Visual

Data Systems and Development group at Woods Hole Oceanographic Institution and a digital macro

camera (Seapix) developed by the Geochemical and Environmental Research Group at Texas A&M

University. The standard video records and the Seapix images were copied to principal investigators

at the conclusion of the cruise. Although the right to further reproduce and distribute these images

resides with the responsible investigators, the cruise participants agreed to freely share the images

among themselves for educational purposes. HDTV images will be made available on a best-effort

basis in the months following the cruise.

Two instruments for physical oceanography were mounted on Alvin throughout the cruise. These

were a 300 kHz acoustic doppler current profiler (ADCP) manufactured by RD Instruments, Inc. and

a SBE11 conductivity, temperature, and depth recorder (CTD) manufactured by Sea Bird, Inc.

Additional data recorded throughout the cruise included multibeam bathymetry and navigation

records for the ship and submarine. Additional over-the-side sampling was conducted at most sites.

PROJECT DESCRIPTION

This program element collected otherwise unobtainable samples from the base and flanks of the

Sigsbee and Florida Escarpments. Together, the Sigsbee and Florida Escarpments extend for

~1,000km and span a depth gradient of >1,000m in most regions. This topographic regime is a

significant component of the benthic environment in the northern GOM and may comprise a
199

significant zoogeographic boundary between the lower continental slope and the abyss. With use

of Alvin, however, it was possible to collect sediment samples for infaunal and geochemical

analysis. It also provided detailed photographic documentation and verbal description of the benthic

ecology and geology of the sites.

The Sigsbee Escarpment forms the southern margin of the central sampling area. Like the Florida

Escarpment, its precipitous slope poses considerable challenges to sampling from surface ships.

Little is known regarding the benthic ecology of the site. A major type of the benthic environment

has recently been documented that required reconnaissance by submersible for basic

characterization. The features have been designated furrows (W. Bryant, personal communication)

and comprise deep, steep-sided gullies, which are often 10m deep and 30m wide. Furrows tend to

run parallel to the base of the escarpment and have been identified as contiguous features that extend

100km or more. The sediment cover, and presumably the benthic communities, is entirely different

between the bottom of furrows and their upper rims. It was anticipated that in the bottom, the fine

Holocene sediments will have been eroded away, exposing coarser sediment. On the rims, the

Holocene drape is still present. The origin of furrows is unknown, but they are thought to be formed

as a result of intense current events. Because of their small cross section, furrows can only be

accurately sampled with use of submersibles.

The investigators also used Alvin and the sampling capabilities of Atlantis to extend sampling and

observation at two sites where deposits of gas hydrate occur near the seafloor. Gas hydrate generates

a dynamic seafloor response, including complex biological and geological interactions. This

phenomenon is fairly well-known in the GOM and has been investigated with sampling from

submarines in depths of about 500 m. This is a setting where it is possible to directly observe and

sample the in-situ characteristics of the material. The two sites where these dives were conducted

are MC853 and AT425, located at depths of 1,040 m and 1,900 m, respectively. These sites are

being considered for an Ocean Drilling Program leg to investigate hydrate deposits in 2003.

SUMMARY OF RESULTS

Seven dives were completed as to support this project (Table 1D.2, dive numbers 3628 through

3634). Sample collection during the dives included push cores, and two small box cores. Additional

sediment samples were collected with the Atlantis deck winch and large box cores. Continual

acoustic Doppler current profile (ADCP) data were collected from Atlantis along the ship’s track

throughout the cruise. A second ADCP was mounted on Alvin along with a conductivity, depth, and

temperature (CTD) instrument. These instruments collected data at the seafloor during each of the

dives. Bottle cast and CTD casts were also collected with the Atlantis rosette. Swath bathymetry data

were recorded with the Sea Beam system mounted on Atlantis. These data provided detailed

bathymetric maps at each of the dive sites. 

A preliminary review of dive results indicates that most of the project objectives were met. The

dives at Farnella Canyon and Green Knoll (dives 3628 and 3629, respectively) confirmed that the

interpretation of geophysical data from the furrows region was essentially correct. Furrows were

found to be distinct, steep-sided features arrayed in parallel bands along the base of the escarpment.

The steep angle of furrow edges and the accumulation of sorted, coarse sediment along the bottom
200

of furrow indicated that strong currents continue to shape furrows in the present day. At the Green

Knoll site, Alvin encountered a strong bottom current sweeping the base of the escarpment along the

length of the furrow zone. Concentrations of suspended sediments, including coarse sediments were

high. Additional sculpting and erosion of bottom sediments was evident on the slope of the

escarpment above the furrow zone. 

Four of the dives targeted two potential sites for an Ocean Drilling Program leg (MC853 and At425,

Table 1D.2). These dives performed an extensive reconnaissance of possible bore-hole locations,

collected sediment samples, and provided the first inspection of active hydrocarbon seeps in water

depths of 1,000 m or greater. The preliminary results confirm that oil saturated sediments and

shallow hydrate deposits occur at the MC853. Macro oil seepage was also confirmed at AT425 and

shallow hydrates were probably sighted as well. Both sites supported seep-related biological

communities comprising seep mussels, vesicomyid clams, and extensive bacterial mats. Strikingly,

vestimentiferan tube worms, which are the ecosystem forming species at seeps in 500-600m,

appeared to be completely absent at these deeper sites. Extensive brine seepage was also noted,

mostly on the flanks of topographic highs associated with shallow hydrates.

A single dive was completed to conduct a video survey of the Florida Escarpment off the northern

part of the state. The scientists encountered intense sedimentation which had produced a large

accumulation of flocculent material at the base of the escarpment. They transited approximate 700m

up the vertical face of the escarpment. The effects of ongoing sedimentation were evident in the

relative paucity of sessile fauna. Corals, sponges, crinoids, and other forms were found in abundance

only where rocky overhangs protected animals from the settling material. The escarpment appears

to be a stressed habitat over much of its surface.

These investigations are expected to produce a number of presentations and peer-reviewed

publications. Proposals for follow-on work are also anticipated. The public response and media

interest in the cruise has been very high. The logistic arrangements offer a model for inter-agency

cooperation in deep-sea science.

Ian R. MacDonald is an Research Scientist at the Geochemical and Environmental Research Group

of Texas A&M Universitry. His primary research interest is the application of imaging and GIS

techniques for marine ecology. He is the program manager for the Stability and Change in Gulf of

Mexico Chemosynthetic Communities Program. MacDonald received a Ph.D. in oceanography in

1990 from Texas A&M University.
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MEGA-FURROWS OF THE CONTINENTAL RISES SEAWARD OF THE

SIGSBEE ESCARPMENT, NORTHWEST, GULF OF MEXICO

Dr. William Bryant

Mr. Dan Bean

Dr. Niall Slowey

Dr. Tim Dellapenna

Department Of Oceanography

Texas A&M University

Mr. Erik Scott

BHP Petroleum (Americas)

An extensive field of mega-furrows has been recently discovered on the seafloor at the base of the

Sigsbee Escarpment in the northwestern Gulf of Mexico (GOM) (Bryant 1999). Texas A&M deeptow data and 3-D seismic data supplied by WesternGeco Inc. show that the scale of these fields far

exceeds anything previously observed in the world’s oceans. These data allow the furrows to be

resolved in unprecedented detail. The size of the furrows, variations in their morphology, and their

orientation relative to large topographic features all suggest that the furrows are produced by strong

deepwater flow. Data from near-bottom current meters confirms that strong, previously unknown,

currents do exist at the base of the Sigsbee Escarpment. The furrows and associated environmental

processes are dominant features of the northwestern GOM, and similar features will probably be

found to exist in many other areas of the world’s oceans. 

A field of sedimentary furrows, large longitudinal erosional bed forms, was discovered on the

continental rise at the base of the Sigsbee Escarpment (approximately 3,000 m water depth) during

a 1999 deep-tow survey of the continental slope and rise in the Bryant Canyon area of the

northwestern GOM. The furrows are long, relatively narrow depressions in the seafloor that are

generally oriented parallel to (along strike) the escarpment. These deep-tow data indicate that

individual furrows are ~1 to 10 m deep and ~5 to 50 m wide. The spacing between individual

furrows (edge to edge) is ~20 to 200 m and the whole field of furrows extends ~10 to 30 km seaward

from the base of the escarpment. 

Data show that the field of furrows in the Bryant Canyon area runs along ~100 km at the base of the

escarpment. Deep-tow data and seafloor surface renderings derived from 3-D seismic data also show

that furrows are present along ~150 km of the continental rise at the base of the Sigsbee Escarpment

in the Green Canyon, Green Knoll and Farnella Canyon areas (approximately 2,200 to 3,100 m

water depth) in the Western Mississippi Fan Fold Belt—a frontier area for deep water oil and gas

exploration. We suspect, but have not verified, that the field of furrows is continuous between the

Farnella Canyon/Green Knoll area and Bryant Canyon (300 km) and may extend along the

Continental Rise to and may be beyond the Alaminos Canyon area. 

Submarine furrows have been previously observed along the base of the continental slope and along

the continental rise in other areas of the world (e.g., Brazilian Margin—Flood 1978; Bermuda and
202

Saharan Rises—Lonsdale 1978a,b; Blake Bahama Outer Ridge—Flood and Hollister 1980). These

observations have generally been based on chance encounters and localized observations in small

survey areas. The massive extent of the furrows recently observed in the northwestern GOM is

unprecedented. In this area they are a dominant morphologic feature of the lower slope/rise, and

their existence indicates that the surficial processes which form the furrows and related bedforms

are quite significant. The detail with which these furrows have been resolved is also unprecedented.

Shipboard multibeam seismic systems are incapable of imaging furrows in water depths of several

thousand meters. We are able to investigate deep-sea furrows over much larger areas and at much

higher resolution than was possible before because we have access to a deep-towed seismic system

and industry collected 3-D seismic data that was not available for previous studies. We suspect that

when such data is collected outside the GOM it will be found that sedimentary mega-furrows are

present on the lower slopes/rises of many other continental margins. 

Sedimentary furrows are one of a series of longitudinal mega-bed forms which can form aligned

with the net direction of flowing water and are typically attributed to the development of secondary

helical circulation cells that occur above the sediment/water interface (Allen 1969; Flood 1981;

Viekman et al. 1989). The massive size of the furrows in the northwestern GOM, variations in their

morphology, and their orientation relative to large topographic features all suggest that the furrows

are produced by strong deepwater flow. A range of furrow morphologies is observed in the deep-tow

data—comparison with Allen’s (1969) laboratory results suggests that these morphologies reflect

different velocities (sediment texture, consolidation history, and other factors undoubtedly play roles

also). A fascinating aspect of the northwestern GOM furrows is their long extent and their

orientation relative to topographic features on the seafloor. An individual furrow can be traced

continuously for at least 50 km on the 3-D surface renderings (it is the longest continuous individual

sedimentary marine bed form on the surface of the Earth). The orientation of furrows about the

Green Knoll (an ~14 km diameter plug of sediment pushed several hundred meters above the

surrounding seafloor by underlying salt) suggests that the knoll formed an obstacle to the flow of

water, resulting in increased velocities (closer, more prominent furrows) as the flow from the

northeast is deflected around and over the knoll. An area of few furrows on the southwestern side

of the knoll suggests drag related turbulence and, perhaps lower velocity, on the western, downcurrent side of the knoll. Near-bottom current meters deployed by the Minerals Management Service

(MMS) and industry show that the high velocity flow implied by the furrows does occur; several

current meters have recorded flow events with velocities of more than100 cm/sec. 

It appears that the processes responsible for these furrows are active at present. Based on the

variation in character of these features from offshore toward the escarpment, and on the rather good

agreement of that variation with the pattern of changes observed in published laboratory studies of

submarine erosion (e.g., Allen 1969; Dzulynski 1965), the tentative conclusion is that bottom

currents responsible for these features have along-isobath components and increase in strength

toward the escarpment. Such work attributes the furrows to rows of counter-rotating helical currents

generally directed along the furrows with rising parts of the helixes over the furrows. No direct

measurements have been reported to test this concept. Laboratory experiments indicate that furrows

of different separation, wavelengths, and fundamental character occur for different flow rates.

However, it is difficult to scale these model results to field conditions. Speculation is that nearbottom speeds of currents responsible for the inshore furrows might be 50 cm/s or even in excess
203

of 100 cm/s and may be sporadic or quasi-permanent. The furrows and the currents responsible for

them may also exist over a considerable part of the yet unexplored base of the continental slope in

the GOM and may represent a distinctly different phenomenon than the other classes of currents

observed to date and presently under consideration.

Direct observations of the nature of the furrows adjacent to Green Knoll and the furrows near

Farnella Canyon by the use of the Deep Submergence Vehicle Alvin were undertaken in October

2000. Dives of 2400 m into the furrows adjacent to the southeastern portion of Green Knoll

indicated that the slope of the furrow walls ranged from almost vertical to 45 degrees. Active

transport of sediment and shells could be observed along a furrow wall. Bottom water currents were

estimated to be from 30 to 50 cm/sec from ADCP measurements. A Dive in 3,000m of water in the

Farnella Canyon area revealed extensive erosion of the seabed, Large flute-like structures exposing

bedded sediment layers were common. as were large sediment ripples composed entirely of large

foraminifera.

Analysis of 3-D seismic data in the Green Knoll area indicates the presence of fossil furrows in the

subbottom. Surface renderings of 3-D data cube revealed a field of fossil furrows at a depth of 200

ms below the seafloor. Other subsurface expressions have been noted and are now being

investigated. It is suggested that the formation of furrows is a high-sea stand event and the filling

and burying of furrows a low-stand event.

The presence of mega-furrows and their association with high-bottom water currents in the deep

water GOM in and adjacent to areas of potential large oil production presents a definite engineering

constraint relative to the stability of seafloor production facilities and pipelines. An exact knowledge

of the seabed and the adjacent water column will go a long way in helping to overcome, in an

economical fashion, the engineering constraints in operating in such a complex environment. 

ACKNOWLEDGMENTS

We wish to acknowledge the support of the Office of Naval Research and the Mineral Management

Service, Bob Avant specifically. WesternGeco supplied the 3-D seismic data. We thank them for

the data. Without it this study would be impossible.

REFERENCES

Allen, J.R.L. 1969. Erosional current marks of weakly cohesive mud beds. J. Sedimentary

Petrology, 39, 607–623.

Bryant, W.R., T. Dellapenna, A. Silva, W. Dunlap and D. Bean. 2000. Mega-Furrows on the

Continental Rise South of the Sigsbee Escarpment, Northwest Gulf of Mexico. AAPG Annual

Meeting, New Orleans La.

Dzulynski, S. 1965. New data on experimental production of sedimentary structures. J. Sedimentary

Petrology, 35, 196–212.
204

Flood, R.D. 1983. Classification of sedimentary furrows and a model for furrow initiation and

evolution. Geol. Soc. Amer. Bull., 94, 630–639.

Inoue. M. and S.E. Welsh. 1997. Numerical simulation of Gulf of Mexico circulation under present

and glacial climatic conditions. OCS Study MMS 96-0067, U.S. Department of the Interior,

Minerals Mgmt. Service, 147 pp.

Hamilton, P. 1990. Deep currents in the Gulf of Mexico. J. Phys. Oceangr., 20, 1087-1104.

Sturges, W., J. Evans, S. Welsh, and W. Holland. 1993. Separation of warm-core rings in the Gulf

of Mexico. J. Phys. Oceanogr., 23, 250-268.
205

SESSION 1E

IMPROVEMENTS IN MODELING OF OIL SPILLS

Chair: Ms. Gail Rainey, Minerals Management Service

Co-Chair: Dr. Walter Johnson, Minerals Management Service

Date: December 6, 2000

Presentation Author/Affiliation

NOAA’s Updated Weathering Model

(ADIOS 2)

Ms. Debbie Payton

National Oceanic and Atmospheric

Administration

SINTEF’s Weathering Model (Version 1.8) Dr. Mark Reed

SINTEF Applied Chemistry, Norway

MMS Trajectory Model, OSRA: Oil-Spill

Risk Analysis 

Dr. Walter R. Johnson

Dr. James M. Price

Mr. Charles F. Marshall

Dr. Zhen-Gang Ji

Ms. Gail B. Rainey

Minerals Management Service

SINTIF’s OSCAR Model 2000 Dr. Mark Reed

SINTEF Applied Chemistry, Norway
207

NOAA’S UPDATED WEATHERING MODEL (ADIOS 2)

Ms. Debbie Payton

National Oceanic and Atmospheric Administration

The Automated Data Inquiry for Oil Spills (ADIOS 2) model was developed to provide guidance

to responders in estimating fate of oil in the marine environment. The model allows responders to

scale the problem (hours or days?), provides guidance to examine possible clean-up alternatives and

gives quantitative estimates for the Unified Command. The most recent version, ADIOS 2 was

released in December 2000. This 2000 ITM presentation focuses on the changes made to this model.

For additional information on the ADIOS 2 model, please refer to Lehr et al. 2000, or use the

extensive help documentation provided with the model. The model can be downloaded from

http://response.restoration.noaa.gov/software/adios/adios.html.

The upgrade to ADIOS 2 was undertaken by NOAA’s Office of Response and Restoration to

provide for changes requested through the broad ADIOS user community as well as changes to

reflect improvements in algorithmic approaches. In particular, this upgrade provided better user

interface, capability for custom oil libraries, more flexibility in defining release scenarios,

incorporation of uncertainty estimates where possible, ability to account for removal, better

algorithms for evaporation, spreading, dispersion and emulsification and two new submodels to

calculate benzene threat and in-situ burn plume estimates. Given the range of research activities

presently underway, ADIOS 2 was engineered as modularly as possible to incorporate additional

advances or opportunities as they become available.

User interface was designed to provide multiple options for entering and displaying information.

Details of the input information are given on the left-hand side of the screen at all times. Output

options are shown along the top bar. Options for changing viewing preferences (i.e., tabular,

graphical, preferred units, etc.) are available. The expanded capabilities for user interface reflect

work done as part of “usability testing” (Evans et al. 1999).

Progressive helps have been developed for ADIOS 2 in standard HTML format. Using these helps,

the user can find out basic help information (what range of values can I use for wind speed?) to more

detailed technical information (how does the wind speed affect evaporation?). The HTML

information serves as both user and technical documentation.

ADIOS 2 contains a library of over 1,000 oils and refined products. This database is a compilation

of data from a number of different sources, including Environment Canada, the U.S. Department of

Energy, the International Oil Companies’ European Organization for Environmental Health

Protection (CONCAWE) and contributions from industry. Data critical to determining the

physical/chemical changes of the oil over time are part of this database (density, viscosity, flash

point, pour point, distillation data, etc.). In addition to the standard database, this version of the

model allows for users to maintain a custom oil library to reflect properties of additional oils.
208

The flexibility of release scenarios that can be described gives the user the capability of having a

simple catastrophic release, a continuous release, or a combination of a large release followed by

a continuing flow of oil for a number of hours or days. In addition, a new algorithm has been

developed to describe the expected loss of oil over time from a damaged tank. The leaking tank

portion of ADIOS 2 is one of the algorithms that we expect to improve as results from laboratory

studies become available (Simecek-Beatty et al. 2001).

Any “model” of a physical process has some inherent uncertainty. Uncertainty in results can be

particularly important for operational spill response. Defining and presenting that uncertainty

becomes more complex as the model becomes more complex. The ADIOS 2 model provides a

mechanism for users to define some uncertainty in the input (i.e., amount of spilled oil, wind speed).

Based on input uncertainty, ADIOS 2 provides a graphical representation of uncertainty in the

output. This is a substantial change from output provided in previous versions of ADIOS.

A summary of the algorithmic improvements in ADIOS 2 is provided here; more complete detail

is provided in Lehr et al. 2000:

• Evaporation: uses a multi-component method (Jones 1997)

• Spreading: uses a combination of Fay gravity-viscous, diffusion, wind effects and currents,

now allows for variable thickness within the slick.

• Emulsification: new methods were developed to estimate emulsification onset and account

for droplet size distributions.

• Dispersion: a new method for estimated breaking waves and new calculations for

fetch-limited cases were incorporated and sedimentation was considered as a contributor to

dispersion.

• Sedimentation: this process is now included following Payne et al. 1987

The ADIOS model has been used for the past number of years during spill response as part of the

effort to address requirements under the Field Operations Guide for mass balance estimates to be

incorporated into the Incident Action Plan (IAP). Removal mechanisms were included in the model

to reflect these needs. In particular, the user may provide information on oil removal from beach

cleanup, skimming or dispersant operations. ADIOS 2 will consider this information in subsequent

calculations and mass balance estimates. As a removal mechanism, in-situ burning not only accounts

for the removal of oil—but estimates plume dispersion from the burn for both neutral and stable

atmospheres for the determination of potential threat from particulates less than 10 microns in

diameter. In addition, ADIOS 2 provides an option to display the information as ICS Form 209.

Beta-testing of ADIOS 2 has been completed by a broad range of users (industry, government,

researchers, and anticipated end-users). The release date of the final version is set for December

2000.
209

REFERENCES

Evans, M., B. Lehr, D. Wesley and D. Simecek-Beatty. 1999. Why Spill Response Should Emulate

a Fire Extinguisher. Proceedings of the 1999 International Oil Spill Conference, American

Petroleum Institute, Washington DC, pp 63-67.

Jones, R.K. 1997. A Simplified Pseudo-Component Oil Evaporation Model. Proceedings of the

Twentieth Arctic and Marine Oil Spill Program (AMOP), Environment Canada, Ottawa, Canada,

pp. 43-61.

Lehr, William, Dave Wesley, Debra Simecek-Beatty, Robert Jones, Gennady Kachook and Jeff

Lankford. June 2000. Algorithm and Interface Modifications of the NOAA Oil Spill Behavior

Model. Proceedings of the Twenty-Third Arctic and Marine Oilspill Program (AMOP).

Environment Canada, Vancouver, Canada. pp 525-527.

Payne, J. R., B.E. Kirstein, J.R. Clayton, C. Clary, R. Redding, D. McNabb and G. Farmer. 1987.

Integration of Suspended Particulate Mater and Oil Transportation Study. Final Report. Report

to Minerals Mgmt. Service, MMS 87-0083, 1987.

Simecek-Beatty, Debra, William J. Lehr and Jeffrey Lankford. 2001. Leaking Tank Experiments

for Heavy Oils. Presented at International Oil Spill Conference, Tampa, Florida, March, 2001.

American Petroleum Institute CD.
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SINTEF’S WEATHERING MODEL (VERSION 1.8)

Dr. Mark Reed

SINTEF Applied Chemistry, Norway

OSCAR2000 is specifically designed to support oil spill contingency and response decision-making.

Environmental consequences are important components of such decisions. The model therefore

needs to address potential effects in the water column with verisimilitude at least equal to that

achieved on the water surface and along shorelines. This paper focuses on the model’s capabilities

for quantifying the evolution of dispersed oil concentrations in the water column, allowing relatively

realistic analyses of dissolution, transformations through degradation, and toxicology, in addition

to the usual surface processes. Key components of the system are a data-based oil weathering model,

a three-dimensional oil trajectory and chemical fates model, and an oil spill combat model. The

system also includes tools for exposure assessment within GIS polygons (delineating, for example,

sensitive environmental resource areas).

Potential effects of oil spills in the water column have long been the focus of scientific debate.

McAuliffe (1986, 1987) has argued that spilled oil, with or without chemical dispersion, is unlikely

to have measurable effects on larvae, juvenile, or adult marine organisms in the water column. In

many situations, especially surface releases in open water, this may be the case. The North Cape

spill, on the other hand, exemplifies a case resulting in very high water column and benthic

mortalities, due to the easily dispersed oil type, the shallow water and high-energy environment in

which it occurred (Michel et al. 1999).

Researchers at SINTEF in Trondheim, Norway, have been studying the weathering of surface oil

for many years, as summarized by Daling et al. (1999). More recent focus has been on development

of a relatively realistic model representation of the formation and composition of the wateraccommodated fraction (WAF) of oil for both treated and untreated slicks. This work has been

carried out over the past three years under the Advanced Management for Oil Spills (AMOS)

Program in the Department of Environmental Engineering (Singsaas et al. 1999). 

The OSCAR2000 oil spill contingency and response analysis model is one of the primary products

of this program. Both surface and sub-surface calculations by OSCAR have been verified in

considerable detail (Reed et al. 1996). OSCAR2000 differs from its predecessors (Reed et al.

1995a,b, 1998, 1999a; Aamo et al. 1995) in that the user can specify a relatively large number (30

in the present version) of individual components, pseudo-components, or metabolites to represent

the oil and its degradation products. Each component is associated with an array of parameters that

govern process rates: solubility, vapor pressure, transformation (first-step degradation) rates,

density, adsorption-desorption partition coefficient, and toxicological parameters. 

Existing three-dimensional oil spill models accounting for multiple components in processes other

than evaporation are few. The U.S. Natural Resource Damage Assessment Model for Coastal and

Marine Environments (NRDAM/CME; French et al. 1996; Reed et al. 1989, 1992) is one example,

representing oil composition using four components. More accurate assessments of water column
211

effects of releases of hydrocarbons to the environment require a more detailed representation of oil

composition, since volatility, solubility, degradation, and toxicity are not well correlated (Reed et

al. 2000). The model by Rye (1995) represents oil with 100 pseudo-components, focusing on the

processes of evaporation, dissolution and physical transport. OSCAR2000 extends the multiplecomponent concept into all environmental areas, including recovered oil.

Dr. Mark Reed is Senior Scientist at SINTEF Applied Chemistry, Division of Environmental

Engineering in Trondheim, Norway, where he has been since 1992. Prior to that, he worked at ASA

in Rhode Island. His area of specialization is marine environmental modeling. Dr. Reed received

his Ph.D. from the University of Rhode Island in 1980 in oil spill-fishery interactions and did postdoctoral work in Trondheim, Norway in fish migration modeling.
212

MMS TRAJECTORY MODEL, OSRA: OIL-SPILL RISK ANALYSIS 

Dr. Walter R. Johnson

Dr. James M. Price

Mr. Charles F. Marshall

Dr. Zhen-Gang Ji

Ms. Gail B. Rainey

Minerals Management Service

BACKGROUND

As an agency within the Department of the Interior (DOI), the Minerals Management Service

(MMS) conducts a competitive leasing program for commercial oil and gas development on the

Outer Continental Shelf (OCS). The MMS conducts the development of mineral resources in an

environmentally safe manner by analyzing environmental consequences of the program prior to

lease sales or approval of industry’s action plans and by publishing either an environmental impact

statement or an environmental assessment. The Oil-Spill Risk Analysis (OSRA) model was

developed in 1975 by the DOI for the analysis of possible oil-spill impact from offshore oil and gas

operations (Smith et al. 1982).

The OSRA model produces probabilistic estimates of oil-spill occurrence and contact to biological

and economic resources using historical records of oil spills, winds, and ocean currents. The model

is an analysis tool for use with “historical” data and was not designed for use in “real time” or

forecast mode.

The rates of spill occurrence were determined from records of past spills and constructed as a

function of volume of oil produced or transported. Different kinds of facilities (platforms, pipelines,

tankers) demonstrated different rates of spills, and different sized spills occurred at different rates.

The spill occurrence rates have been updated with additional data and analysis (Anderson and

LaBelle, 1994). 

MODEL FORMULATION

The OSRA model produces statistical estimates of hypothetical oil-spill occurrence and contact from

operations projected to occur broadly on the OCS. The model initiates thousands of oil-spill simulations at hundreds to thousands of hypothetical spill locations to generate an ensemble of oil-spill

trajectories, which can statistically characterize oil-spill risk over a large area. The spill locations

are in areas of prospective drilling and production and along projected pipeline and tanker routes.

The hypothetical spills are initiated every one to four days and move at the velocity of the vector

sum of the surface ocean currents plus an empirical wind-induced drift of speed equal to 3.5% of

the local wind speed, with a wind-speed-dependent direction according to Samuels et al. (1982). The

model generates oil-spill trajectories by time-stepping interpolated values of the wind and ocean
213

current fields at intervals short enough to use the full spatial resolution of the ocean current and wind

fields.

In addition to the mean advection of the hypothetical spills, the model can simulate dispersion of

the individual spills by small-scale processes. Each oil spill can be represented as a collection of

hundreds of “spillettes,” which start at the same initial spill location and time. At every subsequent

time step, each of the spillettes is advected as described above and additionally by a randomized

horizontal dispersion term of a magnitude comparable to observed small-scale processes.

The model uses a geographic grid of mesh size 1 to 4 km to define the locations of land and offshore

environmental resources and to compare them at every time-step against the locations of the

hypothetical oil spills. Contacts to land and environmental resources are tabulated for specified

intervals after spill initiation—typically 3, 10, and 30 days. A contact to shoreline will stop a

simulated spill, but contact to an offshore resource will not. For a specific oil-spill source, the

number of contacts to a resource divided by the total number of spills initiated from that source is

the estimate of the contact probability.

Additionally, the model estimates the joint probabilities of oil spills occurring and contacting

resources. The joint probabilities are computed by multiplying the contact probability matrices by

the spill rates of the oil-spill sources (platforms, pipelines, tankers) weighted by the estimated

volume of oil to be produced or transported over the period of the analysis. 

ENVIRONMENTAL DATA

The MMS’s Environmental Studies Program has invested millions of dollars to develop supporting

environmental data sets for the OSRA model. These data sets include the best available wind fields

from national and international sources such as the National Center for Environmental Prediction,

European Center for Medium-Range Weather Forecasting (ECMWF), and the Navy’s Fleet

Numerical Ocean Weather Center. Additionally, high-resolution ocean current fields were developed

through extensive, agency-funded observational and numerical ocean modeling studies, such as

coupled sea-ice-ocean modeling studies of the Beaufort Sea.

For example, the model applied to the GOM uses three-hourly ocean current fields over nine years

(1986-1994) generated by the Princeton-Dynalysis Ocean Model (PDOM) (Herring et al. 1999). The

PDOM is driven by synoptic winds, heat flux, and river flows. The wind field is the analyzed

ECMWF surface winds enhanced by observations from meteorological buoys deployed during

MMS’s LATEX (Louisiana-Texas Experiment) project. This wind field is also used in the OSRA

model for the oil drift. Figure 1E.1 shows the stretched, curvilinear computational grid of the

PDOM.

In addition to the driving wind and ocean current fields, the model uses the geographical extents of

biological and commercial resources, such as the Florida sea grass beds, Alaska native subsistence

areas, coastal habitats, and recreational beaches. The MMS works closely with state and other

federal agencies to obtain the best available geographic information on natural resources and the
214

Figure 1E.1. The surface current output grid of the PDOM applied to the Gulf of Mexico. A

current map was generated every 3 hours over the 9 years, 1986-1994. This grid is

also the OSRA model input grid for both ocean currents and winds.

shoreline, which is represented by one or more equal-distant partitions called land segments. Figure

1E.2 shows an example of offshore environmental resources in a portion of the GOM.

The model inputs are fields of ocean currents, wind velocities, ice concentration and motion, if

required, coastline specifications, geographical boundaries of environmental resources, and locations

of oil production and transportation. 

The model outputs are tables of probabilities of contact to environmental resources from the spill

source locations and tables of probabilities of joint spill occurrence and contact. In addition, MMS

has begun developing GIS-based tools to graphically display the output probabilities.

The OSRA model’s supporting environmental data are among the most comprehensive of all oilspill trajectory models. The MMS is conducting studies to obtain better ocean current and wind

fields through observational and numerical modeling projects.

The MMS uses statistical estimates of oil-spill risk prior to conducting lease sales and approving

industry operations. The MMS also uses model results in planning documents to prevent oil-spill

impact. The oil industry is another significant user of the OSRA model results. They are required
215

Figure 1E.2. The boundaries of a few of the offshore natural resources analyzed by the OSRA

model in oil-spill contact simulations.

to develop oil-spill contingency plans approved by the MMS prior to beginning operations. These

plans must predict the likely spill transport and the likelihood of oil-spill occurrence. Industry is

required to obtain this prediction from MMS.

Other federal and state governmental agencies, such as the U.S. Fish and Wildlife Service and the

National Marine Fisheries Service, examine the OSRA model results contained in MMS’s environmental documents to make their coastal zone management consistency determinations, endangered

species consultations, and independent judgments about proposed offshore oil and gas operations.

Finally, the U.S. Coast Guard has used model results to design safe tanker routes along the coast.

PLANS FOR FUTURE MODEL DEVELOPMENT

Improving the modeling and observations of ocean currents and winds and modeling their action

on oil spills with time-varying physical properties are difficult tasks. The MMS is committed to

improving of the OSRA model through studies of ocean circulation and numerical modeling of

oceanic and spill transport phenomena. The MMS has been working and will continue to work

closely with the Hazardous Materials Response Division (HAZMAT), National Oceanic and

Atmospheric Administration, U.S. Department of Commerce. MMS has collaborated with

HAZMAT on oil weathering methodology, oil weathering properties, Langmuir circulation, coastal

circulation modeling, and display of statistical results. 
216

The MMS has several specific objectives for improving the OSRA model over the next fivfe years.

They are as follows:

1. Obtain a realistic hindcast of ocean currents wherever possible, including the tides and

inertial currents, when important. 

2. Increase the length of wind fields with the best available surface wind field products. 

3. Introduce subsurface currents and models of oil-spill buoyancy and three-dimensional

spreading and dispersion to simulate subsurface oil spills.

4. Improve the modeling of the displacement and dispersion of oil spills by small-scale oceanic

processes. This might include the incorporation of Langmuir circulation and other mixed

layer processes.

5. Improve Geographical Information System tools for the display and analysis of the model

results.

6. Improve the numerical integration scheme with a higher order numerical scheme or some

other numerical method for faster integration of the velocity fields.

ACKNOWLEDGMENTS 

The authors thank technical editor Eileen M. Lear of MMS’s Environmental Division and Robert

P. LaBelle, chief of the division, for their many constructive comments.

REFERENCES

Anderson, C.M., & R.P. LaBelle. 1994. Comparative Occurrence Rates for Offshore Oil Spills. Spill

Science and Technology Bulletin. 1: 2, pp.131-141.

Herring, H.J., M. Inoue, G.L. Mellor, C.N.K. Mooers, P.P. Niiler, L.-Y. Oey, R.C. Patchen, F.M.

Vukovich, & W.J. Wiseman Jr. 1999. Coastal Ocean Modelling Program for the Gulf of Mexico.

Technical Report, Dynalysis of Princeton, Princeton, NJ.

Samuels, W. B., N.E. Huang, D.E. Amstutz. 1982. An oil spill trajectory analysis model with a

variable wind deflection angle. Ocean Engineering, 9, pp. 347-360.

Smith, R. A., J.R. Slack, T. Wyant, K.J. Lanfear. 1982. The oilspill risk analysis model of the U.S.

Geological Survey. Geological Survey Professional Paper 1227, U.S. Geological Survey,

Reston, VA.
217

SINTIF’S OSCAR MODEL 2000

Dr. Mark Reed

SINTEF Applied Chemistry, Norway
218

Bench-scale weathering of a crude oil

12-16 different weathering samples from 1 crude oil or petroleum product
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Norne Crude Oil Test Basin in Horten

Testing of Transrec overflow skimmer

Transrec skimmers are not suitable for collection of solidified oils
220

Framo Shovel Skimmer
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226
227
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Dr. Mark Reed is Senior Scientist at SINTEF Applied Chemistry, Division of Environmental

Engineering in Trondheim, Norway, where he has been since 1992. Prior to that, he worked at ASA

in Rhode Island. His area of specialization is marine environmental modeling. Dr. Reed received

his Ph.D. from the University of Rhode Island in 1980 in oil spill-fishery interactions and did postdoctoral work in Trondheim, Norway in fish migration modeling.
231

SESSION 1F

BEYOND OIL AND GAS: THE HUMAN EXPERIENCE—

SOCIAL SCIENCE IN THE GULF OF MEXICO REGION

Co- Chairs: Dr. Claudia Rogers, Minerals Management Service

Dr. Harry Luton, Minerals Management Service

Date: December 6, 2000

Presentation Author/Affiliation

No Single Story Ms. Barbara Wallace

TechLaw, Inc.

Oil, Gas, and Sustainable Development

in a Rural Community

Dr. Charles M. Tolbert

Department of Sociology and Anthropology

Baylor University

Dr. John J. Beggs

Department of Sociology

Louisiana State University

Dr. Deborah M. Tootle

Louisiana Cooperative Extension Service

Louisiana State University

Benefits and Burdens of OCS Activities

on Selected Communities and Public

Institutions

Dr. John S. Petterson

Dr. Karl Eschbach

Impact Assessment, Inc.

Deepwater Program: OCS-Related

Infrastructure in the Gulf of Mexico

Dr. Jeffrey A. Reidenauer

Mr. Jim Burd

The Louis Berger Group, Inc.

Mr. Steve Mobley

Dr. Ron Luke

Dr. David Dismukes

Research & Planning Consultants, Inc.

Dr. Dmitry Mesyanzhinov

Econ One Reserach, Inc.

Dr. Anatoly Hochstein

LSU Ports & Waterways Institute

Louisiana State University

(continued on next page)
232

Presentation Author/Affiliation

Onshore Effects of Offshore

Employment

Mr. Mark Shrimpton

Dr. Keith Storey

Community Resource Services Ltd.

St. John’s, Newfoundland, Canada

Place-Based Community Research and

Resource Management

Dr. Domenico Parisi

Dr. Duane A. Gill

Unit for Community and Environmental Studies

Social Science Research Center

Mississippi State University
233

NO SINGLE STORY

Ms. Barbara Wallace

TechLaw, Inc.

In 1996, a team of economists, anthropologists, and a social historian embarked on a three-year

study to increase the understanding of and document the relationship between Outer Continental

Shelf (OCS) development and the economies, communities, and households of the Gulf of Mexico

(GOM) region. The study examines historical, social, and economic changes in selected coastal

communities since 1930 and the roles of the offshore oil and gas industry in those changes. This is

the second part of a two-phased project to provide a baseline of the social and economic

consequences of OCS development on Gulf Coast communities. The title of the study is Assessment

of Historical, Social, and Economic Impacts of OCS Development on Gulf Coast Communities; it

is also referred to as the Baseline 2 study. A secondary objective of the project was to enhance the

understanding of methodologies for studying offshore oil and gas impacts through the use and

integration of analytical approaches from history, anthropology, and economics.

ISSUE AND STUDY AREAS

The study focused on three issue areas and their relationship to offshore oil and gas in three study

areas. The issue areas were changes in economic and social structure; community and land use

histories (called community landscapes); and occupation and education. The study areas were South

Louisiana, Coastal Bend, Texas, and Mobile Bay, Alabama. The study areas included five counties

or parishes and six communities within the counties and parishes as follows:

South Louisiana Coastal Bend, Texas Mobile Bay, Alabama

– Lafourche Parish

• Galliano

– Terrebonne Parish

• Schriever 

– San Patricio County

• Ingleside

• Mathis

– Baldwin County

•Gulf Shores

– Mobile County

•Theodore

Changes in economic and social structure were examined at the county and parish level using time

series data. Community landscapes and occupation and education were examined at the community

level using rapid ethnographic techniques. Field work for the study was completed in June 1998.

FINDINGS

OCS oil and gas activities have been important to the social and economic characteristics of the

study areas. The level of importance has varied over time and with respect to each of the study areas.

Federal interventions, other than offshore oil and gas development, and global forces have shaped

GOM communities. Extensive and rapid industrialization occurred following World War II which

affected, among other things, educational institutions. OCS activity played a role in that

industrialization.
234

Overarching findings from the three issue areas examined include the following:

• There are similarities among the study areas, but no single story. While there are similarities

across political boundaries in the GOM region, there is no one story as differences occur

between and among the counties. The impacts of OCS oil and gas activities have varied

among the study areas. Direct impacts have been felt most keenly in the South Louisiana

study area, particularly in south Lafourche Parish, an area with strong ties to marine

resources, both fish and oil. In the other study areas, the impacts from oil and gas are seen

in different ways. Coastal Bend Texas is a fabrication center, an oil refining region, and the

home port for the U.S. Navy’s minesweepers, whose primary task is to keep the world’s

harbors and shipping lanes clear. The oil and gas industry is relatively new to the Mobile

Bay study area. Impacts from OCS development are less evident in Baldwin and Mobile

counties than in the other three study area counties.

Oil and gas impacts differ within the study areas as well as among them. For example, oil

economics affect the agricultural communities in the study areas. Good times for the

offshore oil industry can be difficult times for farmers, who are squeezed financially when

oil prices rise. (In terms of impacts from OCS, it should be remembered that oil prices are

set outside the region.)

• Federal, but non-MMS, policies affected the study areas. OCS-related activities were only

one source of change of interest and were not the driver for all that occurred. Despite its

history and rhetoric of separatism, the Gulf Coast, like the South, is tied to the federal

government in a number of ways. Federal policies have driven much of the change in the

study areas. The similarities across the study areas often relate to national, although nonMMS related, policies, such as the GI bill and access to education; civil rights movement

and school desegregation; development of the Interstate highway system; rise in

environmental protection issues; and strategic decisions on military bases and personnel. 

• The mid-1980s decline resulted in changes. The decline, referred to as the “bust,” in oil and

gas activity in the mid 1980's brought change to the economies and to individuals most

directly affected by the offshore oil and gas industry — Lafourche and Terrebonne Parishes

and, to a lesser extent, San Patricio County. The changes are seen in the county-level

statistics and in the personal stories told by individuals who lived through the decline years

and are still living in the study areas. The changes can also be seen within the industry itself.

• Leisure/tourism/retirees economics is incompatible with OCS oil and gas activity. The

transition to new economies, as seen in leisure/tourism/retirees, may be fundamentally

incompatible with OCS oil and gas activity. Areas with leisure/tourism/retirees and oil and

gas economies are dependent on natural resources, but in different ways. The expansion of

leisure time and the rise of leisure/tourism/retiree economies is an example of societal

changes that occurred during the study’s period of interest.

• The oil and gas industry is complex. The statistical analysis and the personal stories told

revealed many characteristics of the oil and gas industry. The industry is international in
235

scope. It has been transformed by technology multiple times. It operates within the larger

context of business and industry and, therefore, is not immune to trends seen in the larger

business world. The industry brings uncertainty and can be an agent of change. Neither the

industry nor its impacts are monolithic.

• The three disciplines contribute to identifying and understanding OCS impacts. The study

demonstrated that the analytical approaches of history, anthropology, and economics are

useful in identifying and explaining impacts of offshore oil and gas on coastal counties,

parishes, and communities. The analytical approaches of each of the disciplines resulted in

new insights about the impacts of offshore oil and gas activities. The integration of the

findings of the three disciplines provided an added dimension to understanding offshore oil

and gas impacts on counties, communities, households, families, and individuals. Yet, in the

end there is still much to be learned about the timing, magnitude, and location of OCS

impacts on coastal communities and the households, families, and individuals who reside

there.
236

OIL, GAS, AND SUSTAINABLE DEVELOPMENT IN A RURAL COMMUNITY

Dr. Charles M. Tolbert, 

Department of Sociology and Anthropology

Baylor University

Dr. John J. Beggs

Department of Sociology

Louisiana State University

Dr. Deborah M. Tootle

Louisiana Cooperative Extension Service

Louisiana State University

INTRODUCTION

This research continues a project that began with a focus on a small community in Southwestern

Louisiana. With funding from the U.S. Minerals Management Service, we are expanding the scope

of our initial work to test hypotheses derived from the community study. Abbeville, a small town

in rural Vermilion Parish, appears to be particularly resistant to the income volatility generally

associated with periods of increasing and decreasing oil and gas development activities. Previous

research on census places in coastal Louisiana indicates that Abbeville experienced relatively less

of the economic upheavals often associated with the downturn of the oil and gas industry in the early

1980s (Tolbert and Shihadeh 1995). Research we are now concluding on Abbeville suggests that

its resiliency during the 1980s reflects a historical and cultural legacy that fosters rich social

resources, facilitates economic development, and yields a local industrial structure that enables it

to weather economic disruptions. Our findings suggest that, unlike most oil and gas dependent

locations, Abbeville has a diverse industrial base. This industrial diversity is reflected in part by

relatively large routine manufacturing, extractive (agriculture), and producer services sectors. This

producer services sector is largely oil and gas related as Abbeville is a center for operations and

logistics. 

In this study conducted partly at the Center for Economic Studies, we employ confidential

longitudinal establishment data to analyze the distribution of coastal industrial labor over time and

space. We are interested in the extent to which spatial and temporal divisions of labor within the oil

and gas sectors similar to those of Abbeville exist elsewhere along the Gulf Coast. We are also

interested in the socioeconomic implications of these industrial patterns for coastal communities.

We hope to improve on our measures of income volatility in coastal areas which have employed

summary information from decennial census long-form data. These findings will contribute to a

better understanding of the role of oil and gas activity vis a vis other industrial activity in local

coastal communities. 
237

FRAMEWORK

Socioeconomic conditions are primarily dependent upon patterns of industrial organization. Local

economies are based on the allocation of employment across distinct industrial sectors. Each sector

is associated with different working conditions, opportunities and job outcomes (Lobao 1990).

Industrial organization theory generally divides industries into extractive, manufacturing, and

service categories. The manufacturing and service sectors can be further divided into four more

discrete sectors, defined on the basis of the magnitude of the complexity of their operations and

earnings/benefits of workers: complex and routine manufacturing, and producer and consumer

services (McGranahan 1988). In general, complex manufacturing and producer services are

associated with higher wages and stable employment while routine manufacturing and consumer

services are associated with lower wages and unstable employment.

In rural areas (where much of the oil and gas activity is staged), sound economic performance is

often a function of a diversified economy. This diversification tends to produce more consistent

economic growth. Specialized economies, on the other hand, can expand rapidly but are particularly

vulnerable to local- and national-level swings in the economy. Because of a division of labor across

space, most rural areas tend to specialize in low wage routine production and consumer service

sector jobs. Typically dominated by a single industrial sector, these communities are vulnerable to

business cycles and foreign competition which encourage capital flight (Bluestone and Harrison

1982; McGranahan 1988). 

Because diversified local economies are not dependent on any single sector source of employment

and earnings, they are better prepared than more specialized economies to weather the economic

downturns associated with specific industries (Killian and Hady 1988), such as the impending

shutdown of such large-scale production facilities throughout southwestern Louisiana (Acadiana).

Abbeville, unlike many of the communities in Acadiana, is not solely dependent upon such largescale production facilities. Oil and gas activity is an integral part of its industrial structure and may

help counter the economic downturns associated with the flight of routine production facilities

offshore by either absorbing some surplus labor or increasing local household earnings. 

Because of the tendency for rural areas to specialize in routine manufacturing and consumer

services, the industrial organizational and rural research literatures pay very little attention to

producer services in rural areas. It is readily apparent that producer services in rural areas are closely

associated with a dominant industrial base, such as mining (Glasmeier and Howland 1995).

However, it is not at all clear how these linkages develop across time and space. The Abbeville area

differs from other oil activity centers because it appears to be more of a center for oil field logistics

and operations than it is for oil field fabrication. We think that the concentration of oil-related

producer services in Abbeville is a major factor in Abbeville’s resiliency to the decline in oil and

gas activity. For the most part, these oil-related producer services firms remained active, albeit at

a diminished rate, throughout the 1980s. However, we currently do not have the necessary spatial

and temporal data to examine and compare the distribution and differential impact of oil and gas

activity across time and space. 
238

The foregoing discussion begs a number of questions: How many specialized service firms are there

in Abbeville? How long have they been there? Have these oil and gas service establishments

agglomerated in identifiable clusters or is there considerable regionalization or spatial dispersion

among them? Are these firms sufficiently embedded in the Abbeville economy to assist in

cushioning the impact of a major plant closure or some other episode of economic volatility? Are

the same industrial patterns exhibited in coastal communities elsewhere? Do those communities also

have a history of less volatile responses to boom and bust episodes? Answering questions of this sort

requires a combination of qualitative and quantitative data and methods that we outline in the

following section.

METHODOLOGY

With CMI funding, we are conducting research that will help us develop a better understanding of

how oil and gas activity contributes to local economic diversity. Our proposed work entails:

1. examining the potential for oil and gas employment to compensate for the loss of

employment with Fruit of the Loom, and 

2. determining whether a spatial and temporal division of labor exists within the coastal oil and

gas sector, and the socioeconomic implications for coastal communities. 

This is an in-depth, multi-method study that encompasses community field study and procedures

and comparative techniques that permit analysis of enterprise-level data over time and space.

Field Study

We have used field study techniques to determine whether expanding oil and gas employment

opportunities might counter some of the economic challenges facing the community with the loss

of employment at the Fruit of the Loom plant. This type of analysis will require more in-depth

analysis than we can conduct with existing place or establishment level data. We reported on some

initial results of the field study at the 17th ITM (Tootle, Tolbert, and Shihadeh 1999). We are

developing an in-depth report on the field study, but can summarize the findings as follows:

• The closure of the Fruit of the Loom plant was a protracted event, lasting almost nine months

after the initial announcements. This permitted employees to explore options, including job

training and other avenues of interim support.

• While the transition period dampened the impact of the closure, there were still clear effects:

1. ethnicity—displaced workers used community, social, and family support sources in ways

that varied by ethnicity. The least likely individuals to avail themselves of governmental and

official services were Vietnamese. 

2. oil and gas industry—FOL workers who had family members in oil and gas industry

employment were among the first to opt out of plant employment. The oil and gas industry
239

served as buffer which permitted the displaced workers in those households to leave and

begin job searches.

3. the well-organized state job training program worked well that also buffered the impact of

the plant closure on the community.

• The diversity of the Abbeville economy—including a large sector of business services oriented

to the oil and gas industry—continues to be a primary basis for economic resilience in the

community. But, our longitudinal approach suggests that a dynamic view of industrial diversity

best explains the sustainability of this rural community:

1. a key source of sustainability in one year turns out to be problematic in a subsequent year;

2. a seemingly problematic aspect of the local economy at one point can contribute to

sustainability at a later point;

3. this suggests we should be wary of cross-sectional assessments of the sources of

socioeconomic vitality.

Analysis of Enterprise Data over Time and Space

We believe our findings in the Abbeville case study are sufficiently robust to recommend a

hypothesis for testing on other communities. The hypothesis is based on our observation of a

thriving producer services sector in the Abbeville economy. Are similar service sectors evident in

other coastal communities? Can such sectors be shown to be statistically related to the desirable

outcomes we have observed in our Abbeville research? 

To adequately assess the development of a producer services sector in Abbeville and other coastal

communities, we plan to develop models of the coastal division of industrial labor, comparing

socioeconomic outcomes for coastal areas with varying industrial and service sector compositions

over time. We are especially interested in the extent to which industrial divisions of labor similar

to that of Abbeville exist in other coastal communities. Assuming we can identify areas with similar

industrial profiles, we will analyze socioeconomic outcomes and compare those to the results we

have in hand for Abbeville.

To accomplish this modeling task, we need data on the location and age of establishments, as well

as very detailed industry classifications. These data requirements surpass readily available data

sources such as County Business Patterns or published versions of data from the Economic

Censuses. While these data compendia are generally very useful, they frequently do not report data

for small areas and small numbers of establishments to ensure confidentiality. Such establishmentlevel microdata are not in the public domain, but can be accessed through an agreement with the

Center for Economic Studies (CES), U.S. Bureau of the Census. 

CES has assembled establishment responses to various economic censuses. These data in

conjunction with an age proxy available from the Census Bureau’s SSEL (essentially a national
240

business register), allow us to study the “embeddedness” of establishments. A major, related--and

exploratory--interest of this project is the study of establishment formation/dissolution/survival and

identifying how measures of churning in these establishment populations relate to measures of wellbeing. The economic census data also provide detailed industrial classification (four- and five-digit

SIC codes) and establishment type (single-unit vs. multiple location) information. Access to these

data represents a significant step forward for socioeconomic analysis. All previous socioeconomic

work under the auspices of MMS has necessarily been based on public domain-data, which are often

suppressed for reasons of confidentiality and which do not contain information on establishment age

or type. By contrast, the economic census data contain no suppression and constitute the universe

of U.S. establishments. We will use these data to develop a longitudinal database on coastal oil and

gas producer services. We have budgeted for database coverage of all states adjacent to the Gulf of

Mexico (GOM), and this has been approved by MMS.

Working at CES, we are developing models of the coastal division of industrial labor, comparing

socioeconomic outcomes for coastal areas with varying industrial and service sector compositions

over time. For MMS resource management purposes, it would be very useful for us to explore the

extent to which the Abbeville case is unique or whether there are other, similar areas whose

industrial mix appears to buffer them from episodes of increasing and decreasing oil and gas

industry activity.

OUTLINE OF CES ANALYSIS

Objectives

1. Employ confidential, longitudinal establishment data to analyze the Gulf Coast industry mix

over time and space and its relationship to income levels and income volatility. 

2. Identify target industries with emphasis on producer services sector. Search for areas with

industrial compositions similar to that of Abbeville, Louisiana (i.e., substantial involvement

in oil and gas activity through service industries as opposed to fabrication and extraction).

3. Explore variations in formation/dissolution (churning) of establishments coinciding with

episodes of increased and decreased oil and gas industry activity. Compare rates of change

for producer services vs. other industries. 

4. Explore use of 1990 long-form microdata to compute selected socioeconomic outcome

measures and to estimate hierarchical linear models.

UNITS OF ANALYSIS

This analysis employs data for roughly 80,000 persons who work in approximately 900 incorporated

places in the states of Texas, Louisiana, Mississippi, Alabama, Florida, and Georgia. All the

incorporated places have populations of at least 2,500 persons. This permits us to match the place

geography on the 1990 decennial information with the place geography found in the economic

census of 1987 and 1992.
241

Developing a Community Typology

To group the communities into meaningful classifications, we employed factor analytic and cluster

analytic procedures to arrive at a typology. From the 1987 and 1992 economic censuses, we

developed measures of employment, wages, receipts/sales, and growth in these factors for the set

of Gulf Coast places. From 1990 census of population and housing long-form records, we selected

measures of employment shares by industry and occupation. The detailed occupational and

industrial information permitted us to identify specific occupations and industries likely to be oil and

gas related. We also developed measures of labor force factors such as working in place of

residence, low-hours workers, and low wages. Lastly, we employed the decennial information to

develop a set of demographic measures, including population size, percentage of African American,

and population density. In all, approximately 90 measures were taken from the economic census and

decennial population census to describe each of the 900 or so Gulf Coast incorporated places.

In a factor analysis of the descriptive measures, we derived a seven-factor solution that accounted

for about one-third of the variance among the indicators. In order of magnitude of eigenvalues, we

labeled these factors: 1) suburban high-skill, high-wage services, 2) high-wage, high-growth,

3) growth in receipts and wages, 4) high productivity-refining, 5) oil and gas dependent, 6) legal,

insurance, and accounting, and 7) retail, especially eating and drinking places. Factor scores for each

incorporated place were then employed in a cluster analysis to derive groupings of the communities

along these dimensions (or combinations of the dimensions). A satisfactory solution was obtained

that indicated six clusters of communities: 

1. Non-metro service and manufacturing communities

2. Low-wage, high-growth communities

3. Suburban services, high-wage, high-growth

4. Non-metro high-wage, high-growth

5. Oil and gas dependent communities

6. Large metro, suburban services, high-wage, high productivity communities

These six community types permit us to contrast oil and gas dependent communities with other

types of communities.

MEASURES OF EMPLOYMENT VOLATILITY

A primary concern about the social impacts of oil and gas industry ties to communities focuses on

potential employment volatility that fluctuations in oil and gas activity may cause. To evaluate the

differences between oil and gas dependent and other communities, we developed several measures

of employment volatility. We first constructed a measure of net employment change: total

employment at some time 2 (T2) minus total employment at a time 1 (TI) divided by total
242

employment TI. Data to construct this measure are readily available from public sources (i.e.

economic censuses or county business patterns). Economists like David Birch and John Haltiwanger

have pointed out the a tremendous amount of job reallocation that is not captured by a gross net

change measure like this one. Net job change is composed of jobs that existed at both time points,

jobs created between TI and T2, and jobs lost between TI and T2. Job creation and job destruction

each have two sources: establishments that existed at both points in time and either expanded or

contracted and establishments that were created or dissolved. 

To correctly evaluate employment volatility, we need to consider all the sources of employment

change. To build such measures, we need establishment-level data for employment at two points in

time. These “microdata” are not available from public sources. They are available to us, however,

at the Center for Economic Studies at the Bureau of the Census. We use microdata from the

economic censuses of 1987 and 1992 to construct our employment volatility measures. We are

limited to those sectors of the economy where data are available at both points in time. We used data

from the manufacturing, wholesale, retail, and service sectors to construct our measures. We wanted

to use the minerals census data also because of our interest in oil and gas employment, but there are

problems with local (substate) geography (discussed below). In all other respects, the economic

census microdata are ideal because we want to gauge employment volatility in local communities.

The establishment microdata include a suite of geography items, including information on the name

of the incorporated place where the establishment is located. This permits us to organize the data

by locality or community. In all, we use data on 907 incorporated places of 2,500 persons or more

from the five states that border the GOM. 

We report information on three measures of employment volatility in coastal communities in this

presentation. Our first measure evaluates overall volatility. It is constructed by summing the jobs

which were created either in existing or new establishments plus the jobs that lost either from

existing or dissolved establishments. This is then divided by this total plus the jobs that existed at

both time 1 and time 2. Our other two measures focus on job creation and job destruction separately.

The first measure is constructed by dividing the jobs created either in existing or new establishments

by employment at time 2. The latter measure, job loss volatility, was constructed by dividing the

jobs lost either from existing or dissolved establishments by employment at time 1. Our focus in this

analysis is on the association of type of community and employment volatility. We do this analysis

through the use of OLS regressions in which we contrast five types of communities with oil and gas

dependent communities. We use a number of controls in these preliminary models so that we can

consider community type net of other potentially relevant constructs. 

Table 1F.1 presents the information on means, standard deviations, and zero order correlations

information that we were able to get through the disclosure process. Table 1F.2 presents the

information on correlations among dependent measures. Table 1F.3 presents the regression results.

The first two columns present the results for our gross net change measure. Four of the five types

of communities have greater net growth than the oil and gas dependent communities. Since the time

period is 1987 to 1992—a period of relative contraction in the oil and gas industry—this result is

not surprising. The model does not fit well at all; 9.15% of variance in this measure is explained.

The second two columns present the results for our measure of overall volatility. While our model

fit is considerably better (r-square is .38) none of the community types is differentiated from the oil
243

Table 1F.1. Means and standard deviations.

Variable Mean S.D.

Clusters

Cluster 1, Non-metro Service and Manufacturing Communities –* –

Cluster 2, Low Wage, High Growth Communities –* –

Cluster 3, Suburban Services, High Wage, High Growth –* –

Cluster 4, Non-metro High Wage, High Growth –* –

Cluster 5, Oil and Gas Dependent Communities –* –

Cluster 6, Large Metro, Suburban Services, High Wage, High

Productivity Communities

–* –

Control Measures

% Employed in Multi-Establishment Enterprise Pieces –* –

% Multi-Establishment Enterprise Pieces 23.89 8.06

Average Establishment Size 12.21 6.26

Receipts Per Employee –* –

% Less Than HS Education 28.74 11.56

% Labor Force Participation 59.28 9.19

% Lived in Household 10 or More Years 37.62 10.27

Median Household Income 24820.85 11579.89

Non-metro Status of Largest County Piece .39 .49

Dependency Ratio .67 .17

Log of Population Size 9.26 1.09

Dependent Measures

Overall Employment Volatility –* –

Net Employment Growth-1987-1992 –* –

Employment Losses-1987-1992 –* –

Employment Gains-1987-1992 –* –

* indicates that statistic was not disclosable

Table 1F.2. Correlations among dependent measures.*

1234

Overall Employment Volatility (1) 1.000 + + +

Net Employment Growth-1987-1992 (2) + 1.000 - +

Employment Losses-1987-1992 (3) + - 1.000 +

Employment Gains-1987-1992 (4) + + + 1.000

* correlation coefficients not disclosable
244

Table 1F.3. Unstandardized OLS regression coefficients predicting measures of employment

volatility.

Employment

Growth

Overall

Employment

Volatility

Employment

Losses

Employment

Gains

b s.e. b s.e. b s.e. b s.e.

Cluster 1 4.35 5.20 -1.71 1.34 -3.32* 1.65 -.69 1.62

Cluster 2 15.90* 6.20 1.31 1.60 -1.00 1.96 4.00* 1.94

Cluster 3 12.35* 6.11 1.20 1.57 -.96 1.93 3.37+ 1.91

Cluster 4 9.87+ 5.91 -1.33 1.52 -3.74* 1.87 -.10 1.85

Cluster 5 (Reference

category)

– –––– – – –

Cluster 6 28.10*** 6.77 3.01+ 1.74 -.17 2.14 5.12* 2.11

% Employed in MultiEstablishment

Enterprise Pieces

.09 .10 -.14*** .02 -.21*** .03 -.06* .03

% Multi-Establishment

Enterprise Pieces

.04 .19 .15** .05 .20*** .06 .10+ .06

Average Establishment

Size

-1.25*** .24 -.65*** .06 -.41*** .07 -.80*** .07

Receipts Per Employee .01 .02 -.01* .00 -.02*** .00 -.00 .00

% Less Than HS

Education

.14 .19 -.02 .00 -.08 .06 .01 .06

% Labor Force

Participation

.20 .20 .04 .05 .06 .06 .04 .06

% Lived in Household

10 or More Years

-.38* .16 -.17*** .04 -.06 .05 -.26*** .05

Median Household

Income

-.00 .00 .00 .00 .00 .00 .00 .00

Nonmetro Status of

Largest County Piece

-1.36 3.09 -2.59** .75 -2.54** .98 -2.51** .97

Dependency Ratio -10.10 9.85 -2.94* 2.54 -1.54 3.12 -4.61 3.08

Log of Population Size -2.97* 1.30 -.79 .33 -1.05* .41 -.87* .41

Intercept 51.78 24.48 88.09 6.30 67.44 7.75 75.60 7.66

R2 .09 .38 .27 .33

+ p<.10, *p<.05, **p<.01, ***p<.001

and gas dependent communities. However, when we look at columns five through eight, we start

to see some of the dynamics at the root of the results for our gross net change measure. The results

for employment gain volatility indicate that community types 2, 3, and 6 have greater net change

than oil and gas dependent communities because they added jobs to their employment base between

1987 and 1992. Conversely, community types 1 and 4 had greater net employment between 1987

and 1992 because they lost jobs a lower rate. 
245

Access to the confidential microdata from the decennial and economic censuses allowed us to

address a research issue we had not been able to address with existing publicly available data. We

are interested in impact of a small sector of the economy (oil and gas) at a low level of geography

(places). The data at CES permit us to develop useful information about the relationship between

oil and gas employment in local communities along the GOM. A number of these communities are

small non-metro places for which limited, if any, information is available. We obtained a greater

understanding of the dynamics of the labor market for these areas through our analysis of the

components of employment change. 

CENSUS OF MINERALS’ GEOGRAPHY

This section consists of a cautionary note about public data sources based on economic census data

collection procedures such as the widely used County Business Patterns. In our work with the

Census of Minerals we have discovered that substate geographies (e.g., metropolitan area, county,

place) are not available, either in public data or in the confidential establishment microdata that we

employ at Census. Upon further investigation, we have learned that there are circumstances for

which the Bureau does not collect or retain information other than state of operation, such as in the

case of large enterprises that may have establishments in multiple locations. This lack of data has

led us to omit minerals industries (SIC code 13) from our employment volatility analyses at the

place level (at least for the time being).

This problem regarding information on minerals industries from County Business Patterns is further

compounded by the Bureau’s suppression of certain data in published reports. This suppression is

used to avoid identifying data for specific establishments, most often, to avoid disclosing data on

a single dominant firm in an area, but there are other reasons that data are suppressed. Suppression

flags appear in data fields of the County Business Patterns for establishment employment and

payroll. More often than not, the flag references a range of possible data values (say, 500-1,000

employees). Experienced users know to observe the suppression flags in public versions of the data

and will typically derive an estimate of employment or payroll by using the midpoint of the interval.

Table 1F.4 illustrates how these two data problems interact to limit substantially the inferences that

can be made from the published data sources like County Business Patterns. Each of the columns

represents one of the Gulf Coast states that are the focus of our ongoing work. The data for Alabama

indicate that 23 Alabama counties are identified as having one or more minerals industries

establishments. In 20 of those 23 counties, however, employment and/or payroll data are suppressed.

There are minerals establishments in other counties of Alabama, but the counties are not identified

(the balance of the data are grouped into a single residual geographic category). Establishment

counts are not suppressed, so we can report 90 minerals industry establishments for which counties

are identified and 41 establishments in the non-identified geographic unit. This sums to the 131

found in the state total section. Payroll and total employment are suppressed for the generic

geographic category in Alabama. What do we miss because of this suppression? Since the state total

payroll (in $1,000s) is $67,792 and the identified county payroll is $10,357, we do not have substate

geography for $57,435 which is 85% of Alabama’s minerals industries’ payroll. Similarly, we

cannot identify a location within the state for 84% of the employment in the industry. We know only
246

Table 1F.4. Limitations of county business patterns data on mining (SIC = 13).

Alabama Florida Louisiana Mississippi Texas

State Totals

Number of Identified Counties

(Valid FIPS) With Mining

Establishments

23 27 54 34 205

Number of Identified Counties

(Valid FIPS) With Mining With

Suppressed Data

20 22 28 26 119

State Total Payroll in Mining 67792 16229 1551169 95173 3913068

State Total Employment in Mining 2016 501 42696 3539 104151

State Total Establishments 131 101 1451 345 6714

Identified Counties (Valid FIPS

Code)

Total Payroll in Mining 10357 1280 409970 21151 2113276

Total Employment in Mining 322 58 13828 743 56021

Number of Establishments 90 85 1284 284 6487

Non-Identified Counties (999)

Total Payroll in Mining X 6898 902555 36233 X

Total Employment in Mining X 191 20776 1132 X

Number of Establishments 41 16 167 61 227

Total Information in

Unidentifiable Geographic Unit

(State Total-Identified)

Payroll (% of State Total in

Unidentifiable Geographic Units) 

57435

(85%)

14949

(92%)

1141199

(73%)

74022

(78%)

1799792

(46%)

Employment (% of State Total in

Unidentifiable Geographic Units)

1694

(84%)

443

(88%)

28868

(68%)

2796

(79%)

1664

(47%)

Total Unaccounted Information

(State Total-(Identified+NonIdentified))

Payroll (% of State Total

Unaccounted for by County Data)

57435 

(85%)

8051

(50%)

238644

(15%)

37789 

(40%)

1799792

(46%)

Employment (% of State Total

Unaccounted for by County Data)

1694 

(84%)

252

(50%)

8092 

(19%)

1664

(47%)

1664

(47%)

X=Total Data Suppressed in CBP

that the place of work is somewhere in Alabama. While Alabama may be the extreme case, there

is substantial unaccounted information for all states in Table 1F.4.

Among the datasets available to us at Census is the underlying establishment microdata for County

Business Patterns. There is no suppression in these data, and we are able to work with precise

figures rather than estimates. This enables us to resolve the suppression problem, but, we have yet

to resolve the geography problem in the minerals data. We have attempted to use several related

datasets including the Standard Statistical Establishment List (SSEL), which is the Bureau’s national
247

establishment register. None of the business data sets has provided a solution for the geography

problem. We are now beginning to use the 1990 population census long-form data from which we

can determine place of work. By careful selection of occupation and industry categories, we hope

to derive a reliable estimate of location of minerals industry employment activities. In a new project,

we will also investigate other solutions, including ES-202 data and proprietary data sources.

REFERENCES

Bluestone, Barry and Bennett Harrison. 1982. The Deindustrialization of America: Plant Closings,

Community Abandonment and the Dismantling of Basic Industry. New York: Basic Books.

Glasmeier, Amy K. and Marie Howland. 1995. From Combines to Computers: Rural Services and

Development in the Age of Information Technology. Albany: State University of New York

Press.

Killian, Molly Sizer and Thomas F. Hady. The economic performance of rural labor markets.

pp.181-200. In David L. Brown, J. Norman Reid, Herman Bluestone, David A. McGranahan,

and Sara M. Mazie, eds. Rural Development for the 1980's: Prospects for the Future. Agriculture

and Rural Economy Division, Economic Research Service, U.S. Department of Agriculture,

Rural Development Research Report No. 69.

Lobao, Linda M. 1990. Locality and Inequality: Farm and Industry Structure and Socioeconomic

Conditions. Albany, NY: The State University of New York Press.

McGranahan, David. 1988. Rural workers in the national economy. pp. 29-40 In David L. Brown,

J. Norman Reid, Herman Bluestone, David A. McGranahan, and Sara M. Mazie, eds. Rural

Development for the 1980's: Prospects for the Future. Agriculture and Rural Economy Division,

Economic Research Service, U.S. Department of Agriculture, Rural Development Research

Report No. 69.

Tolbert, Charles M. and Edward Shihadeh. 1995. Oil and gas development and coastal income

inequality: case studies at the place level. Presentation at the 15th Annual Information Transfer

Meeting, U.S. Minerals Mgmt. Service, New Orleans, LA.

Tootle, Deborah, Charles Tolbert, and Edward Shihadeh 1999. Sustainable development in oil and

gas country: a case study of Abbeville, Louisiana. pp. 228-36. In U.S. Department of the

Interior, Minerals Management Service. Proceedings: seventeenth annual Gulf of Mexico

information transfer meeting, December 1997.U.S. Department of the Interior, Minerals Mgmt.

Service, Gulf of Mexico OCS Region, New Orleans, La. OCS Study MMS 99-0042. 710 pp.

Charles M. Tolbert is Professor of Sociology and Chair of the Department of Sociology and

Anthropology at Baylor University. Tolbert’s research has been funded by the National Science

Foundation, U.S. Departments of Agriculture (National Research Initiative, Economic Research
248

Service), Commerce (Economic Development Administration, National Marine Fisheries Service,

Bureau of the Census), Interior (Minerals Management Service), Labor (Employment and Training

Administration), as well as the Louisiana Universities Marine Consortium (LUMCON) and the

Louisiana Office of Community Services. His research has appeared in leading social science

journals, including the American Sociological Review, American Journal of Sociology, Rural

Sociology, Social Forces, Social Science Quarterly, Environment and Planning A and in policy

outlets such as American Demographics. 

Deborah M. Tootle, Ph.D., is a sociologist with the Louisiana Cooperative Extension Service, LSU.

Previously, she was an Assistant Research Professor with the LSU Department of Rural Sociology

and affiliated with the Louisiana Population Data Center. She was co-principal investigator on the

LSU/MMS CMI Project “Oil and Gas Development and Coastal Income Inequality: Case Studies

at the Place Level.”

John J. Beggs, Ph.D., is Associate Professor, Department of Sociology, Louisiana State University.

He is also Senior Research Scientist in the Louisiana Population Data Center, Louisiana State

University. His research has been funded by the National Science Foundation and the U.S.

Department of the Interior. He has published in journals such as the American Sociological Review,

Rural Sociology, and Social Forces.
249

BENEFITS AND BURDENS OF OCS ACTIVITIES ON SELECTED

COMMUNITIES AND PUBLIC INSTITUTIONS

Dr. John S. Petterson

Dr. Karl Eschbach

Impact Assessment, Inc.

The MMS study entitled “Benefits and Burdens of OCS Activities on Selected Communities and

Public Institutions” is organized to achieve five objectives: 

1. analyze the benefits and burdens of OCS oil and gas activities at the county/parish and labor

market area (LMA) levels of analysis;

2. develop a baseline description of coastal counties/parishes;

3. analyze recent significant changes in the study areas associated with the deepwater program;

4. analyze seven coastal labor commuting areas; and

5. develop recommendations to mitigate potential negative effects of deepwater development.

The geographic scope of the project incorporates all Gulf of Mexico (GOM) coastal counties/

parishes stretching from Alabama to Mexican border, including all LMAs with coastal counties or

parishes (and all counties within them). The 40-month project was initiated in September 1998 and

funded at $640,000. The study team is composed of: (1) John S. Petterson, Ph.D., PI/Project

Manager; (2) Karl Eschbach, Ph.D., PI/Senior Scientist; (3) Jeanne Hurlburt, Ph.D., PI/Team

Leader; (4) Carson Mencken, Ph.D., PI/Demographer; and (5) Nicole Flynn, Ph.D., PI/Team Leader.

The study effort is designed to overcome a number of significant theoretical and empirical

impediments. Perhaps the most obvious is the problem posed by geography. The study area is

composed of over 70 counties and parishes, each with its own unique geographic advantages and

disadvantages with respect to OCS development. They include counties adjacent to the coast,

interior counties, counties with and without ports, rivers, and access to major transportation

corridors. Geographic advantages predetermined, in important ways, where and how offshore oil

development would be concentrated, and how those effects would be distributed. To gain an

understanding of the distribution of impacts, it is first necessary to understand how and why certain

areas became the center of activities while others were ignored. 

A second issue is the timing and duration of the impacts. Near shore, offshore, and deepwater oil

development have occurred at different points in the histories of these coastal counties and LMAs.

As OCS-related activities changed over time, in terms of scale, technology, and geographic location,

the distribution of impacts has also changed over time. Similarly, the sensitivity of each coastal

community and county to impacts associated with OCS activities has changed over time. Fishing

communities of the 1940s and 1950s have, over time, become predominantly OCS offshore oil
250

support communities. If we evaluated the impact of oil activities on Morgan City over the period

1950-1960, it would bear little resemblance to the same analysis over the period 1980-1990. Over

what period, and on what population, are we to evaluate the benefits and burdens of OCS? 

A third issue is that the natural and social histories (size, economic adaptation, occupational orientation, seasonality, etc.) of individual communities creates a differential sensitivity to the effects of

activities carried out in support of OCS development. Where a community of 10,000 residents might

not experience 100 new OCS-related employees as a significant impact on social relationships or

the local economy, a similar impact on a community of 400 residents could be profound. Similarly,

100 new OCS-related employees in an established oil-oriented community would be very different

in a community where no prior oil-related industry existed. These existing differences influence the

threshold at which a particular effect may be perceived as an adverse impact. 

A fourth issue is that the effects of changes brought about by OCS activities are associated with the

specific support function provided by the affected community or county. This results in an industryor function-based distribution of benefits and burdens. Some coastal areas are oriented,

predominantly, to the fabrication of offshore platforms, others to providing transportation to and

from the platforms, others to the fabrication of offshore oil supply vessels, others to the manufacture

of pumps, pipes, and other materials required to build and maintain the rigs, and still others to

accounting and administrative requirements. It is, in turn, the characteristics of these support

operations that determine how the benefits and burdens of the underlying OCS activities are

distributed among the counties and parishes of the GOM. This underscores the importance small

changes in the specific causal agent (e.g., scale, technology, work patterns, location) can have on

the resulting benefits and burdens of OCS activity. 

To address these, and many other, theoretical and empirical impediments, the “Benefits and Burdens

of OCS Activities on Selected Communities and Public Institutions” study has sought to structure

county and parish profiles, and to design replicable economic and demographic monitoring methods

(at State, LMA, and county/parish levels) in a manner that would allow future researchers to track

the distribution of the burdens and benefits of OCS activities.

At the present point in the study effort, we have just submitted our Third Interim Report for MMS

review. This report is designed to provide MMS with a complete LMA analysis of changes

occurring in the Lafayette LMA and its component parishes over the period 1920 to 1990. The

following ITM presentation highlights some of the preliminary findings of that analysis. 

Offshore oil and gas extraction activities’ impact on Gulf Coast counties and parishes occur in the

context of on-going changes in the economies and demographics of these counties. The period of

the emergence of offshore activities after 1947 is one of profound change in these communities. As

important as changes in the oil and gas industry are, changes that are occasioned by cycles in the

industry are not quantitatively the most important changes that occur, even in areas that we

ordinarily think of as being heavily affected by changes in the oil and gas industry. Specifically,

these areas were also affected by broader processes of economic and demographic restructuring

implicit in the transformation from an agricultural to an industrial and then to a service base.
251

A second, complementary, point is that there is not a single characteristic effect of oil and gas on

local communities across time and space. Discussion of oil industry effects have frequently

assimilated the oil and gas extraction industry to other extractive industries and emphasized the

supposedly special risks that extractive industries pose to communities that depend on them. The

wrenching dislocations associated with the frenetic roller coaster ride from 1973 to 1987 in industrydependent areas gave credence to this viewpoint, which achieved the status of an axiom as a

description of effects on oil-dependent metropolitan areas such as Houston and Lafayette. Yet it is

not clear what larger lesson is to be learned from the truly remarkable events of this period, because

it is not clear that the period typifies the industry. 

The run up in exploration, extraction and supporting activities between 1973 and 1982, followed by

the precipitous decline in the next five-year period dominates the analysis of time series detailing

economic changes in this period. The effects on demographic changes are somewhat less striking,

because they occur in the context of other structural changes that are equally dramatic in their

impacts. It is especially unclear that the events of this 15 year period strongly characterize what

happened in the industry either in the preceding 25 years, or the subsequent 13 years, or that they

provide much clue to what will happen in the future, given the dramatic restructuring in the industry.

SHIFT FROM AGRICULTURAL TO INDUSTRIAL/MINING BASE

In the southern Louisiana portion of the Benefits and Burden study area, economic restructuring

throughout the mid-twentieth century is dominated by the decline of agriculture as much as it is by

the rise of oil and gas and manufacturing activities. Between 1940 and 1990, census employment

in agriculture declines in study area parishes by 69,000 workers. These losses to the region’s economic base are offset by the addition of 34,000 jobs in the oil and gas mining sector, and 72,000 jobs

in manufacturing. Net changes in economic base in Louisiana are on the whole not sufficient to

retain the natural increase in the state’s population through this period. Louisiana as a whole is a net

out-migration state for each decade between 1950 to 1999, with the exception of the 1970s. This is

also true of specific subareas in southwest Louisiana where offshore extraction and service activities

were concentrated.

Economic restructuring redistributes economic and population growth within the study area. Among

parishes in the study area, 11 experience losses in agricultural employment that are greater than

offsetting increases in mining and manufacturing combined, and 16 see mining and industrial job

growth that exceed absolute losses of agricultural employment. The Lafayette labor market area in

particular is an area where relatively rapid growth in the oil and gas extraction and supporting

activities did not offset declines in agriculture. Within this labor market, only Lafayette and Iberia

parish see employment growth in mining and manufacturing that exceeds declines in agriculture.

Thus, in spite of the relatively rapid growth in the oil and gas activities in Lafayette Parish in the

1950s and 1960s, the labor market as a whole is a net out-migration area in these decades. Netmigration to the LMA is positive in the 1970s, but virtually all of the growth in concentrated in

Lafayette LMA itself, with balancing declines in the remainder of the LMA.
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HISTORICAL ABSENCE OF REALIZED DEVELOPMENT

ALTERNATIVES IN SOUTHERN LOUISIANA

One important perspective on the role of the emergence of offshore oil activities in Southwestern

Louisiana is that some parishes may have had few alternatives for the development of a base industry. Apparel manufacture was one industry that emerged alongside oil and gas activities, but on a

much smaller scale and with instabilities of its own. St. Landry Parish is a partial example of a parish in which declines in agriculture were not fully offset by the emergence of a manufacturing base,

though even St. Landry benefited to some extent from employment opportunities in oil and gas

extraction activities in neighboring parishes within the Lafayette labor market. In general, however,

the parish continued to experience relative economic decline and high out-migration characteristic

of rural parishes whose location was not conducive to full participation in oil and gas activities.

LMA AND METROPOLITAN SPATIAL PATTERNS

]The spatial re-organization of metropolitan and labor market areas is another factor that helps to

drive patterns of county/parish change in the study area. These are most dramatic in the case of the

New Orleans metropolitan area, where patterns of population redistribution led to rapid growth of

Orleans Parish, followed by growth in Jefferson Parish, and then followed by growth in St.

Tammany Parish and other outlying parishes. Because of these changes, the picture of change at the

labor market level can be quite different from the changes at the county/parish level.

Patterns are more subtle in other LMAs and metropolitan areas in the Benefits and Burdern study

area, because spatial reorganization of settlement and commuting occurs in less densely settled

space and is not so neatly captured by parish boundaries. One implication of the importance of

spatial reorganization is that patterns of economic and demographic change may appear quite

different if viewed at the county/parish or labor market level. 

MIGRATION TURN-AROUNDS

In Louisiana in particular, the industry boom and bust cycle of the 1970s/1980s was associated with

a pattern of migration turn around. Oil and gas involved labor markets that had been net outmigration areas in the decades before 1970 became in-migration areas in the 1970s, and then outmigration areas in the 1980s. However, to put the 1980s experience in perspective, the net out-flows

in this decade were generally at the same or a lower order of magnitude of out-flows in all previous

decades. Preliminary evidence from the 1990s based on Census Bureau estimates shows the end of

these patterns in the 1990s, with many southwest Louisiana labor markets and parishes experiencing

net migration near zero, or, for the first time in the 20th century, small positive migration balances.

Texas, by contrast to Louisiana, is a substantial net in-migration state in every decade since 1950.

Agricultural declines are proportionately less important than they are in Louisiana, and increases

in manufacturing employment far outstrip increases in mining employment as a source of growth.

Interpretation of net-migration pattern must be situated within the broader context of demographic

and economic change. The 1970s net in-migration to oil and gas involved parishes occurs in part in
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the context of reduced out-migration pressure in a formerly agriculture-dependent area, because employment declines in agriculture had slowed and now ceased to have much quantitative importance.

Similarly, migration patterns become increasingly “footloose” because of the aging of the population. This implies an increasing component of migration is driven not by the need to equilibrate

labor markets, but rather to take advantage of amenities such as warm weather or proximity to family. Such shifts become possible because of compositional shifts in the population from large cohorts

of new labor market entrants to a more mature population with resources that are not tied to

participation in spatially anchored labor markets. These shifts are one reason why the out-migration

that had occurred in the 1980s does not appear particularly dramatic compared to prior decades. 

A second corollary of changing population and economic structure is that to some extent the

provision of attractive amenities and quality services becomes a part of a region’s base industry. In

the 1990s, the service industry frequently becomes a leader in employment growth. Within the

service sector, health services is a leading growth industry.

SPATIAL DISTRIBUTION OF 1980S BOOM/BUST EFFECTS ON EARNINGS

Both Texas and Louisiana experienced sharp increases in per capita earnings relative to national

norms in the 1970s, followed by sharp declines in the 1980s. Within these states, per capita earnings

changes were differentially distributed by sub-region, with abrupt and offsetting changes against

state medians in counties and parishes that had a large percentage of employment in oil and gas mining and supporting activities. Oil-dependent counties and parishes have tended by and large to fare

relatively well in the 1990s, and on the whole were relatively advantaged in 1998 compared to 1970.

SHARP DIFFERENCES IN DECLINE AND RECOVERY

Different Gulf Coast areas have fared differently in the post-1987 “recovery” of the industry. Employment in the mining sector continued to decline in both Texas and Louisiana, with a net loss of

2,700 jobs in Louisiana in mining over this period, to 66,000, and a loss of 62,000 jobs in Texas, to

about 250,000. In Louisiana, the Lafayette labor market area posted relatively substantial increases

in oil and gas mining employment (5,100 jobs) . The Houston-Galveston labor market area fared

relatively well, with a net increase in 2,800 jobs in Harris County. The Shreveport and New Orleans

areas experienced relatively large declines in Louisiana, as did Dallas and Corpus Christi in Texas.
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DEEPWATER PROGRAM: OCS-RELATED INFRASTRUCTURE

INTHE GULF OF MEXICO

Dr. Jeffrey A. Reidenauer

Mr. Jim Burd

The Louis Berger Group, Inc.

East Orange, NJ

Mr. Steve Mobley

Dr. Ron Luke

Dr. David Dismukes

Research & Planning Consultants, Inc.

Austin, TX

Dr. Dmitry Mesyanzhinov

Econ One Reserach, Inc.

Houston, TX

Dr. Anatoly Hochstein

LSU Ports & Waterways Institute

Louisiana State University

ABSTRACT

We are approximately 14 months into a two-year study designed to collect pertinent data on existing

OCS infrastructure in the Gulf coastal states. The data will be compliant with the MMS Technical

Information System (TIMS) and integrated into MMS’s CORIS database. In addition, we are

preparing a Fact Book that describes the typical facility for each infrastructure type and provides

analysis of past and possible future trends in the construction, use, and retirement of OCS-related

infrastructure. This information will support MMS NEPA responsibilities and long-range planning

and development of OCS activities.

INTRODUCTION

Oil and gas exploration and production has occurred in portions of the Gulf rim states for over 100

years. Activity in coastal waters and on the Outer Continental Shelf (OCS) has occurred for the last

50 years. During this period, numerous OCS-related facilities have been built, such as refineries, gas

processing plants, port facilities, pipe-coating facilities, pipelines, waste management facilities, and

platform fabrication yards. Because of its statutory responsibilities, MMS must

1. produce lease sale EISs that depict existing, OCS-related infrastructure and its future growth

and trends; 
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2. make a large number of permitting decisions that consider existing, future, and past

infrastructure;

3. annually update Visual 1, a map of the Gulf Region depicting existing OCS-related

infrastructure; and,

4. guide and monitor long-range planning and development of OCS activities.

Coordinated information and improved trend analyses would help in more reliably projecting OCS

development needs, impacts, and opportunities.

Our two-year study began approximately 14 months ago. The objectives of the project are

• To collect pertinent data on existing OCS-related infrastructure in the coastal states of Texas,

Louisiana, Mississippi, Alabama, and Florida;

• To develop a database of historical information since 1950 on the infrastructure in the study

area and to identify any potential National Register-eligible properties;

• To make the collected data compliant with the MMS Technical Information Management

System (TIMS) and to assist in integrating the data into MMS’s Geographic Information

System (GIS);

• To describe the existing infrastructure;

• To analyze historical data to identify past trends and to identify possible future trends in the

construction, use and retirement of OCS-related infrastructure; and 

• To provide MMS staff with an analysis of current Texas, Louisiana, Mississippi, Alabama,

and Florida infrastructure to be used for Lease Sale 181.

DATA COLLECTION

We are collecting data for the following infrastructure types:

• Refineries

• Natural gas processing plants

• Petrochemical plants

• Pipelines

• Pipe coating yards
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• Platform fabrication yards

• Crew supply bases

• Ports

• Ship building yards

• Waste management facilities

• Repair and maintenance yards

Examples of data being collected for each facility:

• Name, location (lat/long), street address, contact information

• Date constructed/operation date

• Size/land area occupied

• Production/capacity/throughput data

• Transportation linkages

Our data collection sources are primarily federal and state agency reports and databases (e.g.,

USEPA, USACE, DOE, FERC), trade journals, industry directories, as well as information from

industry contacts. In addition, we received input from other MMS-funded studies such as the

“Benefits and Burdens of OCS Development” project.

Some of the datafields we initially developed for some of the facilities have been difficult to collect.

These include, for example, the percentage of petroleum-industry waste that comes from the OCS

and for petrochemical plants how much of their material originates from the OCS. We are in the

process of re-evaluating the use of these data fields.

We are in varying stages of data collection for each of the facility types. We have collected a

significant amount of information for waste management facilities, refineries, natural gas processing

facilities, platform fabrication yards, and are at intermediate stages of data collection for the

remaining facility types.

GIS OVERVIEW

As noted previously, the databases that are being developed will be compliant with the MMS

Technical Information Management System (TIMS) and will be integrated into the MMS’s CORIS

database. Below, we describe various components of the project’s GIS development.
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Project Website

A website was created to support the project and provide a means for database development. The

three major existing components for the website are general information, database development, and

internet mapping. The website address is http://gis.louisberger.com/mms_ocs

Database Development

Because the project team was composed of multiple subcontractors, we developed a web-based

approach to the initial database development. Together with MMS, we selected data fields for each

facility type. A handful of data fields are consistent throughout all facility types. Two such fields,

latitude and longitude, describe the spatial location of the facilities and permit database conversion

to Geographic Information Systems (GIS) layers.

Access database tables and internet forms were created to reflect the defined data fields. We used

Microsoft’s Internet Database Connector (IDC) technology to connect the internet forms to the

database using Microsoft’s Internet Information Server. Internet-based viewing and editing pages

have also been created and are in various forms of completion. These pages were created using Cold

Fusion Server technology. 

Once the Access database has been satisfactorily completed, the tables will first be converted to

ArcView shapefiles. The shapefiles will then be converted to Oracle tables using ArcInfo’s Spatial

Database Engine (ArcSDE). The Oracle tables will be delivered to MMS with appropriate metadata

(data about data).

Internet Mapping Site

The project includes the development of an internet mapping site. Internet mapping gives real-time

GIS capabilities to anyone with internet access. The current site uses Map Objects Internet Map

Server (MOIMS) to serve maps the internet. The OCS facilities on the site are based on the old

infrastructure database. Because of time-consuming programming required to access the new

database (which has different data fields), we are currently looking at developing a new IMS site

switching from MOIMS to ArcIMS, a new internet mapping server. ArcIMS provides much more

functionality than MOIMS and requires minimal programming.

FACT BOOK

In addition, to database development, we are preparing a Fact Book which describes OCS-related

infrastructure within the project area. It is organized into chapters by facility type and provides a

general description of the infrastructure, description of a typical facility, range of attributes, and

analysis of past trends. It will discuss future short- and long-term trends in construction, use and

retirement. In addition, it will include a discussion of the types and characteristics of infrastructure

that would likely develop in “frontier” areas such as western Florida or an Atlantic coast state should

exploration occur and should exploration lead to development and production.
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PRELIMINARY FINDINGS

Waste Management Facilities

We have identified 42 waste management facilities within the study area: 26 in Louisiana, 11 in

Texas, 3 in Mississippi, and 2 in Alabama. The facility types include; subsurface injection, salt

cavern disposal, land application, landfilling, separation and reclamation of drilling and completion

fluids, and separation and recycling of industrial wastes. 

We have collected information on the capacity of waste management facilities including throughput

capacity and life-of-site capacity. In addition, there are a number of categories of infrastructure

network for wastes returned to land—(1) transfer facilities at ports, (2) special-purpose oilfield

waste management facilities, (3) generic waste management facilities.

Differences in laws among states lead to differences in waste management methods as well as

industry preferences in siting waste facilities in certain states. For example,

• Texas allows and regulates salt dome disposal of waste, while no other state does.

• Louisiana, Alabama, and Mississippi allow the landfilling of used oil filters and oil-based

drilling muds, while Texas does not.

• Texas has regulations allowing oil-based drilling mud to be recycled, through

bioremediation, into road-building material.

Summary of findings to date:

• Capacity to manage waste generated by OCS drilling and production activities is adequate

for present and for hypothetical future that includes a doubling of current waste volumes.

• OCS activity does not generate a large part of the waste stream into generic waste

management facilities and is not expected to be a significant to the overall capacity of the

industry.

Platform Fabrication Yards

Production operations at fabrication yards include cutting and welding of steel components,

construction of living quarters and other structures, as well as assembling platform components.

Fixed platform fabrication can be subdivided into two major tasks: jacket fabrication and deck

fabrication.

Location of platform fabrication yards is tied to the availability of a navigable channel sufficiently

large to allow towing of bulky and long structures such as offshore drilling and production

platforms. Thus, platform fabrication yards are located either directly on the coast of the GOM or
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inland, along large navigable channels, such as the Intracoastal Waterway. Average bulkhead depth

for water access for fabrication yards in the Gulf is 15-20 feet. 

Due to both the size of the fabricated product and the need to store a large quantity of materials such

as metal pipes and beams, fabrication yards typically occupy large areas, ranging from a just few

to several hundred acres. Typical fabrication yard equipment includes lifts and cranes, various types

of welding equipment, rolling mills, and sandblasting machinery. Besides large open spaces required

for jacket assembly, fabrication yards also have covered warehouses and shops.

Platform fabrication yards vary in the size of the employed workforce, which ranges between less

than a hundred to several thousands. Due to the project-oriented type of work, temporary workers

account for a significant portion of the workforce.

Platform fabrication is not a mass production industry; every platform is custom built to meet the

requirements of a specific project. This feature has given rise to the great degree of specialization

in the platform fabrication. There are no two identical fabrication yards; most yards specialize in the

fabrication of particular type of platform or platform component. Examples of specialization include

construction of living quarters, provision of hook-up services, and fabrication of jackets and decks.

According to the published survey of fabrication yards in the Gulf, out of 50 yards 23 fabricated

jackets, 15 fabricated decks, 29 fabricated modules, 22 fabricated living quarters, and 20 fabricated

control buildings (Gary & Nutter 2000).

Despite a large number of platform fabrication facilities in the Gulf, only a few facilities can handle

large-scale fabrication. According to the survey of fabrication yards, nine yards have single piece

fabrication capacity over 100,000 tons and twelve have capacity to fabricate structures for water

depth over 1,000 feet. Only a few yards fabricate structures other that fixed platforms: only one yard

(J. Ray McDermott, Inc. in Amelia, Louisiana) fabricates compliant towers, and only two yards

(Gulf Island Fabrication Inc., in Houma, Louisiana and Friede Goldman Offshore in Pascagoula,

Mississippi) fabricate tension leg platforms.

Another important characteristic of the industry is a high degree of interdependency and cooperation

among the fabrication yards. Because offshore platforms, particularly the ones destined for the deep

water, are such complex engineering projects, most facilities do not have technical capabilities to

complete the entire projects “in-house,” without the subcontractors and the specialized yards.

Over the whole history of its existence, the ups and downs of the platform fabrication industry have

been closely tied to the fortunes of the oil and gas industry. Drilling and production activities are

sensitive to the changing prices for oil and gas. This sensitivity, in turn, is translated into “boom and

bust” cycles for the fabrication industry, when a period of no work follows a period of more

fabrication orders than a yard can complete. To shield themselves from the volatility inherent in the

oil and gas industry, platform fabrication yards in the U.S. GOM have started to implement various

diversification strategies. These diversification strategies, coupled with the new challenges brought

about by the deepwater oil and gas exploration and development, are significantly changing the

industry.
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To utilize the existing equipment and to keep the highly-skilled workforce in the periods with no

fabrication orders, many fabrication yards are expanding their operations into such areas as, for

example, maintenance and renovations of drilling rigs, fabrication of barges and other marine

vessels, dry-docking, and survey of equipment. These projects, although much smaller in scale and

scope than platform fabrication, nevertheless allow the yards to survive the recessions.

Another interesting avenue of diversification is pursuit of international work in platform fabrication.

The U.S. GOM fabrication yards have a double advantage of great experience in fabrication work

and good climatic conditions, allowing for the year-round operations.

With respect to deepwater development, the challenges for the fabrication industry stem from the

greater technical sophistication and the increased project complexity of the deepwater structures,

such as compliant towers and floating structures. These needs of the deepwater projects will likely

result in two important trends for the fabrication industry. First is the increasing concentration in the

industry, at least with respect to the deepwater projects: as technical and organizational challenges

continue to mount up, it is expected that not every fabrication yard will find adequate resources to

keep pace with the demands of the oil and gas industry. The second trend is the closer integration,

through alliances, amalgamations, or mergers, among the fabrication yards and engineering firms.

The platform fabrication industry is undergoing a period of restructuring, which is characterized by

transformation from privately to publicly held companies on the one hand, and by the consolidation

of the industry through mergers and acquisitions. While implications of these changes are yet to be

understood, it is clear that their impact will be significant.

Given the platform fabrication industry characteristics and trends therein, it is not likely that this

type of infrastructure would emerge in the frontier areas. There are two main arguments to support

that thesis. Firstly, the costs associated with towing a platform to its offshore location are

insignificant relative to the overall costs of fabrication. Therefore, physical proximity of an onshore

fabrication yard to an offshore location where a platform is to be installed cannot be considered a

determining factor in the development of new fabrication yards.

Secondly, the existing fabrication yards do not operate as “stand-alone” businesses; rather, they rely

heavily on a dense network of suppliers of products and services. Therefore, a successful operation

of a new platform fabrication yard in a geographic area where such a network is not developed

seems unrealistic. Further, since such a network has been historically evolving in Louisiana and

Texas for over fifty years, the existing fabrication yards possess a compelling force of economic

concentration to prevent the emergence of new fabrication yards in the frontier areas.

Ports

A U.S. Army Corps of Engineers database that identifies facilities in the GOM region used as

service base ports for the offshore industry shows an astounding number of private port facilities.

This database lists 210 in Louisiana alone. Although none are identified in the Port Fourchon area,

a survey of that area revealed another 27 facilities. Texas shows 84 landside support operations, and

there are others identified in Florida, Alabama, and Mississippi. Even though these are private
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facilities, they operate within the jurisdiction of a public port authority. And, to attract these

operations, the public port must offer certain infrastructural improvements to adequately

accommodate these operations.

All supplies must be transported from land-based facilities to marine vessels or helicopters to reach

offshore destinations. Thus, both water and air transportation are utilized. The intermodal nature of

the entire operation gives ports (which traditionally have water, rail and highway access) a natural

advantage as an ideal location for onshore activities and intermodal transfer points. Therefore, ports

will continue to be a vital factor in the total process and must incorporate the needs of the offshore

oil and gas industry into their planning and development efforts, particularly with regard to

determining their future investment needs. In this manner, both technical and economic determinants

must influence the dynamics of port development.

This extensive network of supply ports includes a wide variety of shore-side operations from

intermodal transfer to manufacturing. Their distinguishing features show great variation in size,

ownership, and functional characteristics. Basically, two types of ports provide this supply base.

Private ports operate as dedicated terminals to support the operation of an individual company. They

often integrate both fabrication and offshore transport into their activities. Public ports lease space

to individual business ventures and derive benefit through leases, fees charged, and jobs created.

These benefits spread throughout the entire area and are viewed as economic development impacts.

Thus, the public ports play a dual role by functioning as offshore supply points and as industrial or

economic development districts. An efficient network of ports will both lower costs associated with

oil and gas production and significantly boost the well-being of citizens of the adjacent

communities.

We have collected data on the physical/operational features of several of the ports within the project

area including:

• Port Fourchon (see example below)

• Port of Morgan City

• Port of West St. Mary

• Port of Iberia

• Port of New Orleans

• Port of Panama City

• Port of Mobile

• Port of Houston

An example of the data we have collected for Port Fourchon is shown in Table 1F.5.
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Table 1F.5. Sample of data collected for Port Fourchon.

Facility Type Physical/Operational Parameters

Location On the Gulf of Mexico, at the mouth of Bayou Lafourche-about 60 miles

south of New Orleans

Channel Access Channel entrance: 300' wide by 24' deep; Interior Channel 300' wide by

23' deep; E-slip 400' wide by 23' deep; Turning Basin 800' wide by 20'

deep

Land Access Highway: LA 3090 2 miles to LA 1, 40 miles to U.S. 90

Docking No public dock suitable for handling general cargo, numerous privately

leased facilities

Intermodal transfer

(on dock)

A large number of privately leased docks with crane service and

loading/unloading equipment

Warehouse Storage A large number of privately leased warehouses. One 8,000 sq. ft.

refrigerated warehouse

Yard Storage Numerous storage yards on individual leases. Improved and unimproved

property available

Inland Transport Connection to the Intracoastal Waterway via Bayou Lafourche, Houma

Navigation Canal, and Barataria Waterway

Cargo Throughput

(per hour)

Cargo throughput varies among docks. Compatibility of heavy lifts up to

200 tons. Numerous 150-ton options

Planned Expansions/Dates

The Northern Expansion Project is a 700-acre development consisting of

600' wide slips and over one mile of waterfront. Phase I of the expansion

is to be complete in 2001.

Constraints/Impediments

Two-lane highway access and lack of rail access are major impediments.

Location on the Gulf of Mexico is an advantage but has limited water

access to major metropolitan centers.

Potential Vessel Service

Ocean/River vessel service, Shortsea Coastal service, Container Port

services.
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ONSHORE EFFECTS OF OFFSHORE EMPLOYMENT

Mr. Mark Shrimpton

Dr. Keith Storey

Community Resource Services Ltd.

St. John’s, Newfoundland, Canada

INTRODUCTION

Most offshore oil workers spend extended periods, one or more weeks, at their workplace— usually

a production platform or a mobile drilling rig. They then leave the workplace and live at home with

their families, if any, for a non-work period that is also commonly one or more weeks. The offshore

accommodations, recreational facilities and food are provided by their employer, who also provides

transportation between the workplace and some onshore “pick-up point,” commonly a heliport.

This work system is variously called “commute,” “fly-in,” “fly-in/fly-out” or “long-distance

commute” employment; the first of these terms is used in the rest of this presentation. It was

originally developed to meet the needs of the offshore oil industry because daily commuting was

not feasible and no “local” workforce or permanent, full-time accommodations were available. It

is now also used by the mining industry and by other land-based and marine activities in remote

and/or hazardous environments, in situations where the local labor force cannot meet industry needs

and where the work schedule makes a daily commute impractical.

The oil industry also uses this system for some onshore operations. For example, about 1,000

production workers commute to gas fields in the Cooper Basin in Southeastern Australia. Commute

systems have been used for major oil industry construction projects. In one example, most of the

labor force building the Hibernia production platform at a green-field coastal site in Newfoundland,

Canada, alternated between living in a well-equipped 3,500-person construction camp and in their

home communities. Commute employment is also used to provide labor to remote mines, and in a

small number of specialist settings.

This presentation provides a summary of some of the findings of a study of commute employment

that is being undertaken under contract to the Minerals Management Service (MMS). This research

was designed to complement other MMS studies by providing detailed information on the effects

of offshore employment and the options for managing them. It saw the initial preparation of an

annotated bibliography on commute employment, its effects and their management. This material

was used in the developing a discussion paper, which draws on approximately 80 papers and reports

about offshore oil employment in, primarily, the United States, Atlantic Canada, the United

Kingdom and Norway. This study will be subject to rigorous peer review, including an international

workshop, with the final report, “The Effects Of Offshore Employment In The Petroleum Industry:

A Cross-National Perspective,” being available in the second quarter of 2001.
264

OFFSHORE EMPLOYMENT ISSUES

The commute system used at most offshore operations differs from traditional work systems

principally because of the distinctive pattern of presence in, and absences from, the place-of-work

and place-of-residence. Other characteristics, such as the extended workday and shift arrangements,

while important, are not unique to commute employment. Other work arrangements may have some,

but not all, of these characteristics. As such, the commute system gives rise to some issues that are

unique and others that are shared with other systems.

Offshore employment should not be seen as inherently problematic—like all other work systems,

it offers both advantages and disadvantages for workers, as well as for others with responsibility for

health and safety, training and other employment-related concerns. It also has implications, which

can again be positive or negative, for employees’ families and the communities and regions in which

they live. Some of the more important of these issues are discussed in two interrelated categories:

human resources and family issues and community and regional issues. The focus throughout is the

social effects of commuting, with the economic effects (for instance, in terms of the purchasing

patterns of commute operations) and management concerns (for example, productivity) only discussed in connection with the effects on workers, families, and the communities in which they live.

It is important to note that there are some important lacunae and biases in the literature on which the

study is based. For example, past research has focused on large operations and companies, fixed

work schedules and married male workers. The data used are often limited and commonly

qualitative or anecdotal. Where quantitative research has been undertaken, different variables often

confound each other and make it impossible to separate cause and effect. Furthermore, some

important studies are old and particular to specific operations and temporal and geographic contexts.

It is not clear to what degree their findings and conclusions are still relevant or can be generalized

to other settings. This problem may be exacerbated by the rapid pace of change in both the oil

industry and the attitudes and expectations of workers and their spouses.

Offshore work has implications for a wide variety of interrelated work and family life issues. These

include the effects on health and safety; the employment of women, minorities, and older workers;

family life; and retention and productivity. It also has a number of related effects on the

communities and regions where the workers live and employers do business. These include the

effects on: residential patterns, expenditures, non-commute employment, local investment,

community life, and social and recreational services. These are all discussed in detail in the report.

RESPONSES

This, however, focuses on responses to these issues. It is clear that employer initiatives in such areas

as work schedules, accommodations, transportation, communications, hiring, orientation,

counseling, and family policies and services can optimize the effects of the offshore employment

in respect to all of the above issues. Regulatory authorities, trade unions, local government agencies,

community groups and others, including the workers and families themselves, may also have an

important role to play. Such optimization can have benefits for employers, workers, their families,
265

their communities and, more generally, local society. A short discussion of these responses is

provided below, based on more detailed review that will be available in the research report.

Work Schedules

Offshore work schedules commonly bring together a roster arrangement, whereby employees work

one or more weeks and then have a similar period at home, with shift work likely involving the use

of extended work days. Where regular rosters are used, they vary for different types of workers,

different employers, and in different parts of the world and change over time. The stay offshore is

commonly a multiple of seven days, with 7, 14, and 21 being most common. However, increasing

number services, contract, and other personnel have very irregular schedules, or are “on-call,”

depending on operational requirements.

Twelve-hour shifts are the norm, although some specialized employees may be on other schedules

or on-call 24 hours a day. Some positions normally only require work during a day shift, but most

involve day and night shifts; in the case of fourteen-day and longer work patterns, there is

commonly a mid-rotation split shift when employees change from night to day shifts, or vice versa.

This discussion can only provide a short summary of the large literature on offshore work schedules

and their effects. The report will include a much longer discussion of this topic, much of it drawing

on Dr. Kathy Parkes’ review of the literature on the effects on stress, health, and safety on North Sea

offshore petroleum installations (Parkes 1998). This review includes an examination of the evidence

of the effects of long work hours in conventional work settings. Parkes concludes that the long hours

worked by most employees raise serious questions about cumulative fatigue, reduced performance,

and impaired well-being among offshore management personnel.

Parkes also discusses the health effects of shift work and notes that onshore research indicates that

prolonged shift work over a period of years appears to have cumulative adverse effects on sleep

patterns and health, not accounted for solely by increasing age. However, the pattern at commute

operations can be more complicated, with workers involved in round-the-clock activities (e.g

production, maintenance, and drilling) being exposed not only to extended shifts and demanding

work, but also to the need for adjustment to day/night shift changes. The scheduling of shifts poses

particular difficulties offshore as rotation patterns are constrained by the helicopter schedules and

limited availability of accommodations. 

While the information on work schedules is often unclear or inconsistent, there is evidence that midrotation shift changes have a variety of negative effects. From a health and safety viewpoint, a strong

argument can be made for implementing “fixed-shift” rotation patterns; however, offshore personnel

strongly prefer the 7 nights/7 days pattern, which allows them to go on leave adjusted to a normal

circadian cycle at the end of each tour.

Accommodations

Parkes also finds evidence that location, size, and type of rigs and platforms are associated with

psychosocial outcomes among offshore personnel. However, she concludes that, while these
266

findings can be attributed in part to the fact that newer platforms have improved design standards,

recreational facilities, accommodations, emergency alarm systems, and escape equipment (the last

two of which may reduce anxiety), they do not allow causal interpretation because new installations

can attract highly motivated and adaptable personnel. This latter fact may contribute to the favorable

responses by employees on these newer platforms.

Parkes also notes that offshore workers are exposed to physical stressors such as noise, vibration,

poor lighting and/or ventilation, confined living accommodation and workspace, and adverse

weather conditions. Ratings of noise and other environmental stressors correlate with measures of

psychological well-being and that the perceived workload may mediate these relationships.

However, the extent of exposure to adverse physical conditions offshore differs across occupational

groups, with construction and drilling crew reporting the highest exposure levels. 

The physical and social environment of the accommodations seems to make an important

contribution to the quality of life and stress-levels of workers. Two factors appeared to be

particularly important: privacy and recreational facilities. In the former case, privacy is seen as a key

element in coping with the extended work schedule and isolated setting, with shared accommodation

placing a strain on workers in this regard. Offshore cabins are normally small, and sharing is not

uncommon; on older rigs and platforms, one may see four-berth cabins and, in times of peak labor

requirements, “hot-bunking.”

The increased privacy provided by having one’s own room can, however, reduce off-duty social

interaction between workers. This isolation can be exacerbated when employees are able to have

televisions in their cabins. One Norwegian Offshore Installation Manager countered this, and

improved the social atmosphere on the Statfjord A platform, by installing a bar which served only

non-alcoholic drinks (Flin 1996). However, space constraints mean that the provision of active and

passive facilities offshore is usually limited, especially on rigs and older platforms.

While the design of accommodations, together with policies respecting room allocations and the like

are important, there is evidence that the overall social environment is of particular significance when

it comes to worker stress. This encompasses aspects of all of the above but is also an independent

reflection of the management approach to the accommodations and related arrangements. This

includes the need, especially given longer rosters, for the workers to create a “home” offshore.

Separating work and non-work life at the workplace, in so far as it is possible, is also important. A

clear separation of work from accommodations areas, and interior decoration that differentiates the

latter from the functionality of the former, encourages this separation. However, the social

environment is also a function of the overall work culture and the full range of management

approaches and personnel policies.

Transportation

Transportation arrangements have two major effects on employees and their families. First, safety

concerns related to helicopter travel are a major cause of employee stress, with implications for both

the worker and his or her family. Second, transportation schedules can be inconvenient from a

family perspective, and disruptions can delay the worker’s arrival home and departure to the
267

workplace, creating stress for all family members. In both cases, there is a range of measures that

can help optimize the effects on workers and their families.

Communications

Difficulties communicating between the workplace and home can cause offshore workers and their

families considerable stress. Policies with respect to vary by company, location, and type of activity.

However, there have been major improvements in communications in the last few years. For

example, North Sea production workers commonly have unlimited use of links with their homes,

using e-mail or a telephone located in their cabin. The increased capabilities and reduced cost of

mobile phones provide another option for some workers, although mobile phone use is limited in

some settings by fire safety concerns related to battery-powered devices. Workers and families value

such high-quality, low-cost, and confidential links whether or not they are used with any frequency;

their availability reduces tensions because family members know the links can be used if

circumstances warrant.

Hiring and Orientation

There is obvious merit in screening out job applicants who would find offshore work highly

problematic and providing an effective orientation program to newly-hired employees. Some

companies think these factors are important in selecting employees. For example, some prefer to

hire people with previous experience of unconventional work schedules or young unmarried or

recently married workers. However, overall, Slaven (1996) concludes that “it is difficult to screen

personnel for the possession of qualities which would suggest a propensity for adaptability to (the

offshore work pattern and environment).”

Researchers have noted the advantages of having women in the commute workforce. For Heen

(1988): “the positive effect on the social environment of having women on platforms is

considerable... (it) ‘normalizes’ the atmosphere and this also lessens the differences between

onshore and offshore life, which in turn makes the transitions between these two periods easier,

lessening the degree of psychological change and making commuting somewhat less of a burden... .

Women have also (through their influence) had an impact on the material quality of the work

environment.” Many oil companies now seek to facilitate the hiring and retention of women, both

onshore and offshore. 

Counseling

Offshore work challenges employees and their families in various ways and leads some to

experience psychosocial problems. Most deal with these problems themselves or use informal

coping strategies. However, North Sea research indicates that offshore workers derive only limited

social support from other workers, and while their spouses and friends may also serve as onshore

confidantes, the spatial dispersal of workers may limit this option.

Further assistance may be provided by offshore and industrial chaplains. However, a more

comprehensive approach, used by increasing numbers of employers, is provided by employee
268

assistance programs (EAPs). These were first developed in North America to provide employees and

their families confidential access to a range of emotional, marital, financial and alcohol and drug

related counseling services. Most UK sector operators now have such programs. Chevron and

Coneco not only use their EAPs for routine counseling, but also for critical incident debriefing

following an emergency. Such programs can also have the incidental merit of providing a measure

of fluctuations in the psychological well-being of the labor force. 

Family Policies and Services

There is clear evidence that home-life problems of many commute workers are in reality work problems and that domestic problems have reciprocal effects in the workplace. The worker brings home

work-related concerns and stress, and the commute system generates its own tensions in domestic

and personal life. These tensions are in turn brought back to the workplace, where they may affect

productivity, safety, retention, and other management concerns. Furthermore, married commute

workers see effects on the family life as the primary determinant of satisfaction with the system.

The research on commute employment indicates the types of responses and interventions that may

be appropriate in addressing the challenges for family life. Drawing on many of the responses and

interventions already described above, they may broadly be placed in four categories:

• Those that improve the compatibility of the work organization and family life. This category

includes such things as improved telecommunication links and transportation arrangements

between work and home, and optimized the rotation pattern from a family life perspective.

• Those that improve the compatibility of the work culture and home life. This category

involves making the workplace and accommodations more familial and less alienating,

thereby decreasing the contrast between the two, and includes changes to both the physical

and social environment.

• Those that improve self-selection during hiring and help new hires and their families get

used to a new work pattern.

• Those that provide assistance, perhaps through an EAP, other counseling program, or

support group, to employees and family members requiring them. This category includes

self-help groups, such as the UK Offshore Women’s Link Support.

McKee, Mauthner and McLean (2000) report a heightened industry awareness of family issues in

the UK, reflected in initiatives in such areas as day care, workplace nurseries, enhanced maternity

and parental leaves, and concentrated work weeks. Industry and corporate image concerns, new EU

and UK legislation, increased numbers of female managers, and examples from international parent

companies are seen as drivers of this interest.
269

CONCLUSION

As was noted above, offshore employment should not be seen as inherently problematic. It offers

both advantages and disadvantages for workers, their families and their communities, as well as for

others with responsibility for health, safety, training, and other employment-related concerns. The

challenge is to recognize these effects and implement policies and practices that effect them. From

an industry perspective, there is evidence that the benefits—in terms of such things as employee

retention, accident rates and productivity—can be considerable and the costs modest.

The literature reviewed for this project contains little systematic information about response initiatives and their success. As a result, it was not possible to identify or allocate responsibilities about

best practices. Instead, the research report will conclude with a preliminary assessment of research

requirements needed to elucidate fully and identify related best practices.

REFERENCES

Flin, R. 1996. Occupational Stress: Identification and Maintenance. In Flin, R. and G. Slaven, eds.

Managing the Offshore Installation Workforce. Tulsa, OK: PennWell Books.

Heen, H.1988. Making Out in a Man’s World: Norwegian Women Workers Offshore. In Lewis, J.,

M. Porter and M. Shrimpton, eds. Women, Work and Family in the British, Canadian and

Norwegian Offshore Oilfields. London: Macmillan.

McKee, L., N. Mauthner and C. Maclean. 2000. “Family Friendly” Policies and Practices in the Oil

and Gas Industry: Employers’ Perspectives. Work, Employment and Society, 14: 3.

Parkes, K.R. 1998. Psychosocial Aspects of Stress, Health and Safety on North Sea Installations.

Scandinavian Journal of Work, Environment and Health, 24: 5, 321-333.

Slaven, G. 1996. Selection and Training of the Offshore Workforce. In Flin, R. and G. Slaven, eds.

Managing the Offshore Installation Workforce. Tulsa, OK: PennWell Books.
270

PLACE-BASED COMMUNITY RESEARCH AND RESOURCE MANAGEMENT

Dr. Domenico Parisi

Dr. Duane A. Gill

Unit for Community and Environmental Studies

Social Science Research Center

Mississippi State University

Sustainable integrated resource management implies a comparative place-based community

approach. Unfortunately, at the present time, there is not a well-defined methodology to identify

place-based communities and link data to them. To overcome this shortcoming, a GIS-based

methodology has been developed to identify, measure, and compare place-based communities.

Compared to traditional county-based research, this methodology provides the following

advantages: (1) it captures the geographical area so that people can be placed in more clearly defined

communities; (2) it allows for a better visualization of the distribution of resources within a

community area; (3) it helps to identify processes of interaction and social infrastructures as they

relate to place-based actions to address local issues; (4) it allows for an analysis of interjurisdictional relationships across administrative boundaries; (5) it captures the area where macrosocial and political processes are more likely to impact peoples’ lives; and, (6) it allows for the

generation of place-based statistics so that community areas can be compared between and within

the rural and urban landscapes. These contributions can open new avenues of research for

community comparative studies in sustainable integrated resource management.

Empirically, the county is generally used to proxy the concept of community. Some, however, have

indicated that the county is not usually coterminous with the geographic dimension of a community

(Beckley 1998; Farmer et al. 1992; Kemmis 1990; Moon and Farmer 2000; Parisi et al. 2000a;

Wilkinson 2000). Consequently, the county might be an inappropriate unit of analysis for addressing

community-based issues. In addition, county-level data are not generally collected to produce

information on community agency (Krannich and Humphrey 1986). Because of the conceptual and

empirical limitations related to the use of counties as a unit of analysis, Parisi et al. (2000a; 2000b;

2000c) developed a methodology to define geographic units that reflect the concept of community

with flexibility to address specific community issues (e.g., welfare reform, economic development,

and natural resource management). To date, this methodology has been applied primarily to issues

of welfare reform and environmental justice related to industrial hog farm location (Taquino et al.

Forthcoming) although applications to other issues are readily apparent.

Conceptually, community boundaries should be established by virtue of social and economic

relationships among people living in geographic proximity to one another, as well as by the

relationships between people and the physical environment where their daily needs can be met

(Parisi et al. 2000a; 2000b; 2000c). In the case of the welfare-reform act, the primary focus is to

transfer responsibility to the clients and the community. Here, community boundaries should be

delineated to identify economic and social resources relevant to move clients off public assistance

and toward achieving economic independence. 
271

C B A

Central Place Smaller Place

Locality Area

Figure 1F.1. Two distances with the same point of origin that people might cover on a daily

basis. The first would be a short distance from A to B to meet daily needs, and the

second a long distance from A to C to gain employment.

In general, community sociologists have identified boundaries within which social and political

action takes place by aggregating a five-to ten-mile radius of outlying areas of diffuse settlement

around a compact place (Bohon and Humphrey 2000; Galpin 1915; Goode 1985; Hawley 1950;

Kassab 1992; Krannich and Humphrey 1983; Lloyd and Wilkinson 1985; Parisi 1998; Wilkinson

1979; Wilkinson 2000). Areas delineated following this rationale are the locus of social and political

action, depicting where people can meet most of their daily needs. However, these same areas may

not provide employment opportunities, particularly in rural areas (Beaulieu et al. 2000; Wilkinson

2000). People in rural areas are often required to travel to larger places to find employment (Young

1999). This suggests that there are two distances with the same point of origin that people might

cover on a daily basis. The first would be a short distance from A to B to meet daily needs, and the

second a long distance from A to C to gain employment (see Figure 1F.1). As illustrated in Figure

1F.1, people can travel the short distance within 360 degrees because A-B may fall at any point

within the small area, and the long distance (A-C) only in the direction of the larger place. It follows

that for a community to be inclusive in terms of meeting the requirements of welfare reform, its area

should be identified based on the A-C distance, as shown in the shadowed area of Figure 1F.1.

Distance per se has little socioeconomic value unless it is expressed in units of time spent to reach

a final destination (Stephan 1979). It follows, then, that to identify a meaningful community, both

short and long distances need to be transformed into an average daily travel time. Given that the

estimated average velocity on an existing road system can be approximated to be 45 miles per hour,

five and ten miles in distance translates into 6.7 and 13.3 minutes travel time, respectively. In
272

1

 In general, the Central Place Theory has been criticized for not being a valuable means of analysis for regional

development in terms of consumption of services and goods. However, it is still valid when it is used in terms of job

opportunities. According to Young (1983, 1999), and Young and Kmaid (1999), larger communities offer greater job

opportunities than smaller communities by creating an hierarchical structural relationship across places.

contrast, if the distance to seek employment outside the ten-minute travel area is considered, then

one can use the average travel time to work as reported for each state by the U.S. Census Bureau.

In Mississippi, the average travel time to work across rural and urban counties is approximately 20

minutes, with a standard deviation of approximately four minutes. Here, counties whose percentage

of people classified as rural was above the overall average for the state were classified as rural.

Within rural counties, the average travel time to work is approximately 22 minutes, while for

counties classified as urban, it is 18 minutes. Consequently, 20 minutes of travel time to a work

destination allows for an identification of a geographic area that is tailored to issues raised by

present welfare policy requirements.

In seeking the delineation of geographic boundaries for communities based on ten- and 20- minute

travel times, one should be aware of the issue of potential overlapping boundaries. One way to

address this problem is to follow the logic of central place theory1

. This logic maintains that larger

places provide job opportunities that are not available in surrounding smaller places. Thus, the

largest place within a state is assumed to attract residents from its surrounding places within a given

travel distance, making up the first community. By keeping the travel distance to work constant,

smaller places included in the first community are excluded when identifying other communities,

which are based on the next largest central place not included in the previous community. 

Translating the two distances into travel times and establishing an approach to avoid overlapping

community boundaries provides a procedure to identify communities’ boundaries using a

Geographic Information System (GIS)-based methodology. The methodology to identify our

communities used the GIS program ArcView. Using GIS technology, place-based communities were

identified in a multistage process based on road travel time. Ten-minute travel time was used to

identify areas where major social and political actions are more likely to take place. The road

network was composed of roads, highways, and interstates with an average speed set at 30, 45, and

60 miles per hour, respectively using 1998 Mississippi street files. 

Incorporated Census Defined Places (CDPs) were used as the starting points for the aggregation.

These areas are recognized political units with both social and governmental infrastructures central

to addressing any place-based policy. Incorporated CDPs have the means for developing

interjurisdictional relationships among themselves and with the state. Mississippi has 324 CDPs.

Following the logic of the central place theory, the CDPs were first ranked by population size.

Aggregation started with the highest populated CDP (in this case, Jackson). Using the latitude and

longitude coordinates of the geographic center of the CDP (provided by the U.S. Census

Department) as the center of the road network, the aggregation included the census block groups

whose centers fell within the ten-minute travel time network of the CDP center, creating the first

ten-minute place (see Figure 1F.2). This process continued until no CDPs remained. Of the original

324 CDPs, 296 were identified as incorporated, ten-minute places (see Figure 1F.3). These compact

areas can be viewed as geographic places that can make up the larger community based on a given

travel distance (A-C).
273

Figure 1F.2. Using the latitude and longitude coordinates of the geographic center of the CDP

(provided by the U.S. Census Department) as the center of the road network, the

aggregation included the census block groups whose centers fell within the tenminute travel time network of the CDP center, creating the first ten-minute place.

After identifying place-based community boundaries, a method for extrapolating decennial census

data was developed. Community-level census data were generated in three steps. First, a database

of census data at the block group level was created using Pro/Filer for Windows, a program

developed by Wessex that allows automated extraction of census data. The second step merged the

census block group database created in step one to the block groups that make up locality areas. This

was based on the block group identification code as a common field to link the data. Third, block

groups were aggregated to the locality level by using a unique identifier developed for each locality.

As a result, demographic and economic data can be measured and compared across places.

Identification of place-based communities can provide a base from which to collect information on

locally-oriented collective action (Parisi et al. 2000a). This is generally accomplished through the

use of community key informants; individuals familiar with local activities through their

experiences. Key informants provide information about the place in which they live, about others
274

Unclassified

Place

Urban

Rural

Figure 1F.3. Of the original 324 CDPs, 296 were identified as incorporated, ten-minute places.
275

in that place, and about themselves. Thus, they should be selected based on their knowledge with

the issue at hand, be it welfare reform, economic development, or natural resource management. Key

informants are generally privy to important events and are able to provide the researcher with

information about them. By using several key informants from each community, the researcher can

compare and pool this information and create indicators that proxy locally-oriented collective action.

Further, by collecting key informant information from all communities in the study area,

comparisons of locally-oriented collective actions can be made across communities.

Using GIS to identify localities has other advantages as well. Data with information, such as

addresses or other indicators that identify specific geographic locations, can be mapped and

associated with these localities. Community boundaries can also be overlapped with other

geographical boundaries such as watersheds, soil conservation districts, and other land use patterns.

A primary advantage, however, is that researchers no longer have to rely the county/parish as a

proxy for community. The place-based approach to community provides an opportunity to develop

data collection strategies that will give more precise information to decision makers.

REFERENCES

Beaulieu, Lionel J., Frank M. Howell, Domenico Parisi, and Lynn Reinschmeidt. 2000. Access to

Opportunities: Welfare to Work Challenges in a Rural Mississippi County. Mississippi State

University: Southern Rural Development Center.

Beckley, Thomas. 1998. The nestedness of forest dependence: a conceptual framework and

empirical exploration. Society and Natural Resources 11:101-120.

Bohon, Stephanie A. and Craig R. Humphrey. 2000. Courting LULUs: Characteristics of Suitor and

Objector Communities. Rural Sociology 65(3):376-395.

Farmer, Frank L., A.E. Luloff, T.W. Ilvento, and B.L. Dixon. 1992. Rural Community studies and

secondary data: aggregation revisited. Journal of the Community Development Society

23:57-70.

Galpin, C.J. 1915. The social anatomy of an agricultural village. Agricultural experiment station of

the University of Wisconsin. Madison, WI: Research Bulletin 34.

Goode, F.M. 1985. The use of microdata to measure employment in small communities. Journal of

Economic and Social Measurement 13:187-89.

Hawley, Amos. 1950. Human Ecology: A Theory of Community Structure. New York, NY: The

Ronald Press Company.

Kassab, C. 1992. Income and Inequality: The Role of the Service Sector in the Changing

Distribution of Income. Westport, CT: Greenwood.
276

Kemmis, Daniel. 1990.Community and the Politics of Place. Normon, OK: University of Oklahoma

Press.

Krannich, R.S. and C.R. Humphrey. 1983. Local Mobilization and community growth: toward an

assessment of the “growth machine” hypothesis. Rural Sociology 48:60-81.

Krannich, R.S. and C.R. Humphrey. 1986. Using key informant data in comparative community

research. Sociological Methods and Research 14:473-493.

Loyd, Robert C. and Kenneth P. Wilkinson. 1985. Community factors in rural manufacturing

development. Rural Sociology 50:27-37.

Moon, Zula and Frank L. Farmer. 2000. Population density surface: a new approach to an old

problem. Society and Natural Resources.

Parisi, Domenico. 1998. Community Action and the Development of Community From a Time

Perspective. Ph.D. Dissertation. 

Parisi, Domenico, Duane A. Gill, and Michael Taquino. 2000a. Building community step by step

to shoulder more responsibility: a procedure to identify and measure community. Social Science

Research Center, Mississippi State University.

Parisi, Domenico, Duane A. Gill, and Michael Taquino. 2000b. Identifying and Measuring Rural

Community: A Necessary Step in Promoting Rural Development in Mississippi and the Nation

at Large. Social Science Research Center, Mississippi State University forthcoming.

Parisi, Domenico, Steven Michael Grice, Louis H. Bluhm, Michael Taquino, Duane A. Gill, Terri

Canaday, and Jarryl B. Ritchie. Under review. The political paradigmatic shift toward local responsibility: the quest for identifying, measuring, and comparing communities. Rural Sociology.

Stephan, Edward G. 1979. Derivation of some social-demographic regularities from the theory of

time-minimization. Social Forces 57:812-823.

Taquino, Michael, Domenico Parisi, and Duane A. Gill. In press. Units of analysis and the

environmental justice hypothesis: the case of industrial hog farms. Social Science Quarterly.

Wilkinson, Kenneth P. 1979. Social well-being and community. Journal of the Community

Development Society 10:5-16.

Wilkinson, Kenneth P. 2000. The Community in Rural America. Middleton, WI: Social Ecology

Press. 

Young, Frank. 1983. Interdisciplinary Theories of Rural Development. London: JAI Press.

Young, Frank. 1999. Small Towns in Multilevel Society. Lanham: University Press of America.
277

Young, Frank and Gonzalo Kmaid. 1999. The Communities of New York State. In New York State

in the 21st Century. Thomas A. Hirschl and Tim B. Heaton, eds. Westport, CT: Praeger.
279

SESSION 2D

STABILITY AND CHANGE IN GULF OF MEXICO CHEMOSYNTHETIC

COMMUNITIES: “CHEMO II”

Co-Chairs: Dr. Robert Avent, Minerals Management Service

Dr. Mary Boatman, Minerals Management Service

Date: December 6, 2000

Presentation Author/Affiliation

Geological and Geophysical Characterization

of Carbonate Mounds on the MississippiAlabama Outer Continental Shelf

 Dr. William W. Sager

Department of Oceanography

Texas A&M University

Dr. William W. Schroeder

Marine Science Program

University of Alabama

Long Lives and Deep Roots: Tubeworms in

Gulf of Mexico Chemosynthetic

Communities

Dr. C. R. Fisher

Dr. D. C. Bergquist

Dr. J. K. Freytag

Dr. R. T. Ward

Dr. J. P. Andras

Dr. B. Begly

Dr. S. Schaeffer

Dr. K. Nelson

Ms. E. McMullin

Ms. S. Carney

S. MacAvoy

Dr. S. Macko

Mr. R. Carey

Dr. I. MacDonald

Dr. M. Van Horn

Department of Biology

Pennsylvania State University

(continued on next page)
280

Presentation Author/Affiliation

Inorganic Biogeochemistry of Cold Seep

Sediments

Dr. John Morse

Dr. Rolf Arvidson

Dr. Samantha Joye

Ms. Susie Escoricia

Dr. Craig Cooper

Mr. Jeffrey Morin

Dr. Luis Cifuentes

Dr. Ethan Grossman

Dr. Steve Macko

Texas A&M University

Program Synthesis and Recommendations for

Future Work

Dr. Ian R. MacDonald

Geochemical and Environmental

Research Group

Texas A&M University
281

GEOLOGICAL AND GEOPHYSICAL CHARACTERIZATION OF CARBONATE

MOUNDS ON THE MISSISSIPPI-ALABAMA OUTER CONTINENTAL SHELF

Dr. William W. Sager

Department of Oceanography

Texas A&M University

Dr. William W. Schroeder

Marine Science Program

University of Alabama

OVERVIEW AND RATIONALE

This study was built on previous MMS-funded reconnaissance mapping of carbonate “pinnacle”

mounds on the Mississippi-Alabama outer continental shelf. Prior studies showed that hundreds of

carbonate mounds exist on the outer shelf in this region, with diameters ranging from a few meters

to nearly a kilometer (Ludwick and Walton 1957; Schroeder et al. 1988; 1989; Brooks et al. 1991;

Continental Shelf Associates 1992; Sager et al. 1992). Additionally, sediments in the region were

deposited by late Pleistocene fluvial deltas (Sager et al. 1999) and consist mainly of reworked relic

sands and biogenic debris. In this study we focused on five “megasites,” several kilometers on a

side, and mapped the carbonate mounds and upper sedimentary layers in detail using high-resolution

acoustic mapping methods (side-scan sonar and chirp sonar). The objectives were to characterize

the carbonate mound substrate and sediments in support of biologic studies focusing on the

ecosystems developed on and around the mounds.

DATA AND METHODS

Approximately 145 km2

 of the outer shelf was surveyed using a digital, side-scan sonar with a

frequency of 72 kHz. Data were collected on 180 track-lines spaced 175 m apart using a 200 m sonar

swath width to achieve 228% coverage of the seafloor. The original sonar swaths have pixel

resolutions of about 1 m. The survey ship was navigated with differential OPS satellite navigation

and the sonar tow-fish was positioned using an ultrashort baseline (USBL) acoustic ranging system.

Chirp sonar records (frequency 2-12 kflz) were collected simultaneously to image the upper

sedimentary layers. The side-scan sonar data were processed to make mosaics of each megasite,

which were in turn studied using GIS methods.

A total of 229 grab samples were collected at 94 stations evenly divided between megasites 1-3 and

5. Of these, 45 stations were repeated four times to examine small-scale variability. Sediments from

the grabs were measured using standard grain size analysis techniques.

RESULTS & DISCUSSION

Mounds in the mosaics appear as irregular features with high acoustic returns (“backscatter”) and

high variability owing to geomorphologic and surface roughness. In contrast, the regional seafloor,
282

characterized by sandy sediments, appears mainly as a low backscatter background. However,

seafloor directly adjacent to the mounds, especially on the southwest sides of the mounds in

megasites 1, 3, and 5, also display high backscatter resulting from coarsening of the sediments.

Megasite 1 contains two clusters of large mounds, several with flat tops, in addition to hundreds of

small- and medium-size mounds. Most of the mounds are circular to subcircular in plan view.

Notable features on the mosaics are areas of moderate to strong backscatter surrounding the mounds,

with strongest backscatter directly adjacent to the southwest sides of the mounds. In addition, many

small and medium mounds are seen to have high backscatter “tails,” typically a few meters or tens

of meters wide and tens to several hundred meters in length. Comparison with chirp sonar profiles

shows that the high-backscatter areas on the southwest sides of the mounds are often erosional

depressions where fine sediments have been removed. Furthermore, the high backscatter tails are

seen to be erosional troughs, typically only a meter or two in depth.

Like Megasite 1, seafloor with high backscatter is also seen around the mounds in Megasite 2;

however, the strong return areas tend to be more symmetrically disposed around the mounds. The

sonar shows many mounds that appear to be low, generally flat carbonate hard-grounds, typically

a few hundred meters in diameter but not more than a few meters in height. Also in this area, many

steep, irregularly shaped mounds are imaged. This is the region of the original “pinnacle” mounds

of Ludwick and Walton (1957). Subbottom profiles show that variability in the thickness of the

upper sedimentary layer, a relict sand deposited during the transgression since the last ice age, is

highest at this megasite near the shelf edge. In many instances, only the tops of the mounds are

exposed because of the formation of extensive sediment aprons on their flanks.

Megasite 3 contains mounds like those in both Megasites 1 and 2. Two broad, low carbonate hardgrounds occur, forming platforms consisting of hundreds of small mounds, 10-20 m in diameter and

less than a few meters in height. Like Megasite 1, several flat-topped mounds appear in the eastern

part of the survey. In the west, linear, medium-sized mounds form a WNW-trending lineament. As

in Megasite 1, the high-backscatter haloes around the mounds are asymmetric and show erosion on

the southwest sides of the mounds. Many mounds also display the high-backscatter tails.

Megasite 4 also contains patches of high backscatter, but none are obviously mounds. Some, small

subcircular features, less than 10-20 m across, may be low mounds, but this has not been confirmed.

Because of the apparent absence of mounds like those in the other megasites, Megasite 4 was not

studied further.

Megasite 5 contains large and small mounds, most of which are aligned in a curvilinear band that

is nearly isobath-parallel. This band contains at least two flat-topped mounds near its center. In

addition, a large, rough, linear mound, over a kilometer in length and over 12 m in height, forms the

northwest end of the group. As in megasites 1 and 3, asymmetric high -backscatter haloes and tails

are seen on the southwest sides of most mounds.

Although the carbonate mounds vary widely in size, we can divide the mounds into three types of

morphology: (1) broad, low, mostly flat hard-grounds, (2) tall, steep-sided, irregular mounds, and

(3) steep-sided, subcircular, mounds. The low hard-grounds are usually several meters in height and
283

several hundred meters or more across. These hard-grounds are often the base for other mounds of

types 2 and 3, some attaining large sizes. Often the hard-ground tops seem to be composed of

hundreds of small, steep-sided, subcircular mounds. It is not clear whether these small mounds

formed on top of the hard-ground or whether they coalesced to form the hard-ground. The tall, steepsided, irregular mounds are the “pinnacles” and found only in Megasite 2. They are typically less

than 100 m in diameter and with heights of 5-18 m. Frequently, these mounds form irregular chains

and have a low hard-ground base. Subcircular mounds come in many sizes, from a few meters across

to several hundred meters. Heights range from one to more than 15 m. Most of these mounds are

small, with diameters of several to several tens of meters and heights of only a few meters. Some

larger mounds appear to consist of amalgamations of tens of smaller, subcircular mounds, and we

speculate that these mounds grow together to form the largest mounds, including the flat-topped

mounds. These mounds are found in megasites 1-3 and 5.

Because it was not a direct goal of this project, we do not have the data to make firm conclusions

about the origin and evolution of the carbonate mounds on this shelf. It appears that many of the

large mounds formed atop an erosional conformity cut during the lowstand of the last ice age. This

indicates that these mounds formed after the ice age, during the last 18 kyr (radiocarbon years). In

addition, several radiocarbon dates from the mound tops are from 11 - 13 kyr, implying the mounds

formed earlier, during the early part of the deglaciation. Additionally, since the mounds are

concentrated in isobath-parallel groups, it appears they may have formed near sea-level during

periods of slow sea-level rise or sea-level standstill.

Sediments from the study area show three main components: (1) sand, (2) clay, and (3) biogenic

debris. Most samples contain mainly sand with variable amounts of clay. Plotted on a sand-silt-clay

ternary diagram, all the samples give compositions that fall along a mixing line from sand to clay.

Furthermore, box core samples show the clay and sand to be well-mixed (as opposed to forming

layers). That sand and clay have very different sensitivities to currents suggests that the sediments

were laid down in energetic redeposition events, perhaps associated with storms. The third

component, biogenic debris, generally takes the form of carbonate fragments or shells. Although

there is some indication that these were shed from the mounds, the relation is not simple since

samples adjacent to mounds can contain highly variable amounts of biogenic debris. It appears that

the coarse component of these sediments is a combination of shells, shell fragments, and carbonate

crusts formed in place in addition to carbonate debris from adjacent mounds.

Comparison of grain-size data with side-scan sonar images indicates that the high-backscaner haloes

and tails near many of the mounds are caused by a coarsening of the sediments. Although silt and

clay fractions change little from low to high backscatter areas, sediments from high backscatter

zones typically contain 40-60% sand and 15-30% gravel as compared with 60-80% sand and

negligible gravel contents for samples from low backscatter areas. Thus it appears that the high

backscatter occurs because of the concentration of gravel. These zones also usually show evidence

of erosion, implying that the formation of a lag deposit caused by current scour. This hypothesis is

strengthened by the observation that the high-backscatter tails (which are erosional troughs) have

directions that correspond to rapid currents recorded during the passage of two hurricanes through

the study area. Apparently, the tails were created during storms by erosion resulting from current

eddies downstream from the mounds.
284

REFERENCES

Brooks, J.M., ed. 1991. Mississippi-Alabama Continental Shelf Ecosystem Study: Data Summary

and Synthesis, Volume I: Executive Summary, Volume II: Technical Narrative, Volume III. U.S.

Department of the Interior. Minerals Mgmt. Service, Gulf of Mexico OCS Regional Office, New

Orleans, LA., 43 pp.(I), 862 pp.(II), 1001 pp. (Ill-i), and 1001 pp. (111-2).

Continental Shelf Associates. 1992. Mississippi-Alabama Shelf Pinnacle Trend Habitat Mapping

Study. U.S. Dept. Interior, Minerals Management Service, Gulf of Mexico OCS Region, New

Orleans, LA. 75 pp.

Ludwick, J.C., and W.R. Walton. 1957. Shelf-edge, calcareous prominences in northeastern Gulf

of Mexico. American Association of Petroleum Geologists Bulletin 41:2054-2101.

Sager, W.W., W.W. Schroeder, K.S. Davis, and R. Rezak. 1999. A Tale of Two Deltas: Seismic

Mapping of Near Surface Sediments on the Mississippi-Alabama Outer Shelf and Implications

for Recent Sea Level Fluctuations. Marine Geology 160:119-136.

Sager, W.W., W.W. Schroeder, J.S. Laswell, K.S. Davis, R. Rezak, and S.R. Gittings. 1992.

Topographic features of the Mississippi-Alabama outer continental shelf and their implications

for sea level fluctuations during the Late Pleistocene-Holocene transgression. Geo-Marine

Letters 12:41-48.

Schroeder, W.W., M.R. Dardeau, J.J. Dindo, P. Fleischer, K.L. Reck, Jr., and A.W. Schulz. 1988.

Geological and biological aspects of hardbottom environments on the L’MAFLA shelf, northern

Gulf of Mexico. Marine Technological Society, Proceedings of Oceans ‘88 Conference,

Baltimore, MD, 17-21.

Schroeder, W.W., S.R. Gittings, M.R. Dardeau, P. Fleisher, W.W. Sager, A.W. Schulz, and R.

Rezak. 1989. Topographic features of the L’MAFLA continental shelf, northern Gulf of Mexico.

Marine Technological Society, Proceedings of the Oceans '89 Conference, Seattle, WA, 54-58.
285

LONG LIVES AND DEEP ROOTS: TUBEWORMS IN GULF OF MEXICO

CHEMOSYNTHETIC COMMUNITIES

Dr. C. R. Fisher

Dr. D. C. Bergquist

Dr. J. K. Freytag

Dr. R. T. Ward

Dr. J. P. Andras

Dr. B. Begly

Dr. S. Schaeffer

Dr. K. Nelson

Ms. E. McMullin

Ms. S. Carney

S. MacAvoy

Dr. S. Macko

Mr. R. Carey

Dr. I. MacDonald

Dr. M. Van Horn

Department of Biology

Pennsylvania State University

Vestimentiferan tubeworms were first discovered associated with hydrothermal vents, and the

species found on most mid-ocean ridges are adapted to the energy-rich ephemeral vent environment.

Species like Riftia pachyptila take up necessary dissolved gasses, including hydrogen sulfide (the

energy source required by their symbionts), from the rich hydrothermal fluid bathing their plume.

Individual sites may only last months to years, and R. pachyptila is one of the fastest growing

invertebrates known. The tubeworms found around cold seeps in the Gulf of Mexico (GOM) are

similar to their vent relatives in that they have not mouth, gut or anus and rely on their

chemoautotrophic bacterial symbionts for nutrition. However, we have found that the most abundant

cold seep vestimentiferan species, Lamellibrachia cf luymesi, has a very different physiological

ecology and life history. Using a new tube staining technique to determine growth rates, we have

found that Lamellibrachia cf luymesi grows very slowly. Using data on almost 600 individuals from

over 20 distinct aggregations we have determined that individuals of Lamellibrachia cf luymesi live

in excess of 170 – 250 years. Based on our studies of intact tubeworm aggregations (described in

part below), the co-occurring Escarpid-like species lives at least as long.

As part of this project, numerous water samples were taken around vestimentiferans. Sulfide was

undetectable (<0.1μm) in the gross majority of samples taken near the plumes (gill-like gas

exchange organs) of the tubeworms and in most samples taken from points closer to the sediment.

On the other hand, sulfide was consistently present in substantial quantities (up to millimolar) in the

interstitial waters around the buried posterior ends of the tubeworms. Using new collection devices,

we were able to collect intact communities of vestimentiferans and found that each tubeworm had

grown a long tortuous posterior extension to its tube (a “root”), which is freely permeable to sulfide.

We have demonstrated that at least one species, Lamellibrachia cf luymesi can take up sulfide across
286

the roots at rates sufficient to fuel net inorganic carbon uptake by the worm. This adaptation

provides the tubeworms access to a much more stable and longer lasting source of sulfide and

provides the explanation for the growth and abundance of tubeworms in areas where sulfide is not

detectable in the water above the sediments. It also has significant implications for the structure of

the associated faunal communities.

Using growth data and analyses of aggregation size and age structure, we have been able to study

the life history of the second species of vestimentiferan, “the Escarpid-like species,” which

co-occurs with L. cf luymesi. The two species settle together over a period of about 10 – 20 years

when the settlement substrate is exposed and the seepage can support new recruits. The

Escarpid-like species grows more slowly than L. cf luymesi as a juvenile and then growth slows even

more when it reaches an anterior tube length of about 50 cm. It persists at least as long as L. cf

luymesi; in fact aggregations consisting of only very large individuals of the Escarpid-like species

indicate it may live even longer than L. cf luymesi.

To obtain collections that allowed a quantitative analysis of vestimentiferan communities, we had

new collection equipment designed and built. The collectors, Bushmaster Sr. and Bushmaster Jr.,

are hydraulically actuated nets that can be placed over vestimentiferan aggregations and allow

collection of the entire aggregation and all fauna associated with the aggregation. Three collections

were made with a prototype device in 1997. The devices were modified by adding a 64μm mesh

liner and four collections were made in 1998. A total of 55 species of animals from 11 phyla (4,624

individuals) were collected with the four aggregations. Thirty-five species had not been documented

from previous collections of seep fauna, and many of those may turn out to be new species.

Although the total number of collections is too small to test hypotheses concerning community

succession in the long-lived vestimentiferan habitat, several patterns emerge from analysis of the

collections of different aged vestimentiferan aggregations which are consistent with our working

model of cold seep tubeworm life history.

The community associated with the juvenile aggregation was similar to the communities associated

with mussel beds (which were also characterized as part of this project). Mussel bed communities

were not very diverse, but had a substantial biomass of a few species of endemic animals. A total

of 12 species of animals were found in ten collections from eight different mussel beds (a maximum

of seven species was found in any single collection). A collection of juvenile tubeworms yielded 19

species of associated fauna, and the highest biomass of associated fauna of any collection. Most of

this biomass was a result of the very high numbers of a few species of endemic animals.

Communities associated with adult aggregations are much more diverse, with about twice the

species richness of the juvenile community. The communities are still dominated by endemic

species, but numerous species of non-endemic animals are present in small to moderate numbers.

The biomass of associated fauna is almost one order of magnitude less (per unit area) than in the

juvenile aggregation. A single collection of a senescent aggregation contained 20 species, half of

which were represented by a single individual. This aggregation was supporting about 20% the

biomass of the adult aggregations, and 69% of that biomass was found in two fish and one crab.

Even endemic fauna were only present in small numbers if present at all.
287

Our current working model for seep tubeworm life history and community succession begins with

larval tubeworms settling in areas of active seepage, where precipitation of carbonate forms the hard

substrate they need for recruitment. For 10 to 20 years, the high level of seepage is maintained at

this point, the carbonate the first recruits have settled on may continue to grow, and recruitment to

this aggregation continues as long as sulfide is released from the seafloor and the carbonate remains

exposed. Because the young aggregation is in a microhabitat of active seepage, only fauna that can

tolerate these conditions are associated with the young aggregations. These fauna include the

animals found in mussel beds and are dominated by endemic seep animals. During this period, the

very young tubeworms are obtaining sulfide across their plume, but also growing a posterior

extension of their tube (a “root”) and begin supplementing their sulfide uptake from interstitial

pools. Over the next century or two, the tubeworms continue to grow while seepage of sulfide from

the sediment into the water column progressively decreases. During this period there is sufficient

primary production associated with the aggregation to maintain a moderately high biomass

community, and yet the toxicity of the habitat has decreased to the point that a wide variety of

non-endemic fauna can colonize or visit the aggregations. At this point the analogy between the

tubeworms and long-lived ecosystem-structuring plants is quite strong. Although they may not be

the prime food source for most of the associated fauna, they are providing a habitat for numerous

species. As the aggregation continues to age, flow of sulfide into the water column continues to

decrease and some thinning of the aggregation occurs. The tubes are often colonized heavily by

non-endemic non-mobile fauna, primary production by free-living bacteria associated with the

aggregation decreases significantly, and the biomass of the associated community drops

significantly. This stage in their life history may also last a very long time because the tubeworms

in these less dense, old aggregations, continue to grow and are in very good condition, presumably

in part because of reduced competition from the remaining vestimentiferans.

It should be noted that the age estimates given above are for two-meter long tubeworms. Our data

are limited to animals below this size because of difficulties inherent in collecting larger animals.

However, we have occasionally collected animals over three meters in length, and the data on the

senescent bushes collected to date does not suggest that these animals are dying. This all implies that

seep tubeworms may in fact live considerably longer than 170 – 250 years, and that the ecosystems

they create are equally long lived.

Three areas of future research important to MMS management concerns were identified over the

course of the work by the Ecology component of this project:

• The first is to determine the biogeographic and phylogeographic distribution of the seep

fauna (exactly who is out there and where are they?). Although not discussed above,

molecular tools were developed over the course of this study that allow determination of

gene flow between populations of tubeworms and mussels. The relatively small geographical

area covered by this project found relatively high levels of gene flow among populations,

but the few samples we have obtained from outside of our primary study sites suggest that

there are significant differences in the communities found in different areas of the GOM. For

example, we know that there are at least five species of tubeworms found in different seep

areas of the GOM, and that very different communities of associated fauna occur at different

depths. It is very possible that tubeworms may be absent from seeps in large areas of the
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GOM, based on the recent observations by MacDonald et al. during the 2000 MMS Alvin

cruise, and by our group during the 2000 Harry Roberts JSL cruise. We have the database,

the field tools and the laboratory tools to not only document the biogeography of the seep

fauna in the GOM, but also to use the data we collect to explain the biogeographic patterns

and therefore predict distributions in other areas.

• The second is to determine the source of the sulfide that sustains the seep vestimentiferans

around their roots. We now know it is there and that they use it, but how the sulfide gets

there is not understood. Until this is understood, one cannot predict where tubeworms will

occur or how long they will last in a given location. One cannot model productivity or

nutrient flow. It is a key question remaining in our understanding of the occurrence,

persistence and stability of lush tubeworm communities in the GOM.

• The third research direction of importance to MMS management concerns is really a type

of research approach. Modelers should guide a Chemo III program. We now have detailed

and testable qualitative models of seep vestimentiferan life history and seep community

succession. These need to be tested in the context of different species of tubeworms and

types of communities (are our current models valid and generally applicable). We are also

on the cusp of having the data necessary to construct quantitative models of sulfide and

methane needs, productivity (tubeworm and mussel), and nutrient (C and N) flow on the

scale of entire seep communities (and by extrapolation the entire GOM). Among other

things, these models can be used to quantitatively evaluate the importance of seep primary

production to the surrounding fauna and the Deep Gulf in general.

Charles (Chuck) Fisher is currently a Professor of Biology and the Assistant Department Head for

Graduate Affairs at The Pennsylvania State University where he has been on the faculty since 1990.

He received his M.S. and Ph.D. from the University of California at Santa Barbara in 1985. His

research emphasis is on the physiology and ecology of the animals that live around deep-sea

hydrothermal vents in the Eastern Pacific and cold seeps in the Gulf of Mexico, and he has published

over 60 peer-reviewed papers on these topics. His research has been supported by the NSF, MMS,

NOAA NURPs, ONR, and NASA.
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INORGANIC BIOGEOCHEMISTRY OF COLD SEEP SEDIMENTS

Dr. John Morse

Dr. Rolf Arvidson

Dr. Samantha Joye

Ms. Susie Escoricia

Dr. Craig Cooper

Mr. Jeffrey Morin

Dr. Luis Cifuentes

Dr. Ethan Grossman

Dr. Steve Macko

Texas A&M University

OVERVIEW

During the first phase of this project, we recognized that a more detailed examination of the

inorganic biogeochemistry occurring in cold seep sediments would be necessary to clarify the

processes responsible for the existence of cold seep benthic communities and their unique

characteristics. Therefore, a team of specialists in this field was assembled, and an integrated

research program was added to the second phase of this research.

The primary focus of the new research was on understanding the processes influencing the carbon

dioxide and sulfide systems. This research is presented in sections that have been divided according

to major activity. Later, these results are included a general synthesis of overall findings. The major

sections are

• Pore water and solid phase chemistry: This section uses a “classical” approach in which

cores were sectioned to establish depth profiles of dissolved and solid phase chemical

components of interest.

• Sulfate reduction rates: It is possible to measure the rates at which bacteria convert dissolved

sulfate into hydrogen sulfide by using a radiotracer technique. Both depth profiles and

“integrated” rates were determined at most sites.

• Stable isotope chemistry: Fractionation of the stable isotopes of carbon, oxygen and sulfur

occurs by both biotic and aboitic processes. Stable isotope ratios of these elements were

determined at selected sites for both dissolved and mineral phases to aid in the interpretation

of the processes occurring in cold seep sediments.

• Microelectrode profiling: An emerging technology was utilized to obtain detailed depth

profiles of dissolved sulfide near the sediment-water interface. This profiling was done to

obtain better estimates of fluxes across the sediment-water interface and behavior of sulfide

in the highly dynamic region.
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PORE WATER AND SOLID PHASE CHEMISTRY

Approximately 120 push cores were collected at four primary chemosynthetic sites (GC233, GC234,

GB425, and GC185) comprising 28 distinct stations (BHAT1, BHAT2, BHB3, BHBC2, BHBXC1,

BHM3, BHM4, BHST1, BHST2, BHUN1, BHUN2, BPAT1, BPB2, GBM1, GBM2,

GBB1@GBM2, GBUN1, GCAT1, GCB1@GCAT1, GCAT2, GCB3 (Orange, White, and Offmat),

GCBX2, GCBXC1, GCJT1, GCJT2, GCST1). Cores were sampled at 2 cm intervals, and over 30

different analyses were performed on extracted porewater and solid phases yielding a large data set

(~10,000 analyses). 

An important geochemical process that discriminates stations is the extent of sulfate reduction. The

reduction and depletion of seawater sulfate in these porewaters yields dissolved H2S, which is absent

in the overlying oxic water column, and an increase in dissolved inorganic carbon(DIC). Elevated

DIC concentrations in turn promote production of solid phase calcium carbonate at the expense of

dissolved calcium. The basic stoichiometry of these coupled reactions is easily identified within the

data set and supports a basic scheme of grouping stations according to the overall extent of reduction

(see discussion in following subsection).

Observed porewater nutrient and DOC variations with depth are generally complex and do not form

a clearly recognizable pattern. Relationships within solid-phase properties and between solid and

porewater parameters are also generally more complex than those existing within the porewater data

set. 

All sediment recovered is distinctly fine-grained. Generally positive relationships are observed

between the abundance of solid phase sedimentary carbon (both total organic and inorganic) and

porewater DIC. Good correlation is also seen within solid phase metal extractions (iron and

manganese). Acid volatile sulfide concentrations are everywhere less than 40 :mols/g (4 :mols/g

average). Total reduced sulfur (TRS) concentrations average 108 :mols/g. The low abundance of

extractable iron indicates that it probably limits the extent of solid phase sulfide formation and is

in part responsible for the very high levels of dissolved sulfide observed at certain stations. 

SULFATE REDUCTION RATES

Sulfate reduction rate measurements were made at selected sites. When these data are combined

with those from the porewater and solid phase geochemistry, they suggest the following

organization:

• Inactive station porewaters show little significant departure from ordinary seawater in

composition, with only slight increases in DIC (up to ~ 4mM, a twofold increase), small

(<10%) to negligible depletions of sulfate and calcium, and sulfide concentrations less than

~250 :M (often below our detection limit of 3 :M). These stations also show integrated

sulfate reduction rates of <10 to 55 mmoles m-2 day-1. Chloride and other major ion

concentrations are within 10% of standard seawater compositions. This group comprises the

largest number of stations, and with the possible exception of bacterial mats, does not
291

distinguish itself biologically in any obvious way. These stations are variously dominated

by adult, juvenile, and senescent tubeworms and mussels.

• Active stations show clear evidence of intense sulfate reduction, either in terms of a high

integrated sulfate reduction rate (>55 mmoles m-2 day-1), or in terms of depleted sulfate and

calcium. These stations include BHUN2 (1998 core), BHM4 (dive 4046), BHB3, GCAT1

(dive 2880), GCAT2, GCB3, and GCJT2. In addition, integrated rates at certain active sites

are so high as to merit further division of this category to high (50—1000 mmoles m-2 day-1)

and extreme (>1000 mmoles m-2 day-1). Active-high stations thus include BHUN2 (1998

core), GCAT2-dive 4048 and GCB3 (orange Beggiatoa mat); active-extreme stations are

limited to GCAT2 (dives 2872, 2886, 4029). The depth at which sulfate is depleted is

variable and ranges from 5-10 cms below the sediment-water interface. Stations dominated

exclusively by Beggiotoa (GCB3) exhibit sulfate depletion curves that are markedly less in

slope compared with those found at GCAT2. In addition, the stoichiometry of sulfate-DIC

relationships in samples for which the extent of sulfate reduction is greater than 90% is

consistent with the organic matter undergoing oxidation being methane.

• Brine stations show clear evidence of mixing between seawater and Na-Ca-Cl brine

compositions, and these stations (GBM2 and BPB2) form a separate category. Although

sulfate reduction in these stations may also be very high, it is limited to the shallow interval

just below the sediment-water interface. Variations in sulfate and sulfide can be understood

in terms of a simple mixing model, in which the brine end member contains zero sulfate and

3x normal seawater sodium chloride.

STABLE ISOTOPE MEASUREMENTS

Based on the above observations, stable isotope measurements were made on selected samples.

Carbon isotope ratios were determined on DIC and calcium carbonate, where oxygen isotopes were

also measured. Sulfur isotope ratios were measured on total dissolved hydrogen sulfide and total

reduced sulfide (dominated strongly by pyrite). Calculating these measurements is a difficult and

laborious task. These results comprise, to the best of our knowledge, the only existing data set for

marine sediments where both major dissolved and solid phase isotope data coexist for the sulfide

and carbonate systems.

A strong correlation (R2

 =0.85) was observed between solid phase carbon and oxygen isotopes. This

correlation is interpreted as a mixing line between biogenic carbonates formed in near-surface

waters and authigenic carbonates formed in sediments that have more positive oxygen and more

negative carbon isotopes. The relative abundance of the authigenic component increases with

increasing sediment calcium carbonate and organic carbon concentrations. There was no obvious

relationship between the carbon isotope ratio in DIC to that of the calcium carbonate. This probably

reflects a variable fraction of authigenic carbonates in the solid fraction; it also suggests that these

carbonates did not entirely form from the current DIC pool.

As is often the case because of the complexities of biogeochemical processes in the sedimentary

sulfur system, there are generally no clear patterns or relationships among the sulfur isotope ratios
292

in different phases or with other probably important sediment parameters. However, in some cases

much of the data closely clump together in a narrow range with other data radiating in a loosely

preferred orientation. 

MICROELECTRODE PROFILES

As part of the geochemistry program, a new solid state microelectrode technology was employed

to obtain millimeter scale profiles of dissolved oxygen, O2,andreduced metabolites, primarilyH2S,

in sediment pore waters. The microelectrode system made possible the simultaneous determination

of O2, H2S, reduced iron (Fe2+) and reduced manganese (Mn2+) concentration. However, Mn2+ and

Fe2+ concentrations were typically below the analytical detection limit of the system, and the O2

concentration was difficult to quantify because of sampling problems associated with the time

between collection and analyses. The primary focus thus became documenting the distribution of

H2S in sediments to obtain improved estimates of sediment-water fluxes. 

Thirteen cores from tube worm bushes, bacterial mats, or control sites (no chemosynthetic fauna)

were microprofiled in 1997. Three cores were from along the drip line of adult tube worm bushes

(BHAT2-2; BHAT1-4; GCAT1-8) and one core was from the drip line of a senescent tube worm

bush (GCST1-5). Twenty-five cores were profiled during the 1998 cruise. Seven drip line cores and

five peripheral cores were sampled from tube worm bushes. Three orange bacterial mats and four

white bacterial mat cores were collected. Two of those cores were collected along a transition zone

from an orange to white bacterial mat. One core was collected from an uninhabited site and three

cores were sub-cored from box cores.

Results of sulfide flux calculations are presented in Table 2D.1. Although there are certainly a few

exceptions that bear close scrutiny, e.g., GCAT2A-3) from both the chemical and biological

perspectives, there are certainly strong tendencies for

1. Controls to have small to negligible sulfide fluxes, as they should in this area;

2. Algal mats to have moderate to very high sulfide fluxes; and

3. Tube worm sites to have negligible to very low sulfide fluxes.

SUMMARY OF RESULTS

The studies of the inorganic benthic biogeochemistry went well and were very close to the initial

plans. The results comprise a unique and large data set documenting the complexity and heterogeneity of these chemosynthetic communities. These results will subsequently be synthesized with

the other components of this project. 

RETROSPECTIVE

A concerted sediment biogeochemical study was not part part of the original Chemo program and

did not commence until the Chemo 2 phase of the study. The sediment biogeochemistry program
293

Table 2D.1. Calculated approximate H2S fluxes for sampling events in 1997 and 1998. A *

indicates an apparent small influx of sulfide due to storage problems. Fluxes at these

sites can generally be expected to be small.

1997 H2S FLUX

(UMOL CM^-2 DAY^1)

1998 H2S FLUX

(UMOL CM^-2 DAY^1)

Tube Worm Bush Tube Worm Bush – Drip Line

GCST1-5 0.0 BHAT1-3 0.0

BHST2-7 -760 BHST1-5 0.0

BHAT2-2 * GCAT2-1 -0.1

GCAT1-8 * BPAT1-4 0.0

BHAT1-4 * BHAT2-2 0.0

GCJT2-4 0.0

BHM3-8 -350

Tube Worm Bush – Peripheral

BHAT1-6A 0.0

GCAT2A-3 -3600

GCST1-5 0.0

GCAT1-9A 0.0

BHAT2-7A 0.0

Orange Mat Orange Mat

GBM2-6 -810 GCB1-4 -110

GCAT2-6 -260 BPB2-5 -1400

GCAT2-3 -1100 GCB3-4 -660

White Mat White Mat

GCB-6 -480 BHB1-3 -540

GCB-1 -1900 BHB3-2 -300

BHST1-5 -62 GCB1-3 -2100

GBM2-5 -3200

Controls Controls

BHBC2-4 * GCBX2-5 *

BHUN1 0.0 BHBXC1-4 0.0

GCBXC1-3 -3.3

GBUN1-5 -60

was largely designed to establish how the C & S systems varied in relationship to the distributions

of different macro-epifaunal organisms. This significantly limited the extent to which processes and

the basis for high-chemical heterogeneity could be studied. In hindsight, a much better effort was

needed on organic geochemistry and microbiology.
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RECOMMENDATIONS FOR FUTURE STUDIES

To better understand the biogeochemistry of the system, we need

• a better sampling plan not driven so strongly by the distribution of macro-fauna;

• to focus on parameters that were established as important;

• more emphasis on organic geochemistry;

• a specialist in methane oxidation;

• to reprioritize objectives based on what was learned from present study; and

• to look into cheaper non-submersible sampling.

John W. Morse is the Scherck Professor of Oceanography at Texas A&M University, where he holds

a joint appointment in the departments of Oceanography and Geology. His Ph.D. is from Yale

University, and he has served on the faculties of Florida State University and the University of

Miami. He is widely recognized as an expert on the geochemistry of sedimentary carbonates and

sulfides, having written or co-authored over 100 peer reviewed papers and co-authored a major book

on sedimentary carbonates.
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PROGRAM SYNTHESIS AND RECOMMENDATIONS FOR FUTURE WORK

Dr. Ian R. MacDonald

Geochemical and Environmental Research Group

Texas A&M University

INTRODUCTION

This contract has considered results from an extensive program of field collections and laboratory

analysis that spanned numerous disciplines within marine science. A team of sixteen investigators

and their students or associates from seven separate institutions was assembled to formulate and

carry out the work. During the course of two ambitious field seasons, program investigators

collected samples from over fifty stations distributed among four principal sampling sites with use

of the submarine Johnson Sea Link. Extensive additional collections were made with use of the R/V

Gyre and vessels of opportunity including the U.S. Navy Submarine NR-1. The primary

geochemical samples included more than fifty sediment cores, which were extensively sub-sampled

by sediment depth. Extensive collections of chemosynthetic and heterotrophic animals were

obtained for a diverse array of investigations to determine, among other objectives, growth rates,

health, genetic diversity, and food-web structure. A regional context for the targeted sampling was

established through geophysical survey, sediment coring, and layered comparisons between

community and regional-scale data with use of geographic information system (GIS) tools. Although

regional-scale physical oceanography was beyond the scope of the program, valuable time-series

records of current, water temperature, and fluid discharge properties of the seep environment were

obtained from in-situ instruments and moorings. Serendipitously, remote sensing records were

obtained through cooperation with industry. These data illustrated large scale changes in

hydrocarbon discharge at one of the study sites. Throughout the program, the investigators benefited

from similar cooperative arrangements with other agencies and interests. Mention should be

particularly made of assistance received from the NOAA National Undersea Research Center at the

University of North Carolina, Wilmington, the Naval Research Laboratory Washington DC

laboratory, and the U.S. Navy SUBLANT group, all of whom assisted with obtaining ship and

submarine time over and above what would have been possible under the contract. Data sharing was

an important component that enriched the program data resources. Contributions by Western

Geophysical, Inc. and Unocal, Inc. are particularly noted.

Results from the main body of program efforts have produced a substantial body of research results,

which include numerous peer-reviewed publications and student theses in addition to the results

detailed in the preceding chapters of this report. Given the pace of publication, it is likely that this

productivity will continue for some time to come. The purpose of this section is to revisit the

individual investigations of the program with a interdisciplinary perspective. The major program

objectives, as specified in the request for proposal and contract are reviewed below and briefly

reprised. Wherever practical, this section will attempt to synthesize the separate results into themes

that address MMS concerns. Finally, recommendations for future study will be outlined.
296

PROGRAM OBJECTIVES

The request for proposal that initiated this program specified the following objectives for study

(taken verbatim from solicitation number 3813):

1. Review biotic and abiotic features of existing conceptual models of chemosynthetic

communities which explain observed patterns of distribution and abundance, in order to

develop an effective, refined plan for continued research.

2. Further evaluate the physical-chemical factors (e.g., depth, temperature, water chemistry,

sediment types, and dissolved gasses) which influence, limit, enhance, or control the

distribution, abundance and growth of chemosynthetic communities.

3. Further investigate the sources (e.g. deep versus shallow, or petrogenic versus biogenic) of

any necessary dissolved gasses and the likelihood that petroleum production may ultimately

deprive the animals of an energy source.

4. Further determine whether chemosynthetic communities are robust or fragile and whether

they are essentially permanent or ephemeral; characterize age, growth rate, turnover rates,

reproduction and recruitment, and patterns of senescence and death in the dominant

chemosynthetic animals; further examine recovery rates of communities damaged by

physical disturbance.

5. Further determine the reliability of methods for detecting chemosynthetic communities using

remote acoustic and/or geophysical devices, imaging instrumentation, hydrocarbon

measurements, and/or other available technologies.

In considering objective number one, a thorough review of published literature and reports was

completed. A principal conclusion was that the chemosynthetic fauna from hydrothermal vents (tube

worms and mussels) were taxonomically and functionally similar to that of vents, but inhabited an

ecosystem that was fundamentally distinct. Therefore, new conceptual models of colonization,

persistence, and interaction would have to be developed to describe seep chemosynthetic

communities. The plan for further research needed to reference the ambitious goals laid in the

remaining objectives. It was determined that most of the sampling would have to be carried out

within a few discrete sampling areas. Four sites were selected because they represented two pairs

of distinct habitat types (brine pooling and sediment diffusion), because previous work provided a

strong basis for further study, and because they were close enough together for effective field

sampling (Figure 2D.1). The plan specifically did not allow for sampling communities occurring at

depths greater than 1000m (the maximum depth for available submarines) nor did it permit broad

survey of the northern Gulf of Mexico in attempts to define the overall prevalence of communities.

Objective two was addressed by deploying a current meter mooring at one of the study sites

(GC185) and by deploying bottom thermistors at two other sites (GC234 and GB425). These

instruments showed that the currents at the relevant depths are of sufficient magnitude to disperse

the larvae chemosynthetic fauna across the entire upper slope. Additionally, the variation in bottom
297

Figure 2D.1. Map of the northern Gulf of Mexico showing locations of program study sites

(triangles) and mega-sites for geophysical survey (stippled boxes). 

water temperatures indicate that the study sites are sufficient to provide the organisms with distinct

environmental cues concerning timing of stronger currents. This temperature variation will also

potentially define the stability envelope for shallow gas hydrate. Thermistor records from the seeps

provide some long term information on the discharge rates from the brine-pooling type habitats. 

Objectives three and four were addressed through a program of sample collection with submarine

Johnson Sea Link. Noteworthy results include the confirmation of extreme longevity among seep

tube worms and the prevalence of parasitism among seep mytilids—in many cases, the parasite load

was great enough to significantly affect the health of the infected animals. Diverse investigations

examined the geochemical processes that support chemosynthetic species. Sulfide-dependent

chemosynthetic species are found among sediments that sustain sulfate reduction rates that are two

orders of magnitude greater than anything previously reported. Rates of this magnitude are patchily

distributed and can only be sustained with some process to mix seawater sulfate down into the

sediments. A biological mediation is indicated. Gas hydrate, while recognized as being a component

of seep communities, was not anticipated to play a major role in seep ecology during the course of

the program; however, a new species of polychaete worm (Hesiocaeca methanicola) was found to

make extensive burrows in shallow hydrate deposits. Preliminary evidence points to hydrate as a
298

possible intermediate source for necessary dissolved gasses at seeps. The question of whether seeps

are robust or fragile was addressed in two ways. By examining the DNA fingerprints of seep

mussels and tube worms, it was possible to determine that genetic exchange among study sites is

in all cases adequate to sustain species integrity across the sites. This indicates that larval

recruitment from external locations could recolonize sites that had suffered a loss of population.

Trophic studies show that although seep fauna do provide a source of food for animals living away

from seeps, there is no sign that non-seep fauna depend exclusively on seep productivity as a food

supply.

Objective five was addressed through compilation of a side-scan sonar mosaic over two mega-site

regions. This geophysical data was then extensively ground-truthed at multiple scales with use of

GIS techniques and additional survey with submarine NR-1. Additional geophysical characterizations were obtained by selective reprocessing of industry multi-channel. These results narrowed

and refined the search pattern for chemosynthetic communities, but did not demonstrate that any

remote sensing survey could provide absolute certainty regarding the presence or absence of chemosynthetic communities. Additional work underlined the usefulness of satellite remote sensing data

for determining the areal and temporal distributions of natural oil discharges.

RECOMMENDATIONS FOR FUTURE WORK

The program investigators agreed that new approaches would be needed for future studies. Two

principal directions were indicated. Detailed studies, which extend sampling deeper into the

sediment column beneath clusters of chemosynthetic fauna, are needed to delineate the bacterial and

metazoan consortia and the elemental cycling that were indicated by results to date. New sampling

techniques will be needed for this work. Broad area surveys will be required to characterize the

regional distribution and variability of chemosynthetic ecosystems. The results from the present

study indicate that a more robust and cost-effective suite of geochemical samples could provide a

basic screening for areas affected by seepage. Much sampling could probably be conducted from

surface ships. However, the 650-m maximum depth of the site examined during the present study

leaves much of the lower slope unexplored—and this at a time when exploration and production on

the lower slope is expected. New studies should focus on the deeper areas. This work will probably

have to be done from ROVs rather than occupied submarines and will require careful planning to

ensure that the results are comparable with previous work.

Ian R. MacDonald is an Research Scientist at the Geochemical and Environmental Research Group

of Texas A&M University. His primary research interest is the application of imaging and GIS

techniques for marine ecology. He is the program manager for the Stability and Change in Gulf of

Mexico Chemosynthetic Communities Program. MacDonald received a Ph.D. in oceanography in

1990 from Texas A&M University.
299

SESSION 2E

NEW INITIATIVES IN MODELING OF OIL SPILLS

Chair: Ms. Gail Rainey, Minerals Management Service

Co-Chair: Dr. Walter Johnson, Minerals Management Service

Date: December 6, 2000

Presentation Author/Affiliation

Modeling a Deep Water Oil/Gas Spill under

Conditions of Gas Hydrate Formation and

Decomposition

Mr. Fanghui Chen

Mr. Li Zheng

Dr. Poojitha D. Yapa

Department of Civil and Environmental

Engineering

Clarkson University

SINTEF’s DeepBlow Model Dr. Mark Reed

SINTEF Applied Chemistry, Norway

The Fate and Effects of Barium and RadiumRich Fluid Emissions from Hydrocarbon

Seeps on the Benthic Habitats of the Gulf of

Mexico Offshore Louisiana

Dr. Paul Aharon

Mr. Dan VanGent

Dr. Baoshun Fu

Department of Geology and Geophysics

Louisiana State University

Dr. L. Max Scott

Radiation Safety Office, Nuclear Science

Center

Louisiana State University

NOAA’s Other Oil Modeling Initiatives

(GNOME/Wizards/TAP)

Ms. Debbie Payton

National Oceanic and Atmospheric

Administration

ASA Oil Spill Models: Modeling the

Movement of Oil and Gas Released from

Deep Well Blowouts

Mr. Eric Anderson

Applied Science Associates, Inc.

ASA Oil Spill Models: 3-D Fates and Effects

Modeling Applications for Gulf of Mexico

Spills

Dr. Deborah French McCay

Applied Science Associates, Inc.
301

MODELING A DEEPWATER OIL/GAS SPILL UNDER CONDITIONS OF GAS

HYDRATE FORMATION AND DECOMPOSITION

Mr. Fanghui Chen

Mr. Li Zheng

Dr. Poojitha D. Yapa

Department of Civil and Environmental Engineering

Clarkson University

INTRODUCTION

Oil exploration and production from deepwater locations are increasing steadily. As the production

increases, the potential for an oil/gas spill increases. Major concerns from a deepwater oil/gas spill

are fire hazard to the people working on the surface installations and loss of buoyancy of ships and

any floating installations. For this purpose it is important to know if, when, and where the gas may

surface and how much it will be. Another environmental concern is the issue of whether oil will

surface and if so, where, when, and what the oil slick thickness will be. To meet these new

challenges, spill response plans need to be upgraded. An important component of such a plan would

be a model to simulate the behavior of oil and gasses, if accidentally released, in deepwater. 

In deepwater, the pressure is high and the temperatures are low. In these conditions two aspects of

gas behavior differ significantly when compared with a release from relatively shallow depths. First,

under these high-pressure conditions, the gases may not behave according to ideal gas conditions.

Our computations showed that at depths of 1,000 m water depth, the behavior of methane and

natural gas deviate significantly from the ideal gas conditions. Second, in these high-pressure and

low-temperature conditions the gases are likely to form “gas hydrates.” Hydrate formation is a

physical process that is reversible. As these buoyant hydrates travel upwards, they encounter regions

of lower pressure. The hydrates can decompose into free gas under these conditions. The presence

or absence of hydrates has a significant impact on the behavior of the jet/plume due to the alteration

of the buoyancy. The free gas may dissolve in water.

Studies on gas hydrates could be divided into two categories: thermodynamics and kinetics.

Thermodynamic studies focus on the conditions of hydrate formation, such as equilibrium temperature and pressure. Kinetic studies focus on the rate of formation and decomposition. The actual

existence of hydrates depends on not only the thermodynamics but also the kinetics of formation.

The latter aspect is important to deepwater spills.

This paper describes a computer model developed to simulate the behavior of oil and gas released

from deepwater locations in the ocean. The model integrates the hydrodynamics and thermodynamics of the jet/plume with kinetics and thermodynamics of hydrate formation/decomposition.

Model formulation and comparison of results with laboratory data for hydrates is presented.

Scenario simulations show the behavior of oil/gas under different deepwater conditions. These

include the jet/plume reaching a neutral buoyancy level before continuing to travel upward.
302
303

 
304
305
306
307

DeepBlow

Lagrangian Integral Plume Model

for Oil and Gas Blowouts in

Deep and Shallow Waters

Mark Reed (for Øistein Johansen)

mark.reed@chem.sintef.no

Senior Research Scientist

SINTEF Applied Chemistry

Trondheim, Norway

Goals of DeepBlow Model

Development

• Health and safety: risks at the sea surface

from underwater gas and oil releases

– shallow or deep

– arbitrary mixture of gases, oil, and water

• Spill response: distribution of oil thickness

and weathered state on the sea surface

following an underwater release

– blowout

– pipeline leak

– gas, oil or a combination

SINTEF’S DEEPBLOW MODEL

Dr. Mark Reed

SINTEF Applied Chemistry, Norway
308

What’s special about deep waters?

High pressures: 1000 m = 101 atmospheres

Cold water: -1 to 5oC

Which implies:

• Non-ideal gas behavior

• Increased solubility of gas in sea water

• Gas may combine with sea water and form

hydrates

• Effects of cross-flow increase with depth

Hydrographic profiles

CH4

Natural gas

0

200

400

600

800

1000

1200

1400

1600

-10 0 10 20 30

Temperature, dgr. C

Depth, m

Norwegian Sea

Gulf of Mexico

Greenland Sea

North East Atlantic

0

200

400

600

800

1000

1200

1400

1600

34 34.5 35 35.5 36 36.5

Salinity, ppt

Depth, m
309

Compressibility (z-factor)

(3) (2) (1)

0

200

400

600

800

1000

1200

1400

1600

0.0 0.2 0.4 0.6 0.8 1.0

z-factor

Depth, m

(1) 100% C1

(2) 90% C1, 7% C2, 3% C3

(3) 75% C1, 12% C2, 13% C3

S ea temperature 5 dgr C

0

10

20

40 80 oC

0

200

400

600

800

1000

1200

1400

1600

0.0 0.2 0.4 0.6 0.8 1.0

z -factor

D epth, m

75% C1, 12% C2, 13% C 3

Solubility of methane

0 dgr C

10

5

15

20 25

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 200 400 600 800 1000 1200 1400

Depth, m

Solubility, g/Lwater
310

Natural gas hydrates

Methane molecule trapped in ice cage Sample of hydrate from sediments

Gas hydrates

Some facts:

• Equilibrium temperature depends on pressure and

composition of gas

• Density of ice matrix: 780 kg/m3

• Gas to water ratio (moles): 15% gas/85% water

• Density of hydrate: ≈ 900 kg/m3

• Latent heat of freezing*)

: 440 kJ/kg hydrate

*)

Latent heat of freezing for water/ice: 335 kJ/kg water
311

Depth of Trapping vs Cross-flow Speed

0

200

400

600

800

1000

1200

0 5 10 15 20 25

Current speed, cm/s

Depth of trapping, m

Gas well - GOR 2000:1

Oil well - GOR 150:1

Deep water blowouts

Oil droplets surface

Outflow of oil and gas

Sea water temperature

Plume of entrained

water, oil and hydrate

Gas converted to hydrate

Hydrate

line
312

Key concepts affecting plume and

surface slick formation:

• compressibility of gas (not ideal gas)

• hydrate formation (and melting!)

• gas dissolution

• effects of cross-flow

– depth of trapping

– horizontal displacement

• oil droplet size distribution

DeepBlow: Lagrangian plume

model for deep waters

u, v, w

h

b

Qi,T, S

Lagrangian plume element
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Composition of plume element

Oil

Dissolved Free

Gas

Hydrate

XH

Seawater

1 - XH

Mass fraction of

gas converted to

hydrate

Buoyancy

• Volume of plume element:

– Qi

 = mass of component i

– ρi

 = density of component i

• Archimedes law: Buoyancy =

volume of element × specific weight of sea water

=∑

i

Qi V

ρ
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Latent heat of hydrate formation

released over a temperature interval

CH4

Equilibrium line for

natural gas mixture

∆HL

Temperature

XH = 100%

XH = 0%

Heat content

Input to DeepBlow

• Discharge data:

– Depth (m)

– Oil rate (m3/hour)

– Gas-to-oil ratio (GOR)

– Oil density (kg/m3)

– Gas density (kg/Sm3)

– Temperature

– Outlet diameter

• Environmental data:

– Hydrographic profiles

– Current profiles:

 Simultaneous timeseries of ocean

currents measured at

different depths
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Output from DeepBlow

• Summary results for

different current

situations:

– Depth of trapping (DOT)

– Rise time to DOT

– Plume radius at DOT

– Concentration of oil at DOT

– Mass fraction of gas

converted to hydrate and/or

dissolved in water at DOT

• Detailed description of

each simulated plume:

– Plume trajectory (x, y z)

– Plume radius

– Plume velocities (u, v, w)

– Plume composition,

temperature etc.

Plume geometry

Calibrated to field trials; Discharges from 105 m depth

0

20

40

60

80

100

120

-80 -60 -40 -20 0 20

Distance downstream, m

Depth, m

GWR 18:1

0

20

40

60

80

100

120

-80 -60 -40 -20 0 20

Distance downstream, m

Depth, m

GOR 67:1
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Plume trajectory from 1200 m

0

200

400

600

800

1000

1200

-1600 -1400 -1200 -1000 -800 -600 -400 -200 0 200

D ista nce East, m

Depth, m

Formation of surface slick

• Plume trapped below surface; “flags”

with the cross-current

• Oil droplets of different sizes rise to the

surface through a depth- and timevariable current field

• Oceanic diffusion contributes to

horizontal spreading (especially for

droplets with long settling times)
317

Oil droplets rising from 600 m depth.

(Current measurements from Gjallarryggen)

0.2 mm

0.5 mm

1.0 mm

2.5 mm

5.0 mm

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.1 1 10 100

Radial displacement, km

Fraction of droplets

Oil slick from marine diesel experiment

Underwater currents against the wind
318

Example

computed

surface slick,

release of oil

and gas from

800 m

-5

0

5

10

-5 0 5 10

Distance East, km

Distance North, km

> 0 micron

> 5 micron

> 10 micron

> 50 micron

> 100 micron

> 200 micron

Discharge 

location

-2.5

0.0

2.5

5.0

7.5

-15.0 -12.5 -10.0 -7.5 -5.0 -2.5 0.0 2.5

Distance east, km

Distance north, km

h > 0 mm

h > 0.02 mm

h > 0.2 mm

h > 1 mm

Example of surface slick
319

Summary

Key concepts affecting plume and surface

slick formation:

• compressibility of gas (not ideal gas)

• hydrate formation (and melting)

• gas dissolution

• effects of cross-flow

– depth of trapping

– horizontal displacement

• oil droplet size distribution

Final Query:

• Can we use simple models, accounting only

for:

– compressibility of gas (not ideal gas)

• ... and then define the envelope of possible

answers by assuming extreme values for

– hydrate formation and melting

– gas dissolution

– effects of cross-flow varying in time and vertical

location (entrainment, displacement)

– oil droplet size distributions
320

Dr. Mark Reed is Senior Scientist at SINTEF Applied Chemistry, Division of Environmental

Engineering in Trondheim, Norway, where he has been since 1992. Prior to that, he worked at ASA

in Rhode Island. His area of specialization is marine environmental modeling. Dr. Reed received

his Ph.D. from the University of Rhode Island in 1980 in oil spill-fishery interactions and did postdoctoral work in Trondheim, Norway in fish migration modeling.
321

THE FATE AND EFFECTS OF BARIUM AND RADIUM-RICH FLUID EMISSIONS

FROM HYDROCARBON SEEPS ON THE BENTHIC HABITATS OF

THE GULF OF MEXICO OFFSHORE LOUISIANA

Dr. Paul Aharon

Mr. Dan VanGent

Dr. Baoshun Fu

Department of Geology and Geophysics

Louisiana State University

Dr. L. Max Scott

Radiation Safety Office, Nuclear Science Center

Louisiana State University

During routine submersible dives in 1993 followed by additional targeted dives in 1997, we

discovered that in addition to hydrocarbons some of the seeps occurring at upper bathyal depths (510

to 657 m) in Garden Banks-382 (27° 37.77' N; 92° 28.08' W), Garden Banks-338 (27°37.79';

92°28.12') and Mississippi Canyon-929 (28° 01.46'N; 89°43.63'W) are also issuing copious amounts

of barium and radium-rich fluids. Upon their exit on the seafloor, these fluids were likely to

constitute the primary source for the extensive radium-rich barite deposits of varied morphological

shapes documented by us on the seafloor. At the time of the submersible observations, the impact

of the excess barium and radium on the benthic habitats was unknown.

The inference that hydrocarbon seeps may act as additional sources and sinks for barium and radium

in the benthic environment of the OCS Gulf of Mexico complicates previous assessments

concerning the fate and effects of offshore drilling. These assessments have assumed that the only

external source for these toxic/radioactive elements is derived from the drilling muds and produced

waters, respectively. Therefore, to establish a technical basis for decisions concerning possible

impact of deepwater drilling offsetting the subsurface hydrology and industrial discharges on the

deepwater marine habitats, it was necessary to evaluate the contribution of barium and radium

derived from seeps, their removal into the sediment, and their uptake by the chemosynthetic

communities associated with the seeps.

In contrast to the shelf area, where 50 years of drilling and production of hydrocarbons occurred,

the deepwater habitats along the slope are relatively pristine. However, as the oil and gas industry

is moving its exploration and production main activities to deepwaters, the habitats’ present pristine

status is likely to change. It is, therefore, important to explore the natural processes occurring in

deepwaters ahead of the anticipated anthropogenic complications. 

The primary objectives of this study were to document products and processes related to naturally

occurring barium and radium-rich fluid emissions from hydrocarbon seeps and to assess their impact

on the offshore habitats in deepwater Gulf of Mexico. The specific questions we have addressed are

as follows: 
322

1. What are the levels of barium and radium in the pore fluids underlying seeps, in the barite

deposits forming around the seeps, and the chemosynthetic communities? 

2. What are the nature and origin of barite deposits and the processes promoting their

formation?

3. What are the timing and duration of emissions? Are these emissions altered or accelerated

by anthropogenic activities?

4. Do recently discovered radium-rich fluid emissions pose a significant internal and/or

external radiation threat to the existing seep communities?

The first and second questions were addressed by a direct approach involving (1) specific

determinations of barium, radium, and selected chemical elements and their isotopes in pore fluids

squeezed from sediment cores taken with the submersible robot arm from barite-bearing seep sites;

(2) measurements of barium, radium, and selected chemical elements and their isotopes in solid

barites, and (3) determinations of radium and barium in both soft tissues and hard skeletons from

methanotrophic mussels and heterotrophic fauna living in the proximity of the barite seeps. These

results were compared and contrasted with radium and barium determinations from pore fluids and

fauna from carbonate-bearing seeps that appear to represent natural, unperturbed, background

radioactive and chemical emission sites. We found that pore fluids contain important information

concerning their source and migration pathways, and their chemical fingerprinting allowed us to

identify their subsurface source/s with a fair degree of certainty. The third and fourth questions are

much more difficult to resolve definitively within the time-limited scope of this study. An indirect

approach to the problem was taken, which involved inferences from spatial and temporal distribution

patterns of barium and radium within the barite deposits. Radium and barium in growth increments

from the barite chimneys were used as an archived history and record of episodic venting whose

chronology was derived from the radium-decay series isotopes. The youthfulness of all the barite

deposits may be taken as an indication of possible accelerated emissions from the seeps, implicating

unusual nonuniform disturbances of the subsurface hydrology increasing formation water ascent to

the seafloor through normal faults from deep reservoirs. To resolve the fourth question, external

gamma ray and internal alpha radiation (derived by ingestion of radioactive barite) exposure and

dose to epifauna inhabiting the barite seeps, consisting of vagrant heterotrophs (galatheid crabs,

starfishes) and sessile methanotrophic mussels, was estimated from measured radium-decay seriesspecific concentrations by means of a computerized dose calculation program (Microshield 5.0). 

The results of our investigation can be summarized as follows:

1. Three chemical types of pore fluids associated with hydrocarbon seeps occur in the

deepwater Gulf of Mexico. Two are derived from the ambient seawater and their chemical

compositions are altered by microbial interactions and by dissolution of sub-seafloor salt

diapirs. The third type, highly enriched in Ba and Ra, is derived from deep-seated formation

waters and its advection on the seafloor through fault conduits associated with salt diapirism

impacts adversely the ambient benthic habitats.
323

2. Formation-water-derived fluids emerging on the seafloor are anomalously enriched in Ra

and Ba relative to seawater by factors of up to 4.5x104 and 15x104, respectively. Their

migration time from the source to the seafloor is established to be < 20 years on the basis of

the relatively short-lived 228Ra isotope content.

3. Barite (BaSO4) deposits consist of chimneys, crusts blanketing mud volcanoes, and

unconsolidated sands infilling gulleys. The chimneys are dominated by the mineral celestobarite (i.e., Sr-rich barite), whereas the crusts consist of both barite and calcite. The Gulf of

Mexico seep barites are anomalously enriched in Sr, Ca and Ra by comparison with barites

from normal marine settings elsewhere.

4. Sulfur, oxygen and strontium isotope compositions indicate that the Gulf of Mexico seep

barite deposits form by the mixing of sulfate-rich seawater with Ba-, Sr-, and Ca-rich

formation fluids seeping with gaseous hydrocarbons, primarily thermogenic methane. The

chimneys are erected vertically above the seafloor whereas the crusts drape mud volcanoes

and/or form pavements at the sediment/water interface. 

5. Both 226Ra and 228Ra are “orphans” in the sense that their respective parents 238U and

232Th are practically absent in the fluids and barites. The “orphan” property of Ra affords

radiometric dating of the barites by 210Pb/226Ra and 228Th/228Ra daughter/parent isotope

pairs. The assays indicate that chimney ages range from 0.5 to 6.5 years whereas the crust

ages range from 9.0 to 23.1 years. The growth rates of the chimneys vary from 4.4 cm/yr to

9.1 cm/yr. These results indicate that the Ba-Ra-rich fluid expulsion on the seafloor,

triggering barite deposition, is a rapid and recent event. At this point, we cannot discern

whether or not the intensified emissions are related to disturbances in subsurface hydrology

triggered by exploration and production from deepwater platforms. This question must be

addressed responsibly in future studies.

6. The uptake of Ba and Ra by the fauna inhabiting the barite-bearing seeps was found to be

proportional to the Ba/Ra ratio in the pore fluids. Mussels harboring methanotrophic

endosymbionts average 0.6 dpm/g and 0.5 dpm/g 226Ra for soft tissues and calcareous

shells, respectively, which are significantly higher than those reported for shallow marine

mussels. Vagrant, heterotrophic, fauna living around the seeps yield 226Ra and Ba up to

10.7 dpm/g and 4,319 ppm, respectively. The considerably higher levels of Ra and Ba in the

heterotrophs are probably acquired through ingestion of barite particles. 

7. The largest possible radiation dose to fauna from Ra-rich barites (0.0128 mGy/day) is

substantially lower than the threshold of detrimental radiation effects for aquatic animals.

However, the cumulative radiation dose and consequential genetic effects over a mean

lifespan of 25 years for mussels could be substantial. These estimates have not considered

the radiation exposure derived from 222Rn gas dissolved in the surrounding bottom waters

because of absence of data. There is a need to determine the level of radon in the ambient

seeps to properly assess the impact of radon radiation hazards.
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NOAA’S OTHER OIL MODELING INITIATIVES (GNOME/WIZARDS/TAP)

Ms. Debbie Payton

National Oceanic and Atmospheric Administration

The National Oceanic and Atmospheric Administration (NOAA) conducts a number of modeling

activities in the Hazardous Materials Response Division (HAZMAT). These modeling activities

range from real-time operational support during spills of oil and other hazardous materials to

modeling for drills and planning. Our focus for the past year has been in three areas:

(1) improvements in trajectory analysis; (2) development of tools for end-users other than

HAZMAT; and (3) development of planning tools.

To improve our present trajectory analysis capabilities, we have been investigating implementation

of 3-D modeling, improving weathering estimates, developing an extended outlook approach, and

improving our circulation models. For 3-D modeling, we are focusing on the application of 3-D

models to dispersant application. We have been involved in a number of Environmental Risk

Workshops around the country to look at the tradeoffs of dispersant use during oil spills. As part of

these workshops, HAZMAT has been providing estimates of dispersed oil concentrations in the

water column. We have been using a number of models to accomplish these estimates. Our efforts

for the present and through the next two years will be on coupling these models together so that they

can be more readily used operationally. Weathering improvements are discussed in a separate

presentation. 

In providing operational trajectory analysis, we are often limited by the time-scale of the available

reliable weather forecast. Typically we provide estimates for up to two days in the future. In some

instances, particularly large spills, spills of very persistent oils or vessels that are endangered but

have not yet lost their cargo, it is useful to have longer trajectory estimates. We are developing an

“extended outlook” that will be based on the standard trajectory analysis assumptions for the first

48 hours or so and transition to climatological data beyond that time. This will provide us with the

capability to generate useful trajectory information beyond the standard 48 hours.

The circulation used in most of our trajectory analysis is based on models that we have developed

in-house for certain hydrodynamic regimes. The results from these hydrodynamic models are scaled

using on-scene observations, literature or local expertise. We are working on both expanding the

types of regimes we can reasonably model and developing methods to use results from other

hydrodynamic models to drive the circulation needed as part of the trajectory.

The General NOAA Oil Modeling Environment (GNOME) has been under development for the last

few years. It is now our operational model as well as a model that others can use to investigate

potential pollutant movement. We have developed 15 locations around the United States that have

“pre-loaded” data for use with GNOME. For the standard user interested in specific scenarios for

drills, intuition building or exploring uncertainty, these location files can be quite useful. Location

files are distributed over the internet with a “wizard” front-end that leads the user through important

questions to define the necessary conditions (river flow rates, location to start spill, amount and type
325

of oil spilled, etc.). We expect to continue development of these location files over the next three

years, until we have completed all 38 locations identified by the USCG as high-priority sites. Used

in a more advanced mode (diagnostic mode), GNOME provides the necessary tools for a trajectory

analyst to estimate movement during an actual spill event. 

In the past, trajectory models, such as GNOME, were used to address planning needs as well.

“Worst Case” scenarios were developed, run through a model, and one component of planning was

based on what the threats were estimated to be. NOAA/HAZMAT has been working on the

development of a Trajectory Analysis Planner (TAP) to more completely address spill planning

needs. TAP is model that uses climatological data and runs hundreds (or thousands) of spill

scenarios to define potential threats. TAP has been developed for San Francisco, San Diego and

Kaneohoe Bay. HAZMAT is working with the Navy to improve TAP in San Diego so that

allowances for booms, skimming or other removal processes can be reflected in the ultimate fate of

the oil. At present, TAP is still in the research and development phase. When it becomes operational,

we anticipate TAP to provide significant contributions to the planning process.
326

ASA OIL SPILL MODELS: MODELING THE MOVEMENT OF OIL AND

GAS RELEASED FROM DEEP WELL BLOWOUTS

Mr. Eric Anderson

Applied Science Associates, Inc.

INTRODUCTION

Over the past twenty years, Applied Science Associates has developed a system of models which

evaluate the fates and biological effects of oil and chemical spills. The models use a common

framework of geographical and current databases for input data, and outputs are displayed in a

Windows interface that shows surface oil distributions and concentrations of oil and chemicals in

the water and sediments.

In the last five years, offshore drilling of oil wells has moved to deeper and deeper continental shelf

areas, with several existing and planned drilling operations at depths beyond 1,000 meters. When

oil and gas are released from a subsea blowout, the movement of the oil and gas mixture is defined

as a plume emanates from the release location. At the relatively shallow water depths (less than

500m) previously drilled, the gas commonly released with the oil has driven the upward movement

of the oil and gas plume. Equilibrium theory and observations show that methane (the primary gas

released) will form a hydrate at the pressures and temperatures existing at these depths. The specific

gravity of the gas hydrate is very close to the specific gravity of oil. Therefore, if hydrates form

during a deep water blowout, the driving force behind the rapidly rising oil and gas plume is dissipated, and the travel time of the released oil is markedly increased. Interest in the modeling of

potential blowouts from such drilling operations now includes the modeling of the formation of

these hydrates. The basic framework for the model system is described in previous works, both in

the manuals for the systems themselves (ASA 1996, 1997), and in published hindcast studies of previous well-studied oil spills (Kolluru et al. 1994; Spaulding et al. 1992a, 1992b, 1993, 1994, 1996).

SUBSURFACE PLUME MODEL

The plume generated from an oil and gas blowout is a mixture of gases, liquids, and solids which

has coherent spatial volume and definable spatial movement. In the region immediately near the

release point, the movement of this plume is governed by the momentum of the released materials.

Due to the relatively high mass of the receiving water, this phase of the plume is very short (on the

order of one to a few meters). After the initial momentum-forced stage, the movement of the plume

upward is governed by the differential in the density of the material inside the plume boundary and

the density of the receiving water outside the plume. The greater the differential densities, the

greater the speed of plume rise. When gas and oil are released from a well that is blowing out,

typical volume ratios of gas to oil are in the range of hundreds to one. Thus a hundred cubic meters

of gas may be released with a single cubic meter of oil. ASA’s plume model has been in use over

the past fifteen years with applications to sub-sea blowouts without hydrate formation, drill cuttings

and mud dispersion, and produced water dispersion modeling.
327

Figure 2E.1. The model for the formation of methane hydrates.

In 1999, ASA engaged a leading expert in the deep sea hydrate formation process, Dr. Raj Bishnoi

of the University of Calgary, to include the potential for the hydrate formation process in the plume

model dynamics. Dr. Bishnoi and his associates generated a model for the formation of methane

hydrates at the pressures and temperatures to be found in the drilling regimes to be studied (Figure

2E.1). Figure 2E.2 shows an example of this equilibrium solution. Increasing water depth is

represented as positive change on the vertical axis. Increasing water temperature is positive

horizontal change. If methane gas is released in the zone to the left and above the red curve (marked

with circles) and sufficient water is available, hydrates will be formed. If methane hydrates move

to the region to the right and below the hydrate curve, these hydrates will revert to gaseous form and

release water. Adding this hydrate formation to our existing plume model, we find that the mixing

of water into the methane-oil-water plume is the limiting factor for the formation of hydrates.

PLUME TRAPPING

A good deal of attention has been paid to the phenomenon of plume trapping. The term “trapping”

here implies that the forcing mechanism that causes the mixture of gas and fluid in the rapidly rising

plume diminishes to the point that there is no difference between the density of the outside fluid and

the density of the mixture in the plume mass. If the gas that is forcing upward plume movement

changes state to hydrate form, the primary forcing for the upward movement of the plume will be lost,
328

Figure 2E.2 An example of the equilibrium solution.

and the plume is likely to disappear. The oil and hydrates released at the end of the plume movement

will generally be of lower density than the surrounding water and will continue toward the surface

at the rise rates for the individual particles themselves. The hydrate particles are generally not of great

concern. We follow the movement of the oil particles to predict the time when these particles will

reach the surface. The larger the particle size for these oil particles, the faster will they rise. Thus, the

particle size distribution for these oil droplets is of great concern. Table 2E.1 below shows some

examples of computed rise times for a release of Foinaven crude from the top of a trapped plume at

890m below the sea surface. The range of droplet sizes assumed is from experimental work done by

Delvigne and Sweeney (1998). One can see that if the majority of oil droplets are in the range of 500

micrometers, the oil will rise to the surface in about one day. If the majority of the droplet sizes are

on the order of 100 micrometers, the mean rise time will be more like a month. ASA has applied this

model system to several potential blowout locations in drilling areas off the Americas, the UK, and

Africa. The need for validating data, both for hydrate formation and for released oil particle sizes is

demonstrated by these model simulations.

CONCLUSIONS

A model of the movement of oil and gas plumes released at depths more than 500m below the sea

surface has been developed and applied to several potential scenarios in oil-producing areas 
329

Table 2E.1. Rise velocities and times from 890 m depth for various size oil droplets. Droplets are

assumed to have the Foinaven crude specific gravity of 0.902 in seawater with a

specific gravity of 1.026. Rise velocities are computed using the Stokes formula with

a dynamic viscosity of 1.8 x10-6 (m2/s).

Droplet diam. 

(μm)

Oil Specific

Gravity

V

(cm/s)

V

(m/day)

Rise Time from

890m (days)

50 0.902 0.00886 7.7 116.3

100 0.902 0.03544 30.6 29.1

200 0.902 0.1418 122.5 7.3

300 0.902 0.3189 275.6 3.2

400 0.902 0.567 489.9 1.8

500 0.902 0.8605 743.5 1.2

throughout the world. The importance of the droplet size distribution for oil released during these

blowouts is shown. The need for field data of natural or simulated oil blowouts is needed for the

calibration of such deep blowout models.

REFERENCES

Applied Science Associates, Inc. (ASA). 1996. Technical Manual for Spill Impact Modeling

(SIMAP). Version W1.0, Applied Science Associates, Inc., Narragansett, RI.

Applied Science Associates, Inc.(ASA). 1997. OILMAP Users Manual Applied Science Associates,

Inc., Narragansett, RI.

Bishnoi, P.R. and B.B. Mainik. 1979. Laboratory study of behaviour of oil and gas particles in salt

water, relating to deepwater blowouts. Spill Technology Newsletter, 4:1, pp. 24-36.

Bishnoi, P.R., A.K. Gupta, P. Englezos, Kalogerakis. 1989. N. Fluid Phase Equilibria, 83, 97.

Delvigne, G.A.L., and L.J.M. Hulsen. 1994. Simplified laboratory measurement of oil dispersion

coefficient – application in computations of natural oil dispersion. Proceedings of the Seventeenth

Arctic and Marine Oil Spill Program, Technical Seminar, 8-10 June 1994, Vancouver, British

Columbia, Canada, pp. 173-187.

Delvigne, G.A.L., and C.E. Sweeney. 1988. Natural dispersion of oil. Oil & Chemical Pollution 4,

281-310.

Kolluru, V., M. L. Spaulding, and E. Anderson. 1994. A three-dimensional subsurface oil dispersion

model using a particle based technique, 17th Arctic and Marine Oil Spill Program, Technical

Seminar, 8-10 June 1994. Vancouver, British Columbia, Canada, pp. 767-784.
330

Spaulding, M.L., P. R. Bishnoi, E. Anderson, and T. Isaji. 2000. An Integrated Model for Prediction

of Oil Transport from a Deep Water Blowout. 23rd Arctic and Marine Oil Spill Program,

Technical Seminar, 14-16 June 2000, Vancouver, British Columbia, Canada, pp. 611-635.

Spaulding, M.L., E. Howlett, E. Anderson, and K. Jayko. 1992a. OILMAP a global approach to spill

modeling. 15th Arctic and Marine Oil Spill Program, Technical Seminar, 9-11 June 1992.

Edmonton, Alberta, Canada, pp. 15-21.

Spaulding M.L., E. Holwett, E. Anderson, and K. Jayko. 1992b. Oil spill software with a shell

approach. Sea Technology, April 1992. pp. 33-40.

Spaulding, M.L., E. Anderson, T. Isaji, and E. Howlett. 1993. Simulation of the oil trajectory and fate

in the Arabian Gulf from the Mina al Ahmadi spill. Marine Environmental Research, 36:2, pp.

79-115.

Spaulding, M.L., V. S. Kolluru, E. Anderson, and E. Howlett. 1994. Application of three dimensional

oil spill model (WOSM/OILMAP) to hindcast the Braer spill. Spill Science and Technology

Bulletin, 1:1, pp. 23-35.

Spaulding, M.L., T. Opishinski, E. Anderson, E. Howlett, and D. Mendelsohn. 1996a. Application

of OILMAP and SIMAP to predict the transport and fate of the North Cape spill, Narragansett,

RI. 19th Arctic and Marine Oil Spill Program, Technical Seminar, 12-14 June 1996. Calgary,

Alberta, Canada, pp. 745-776.

Spaulding, M.L., T. Opishinski, and S. Haynes. 1996b. COASTMAP: An integrated monitoring and

modeling system to support oil spill response. Spill Science and Technology Bulletin, 3:3, pp.

149-169.
331

ASA OIL SPILL MODELS: 3-D FATES AND EFFECTS MODELING

APPLICATIONS FOR GULF OF MEXICO SPILLS

Dr. Deborah French McCay

Applied Science Associates, Inc.

INTRODUCTION

Over the past twenty years, Applied Science Associates has developed a system of models that

evaluate the fates and biological effects of oil and chemical spills. The models use a common

framework of geographical and current databases for input data, and outputs are displayed in a

Windows interface that shows surface oil distributions and concentrations of oil and chemicals in the

water and sediments.

SIMAP (for oil) and CHEMMAP (for chemicals) were originally developed from ASA’s oil

trajectory models and the fates and biological effects submodels in the Natural Resource Damage

Assessment Model for Coastal and Marine Environments (NRDAM/CME). The NRDAM/CME was

developed by ASA for the U.S. Department of the Interior. The NRDAM/CME (Version 2.4, April

1996) was published as part of the CERCLA type A Natural Resource Damage Assessment (NRDA)

Final Rule (Federal Register, 7 May 1996, Vol. 61, No. 89, p. 20559-20614). However, considerable

further development beyond that contained in the NRDAM/CME has been accomplished in SIMAP

(French et al. 1999) and CHEMMAP (French 2001), including incorporation of hydrodynamic

modeling for currents, specific model tracking of subsurface oil, and probabilistic modeling for both

oil and chemicals.

The presentation and summary below include

• Descriptions of the models

• Validation studies

• Applications to the Gulf of Mexico (GOM)

PHYSICAL FATES MODEL

The physical fates model estimates distribution (as mass and concentrations) of contaminant on the

water surface, on shorelines, in the water column, and in sediments. The model is three-dimensional,

using a latitude-longitude grid for environmental data and projecting model results into that grid. A

geographical information system (GIS) database supplies values for water depth, sediment type,

ecological habitat, shoreline type, and ice cover throughout the gridded domain. The chemical

database supplies physical-chemical parameters required by the model. The user supplies a wind time

series and current data set specific to the time and location of the spill.
332

The physical fates model tracks the center and surrounding distribution of mass for a large number

of “spillets” (sub-lots of the total mass spilled). If the density of a spilled chemical is less than or

equal to that of water (e.g., oils) the model estimates surface spreading, slick transport, entrainment

into the water column, and evaporation, to determine trajectory and fate at the surface. Surface slicks

interact with shorelines, depositing and releasing material according to shoreline type. A contaminant

heavier than water is initially modeled as a convective plume which may reach an equilibrium

position in a stratified water column or sink to the bottom.

The processes modeled include spreading, evaporation, transport, dispersion, emulsification,

entrainment, dissolution, volatilization, partitioning, sedimentation, and degradation. For oil, mass

is tracked separately for low molecular weight aromatics (monoaromatics, BTEX, and 2 to 3-ring

polynuclear aromatic hydrocarbons, PAHs) which cause toxicity, other volatiles, and non-volatiles.

The physical fates model computes concentrations in the water column and sediments, and the area

of water and shoreline covered by surface slicks in space and time. This information is passed to the

biological effects model, which then calculates biological effects of those concentrations and areas

of coverage.

BIOLOGICAL EFFECTS MODEL

The biological effects model calculates the portion of a population affected by slicks and subsurface

contamination. Habitat-specific estimates of fish, shellfish, bird, mammal, and reptile abundance, and

productivity of plant and animal communities at the base of the food chain, are used to determine

biomass lost as a result of the spill. A rectangular grid of habitats represents the area potentially

affected by the spill, with each grid cell coded for habitat type. Habitats include deepwater, nearshore,

wetland, and shoreline environments. Fish, birds, and mammals are assumed to move at random

within each habitat. Planktonic stages (eggs and larvae in the water column) are moved with the

currents.

In the model, surface slicks (e.g., oil and petroleum products) interact with wildlife (birds, mammals,

reptiles). A portion of wildlife in the area swept by the slick are assumed to die based on probability

of encounter with the slick, dosage, and mortality once oiled. Estimates for these probabilities are

derived from information on behavior and field observations of mortality under similar

circumstances.

The biological model estimates acute toxic response of aquatic biota. Fish and their eggs and larvae

are affected by dissolved contaminant concentration (in the water or sediment). Mortality is

calculated using laboratory acute toxicity test data (LC50, concentration lethal to 50% of test

individuals) corrected for temperature and duration of exposure, and assuming a log-normal

relationship between percent mortality and dissolved concentration. 

The effects of oil on aquatic organisms may be quantified as a function of (1) low molecular weight

aromatic content and composition in the oil and (2) the fate and partitioning of those components in

the environment. Low molecular weight aromatics have a narcotic mode of action. Thus, an additive

toxicity model may be used to estimate the toxicity of the aromatic mixture in oil. Estimated toxicity
333

of the individual aromatics is based on a regression against the octanol-water partition coefficient

(Kow), a measure of solubility. This model was verified with available oil bioassay data. Both

volatility and solubility decrease with increasing Kow, while toxicity increases strongly with Kow. The

aromatics with the lowest Kow dissolve the fastest, but are also rapidly lost from the water due to

volatilization. If the dissolution of higher Kow aromatics is enhanced by submergence of the oil and

high turbulence, which greatly increases the surface area of the oil-water interface, the concentrations

of the higher molecular weight aromatics (i.e., PAHs) can become high enough to cause significant

acute toxicity.

Movements either of biota, active or by current transport, are accounted for in determining

concentration and duration of exposure. Organisms killed are integrated over space and time by

habitat type to calculate a total kill. Lost production of plants and animals at the base of the food

chain is also computed. Lost production of fish, shellfish, birds, and mammals due to reduction or

contamination of food supply is estimated using a simple food web model.

In addition to the direct kill and food-web losses of eggs and larvae, fish young-of-the-year may be

lost via habitat disruption. This loss is included in the model for wetland and other nursery habitats

destroyed by lethal concentrations or oiling. Losses are related to the habitat loss. Thus, recovery of

spawning and nursery habitat in wetlands follows recovery of plant biomass and production.

The biological effects model computes reduction of fish and shellfish catch in the present and future

years using standard fisheries models. Lost catch includes losses due to mortality of adults, juveniles

and larvae due to the spill. Relatively high natural mortality rates of fish eggs and larvae are

considered in the model, since a high number killed at the time of the spill would have died anyway.

Young-of-the-year (eggs, larvae, and juveniles less than one year old) of each fish species category

are tracked as percents of the one-year-old population. Young-of-the-year and older age classes are

not assumed to inhabit the same environment concurrently, and their losses are calculated separately.

Using similar models, the numbers of birds and mammals missing and not hunted in present and

future years are also calculated. For all fish and wildlife, population losses are the number not left

alive in present and future years as the result of the spill, after constant natural mortality (and hunting

mortality) is subtracted.

SIMAP MODEL VALIDATION

The physical fates and biological effects models in SIMAP have been validated using data from

twenty-eight oil spills. For twenty-seven of these case histories (French and Rines 1997),

observational data were available for surface oil impacts, as field observations after spills focus on

these effects. The validation studies show that the model is capable of hind-casting the oil trajectory

and shoreline oiling, given (1) accurate observed wind data following the spill and (2) a reasonable

depiction of surface currents, both tidal and background. As winds and currents are the primary

forcing variables on oil fate, obtaining accurate data on these is very important to the accuracy of any

simulation.
334

Figure 2E.3. Model and field data on the Exxon Valdez oil spill.

In most cases, impact information for the spill consists primarily of counts of rescued or dead wildlife.

The model results either agree well with field estimates or underestimate the observed kill, as with the

Exxon Valdez spill shown in Figure 2E.3. The cases where wildlife kills are underestimated are those

in which an unusually high abundance of certain species occurred in the spill path, or in which data

on abundance of animals were not available. Many of these cases were in fact considered highly

significant spills both because of the size of the spill and of the presence of unusually high

aggregations of certain wildlife species. Modeling results show that the impact algorithms in the model

are valid when input data on abundance are accurate.

In one case, the North Cape oil spill of January 1996 in Rhode Island, field observations were available

for both surface and subsurface fates and impacts. The model’s prediction of the oil’s fate agreed with

observations of surface oil movements and measurements of total hydrocarbons and aromatics in the

water. The model estimate of birds oiled was 2,200-4,400, depending on the pre-spill abundance data

assumed. The mid-point of this range is 8.5 times the number of birds collected on beaches, in

agreement with estimates for other spills. (The negotiated settlement used a factor of six for this spill.)

Impacts on water column organisms were validated by comparison of the model estimate to the field

observations of the lobster kill (8.3 million and 9 million, respectively). The model estimates of

impacts to other marine species were used in the government’s natural resource damage claim to the

responsible party. This claim was settled based on these estimates of injury.
335

Success of a model simulation is dependent on both the algorithms and the accuracy of the input data.

Results of the validation exercises verified the model algorithms. The most important input data in

determining accuracy of results are winds, currents, and biological abundances of the affected species.

Thus, the model system applied with accurate environmental and biological data inputs, can

quantitatively and objectively estimate the impacts of spills into aquatic systems.

STOCHASTIC MODEL APPLICATIONS FOR ECOLOGICAL RISK ASSESSMENT

Stochastic modeling is used to quantify the probability of impact from an oil or chemical discharge.

These data provide needed information for risk assessments and contingency planning. Stochastic

modeling consists of running the model many times, varying key parameters, such as environmental

conditions and spill amount, to create a picture of the most probable impacts from expected spills.

For SIMAP and CHEMMAP applications in the GOM, long-term (>10 year) historical wind and

current data are assembled for the area of interest. The model is run multiple times, randomizing the

start date and time within a specified range of months of the year. The spill volume is either held

constant or randomized from 0% to 100% of the worst-case amount each run. An effects endpoint

is selected, which provides a threshold above which probabilities are to be reported. 

Model output includes maps of oil/chemical

• mass on the water surface,

• mass on shorelines,

• dissolved concentration in the water column,

• concentration of submerged particles in the water column, and

• mass in the sediments.

Statistics are produced for each location (cell) in the model grid, including

• probability of (any) mass or concentration exceeding the threshold, 

• time when mass or concentration first exceeds threshold, 

• mean expected maximum mass or concentration (i.e., mean of all runs), and

• worst-case (maximum possible) mass or concentration (i.e., maximum of all runs). 

The worst-case spill conditions is identified from the probability analysis described above. The

worst-case is for those wind and current conditions that maximize exposure to sensitive resources

near the spill site. A specific worst case scenario may then be forecast using the three-dimensional

fates and biological effects models in SIMAP or CHEMMAP. This quantifies the worst possible
336

Figure 2E.4. Sample worst-case scenario map from chemical spill.

concentrations and biological effects for a spill site (see Figure 2E.4). Sensitivity analysis provides

measures of uncertainty for these predictions.

Spill Consequence Modeling for the NRC Double-Hull Tanker Committee

The U.S. Coast Guard commissioned a National Research Council (NRC) committee to evaluate the

cost-benefits of double hull tankers as opposed to other tanker designs. At the request of the NRC

Double-Hull Tanker Consequences Sub-Committee, ASA performed oil spill consequence modeling

using SIMAP in stochastic mode. The purpose of the spill modeling was to develop quantitative

estimates of the relationship between spill size and consequences. Consequences include all of the

economic, financial and environmental implications of a spill. Spill modeling provided measures

of oil-impacted areas and volumes to be used in these calculations.

The modeling was performed for spill sites in different regions of the US, including the GOM near

Galveston. Model scenarios included two oil types and seven volumes. The results showed that the

impact (consequences) of one large spill is less than the sum of several smaller spills totaling the

same volume (French et al. 2000). The NRC committee is evaluating the over-all risks for double

hull tankers, where spills would be larger and less frequent, versus other designs.
337

Chemicals Related to Deepwater Oil and Gas Operations in the Gulf of Mexico

ASA performed chemical spill modeling with CHEMMAP, which was used to analyze

environmental risks associated with chemical products used in deepwater oil and gas operations in

the GOM. The team lead by A.D. Little used the model results to evaluate risks of impacts from

spills. Seventeen scenarios were run for hypothetical spills in the offshore GOM. An assessment of

potential ecological risks is based on these modeling results (Boehm et al. 2001).

CONCLUSIONS

Numerical models offer a powerful range of tools to better assess the consequences of spill incidents

whether this be at the planning stage or to evaluate a specific spill incident. These integrated model

systems may be used to quantify environmental impacts of real hazardous spill events (for natural

resource damage assessment and other purposes), of hypothetical spills (probabilities in a risk

assessment) and of response management strategies (contingency planning). Embracing the

traditional scientific methods of collecting and analyzing relevant environmental data, these tools

can convey to interested parties answers to important marine-related environmental issues, which

can be complex and often difficult to assimilate.

REFERENCES

Boehm, P., D. Turton, A. Raval, D. Caudle, D. French, N. Rabelais, R. Spies, and J. Johnson. 2001.

Deepwater Program: Literature Review, Environmental Risks of Chemical Products Used in

Gulf of Mexico Deepwater Oil & Gas Operations, Final Report to US Department of the

Interior, Minerals Mgmt. Service, Gulf of Mexico OCS Region, February 2001, OCS Study

MMS 2001-011, 326 pp. plus appendices.

French, D. P. 2001 Chemical Spill Model (CHEMMAP) for Forecasts/Hindcasts and Environment

Risk Assessment. Proceedings of the 2001 24th Arctic and Marine Oil spill Program (AMOP)

Technical Seminar 13-15 June 2001.

French, D.P. and H. Rines. 1997. Validation and use of spill impact modeling for impact assessment.

In Proceedings of the 1997 International Oil Spill Conference, American Petroleum Institute, Fort

Lauderdale, Florida, Publication No. 4651, pp. 829-834, 1997.

French, D., H. Schuttenberg, and T. Isaji. 1999. Probabilities of oil exceeding thresholds of concern:

examples from an evaluation for Florida Power and Light. in Proceedings of the 22nd Arctic and

Marine Oil Spill Program (AMOP) Technical Seminar, 2-4 June 1999, Environment Canada,

pp.243-270.

French, D., H. Schuttenberg, T. Isaji, C. Galagan, and D. Field. 2000. Final Report of the National

Research Council Double-Hull Tanker Consequences Sub-Committee. 28 June 2000. ASA

report 99-149.
339

SESSION 2F

SOCIOECONOMIC MODELING

Chairs: Ms. Stephanie Gambino, Minerals Management Service

Ms. Vicki Zatarain, Minerals Management Service

Date: December 6, 2000

Presentation Author/Affiliation

Modeling the Economic Impact of Offshore

Activities on Onshore Communities

Dr. David E. Dismukes

Econ One Research, Inc. and

Center for Energy Studies

Louisiana State University

Williams O. Olatubi

Center for Energy Studies

Louisiana State University

The Minerals Management Service’s New

Consistent Approach to Modeling Regional

Economic Impacts

Ms. Vicki Zatarain

Mr. Kim Coffman

Minerals Management Service

An Analytical Model of Operating Platforms

on the U.S. Gulf of Mexico Outer Continental

Shelf (OCS), 1947-1997

Dr. Omowumi O. Iledare

Dr. Allan G. Pulsipher

Dr. Dmitry V. Mesyanzhinov

Dr. Alan Dupont

Ms. Qiaozhen “Lucy” Zhu

Center for Energy Studies

Louisiana State University

Modeling of Platform Installations and

Removals: The MMS Perspective

Mr. Thierry DeCort

Ms. Stephanie Gambino

Minerals Management Service

The Offshore Environmental Cost Model Dr. William King

Minerals Management Service
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1

 A similar, but slightly different, version of this paper was presented and published in the proceedings of the

International Association of Energy Economics Annual Meetings of September 2000. 

MODELING THE ECONOMIC IMPACT OF OFFSHORE ACTIVITIES

ON ONSHORE COMMUNITIES

Dr. David E. Dismukes

Econ One Research, Inc. and

Center for Energy Studies

Louisiana State University

Williams O. Olatubi

Center for Energy Studies

Louisiana State University

INTRODUCTION1

The economic impact of offshore activities has become an increasingly important issue to the

Department of Interior, Minerals Management Service (MMS). A very large portion of this research

is subsumed within the agency’s Environmental Studies Program (ESP) and defined in its National

Strategic Plan (NSP):

The ESP Strategic Plan addresses a wide variety of environmental concerns and

issues on a national scale by identifying emerging and ongoing program areas. It

complements and builds upon broader strategic plans that set Agency-wide policies

and directions. Within these broad issues or themes, multi-disciplined studies will

be developed, as budget allocations allow (LTG Associates, Inc. 2000).

The socioeconomic studies component of the program

• Provides information essential to understanding the consequences of OCS-related activities

for the populations, economies, and social and cultural systems in areas where the activities

occur;

• Supports the MMS’s planning and management processes; and

• Provides information essential for effective interaction with the public about the effects of

OCS activities (LTG Associates, Inc. 2000).

The MMS’s primary legal mandate to analyze the socioeconomic impacts of natural resource

management issues is provided in both the Outer Continental Shelf Lands Act, as amended in 1978

(OCSLAA), and the National Environmental Policy Act of 1969 (NEPA). 
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Over the past several years, the ESP has been becoming increasingly more engaged in the

socioeconomic research of coastal communities in support of its EIS mission. In the past 10 years,

the quantity of research funded under this program has tripled. While one cannot predict the levels

of funding that will be provided in years to come, a recent meeting of social scientists and

researchers indicated that both interest in and commitment to these issues would continue to be

strong. Of the three major MMS regions (Alaska, Pacific, and Gulf of Mexico), the Gulf of Mexico

(GOM) would appear to have a pressing need for continued socioeconomic impact analyses. The

Gulf, in addition to providing a significant number of reserves and production, is also undergoing

unique developments in both deepwater activity (900 meters and above) and the potential

development of frontier areas in the eastern Gulf off the coast of Florida. 

As early as the mid-1980s, the MMS Gulf of Mexico region began its efforts to model the

implications that offshore development had on coastal communities. For close to 10 years, however,

a good portion of these regional modeling initiatives focused more on past consequences of outer

continental shelf (OCS) oil and gas development than on predictive methods. These initiatives could

be broken into two general categories: (1) individual historic “consequences” analyses and (2) the

development of baseline analyses (Lutton and Cluck 2000). Information from both types of studies

were regularly used to examine economic impacts to local communities for EIS purposes.

In the past several years, however, there has been a concerted effort by the MMS to develop more

sophisticated modeling approaches that incorporate both more quantitative rigor and applied realism.

One of the first studies to examine offshore activities from a more rigorous and applied perspective

was conducted by Foster Associates (Ongoing) for the federal waters off the coast of Alabama Wade

and Mott 1998). This study revealed a number of unique expenditure patterns that were required to

support production of caustic (high H2S) natural gas. The results of this study help move the agency

in the direction of (1) employing Input-Output (IO) models as a basis for measuring the economic

impact of all offshore activities and (2) incorporating real-world differences in the production

characteristics of particular offshore areas.

One of the major advantages of moving forward with the use of IO models was their ability to allow

a researcher to simulate the effects that a change in one or several economic activities has on the

entire regional economy. It is more predictive in the sense that the economic impacts associated with

hypothetical events, like the opening of several new offshore blocks in the GOM, can be modeled.

A shortcoming with most IO analysis is that the impact drivers (or multipliers) in the model are

typically taken from national, as opposed to regional, trends and industries. Such an approach

assumes, among other things, that industries in any given area will use inputs in the same proportion

as the national average. The concept of multipliers plays key roles in the understanding of regional

economic models because they define and form the basis of impact analysis. Multipliers are based

on the fundamental notion that one person’s expenditure is another’s income, and since consumption

usually increases when income increase, any extra expenditure feeds through into further

expenditure. These effects become smaller and smaller amounts each time around because of

leakages of income outside the region or system. 
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For oil and gas firms operating in the Gulf OCS, the standard IO and hence, its accompanying

multiplier analysis (i.e. impact estimation), assumes that input expenditures are made in the same

proportion as the national oil and gas industry average. Not only does such an approach assume

regional similarities, but it also assumes that onshore and offshore production functions are similar.

It is this last problem that causes the most difficulty in using existing regional IO models to examine

the economic impacts of offshore activities. The purpose of this paper is to discuss methodological

and data collection methods that can help remedy this potential problem.

MODELING METHODS AND ISSUES

There are a number of methodological issues associated with modeling something as complicated

and multifaceted as the offshore oil and gas industry. Our research goal has not been to address

every methodological issue, but to concentrate on four of the more important issues that were

identified by MMS:

1. Can unique offshore expenditure profiles be defined and incorporated into a standard

economic input-output framework;

2. Can these expenditure profiles be separated into individual offshore activity phases;

3. Can these expenditure profiles be defined for a given water depth; and

4. How should these offshore expenditure profiles be allocated to onshore areas?

Defining Offshore Expenditure Profiles

The exploration, development, and operation of offshore facilities present considerable logistical

challenges. These challenges can be inferred from the types of expenditures made by offshore

operators. Thus, the first step in the analysis of offshore activities was to define a relevant set of

expenditures, taking into account many of the unique expenditures required this special sector of the

oil and gas industry. Some of the expenditure categories with unique implications for offshore

activities include:

• Water and Air Transportation—Transportation is important in moving both personnel and

equipment from onshore supply and staging bases to areas supporting offshore activities.

• Food and Catering Services—Often food and catering services are contracted by offshore

operators to feed crews supporting exploration, development, and production activities;

• Water Supply—Potable water for drinking, as well as water for certain types of drilling

muds, lubricants, and fluids, has to be transported to offshore areas;

• Waste Disposal—While this activity is important to both onshore and offshore activities,

transportation and onsite storage can create a number of unique logistical challenges to

offshore activities; 
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2

 Data methods underlying most input-output analysis are based on survey, nonsurvey (or ready-made), or hybrid

approaches.

• Turbines and Fuel—Most offshore platforms have both primary and secondary power

generation equipment as well as primary, and in some cases secondary, fuel to operate these

generators; and

• Communications, Instrumentation and SCADA Systems—Digital and mobile technologies

have had a growing importance for offshore activities.

Our primary IO modeling approach relies on IMPLAN. IMPLAN is an input-output modeling

system that belongs to the class of ready-made approaches, originally developed by the U.S. Forest

service. However, our subsequent analysis supplemented the existing IMPLAN data with other

primary or secondary data; hence, it is classified as a hybrid approach. Such an approach improves

impact estimates considerably because of reliability engendered by more realistic ‘local’ conditions

as opposed to ‘average’ national outlook.2

During the course of our research, we provided the MMS with a comprehensive listing of the unique

expenditure categories, and their IMPLAN sector identifications. The categories used in modeling

the economic impacts of offshore activities have been provided in Table 2F.1.

Defining Offshore Activity Phases

Another important area of examination is defining the relevant phases of offshore activity. Most IO

models, as well as National Income and Product Accounts (NIPA), treat oil and gas activities in a

highly aggregated form. As noted before, onshore and offshore activities are rarely separated, and

even then, are aggregated into either drilling or production activities. MMS, however, must consider

a range of offshore oil and gas activities over relatively long periods of time in the EIS evaluation.

The activities that were defined by MMS as being important for socioeconomic modeling purposes

include: exploratory drilling; development drilling; platform fabrication and installation; pipeline

fabrication and installation; gas processing installation; production; workovers; oil spills; and

platform removal & abandonment. For typical EIS analyses, socioeconomic analyses will begin with

a forecast of activities (in units) for each of the above activity phases. The Resource Evaluation

Division within MMS develops these forecasts independently. These units, when multiplied by total

costs, yield the total potential economic shock resulting from that activity. Thus, if a given potential

lease sale is forecasted to yield five (5) new exploratory wells at an average total cost of $2 million

per well, then the total direct economic shock would be $10 million. The next step in the process

is to allocate this $10 million impact by the expenditure profile developed for exploratory drilling.

MMS believed it was important for their impact modeling to develop different expenditure profiles

by activity phase given their tendency for variability and substantial composition differences. In

addition, there is a tendency for expenditure patterns, and activities, to shift as the development of

a potential lease matures. This has implications for economic impacts since many expenditures can

move from more capital intensive, construction-oriented activities in the exploration, development,
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Table 2F.1. Offshore expenditure categories.

IMPLAN

SECTORS Sector Description

IMPLAN

SECTORS Sector Description

38 Oil & Gas Operations 399 Transportation Equipment, NEC

50 New Gas Utility Facilities 401 Lab Equipment

53 Misc Natural Resource Facility

Construct

403 Instrumentation

56 Maintenance and Repair, Other

Facilities

435 Demurrage & /Motor Freight

57 Other Oil & Gas Field Services 436 Water Transport

160 Office Furniture and Equipment 437 Air Transport

178 Maps and Charts (Misc

Publishing)

441 Communications

206 Explosives 443 Electric Services

209 Chemicals, NEC 444 Gas Production/Distribution

210 Petroleum Fuels 445 Water Supply

232 Hydraulic Cement 446 Waste Disposal

258 Steel Pipe and Tubes 454 Eating/Drinking

284 Fabricated Plate Work 455 Misc Retail

290 Iron and Steel Forgings 459 Insurance

307 Turbines 462 Real Estate

311 Construction Machinery &

Equipment

469 Advertisement

313 O&G Field Machinery 470 Other Business Services

331 Special Industrial Machinery 473 Misc. Equipment Rental and Leasing

332 Pumps & Compressors 490 Doctors & Veterinarian Services

354 Industrial Machines, NEC 494 Legal Services

356 Switchgear 506 Environmental/Engineering Services

374 Communication Equipment, NEC 507 Acct/Misc Business Services

392 Shipbuilding and Ship Repair 508 Management/Consulting Services

 509 Testing/Research Facilities

pipeline, and gas processing construction phase to more labor intensive, maintenance-oriented

activities in the production, workover, gas processing and transportation activities.

For instance, steel pipe expenditures can represent close to 29% of total expenditures during

platform fabrication activities yet represent only 3% of total expenditures during the production

phase. Likewise, instrumentation costs can represent close to 3% of total expenditures during

production, but could be a relatively insignificant cost during all other offshore activity phases.

Defining Relevant Water Depths

Another methodological challenge rests with modeling variations in expenditure profiles across

water depths. For instance, should, or do, expenditure profiles change as offshore activities move

into deeper waters? Conventional wisdom would tend to support the hypothesis that there is a 
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Table 2F.2. Expenditure profiles for development drilling by water depth.

Sectors Sector Description 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters

38 Oil & Gas Ops 0.65341 0.52344 0.64192 0.69198

57 Other Oil & Gas Svc 0.03447 0.02107 0.04069 0.03348

210 Petroleum Fuels 0.02746 0.03349 0.03049 0.02664

232 Hydraulic Cement 0.06566 0.11871 0.07490 0.06410

258 Steel Pipe and Tubes 0.07104 0.15527 0.06077 0.05149

313 O&G Field Machinery 0.01545 0.01524 0.01039 0.00947

403 Instrumentation 0.04110 0.04222 0.04375 0.03817

436 Water Transport 0.08355 0.08276 0.08873 0.07739

437 Air Transport 0.00787 0.00780 0.00836 0.00729

Total 1.00000 1.00000 1.00000 1.00000

positive, and probably close to linear, relationship between certain relative costs and water depth.

Water transportation costs come to mind as being a relative cost that should increase as water depth,

and hence distance, increases. However, the unique realities of offshore activities, coupled with

inconsistencies in data collection and (internal) reporting, can lead to significant challenges in what

should appear to be an obvious conclusion. Table 2F.2 presents an example of expenditures for

development drilling where shifts in expenditure trends are obvious for Sector 38 (oil and gas

operations).

Defining the Onshore Allocation of Offshore Activities: The allocation of expenditures to onshore

areas is probably one of the more important factors for determining the region-specific economic

impacts associated with offshore activities. These break-outs are important because certain onshore

support activities tend to be concentrated in particular geographic areas. This concentration has

tended to occur in Louisiana and Texas and has continued despite the movement of offshore

activities into deeper water and into the Central Eastern portions of the GOM.

The first task at hand in this portion of our analysis has been to allocate offshore expenditures, by

commodity categories outlined in Table 2F.1, to the 10 major onshore regions defined by MMS.

These regions are presented in Figure 2F.1. Additional regions included in the analysis include

Other, Non-Coastal Gulf of Mexico and Rest of World (ROW).

DATA COLLECTION ISSUES AND CHALLENGES

During the course of our analysis, two data collection issues became particularly important:

1. How to identify, locate, and secure reliable sources of information that did not require the

use of survey instruments; and

2. How to reconcile accounting classifications to economic classifications.
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Figure 2F.1. MMS Gulf of Mexico coastal areas.

The first issue was the more problematic of the two and one that plagues ongoing MMS social

science research. Our research needed to find a way to collect information that did not use survey

or survey-type instruments. Therefore, mailing questionnaires to numerous companies operating

offshore was not allowed. This restriction on data collection is placed on MMS by the Paper Work

Reduction Act of 1980, and reauthorized in 1995. 

This purpose of the Act is to minimize the paperwork burden the federal government places on the

public and to improve the quality and use of federal information (Lauterback 2000). The Act also

requires each federal agency to seek and obtain approval from the Office of Management and

Budget (OMB) before requesting information from ten or more persons. Furthermore, any reporting,

record-keeping, or disclosure requirement contained in a rule is deemed to involve ten or more

persons. OMB approval is also needed to continue a collection for which OMB’s approval and the

validity of the OMB Control Number are about to expire. OMB usually approves a collection for

a maximum of three years.

To use a survey-based approach for this research project, we would have had to enter into a survey

instrument review process that, under the best of situations, would have taken six to eight months.

Another four to six months probably would have been required to execute the survey, assuming the
348

best of luck on survey responses and data collection. This project, like many MMS-funded research

projects, was needed for immediate use and required completion within 12 months. OMB survey

requirements, in this instance, seemed too onerous to use as a vehicle for collecting this type of

information.

Our alternative approach was to compile this information from a variety of different sources, that

varied by offshore activity phase. In general, we scoured all government, industry, trade, and

academic publications, periodicals, and databases for relevant information. Some of these

publications were readily available and straightforward. For instance, there is considerable

information on drilling expenditures and patterns from the Joint Association Survey of the U.S. Oil

and Gas Producing Industry compiled annual and published (jointly) by the American Petroleum

Institute (API), the Independent Petroleum Association of America (IPAA), and the Mid-Continent

Oil and Gas Association. Likewise, considerable information on pipeline construction costs and

expenditures is filed regularly before the Federal Energy Regulatory Commission (FERC).

When direct “secondary” sources of published information were unavailable, we turned to

information requests from industry or relied on trade association information and surveys previously

(and independently) compiled. These requests were limited and did not violate the spirit or intent

of the Paperwork Reduction Act. Information gathered in this process was simply used to fill in the

blanks from our search of secondary sources of information.

The additional data issue was taking disparate documents and information, most of which were

provided in accounting-based formats, and translating them into economic information for modeling

purposes. Accounting information, for instance, rarely makes distinctions between fixed and variable

costs or clear-cut differentiations between capital and labor. Thus, a painstaking process of

reviewing accounting information on a line-by-line basis was required. Because both accounting

entries, and the economic classifications included in Table 2F.1, are limited, judgment calls were

required to separate a limited amount of information into limited classifications.

The process of making judgment calls on some classifications was most apparent in dealing with

contracted services. Many costs associated with offshore activities would appear as contracted

services from one firm to another, although both were engaged in the same activity. For instance,

a company developing an exploratory well(s) would often, particularly in shallow water, contract

drilling services out to a separate company. This company, in turn, would have direct expenditures

for labor, materials, equipment, and other items that would “escape” our data collection ability. This

has led to slight biases (overstatements) in general categories such as IMPLAN sector 38 (oil and

gas operations) or 57 (other oil and gas field services).

CONCLUSIONS

The process of trying to create real-world models for offshore oil and gas activities in the GOM can

yield meaningful difference from the standard approaches contained in generalized IO models. The

MMS motivation for moving forward with creating these customized approaches appears to be

justified. Using a hybrid approach based primarily on IMPLAN and a more realistic allocation and

expenditure profiles helps to improve the existing multipliers—a crucial link in generating reliable
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Table 2F.3. Estimated economic impacts for exploratory drilling, LA-2 Region.

Estimated Annual Impact -- Standard Analysis (1998 Dollars)

 Direct Indirect Induced Total

Output 179,502,016 16,454,092 15,543,905 211,500,011

Labor Income 14,524,824 3,839,397 5,936,279 24,300,500

Total Value Added 49,131,317 8,382,280 9,560,596 67,074,189

Employment (Number) 273 111 246 629

Estimated Annual Impact -- Modified, Gulf-Specific Analysis (1998 Dollars)

 Direct Indirect Induced Total

Output 178,219,407 29,111,563 21,800,854 229,131,826

Labor Income 17,490,114 8,875,273 8,325,832 34,691,221

Total Value Added 47,687,687 15,538,328 13,409,060 76,635,075

Employment (Number) 391 278 345 1,014

impact estimates. Table 2F.3 presents a summary of the IMPLAN output for the LA-2 region

identified in Figure 2F.1. Two columns have been provided that present the economic output from

shocking both the generalized IMPLAN model and the hybrid IMPLAN model using our specialized

expenditure profiles and onshore allocations. 

The differences in output, for instance, are 8% lower using our revised method of measuring

economic impacts, than the standard approach included in IMPLAN. Labor income, however, is

about 42% higher in our analysis relative to standard approaches. Value added is 14% higher in our

model, while employment opportunities, represented by the number of jobs created by new

exploratory wells, is 62% higher in our model than the standardized approach. These results, at

minimum, support the notion that there are unique economic differences in the offshore industry and

that further research should be conducted to better understand those differences and the impacts they

have on human communities of the GOM.

ACKNOWLEDGMENTS

The authors would like to acknowledge the financial assistance of the Minerals Management Service

in funding a portion of this study through the Coastal Marine Institute program at the Louisiana State

University. We would also like to thank the additional matching financial support provided by the

Center for Energy Studies, Louisiana State University and its Industry Associates Advisory Board.

This paper is an abbreviated version of a much longer report on the topic that is forthcoming. This

paper, its lengthier report, and underlying research could not have been possible without

considerable assistance from a number industry, academic, and government professionals. While

a lengthier acknowledgment will be provided in our forthcoming report, we would like to thank Kim

Coffman, Stephanie Gambino, Vicki Zatarain, and Richard Deselles, all with the MMS, for their
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comments, suggestions, assistance, and advice. We would also like to thank Barbara Kavanaugh,

Ric Pincomb, and Dmitry Mesyanzhinov, at CES/LSU, for their research assistance.

REFERENCES

Foster Associates. Ongoing. Historical and Socioeconomic Assessment of Oil and Gas Industry in

Coastal Alabama. No. GM-96x6, MMS Contract No. 30829.

Lauterback, Jo Ann. 2000. Office of Management and Budget Paperwork Reduction Act Procedures

Appendix. In LTG Associates, Inc. 2000. Report on the 1999 Minerals Management Service

Social and Economic Studies Conference. OCS Study MMS 2000-016. Department of the

Interior, Minerals Mgmt. Service.

LTG Associates, Inc. 2000. Report on the 1999 Minerals Management Service Social and Economic

Studies Conference. OCS Study MMS 2000-016. Department of the Interior Minerals Mgmt.

Service, Environmental Studies Program: 4.

Lutton, Harry and Rodney Cluck. 2000. Applied Social Science in MMS: A Framework for

Decision Making. Department of the Interior, Minerals Mgmt. Service, Environmental Studies

Program: 15.

Wade, William W. and Robert T. Mott. 1998. Research and modeling challenges to estimate

economic effects of Mobile Bay exploration and development. MMS Workshop on Modeling

Demographic and Economic Change in Local Coastal Areas. 26-27 March 1998, New Orleans,

LA.
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THE MINERALS MANAGEMENT SERVICE’S NEW CONSISTENT APPROACH

TO MODELING REGIONAL ECONOMIC IMPACTS

Ms. Vicki Zatarain

Mr. Kim Coffman

Minerals Management Service

INTRODUCTION

The U.S. Minerals Management Service (MMS) is responsible for managing mineral resources on

the Federal Outer Continental Shelf (OCS). Among the many factors decision-makers must consider

prior to scheduling and conducting OCS oil and gas lease sales (auctions of development rights) are

the magnitude and location of economic impacts on local communities. In the late 1990s, MMS

developed a new framework for estimating regional economic impacts that recognizes regional

differences but provides for the development of consistent models for all coastal areas and for

different levels of analysis. This paper presents a general description of that framework and the

models themselves, focusing on models for Gulf of Mexico (GOM) analyses. For more details on

the various activities that comprise an offshore oil and gas project, the resulting expenditures, and

the allocation of those expenditures to specific industrial sectors in designated onshore economies,

see David Dismukes’ paper in this volume.

LEGAL MANDATE

The OCS Lands Act, as amended, established a policy for the management of oil and natural gas on

the OCS and for protection of the marine and coastal environments. The mandate given MMS under

the OCS Lands Act and other laws, is essentially 

• to expedite exploration & development of the OCS;

• to protect human, marine, & coastal environments;

• to obtain fair & equitable return for public on OCS resources;

• to preserve & maintain competition; and 

• to balance this range of objectives under all market conditions.

Regional economic impact analyses play a part in two kinds of planning to help carry out this

mandate. The first is the development of a new five-year program—a five-year schedule of proposed

auctions of mineral rights, which are called lease sales. The OCS Lands Act requires that a five-year

program be in place and lays out a variety of considerations and requirements for developing one.

After a five-year program has been approved, and prior to each lease sale, MMS conducts more

detailed analyses for decision makers, who then decide whether the sale will be held as proposed,

modified, delayed, or cancelled.
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The regional economic impact analyses conducted in these planning phases help satisfy two primary

statutory requirements. Section 18 of the OCS Lands Act requires that, in the development of a fiveyear program, the 

[t]iming and location of exploration, development, and production of oil and gas

among the oil- and gas-bearing physiographic regions of the outer Continental Shelf

shall be based on a consideration of...(B) an equitable sharing of developmental

benefits and environmental risks among the various regions... . [43 U.S.C.

1344(a)(2)]

The equitable sharing analysis, which examines all coastal areas near lease sale areas on a proposed

schedule, is included in the decision document for each of three stages in the development of a new

five-year program.

In addition, the National Environmental Policy Act (NEPA) of 1969 states that ... 

[t]he Congress authorizes and directs that, to the fullest extent possible: ... (2) all

agencies of the Federal Government shall...(C) include in every recommendation or

report on a proposal for legislation and other major Federal Actions significantly

affecting the quality of the human environment, a detailed statement by the

responsible official on (i) the environmental impact of the proposed action, ... . [42

U.S.C. 4332]

To this end, MMS prepares Environmental Impact Statements (EISs) and environmental assessments

(EAs); acquires marine environmental data; analyzes data, literature surveys, socioeconomic studies,

and special studies; and holds public conferences. The EIS for a proposed five-year program

contains a regional impact analysis for each coastal area throughout the nation near a sale on the

proposed schedule, while the EIS for an individual lease sale includes an analysis for the local

coastal areas.

APPLICATION OF REGIONAL ECONOMIC IMPACT ANALYSES TO MMS MANDATE

However they measure regional economic effects of new investments or activity, such as OCS oil

and gas development, regional scientists generally classify the effects as direct, indirect, or induced.

For the equitable sharing and EIS analyses, direct effects are those resulting from the first round of

“new” spending by companies working directly on an OCS project(s). Indirect effects result from

the additional project-related spending of contractors, vendors, and others who provide goods and

services to the companies working directly on the OCS project(s). Induced effects result from the

additional consumer spending by employees (and their families) of the businesses working directly

on, or providing goods and services in support of, the project(s).

The MMS bases all its analyses of proposed lease sales, not just those of regional economic impacts,

on Exploration and Development (E&D) Scenarios. The appropriate MMS regional office Resource

Evaluation unit (RE) prepares an E&D Scenario for each sale or schedule of sales. In it, RE

provides, by broad categories of water depth (in the GOM), annual estimates of the amount of
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infrastructure required for development anticipated to result from the proposal in question. For the

GOM, this includes number of exploratory wells, number of development wells, miles of new

pipeline, number of platforms, and other such measures of OCS activity. The E&D Scenario

encompasses all anticipated projects in each OCS planning area included in pre-sale or proposed

five-year program analyses. For post-lease analyses, a specific project (and often direct effects) is

(are) known.

MMS refers to any model, or submodel, that translates E&D Scenario data into direct effects as a

“first-step” model. For each OCS activity related to a specific OCS planning area and water depth,

the first-step model must estimate the level of industry expenditure and how that spending is

allocated to onshore geographic areas. Depending on the input requirements of the “second-step”

model or submodel, the first-step model must implicitly or explicitly allocate spending or

employment to specific industry sectors.

The second-step model or submodel is used to estimate indirect and induced effects. Such models

must be developed specifically for OCS oil and gas analyses or must be customized to reflect the

unique expenditure and commuting patterns of OCS-related companies and their employees in order

to properly estimate indirect and induced effects. For example, OCS activities require much larger

purchases of steel pipe and air and water transportation than do onshore activities, where a higher

proportion of expenditures necessarily goes to the other factors, including ground transportation.

Indeed, impacts may vary by how far offshore the exploration or production facilities are located.

An accurate model must also reflect typical commuting patterns for workers in OCS-related

industries. For example, OCS platform workers tend to spend a week or more offshore, followed by

the same period at home. This allows them to commute longer distances and results in such workers

spending most of their income outside the areas of analysis. Therefore, to accurately model the

onshore effects of OCS activities, an analyst must know what percentage of workers spend what

portion of their income where, then must use a customized model or must “recalibrate” a more

general model to properly characterize certain industries.

REGIONAL ECONOMIC MODELING: PREVIOUS MMS METHODOLOGY

Prior to the Autumn of 2000, the Alaska OCS Regional Office and the GOM Regional Office used

independently developed processes to estimate regional employment impacts for EISs. The equitable

sharing analysis was done without the benefit of any impact models.

In the Alaska office, MMS used the “Manpower” model to convert E&D scenarios into estimates

of direct employment expected to result from a proposed OCS lease sale. Manpower, which was

developed by MMS employees with contractor assistance, consists of a set of simple multipliers on

spreadsheet pages in a Corel Quattro Pro notebook. MMS used the Rural Alaska Model (RAM),

developed by the University of Alaska, and the output from Manpower to estimate indirect and

induced employment. The RAM consists of a set of worksheets in a Microsoft Excel workbook. Like

Manpower, it uses simple multipliers to estimate results. The RAM is actually a collection of 10

models, one for each of 10 local onshore areas.
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3

 A static model approximates an outcome for which all changes occur at once, as opposed to a dynamic model, which

is much more complex but allows for interactions over time. An input-output model estimates the monetary interactions

among all industries required to achieve a specified change in output in one or more sectors.

In the GOM office, MMS used an unnamed, staff-developed, MS-Excel spreadsheet to estimate

direct, indirect, and induced employment effects. The GOM office based its direct employment and

population projections on average employment requirements for OCS activities (by type of activity

and water depth), determined through an informal survey of industry employment types and

locations. The GOM region allocated onshore direct effects using historical data from an offshore

rig locator service. The same model used exogenous “multipliers” developed and modified over time

from County Business Pattern data to estimate indirect and induced employment. 

Recently, there have been no models in place to estimate regional employment impacts for the

Atlantic OCS region or the Pacific OCS region. The Pacific OCS Regional Office had planned to

use analyses of the environmental studies products to help estimate direct employment effects and

to use IMPLAN for indirect and induced employment effects, but there have been no lease sale

proposals on the Pacific OCS for many years.

THE NEW MMS CONSISTENT APPROACH TO REGIONAL

ECONOMIC IMPACT MODELING

In the mid-1990s, MMS formed the Developmental Benefits Model Assessment Team (DBMAT)

to develop proposals to improve its regional economic impact models. The DBMAT was composed

of members from each MMS OCS regional office and relevant units at MMS headquarters. 

While the DBMAT researched a broad range of models used for regional economic impact analyses,

it is important to note that there was, and is still, no secondary source from which MMS could obtain

data showing how a given expenditure on OCS oil and gas activities reverberates through onshore

economies. No standard statistical series, such as those compiled by the Departments of Commerce

and Labor, gathers data on the offshore natural gas and oil industry. In every case, offshore is

combined with onshore oil and gas or with all mining. To further complicate matters, MMS also

must distinguish between state offshore and OCS oil and gas development. The distinction is

important because the relative spending among industrial sectors and among onshore areas differs

not only for onshore and offshore activities but for activities in different water depths. And the

sector in which money is spent and workers are employed can strongly influence the level of indirect

and induced effects. As a result, MMS must always gather or model the information it needs to

estimate direct impacts from OCS activities. This would be required regardless of which model

MMS employed to estimate indirect and induced effects. 

The DBMAT proposed a two-step modeling process that would allow the development of regionspecific models to be developed under a consistent methodology, whether for large, multi-state areas

in equitable sharing analyses or for sub-state areas in specific pre-sale analyses. Given the Team’s

belief that there was no single readily available model adequate for all MMS analyses, this proposal

called for region-specific first-step models to estimate direct effects and a single static input-output

model3

 (with region-specific data bases) to estimate indirect and induced effects. Accordingly, the
355

4

 The MMS calls the spending estimation and allocation to industry sectors a “cost function” to avoid confusion with

the similar “production function” for each sector in the second-step model. Because the analysis of direct effects also

requires allocation of expenditures to the appropriate onshore geographic areas, this sometimes also is inferred by the

term “cost function.”

direct-effects, or first-step, model would include a cost function4 that not only estimated the total

required annual expenditures for each of these categories but also allocated expenditures and labor

among industrial sectors.

After the proposal was approved, the Center for Energy Studies at Louisiana State University was

employed under a Coastal Marine Institute contract to develop the data for the cost functions and

onshore allocations. (In Alaska, Jack Faucett Associates was hired to develop first-step models for

the Arctic and Sub-Arctic Alaska OCS.) The DBMAT selected the IMPLAN (IMpact Analysis for

PLANning) model as the universal second-step model, because it had the simplicity and flexibility

to meet all MMS needs and it was the most widely used input-output model available with regularly

updated data for all coastal areas. Furthermore, IMPLAN had been used to analyze impacts from

oil, gas, and non-oil related economic shocks in all MMS regions.

Microsoft Access was selected as the software to link the E&D scenarios, the first-step models, and

IMPLAN. Because the magnitude of the ripple effect (indirect and induced effects) for each industry

varies by geographical location, MMS develops a separate MS-Access model for each onshore area

in an analysis. Given the large number of inputs for the second-step model, usually numbering many

thousands, IMPLAN Pro software and data are used only to provide and regularly update sets of

multipliers for the MS-Access model. The software itself also could be used for analyses not

requiring extensive data entry.

For GOM analyses, the two-step process is incorporated into one MS-Access model, as shown in

Figure 2F.2, which shows the design view of a sample MS-Access “query” that illustrates how the

GOM models work. The first box in the upper left corner of the figure represents the Exploration

and Development scenario, required for any model to produce data. The second required component

is the first-step model, the third box from the left, which contains the cost functions by phase (e.g.,

exploratory drilling) and water depth. It converts the activities into expenditures and allocates those

expenditures to industrial sectors in the relevant onshore area. So for each exploratory well in 0-60

meters of water, for example, some portion of $4.25 million will be allocated to sector 38 in the

group of parishes called LA-2.

The other boxes to the right comprise the second step of the model. These are the multipliers for

employment, employee wages, personal income, total value added, and total economic output. They

estimate, for example, the number of industry jobs created in onshore area LA-2 as a result of each

million dollars spent, as well as the number of jobs created by secondary industries, and by

households with industry employees.
356

MS-Access Model for GOM MS-Access Model for GOM

Figure 2F.2. Sample view of Microsoft Access model for Gulf of Mexico.

For the Five-Year Program’s equitable sharing analysis, the models will allocate impacts to the

onshore “regions” used in equitable sharing analyses previously upheld by the court. For the GOM,

these would be

• Region III—Florida

• Region IV—Texas, Louisiana, Mississippi, Alabama.

The requirement for an equitable sharing analysis applies only to a new five-year program, while

the NEPA analysis must be done for both the five-year program and the lease sale decision

processes.

For pre-sale analyses for the GOM, the onshore areas are more narrowly defined, ranging from five

to 13 coastal and near-coastal counties or parishes per area.
357

REGIONAL APPLICATION OF COST FUNCTION DATA AND IMPLAN MODEL

The model for the GOM has two steps. Because there are no publicly available models that estimate

the expenditures resulting from OCS oil and gas activities, e.g., drilling an exploratory well, the first

step estimates the expenditures resulting from all the activities in the Exploration and Development

Scenario for a proposed Lease Sale and assigns these expenditures to industrial sectors in eight

MMS coastal subareas. The Exploration and Development Scenario is developed internally (by the

MMS’s Resource Evaluation Division) which denotes the schedule of oil and gas development

activities and offshore location (shallow, moderate, deep and ultradeep water) estimated for a typical

OCS Lease sale. The second step in the model uses multipliers from the commercial input-output

model IMPLAN to translate these expenditures into direct, indirect, and induced employment and

other economic factors. Direct employment results from the first round of industry spending. It is

that employment that results from the initial dollars spent by the oil and gas industry on the activities

listed in the Exploration and Development scenario. Indirect employment results as the initial

spending reverberates through the economy. First, the suppliers of the goods and services for the

OCS development activities spend the initial direct dollars from the industry. Then these dollars are

re-spent by other suppliers until the initial dollars have trickled throughout the economy. Labor

income produces induced spending by the households receiving that income.

Both the level (the amount spent) and the sectoral allocation (the industry in which it is spent) of

expenditures can vary considerably by the phase of OCS activity and by the water depth of the

activities. For example, an exploratory well in 0-60 m of water is expected to be drilled using a jackup rig and cost about $5 million, whereas an exploratory well in 900 m or greater water depth is

expected to be drilled using a drill ship and cost about $10 million to complete. In addition, spending

on materials such as steel will be much higher for platform fabrication and installation than for

operations and maintenance once production begins. These data (total expenditures and sectoral

allocation of expenditures by phase) are supplied from the Cost Function Study. Therefore, the

model estimates and allocates expenditures by OCS development activities (exploratory drilling;

development drilling; production operations and maintenance; platform fabrication and installation;

pipeline construction; pipeline operations and maintenance; gas processing and storage construction;

gas processing and storage operations and maintenance; workovers, and platform removal and

abandonment) in four water depths categories (0-60 m; 61-200 m; 201-900 m; and >900 m).

Because employment and other economic impacts occur onshore and the expenditures are associated

with activities offshore, an onshore allocation matrix was developed.

Because local economies vary, a separate set of IMPLAN multipliers is used for each MMS coastal

subarea to which expenditures are assigned. Each set of multipliers is based on the actual historical

patterns of economic transactions in the area. Model results for employment are presented in number

of jobs per year, where one job is defined as a year of employment. This does not necessarily mean

only one person occupies the position through out the year. One job may be equal to two part-time

positions occupied over the year or one person occupying a position for six months, while another

person occupies it for the other six months. Model results are then compared to a baseline

employment projection in the absence of the proposed lease sale to determine the impact of the

proposed sale on the local economies.
358

LOOKING FORWARD

The new consistent approach to regional economic impact modeling will be thoroughly tested over

the next year or two, as MMS conducts an equitable sharing analysis and EIS for the Five-Year Oil

and Gas Program for 2002-2007—which must be in place by mid-2002, in addition to a multi-sale

EIS analysis for GOM planning areas. During this period, MMS will be looking for ways to improve

upon the initial models that have been developed under this approach.

Some of these improvements will come from better data. For example, MMS is confident that its

allocation of expenditures to specific onshore areas is fairly accurate overall; however, it may be

appropriate to further refine the allocations according to planning area and water depth of oil and

gas resources in question, as well as by sector. For example, it’s likely that the drilling equipment

and platforms for deep-water projects are likely to be manufactured in geographic locations other

than those for shallow-water projects.

In other cases, these improvements may come from refinement of existing data, for example,

developing cost functions for specific technology (e.g., jack-up rigs) that could be used to analyze

identified projects, rather than the weighted averages for mixed technology used for more general

proposals, like lease sales. Given that the existing models use a static input-output model to

approximate a dynamic process, MMS intends to develop a methodology to spread E&D

expenditures across years, where appropriate (e.g., for fabricating and installing platforms in deep

water).

Other changes will result from the incorporation of additional research results on commuting (&

spending) patterns for offshore workers, wage rates in related industries, state and local government

revenue collection and expenditure patterns, and offshore contractor expenditure patterns that may

be masked in existing data.

Finally, MMS hopes to take advantage of more sophisticated features of MS-Access software and

improvements to IMPLAN Professional software and data. Future versions of IMPLAN Pro may

allow MMS to create multi-regional models, which would capture more of the inter-regional trade

interactions. MMS also can develop uniform input formats and Visual Basic programming

instructions within MS-Access to make models easier to update and easier to link to new E&D

scenarios, as well as to make them more user-friendly.
359

 5 This paper is an extract from a research report partially funded by the Minerals Management Service (MMS) of the

U.S. Department of the Interior (Pulsipher et al.1999) . All conclusions, errors, and recommendations, however, are the

sole responsibility of the authors.

AN ANALYTICAL MODEL OF OPERATING PLATFORMS ON THE U.S. GULF OF

MEXICO OUTER CONTINENTAL SHELF (OCS), 1947-1997 5

Dr. Omowumi O. Iledare

Dr. Allan G. Pulsipher

Dr. Dmitry V. Mesyanzhinov

Dr. Alan Dupont

Ms. Qiaozhen “Lucy” Zhu

Center for Energy Studies

Louisiana State University

ABSTRACT

The most common practice for firms operating on the OCS is to undergo detailed engineering and

economic planning studies to schedule platform installations and removals on their leases. However,

little analysis has focused on how the entire collection of offshore platforms operating on the OCS

is likely to change over time and what variables are responsible for those changes. This paper

presents an analytical model of offshore structures operating in the Gulf of Mexico OCS region

using data on platform installations and removals from 1947 through 1997. The model framework

has two behavioral equations and an identity relationship. The estimated behavioral equations

explains nearly 80% and 95% of the variation in platform installations and removals from 1947-

1997, respectively. The results confirm the expectations that the greater the expected size of new

fields, the larger the number of platforms to be installed, but the increase in platform installation

occurs at a declining rate with cumulative size of new field additions. The empirical results also

show that a favorable economic environment will lead to a statistically significant but inelastic

increase in the number of installed platforms. Although the empirical results are consistent with the

a priori expectation that platform installation began to decline—since 1986 as a result of structural

changes in the industry, deep water drilling techniques, and completion technology, the point

estimate of the variable included in the model to capture the effects of technology and institutional

changes is not statistically different from zero. It is estimated that less than 5% of platforms

currently operating on the OCS are older than 33 years or more and about 65% are 21 years or less.

INTRODUCTION 

The stock of offshore platforms in the U.S. Gulf of Mexico (GOM) OCS region is one of the

primary components of U.S. economic and physical capital. Constructing, operating, and removing

platforms interact with the economies and ecologies of adjacent coastal areas in positive and

negative ways. Although firms operating in the GOM conduct detailed engineering and economic

planning studies to schedule platform installations and removals on their leases, little analysis has
360

focused on how the entire collection of offshore platforms is likely to change over time and what

variables or influences are responsible for those changes.

This paper develops a set of equations to describe the trend in operating offshore structures on the

GOM OCS region and uses the model framework to forecast the number of operating offshore structures over the next two decades. The framework adopted in this study assumes that as more fields

are discovered and developed, the incentives to install new offshore structures will also increase,

but at a decreasing rate. The lead time required to design, obtain permits, and install an offshore

platform, even with strengthened incentives, may not lead to more platforms during a given period.

Other factors such as changes in economic conditions and expectations or cost-reducing- improvements in technologies may also affect the number of platforms and the rate at which firms may wish

to install them. As economic conditions and expectations become more favorable and stable, the

incentives to install new offshore structures will strengthen. Similarly, as technologies for finding

and producing petroleum improve, the need for additional offshore structures may also change.

TRENDS IN OPERATING OFFSHORE STRUCTURES ON THE OCS

The number of operating platforms grew in every year except 1992, when Hurricane Andrew blew

through the oil producing area in the GOM. A plateau of about 3,900 structures was reached and

maintained during the 1990s; this represents the drop-off-period for the decline. 

At 31 December 1997, there were about 3,900 platforms operating on the OCS. Of these, 73.9% are

located in water depths of less than 400 feet and 4.6% located in waters deeper than 900 feet. Table

2F.4 presents the number of operating platforms by water depth.

Table 2F.4. Water depth of fixed offshore structures operating on the Gulf of Mexico OCS as of

31 December 1997.

Depth Ranges

Non-Major

Structures Major Structures All Structures

0-20 17 11 28

21-50 166 44 210

51-100 388 120 508

101-150 444 210 654

151-200 369 258 627

201-300 245 255 500

301-400 132 233 365

401-500 51 184 235

501-900 117 492 609

> 900 13 167 180

Total 1942 1974 03916
361

MODEL SPECIFICATION AND ESTIMATION

The stock of operating platforms on the OCS in a given period can be estimated using an arithmetic

identity relationship defined simply as cumulative platforms installed less cumulative platforms

removed. Symbolically, the above definition translates to an identity equation of the form:

 (1)

where:

OPP(t) is the number of operated platforms in time t 

INS(t) equals number of installed platforms in time t 

REM(t) represents the number of platforms removed in time t. 

The definition set forth in equation (1) forms the basis for the modeling approach to forecasting the

number of platform installed, removed, and operated on the OCS in this report.

According to equation (1), the number of platforms operated in a given period depends on the

number of platforms removed and installed during the period, ceteris paribus. To use this identity

to forecast, we have to be able to model and forecast those factors that explain platform installations

and platform removals. For the sake of simplicity, it is assumed that a platform installed in a given

period on the OCS becomes operational during that period. It is also assumed that the number of

removed platforms in a given year is some function of the stock of operating platforms at the end

of the previous year as well as the age of the platform.

Thus, the number of platforms removed in year t can be expressed as the sum of the proportion of

platforms installed in previous periods that were removed in the current period. Symbolically we

may represent this proposition as follows:

 (2)

where:

"j

 represents the proportion of platforms removed in year t that were installed in year t-j such

that 0 # "j # 1 and j represents the age of removed platform.

Planned installation of new platforms in order to explore and produce oil or gas is expected to be

affected by short-run changes in the petroleum economy and political environment, and perhaps by

other determinants such as structural changes in the industry in addition to the expected size of

petroleum discoveries. Thus, the functional equation describing planned platform installation

behavior may be specified as follows:

 (3)

where:

$i

 (i=0,1,2,3,4) are constant parameters to be estimated

INS*

t

 = desired or planned number of installations in period t.
362

CFZ t = cumulative total field size at the beginning of period t

CPR t = the average current crude oil price on the Gulf OCS

TEK = time trend as a proxy for technical progress 

D86 = dummy variable, such that, D86 = 1 for time period after 1986 and zero otherwise

,t

 = independent random error term

The dummy variable D86 is included to capture the effects of changes in expectations and behavior

of the oil and gas industry in the GOM OCS subsequent to the collapse of the world crude oil market

in the summer of 1986.

The short run adjustment process can be measured using the following partial adjustment model

specification:

 (4) 

where:

8 represents the rate of response of the change in installed platforms to the difference between

the desired installations and past value of installed platforms such that 0 # 8 $ 1, and T =

independent random error term. 

Conceptually, equation (4) measures the proportion of adjustment to the desired number of platforms

achieved within a year. The error term T measures the failure of the adjustment process to

accomplish the desired number of platforms.

Substituting equation (4) into equation (3) and simplifying the new equation yields an equation

describing the relationship between the number of platforms installed (or to be installed) and its

determinants. 

 (5)

If Bi = 8$i, then

 (6)

The independent or explanatory variables and their hypothesized relationships to the dependent

variable, INS, are defined as follows:

log(CFZt)–The logarithm of cumulative field size in million barrels of oil equivalent (MMBOE).

Our hypothesis is that as the size of field increases on the OCS, the number of installed

platforms will increase at a decreasing rate. The coefficient B1 is expected to be positive. 

CPRt–Current crude oil price on the GOM OCS. The hypothesized relationship is that the

economic environment will tend to shift the long-time relationship between installed platforms

and cumulative discovery outwards. This means that we expect a positive coefficient for CPR,

our measure of economic conditions.
363

TEKt–This is a proxy for the impact of technology on platform installations. The expectation is

that the more rapid technical progress has been over the past 10-15 years the fewer the number

of platforms that need to be installed to produce a given level of reserves. Less abstractly, as

technologies such as horizontal and directional drilling, down-hole completion, etc., are

developed, fewer platforms will be required to develop new fields in deeper water.

D86–Dummy variables for changes in expectations and behavior since the collapse of the world

oil prices are expected to affect negatively the shifting effect of prices on the relationship

between platforms and discovery size. 

The collapse of world crude oil prices in 1986 brought with it several organizational and institutional

changes on the OCS including a massive reduction in employment, an increase in the importance

of independent operators, an increase in reliance on contract services, and the adoption of less

hierarchical decision-making as well as technological innovations (Bohi 1997). The likely effect of

these changes on platform installation on the OCS is examined by including an interaction between

the 1986 dummy variable and time trend such that the interactive dummy equals 1 from 1986

forward and 0 otherwise.

The Ordinary Least Square (OLS) estimation results for equation (6) are presented in Table 2F.5.

Equation (6) is a linear-log model. The general expectation from our model specification using the

linear log function is that the greater the size of new fields, the larger the number of platforms to be

installed, but the increase in platform installation occurs at a declining rate.

Table 2F.5. OLS Estimates of the platform installation model (t-statistics in parenthesis).

Variable Coefficient

Intercepts -113.931

(-2.847)

Cumulative New Fields (CFZ) 16.618

(3.118)

Average Current OCS Oil Price (CPR) 2.089

 (2.416)

Number of Platform Installed (INSt-1) 0.457

 (3.641)

Technical Progress -0.163

(Interactive Dummy) (-0.706)

Observations 49

Adjusted R2 0.791

Error of Regression 27
364

 6 For every observation in the series (1947-1997), new variables were created. These variables represented

consecutive lags for the installed platforms. For example, lag_1 for 1948 contains platforms installed in 1947; lag_2 for

1950 contains platforms installed in 1948, and so forth. In certain cases, statistical software created missing values. For

example, lag_2 for 1948 is a missing value, because there were no platforms installed in 1946. All missing values were

substituted with zeroes. Then, a step-wise OLS regression was performed with the annual number of removed platforms

as a dependent variable and 40 lags (lag_1, lag_2,..., lag_40) of installed platforms as independent variables. Out of the

40 independent variables, the step-wise regression procedure selected, based on the resulting R square, ten best models.

The first model included only one independent variable, the second model included two independent variables, and so

Overall, the model results explain nearly 80% of the variation in dependent variables. The point

estimate of the coefficient of the lagged value of the dependent variable is 0.463, making the

adjustment coefficient 0.537. Thus, on average, firms achieve about 54% of their desired or planned

number of platforms to be installed within a given year. 

The parameter estimate for the variable representing the economic environment—the average

current price of OCS crude oil—is positive, as expected. Therefore, we conclude that a favorable

economic environment, according to our model, leads to a statistically significant increase in the

number of installed platforms. The short-run price elasticity of platform installation on the OCS is

estimated as 0.25; and since the adjustment coefficient is 0.537, the long-run price elasticity of

platform installation by our model estimate is approximately 0.46. This means that a 10% increase

in the current average price of OCS crude oil will lead to about 4.6% increase in the number of

platforms installed over the long run compared to a short-run increase of about 2.5%. 

The results show that cumulative field size is an important determinant of the number of platforms

installed. As expected, the coefficient is positive and statistically significant at the 99% significance

level. However, the short run and long run elasticity of cumulative reserves is on average

significantly less than unity.

The empirical result is consistent with our expectation that since 1986, platform installation did

decrease as a result of structural changes in the industry, deepwater drilling techniques and

completion technology. However, the point estimate of the interactive dummy included in the

regression to capture the effects of technology and institutional changes, although negative as

expected, is not statistically different from zero. Figure 2F.3 shows that the prediction using the

estimated equation (6) presented in Table 2F.5. The predicted trend tracks the actual trend in

platform installation closely.

In order to model the physical reality in which only installed platforms can be removed, we selected

a specification with a suppressed intercept. Thus, when values for both independent variables are

set to zero, the value for the dependent variable is also equal to zero. The statistical equation applied

for predicting platform removals is a reduced form of equation (2) reproduced below in an estimated

form as equation (7):

 (7)

Of the several alternative forms of equation (2) that we examined, equation (7) yields the best

statistical fit to the available historical data on removed platforms.6
365

forth up to ten. The model with two explanatory variables provided a much better fit than the model with just a single

explanatory variable; however, a model with three explanatory variables provided only a marginal improvement over

the model with two explanatory variables. Therefore, the model with the two lags–lag_32 and lag_21– was selected as

the most parsimonious.

Figure 2F.3. Actual and predicted number of platforms installed.

The above estimated removal equation (7) is obtained using a statistical method that lacks the

conceptual foundation that the forecasting equation for platform installations enjoys. The final

relationships estimated in the equation state that 95.3% and 35.1% of platforms installed in year

(t-33) and (t-21), respectively, are removed in year t. The model explains more than 95% of the

observed variation in platform removal. Parameter estimates of the independent variables are also

statistically significant. However, the mean absolute percent error and the root mean square percent

error of the predicted values are a high 22% and 21%, respectively. Figure 2F.4 plots the actual and

predicted number of removed platforms for the period 1947 - 1997.

Using equations (6) and (7) in combination with the identity equation (1), predicted values of

operating platforms were calculated. Figure 2F.5 shows a pictorial view of the predicted number of

operating platforms over the period for which we have data. The predicted values tracked the actual

values quite well, with the moving average percent error (MAPE) for the period 1947-1997 being

7.75% while the root mean square is approximately 4.48%.
366

0

20

40

60

80

100

120

140

160

180

200

1947 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997

Year

Number of Removals

Predicted

Actual

Figure 2F.4. Actual and predicted number of platforms removed.

The model results in Table 2F.5 were also used to generate annual forecasts of the number of

platforms installed for the period 1999-2023. The values assumed for all the parameters and

variables used to forecast platform installations are reported in Table 2F.6. Equations (6) and (7)

were subsequently applied to calculate future removals and installations, and the corresponding

number of platforms operating annually was estimated using the identity equation (1). 

The reference forecast, or the forecast that in our view is the most likely, is summarized in Table

2F.7. During the forecast period new platforms are projected to be installed at an annual rate of

about 142 platforms per year. Over the 25-year period, 3,543 platforms would be installed. A total

of 4,645 platforms are forecast to be removed, which is an approximate annual rate of about 186

over the forecast period. Operating platforms are predicted to decrease from 3,687 in 1999 to 2,612

in the year 2023. This is a decline of 1,075 or about 29%. Figure 2F.6 presents a pictorial view of

the trends in operating platform forecasts under a reference case scenario and two alternative

scenarios.

SUMMARY AND CONCLUSIONS

An analytical model of operating offshore structures in the GOM OCS region using data on platform

installations and removals from 1947 through 1997 has been developed. The model framework has

two behavioral equations and an identity relationship. The framework adopted in this study assumes

that as more fields are discovered and developed, the incentives to install new offshore structures
367

0

1,000

2,000

3,000

4,000

5,000

1947 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997

Year

Number of Operating Platforms

Predicted

Actual

Figure 2F.5. Actual and predicted number of operating platforms.

will also increase, but, at a decreasing rate. It is also assumed that other factors such as changes in

economic conditions and expectations or cost-reducing improvements in technologies may also

affect the number of platforms and the rate at which firms may wish to install them. 

The estimated behavioral equations explains nearly 80% and 95% of the variation in platform

installations and removals from 1947-1997, respectively. The results confirm the expectations that

the greater the expected size of new fields, the larger the number of platforms to be installed, but

the increase in platform installation occurs at a declining rate with cumulative size of new field

additions. The empirical results also show that a favorable economic environment will lead to a

statistically significant but inelastic increase in the number of installed platforms. 

The total number of oil and gas platforms located in the U.S. GOM OCS region is forecast to begin

a slow but steady decline over the first quarter of the next century. The plateau of about 3,900

structures that was reached and maintained during the 1990s is a peak, according to the forecast, and

the drop-off-period for the decline. 

By the year 2023 the number of platforms in the Gulf is forecast to be roughly 2,600, a drop of 1,075

platforms for a total that will be about 29% below the current peak. Alternative forecasts made by

changing the values of the forecasting variables did not result in major differences from the 
368

Table 2F.6. Estimated values of model variables and parameters used to forecast the number of

platforms installed from 1998 – 2023.

Year

Wells 

#

Wildcats

Fields

(MMBOE)

New Fields

Size Rate

Field Size

Head Price

(Dollars/Bbl)* Success Avg. Well

1998 110 18 24.5 0.16 15.74

1999 114 14 15.4 0.12 15.96

2000 101 14 13.1 0.14 16.17

2001 104 12 16.9 0.12 16.38

2002 100 12 21.0 0.12 16.61

2003 103 13 34.8 0.13 16.83

2004 109 14 12.4 0.13 17.05

2005 102 11 17.6 0.11 17.28

2006 99 12 14.2 0.12 17.40

2007 101 10 15.2 0.10 17.52

2008 96 11 21.7 0.11 17.64

2009 102 11 14.6 0.11 17.77

2010 98 10 14.8 0.10 17.89

2011 96 10 38.4 0.10 17.99

2012 105 11 13.9 0.11 18.06

2013 97 8 9.3 0.08 18.19

2014 90 10 14.8 0.11 18.29

2015 98 7 5.4 0.07 18.39

2016 86 9 16.2 0.10 18.49

2017 97 9 8.8 0.09 18.59

2018 92 9 16.4 0.10 18.69

2019 96 8 4.9 0.08 18.80

2020 89 9 16.2 0.10 18.90

2021 97 8 9.3 0.08 19.00

2022 90 6 1.8 0.07 19.11

2023 84 9 32.3 0.11 19.22

* See Pulsipher, et al. (1999) for detailed discussion on forecasting model variables.
369

Table 2F.7. Forecasts of the number of platforms to be installed, removed, and operated on the

Gulf of Mexico OCS, 1999 - 2023 – Reference Case.

Year Platforms

Operating

Platforms

Installed

Platforms

Removed

1999 3,687 137 165

2000 3,642 138 183

2001 3,623 138 158

2002 3,605 139 157

2003 3,566 140 178

2004 3,550 140 157

2005 3,498 141 193

2006 3,475 141 165

2007 3,529 142 87

2008 3,534 142 136

2009 3,510 142 166

2010 3,475 142 177

2011 3,402 142 215

2012 3,342 143 203

2013 3,292 143 192

2014 3,233 143 202

2015 3,130 143 246

2016 3,064 143 208

2017 2,957 143 251

2018 2,855 143 245

2019 2,849 143 149

2020 2,834 143 158

2021 2,772 144 206

2022 2,682 144 234

2023 2,612 144 214
370

Forecasted Number of Operating Platforms 

1500

2000

2500

3000

3500

4000

1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 2013 2017 2021

Number of Platforms

CES Low Price 

and Small New 

Fields Case

Reference Case

CES High Price and 

Large New Field Case

Historical Data

Figure 2F.6. Forecasted number of operating platforms.

reference forecast. The decline in operating platforms in high forecast was still more than 20%, as

compared to 29% in the reference forecast. The decline in the corresponding low forecast was about

35%.

 REFERENCES 

Bohi, Douglas R. 1997. Changing Productivity of Petroleum Exploration and Development in the

U.S. Resources for the Future Discussion Paper, January 1997, Washington D.C.

Pulsipher, Allan G., et al. 1999. Forecasting the Number of Offshore Platforms on the Gulf of

Mexico OCS to the Year 2023. OCS Study report prepared by the Center for Energy Studies,

Louisiana State University, Baton Rouge, LA.
371

MODELING OF PLATFORM INSTALLATIONS AND REMOVALS:

THE MMS PERSPECTIVE

Mr. Thierry DeCort

Presented by Ms. Stephanie Gambino

Minerals Management Service

The office of Resource Evaluation (RE) in the Gulf of Mexico Region (GOMR) currently has a

process in place where one of the products is a forecast of platform installations and removals by

water depth and planning area. RE’s forecast of platform installations and removals is used by RE

for preparation of the National Assessment. The forecast is also used by Leasing and Environment

(LE) in the GOMR as well as Headquarters in Herndon, Virginia, for preparation of each Five-Year

Leasing Program and for Environmental Impact Statements.

The MMS will benefit from and RE will support and participate in a new platform installation and

removal-forecasting project that focuses on improving our current forecasting methods, models,

techniques, and data types used. This study, to begin in January of 2001 by the Center for Energy

Studies at Louisiana State University, will focus on identifying the best platform forecasting

methods and techniques worldwide rather than just on the result of a forecast. This will help RE to

improve our current forecasting process and models, thereby providing years of improved

forecasting results for both the GOMR and Headquarters.

The objectives of the new study are the following:

1. to identify, develop, and investigate alternate platform installation and removal forecasting

methodologies from around the world – i.e. best practices and benchmarks. This would also

include RE’s methodology;

2. to identify the best data variables to use for platform forecasting. This includes identifying

the data MMS currently possesses and how this data can be put to its best use; and

3. the development of a modern forecasting model that employs the most relevant data and the

best statistical and econometric modeling techniques – i.e. sensitivity analysis.
372

THE OFFSHORE ENVIRONMENTAL COST MODEL

Dr. William King

Minerals Management Service

The essential question this paper addresses is, “What is the OCS program worth?” MMS is

mandated to consider this question by the OCS Lands Act as Amended. Section 18 of that act

requires the Department of the Interior, through the MMS to prepare a Five-Year Program. The first

subsection of section 18, states:

(a)(1) Management of the outer Continental Shelf shall be conducted in a manner

which considers economic, social, and environmental values of the renewable and

nonrenewable resources contained in the outer Continental Shelf, and the potential

impact of oil and gas exploration on other resource values of the outer Continental

Shelf and the marine, coastal, and human environments.

MMS has decided (and the Courts have sanctioned) the use of cost-benefit analysis (CBA) as the

form of economic analysis to be used to estimate the social and economic value of the program.

The Five-Year Program process produces the following sets of documents, which include CBA:

• The Draft Proposed Program, which ranks all active planning areas based on total available

resources 

• The Proposed Program, which ranks relevant program areas based on total available

resources and evaluates program alternatives based on anticipated production

The theory and practice of CBA has sanctioned a specific measure for determining the desirability

of a public action. This measure is the present value of the future stream of net social benefits (gross

benefits minus gross costs) from the investment or policy. In this case, the net benefits under

consideration are those that would accrue to society from the OCS natural gas and oil leasing

included in the Five-Year Program. These benefits and costs are counted over the life of the project

or action and discounted to the present to account for the time value of money.

The CBA MMS performs for the Five-Year Program builds on results from three models:

• NEV

• OECM

• MktSym2000

NEV, which Larry Slaski created and runs, is a discounted cash flow spreadsheet that estimates the

gross producer surplus from the OCS program.
373

The OECM has a fairly long history in MMS and the Department. Among the early environmental

cost calculations upon which it is based is the original Natural Resources Damage Assessment

Model (NRDAM), whose original development is linked to the name Tom Grigalunas. This was followed by the General Purpose Environmental Cost Model (GPECM) prepared by A.T. Kearney and

used by MMS for the past two Five-Year Programs. Unfortunately, the GPECM would only run

reliably in Lotus123 release 2.2. It was further burdened with a strange structure, bizarre programming, quirky results, and an outdated empirical basis. The GPECM included the following sectors:

• OCS Air Emissions

• OCS Effluent Discharges

• Spill Avoidance

• Infrastructure

• Preemption/Gear Loss

• Wetland Losses

• Property Value Losses

• Oil Spill Control/Clean-up

• Recreation/Tourism Losses

• Commercial Fishery Losses

• Wildlife/Ecological Losses

• Subsistence Losses

• Legal Costs

• Administrative/Research Costs

This would never do for the upcoming Five-Year Program. MMS needed something new to estimate

environmental costs in the new millennium.

MMS’s response was to contract with Foster Associates for the Offshore Environmental Cost Model

(OECM). Bill Wade has been the Project Manager, Jay Plater, a Resource Economist, has been the

team modeler, and Brian Roach of the University of Maine has done the majority of the research on

which the model is based.
374

The new model has the following sectors:

• Air quality

• Water quality

• Fauna

• Faunal habitat and flora

• Recreation

• Commercial fishing

• Subsistence

• Onshore infrastructure and fiscal impacts

• Onshore property values

Clearly, this model offers less than the GPECM.

In this short paper it is impossible to show how the model works or much of its structure. Table 2F.8

shows what one of the results panels looks like following a recent run for the Draft Proposed

Program.

Reviewing where we are now, we calculated gross producer surplus using NEV. If we now subtract

environmental costs that we obtain from OECM we get what economists call net producer surplus.

Most other people know it as pure economic profit.

Several years ago the National Committee on Oil Import Dependency looked at the costs and

benefits of oil imports versus domestic oil production. After extensive study, this team came to the

conclusion that the only benefits from domestic oil production are producer surplus and consumer

surplus. We have calculated net producer surplus, but we still need an estimate of consumer surplus.

But what is consumer surplus? It is the difference between what consumers pay for a good or service

and what they would be willing to pay.

The original Market Simulation Model contained a simultaneous equation system of up to nine

constant elasticity equations with a manually triggered convergence algorithm. While it was a clever

spreadsheet model, it was unlikely that anyone other than the creator would ever be able to run it.

Jay Plater of Foster Associates performed his magic on the system and the result is MktSym2000,

which is a slick system of three spreadsheets. One is for inputs, one is the model itself, and displays

the summary of results.

Table 2F.9 shows the oil submodel at a single point in time (2010).
375

Table 2F.8. A results panel following a recent run for the Draft Proposed Program.

DPP – Low

Annual Environmental Costs

National Cost Allocation/Import Backout Enabled - Base

Summary of Environmental Costs - All Cost Sectors

($2002) (in $000)

OCS Region Present Value

Planning Area

N ATL North Atlantic -

Mid-Atlantic -

A South Atlantic -

Straits of Florida 232

T G Eastern Gulf 4,111

o Central Gulf 140,704

I M Western Gulf 109,852

PAC Southern California -

O Central California -

Northern California -

N Washington/Oregon -

Gulf of Alaska -

A Cook Inlet 9,164

A Kodiak -

L Shuimagin -

L North Aleutian Basin -

Aleutian Arc -

A St. George Basin -

C St. Matthew Hall -

S Bowers Basin -

O Aleutian Basin -

K Navarin Basin -

S Norton Basin -

A Hope Basin (0)

T Chukchi Sea 5,331

Beaufort Sea 10,180

S Total 279,575
376

Table 2F.9. The oil submodel at a single point in time, 2010.

Oil Submodel

30-Jan-01

A Constant Price Elasticity Model To Estimate Consumer Surplus Benefit Losses Associated With Program Alternatives

Year Of Analysis - 2010

No Action Alternative

Assumed Oil Price $18.00 Production Loss 0.5935 18.08

(2002 $/BBL) (MMBPD)

No Action Price $18.08 Consumer Surplus Loss $483.91

(2002 $/BBL) (2002 $MM)

P R O D U C T I O N

Producing Region DPP Low No Action Alternative

Price

Elasticity

Quantity

Produced

Constant Quantity

Produced

Difference

(Base - NA)

(MMBPD) (MMBPD) (MMBPD)

OCS 0.64 2.08 0.33 1.49 (0.59)

Onshore Domestic 0.58 6.64 1.24 6.66 0.02

OPEC 1.10 42.16 1.75 42.37 0.21

Rest Of World 0.65 43.85 6.70 43.98 0.13

Stock Change 0.30 0.30 - 

Total Production 95.03 94.80 (0.23)

C O N S U M P T I O N

Producing Region DPP Low No Action Alternative

Price

Elasticity

Quantity

Consumed

Constant Quantity

Consumed

Difference

(Base - NA)

(MMBPD) (MMBPD) (MMBPD)

US -0.50 22.70 96.31 22.65 (0.05)

Rest Of OECD -0.65 28.04 182.99 27.96 (0.08)

OPEC -0.36 7.78 22.02 7.77 (0.01)

Rest Of World -0.50 36.51 154.90 36.43 (0.08)

Total Consumption 95.03 94.80 (0.23)

US Imports 13.98 14.50 0.52

Discrepency - 0.000
377

The summary sheet looks like Tables 2F.10 AND 2F.11.

Table 2F.10. Sample summary sheet, part 1.

NPV of Consumer Surplus Benefits from OCS Production

 DPP Low vs. No Action Alternative 

OCS Region Oil Production Gas Production Total Oil & Gas

Planning Area

($ MM) ($ MM) ($ MM)

A North Atlantic - - - 

T Mid-Atlantic - - - 

L South Atlantic - - - 

Straits of Florida 6.4 0.1 7 

G Eastern Gulf 183.0 68.55 252 

o Central Gulf 2,057.6 1,344.9 3,403 

M Western Gulf 1,399.8 1,026.3 2,426 

P Southern California - - - 

A Central California - - - 

C Northern California - - - 

Washington/Oregon - - - 

A Gulf of Alaska - - - 

L Cook Inlet 374.2 62.6 437 

A Kodiak - - - 

S Shuimagin - - - 

K North Aleutian Basin - - - 

A Aleutian Arc - - - 

St. George Basin - - - 

St. Matthew Hall - - - 

Bowers Basin - - - 

Aleutian Basin - - - 

Navarin Basin - - - 

Norton Basin - - - 

Hope Basin - 0.6 1 

Chukchi Sea 479.8 - 480 

Beaufort Sea 1,016.4 213.6 1,230 

Total Benefits - All Regions 5,517 2,717 8,234 

Consumer Surplus Benefits $ / bbl $ / mcf $ / boe

Per Unit Of Production $2.14 $0.28 $1.91 
378

Table 2F.11. Sample summary sheet, part 2.

Production and Consumption Effects

DPP Low vs. No Action Alternative 

 (2002 - 2056) 

Sector DPP Low No Action

Alternative 

Change In

Sector

% Change In

Sector

% Of Lost OCS

Production

 DPP Low No Action Alternative 

 DPP Low No Action Alternative 

OIL (BBO)

Production Effects

OCS Production 45.4 34.8 (10.6) (23.3%) (100.0%) 

Onshore Production 141.1 141.4 0.3 0.2% 2.5% 

Imports 390.5 399.8 9.4 2.4% 88.4% 

Consumption Effects

U.S. Consumption 576.9 576.0 (1.0) (0.2%) 

Conservation 5.5% 

Switch To Gas 3.6% 

GAS (TCF)

Production Effects

OCS Production 791.8 764.5 (27.2) (3.4%) (100.0%) 

Onshore Production 1,048.9 1,056.6 7.7 0.7% 28.3% 

Imports 344.9 349.4 4.4 1.3% 16.3% 

Consumption Effects

U.S. Consumption 2,185.6 2,170.5 (15.1) (0.7%) 

Conservation 16.1% 

Switch To Oil 39.3% 

Returning to our review of where we are now: We have producer surplus from NEV. From that we

subtract environmental costs from OECM. This gives us net producer surplus. To that we add

consumer surplus benefits from MktSym200, which gives us the total net benefits of the OCS

program. Details of this process can be found in Economic Analysis for the OCS 5-Year Program

1997-2002: Theory and Methodology. OCS Report MMS 96-0048.

These models are not only used in the Five-Year Program. They can also be applied to policy

analysis questions. For instance, OECM was used to estimate the environmental costs of gas

developments on Destin Dome for the Coastal Zone Consistency Report. When Congress asked how

large a decrease in oil prices could be attributed to increased OCS production attributable to royalty

rate reduction, MktSym2000 was used to estimate the decrease in price and the value to society.
379

 SESSION 1G

ENVIRONMENTAL SCIENCES

Chair: Mr. Greg Boland, Minerals Management Service

Co-Chair: Ms. Debra Vigil, Minerals Management Service

Date: December 7, 2000

Presentation Author/Affiliation

Long-Term Monitoring at the East and

West Flower Garden Banks National

Marine Sanctuary 1998-1999

Dr. Quenton R. Dokken

Dr. John W. Tunnell

Mr. Carl R. Beaver 

Ms. Susan A. Childs

Mr. Thomas W. Bates

Dr. Kim Withers

Center for Coastal Studies

Texas A&M University-Corpus Christi

Dr. Ian R. MacDonald

Dr. Terry Wade

Geochemical Environmental Research Group

Texas A&M University

Surveys and Satellite Tracking Loggerhead

Sea Turtles (Caretta caretta) in and around

the Flower Garden Banks, Northwest Gulf

of Mexico

Ms. Emma L. Hickerson

Flower Garden Banks National Marine

Sanctuary

Texas A&M University

Platforms for Research: The “Migration

Over the Gulf” Project

Dr. Robert W. Russell

Center for Coastal, Energy, and

Environmental Resources (CCEER)

Louisiana State University

Effects of Oil and Gas Exploration and

Development at Selected Continental Slope

Sites in the Gulf of Mexico

Dr. Alan D. Hart

Continental Shelf Associates, Inc.

Jupiter, Florida

Bluewater Fishing and Deepwater OCS

Activity: Interactions Between the Fishing

and Petroleum Industries in Deepwaters in

the Gulf of Mexico

Mr. David B. Snyder

Continental Shelf Associates, Inc.

Jupiter, Florida

(continued on next page)
380

Presentation Author/Affiliation

Evaluation of Oil and Gas Platforms on the

Louisiana Continental Shelf for Organisms

ith Biotechnology Potential

Dr. Lawrence J. Rouse

Department of Oceanography and

Coastal Studies Institute

Louisiana State University
381

LONG-TERM MONITORING AT THE EAST AND WEST FLOWER GARDEN

BANKS NATIONAL MARINE SANCTUARY 1998-1999

Dr. Quenton R. Dokken

Dr. John W. Tunnell

Mr. Carl R. Beaver

Ms. Susan A. Childs

Mr. Thomas W. Bates

Dr. Kim Withers

Center for Coastal Studies

Texas A&M University-Corpus Christi

Dr. Ian R. MacDonald

Dr. Terry Wade

Geochemical Environmental Research Group

Texas A&M University

INTRODUCTION

Deep-water coral habitats in the northwestern Gulf of Mexico, the Flower Garden Banks (FGB)

were given “National Marine Sanctuary” status in 1992. The FGB are located on the edge of the

outer continental shelf of the Gulf of Mexico (GOM). East Flower Garden Bank (EFGB) located at

27o 54.5' North latitude and 93o 36.0' West longitude is approximately 193 km southeast of

Galveston, Texas. West Flower Garden Bank (WFGB) is located approximately 172 km southeast

of Galveston at 27o 52.4' North latitude and 93o 48.8' West longitude (Figure 1G.1). Both banks are

topographic highs created by uplift of underlying salt domes of Jurassic, Louann origin (Rezak

1981). These domes of bedrock overlying uplifted salt domes and capped by an overgrowth of

calcareous marine organisms represent the largest charted calcareous banks in the northwestern

GOM (Bright et al. 1985) and the northernmost coral reefs on the continental shelf of North

America (Bright et al. 1984). 

The coral cap varies in depth from approximately 18 to 36 m (Rezak et al. 1985). The pear shaped

EFGB, encompassing an area of approximately 67 km2

 (Rezak et al. 1985) slopes from the crest at

approximately 20 m to a seabed plane of terrigenous mud surrounding the banks at a depth of 100-

120 m. The eastern and southern edges of the bank slope steeply while the area to the north and west

of the coral cap exhibits a more gentle slope (Figure 1G.2). The major features of the 137 km2

WFGB are three crests aligned along an east-west axis (Figure 1G.3). The middle crest rises from

a depth of 100 – 150 m to within 18 m of the surface and supports a coral reef habitat (Rezak et al.

1985).

The FGB are unique in that they exist in the most active offshore oil/gas exploration and production

area in the world. Approximately 4,000 production platforms are located in the northern GOM

primarily in the northwestern quadrant with the FGB. Two kilometers to the east of the EFGB, a

production platform was installed in 1982 and has been producing natural gas since installation. In
382

Figure 1G.1 Location map of the East and West Flower Garden Banks in relation to the

continental shelf and other topographic features of the northwestern Gulf of

Mexico, (from Gittings et al. 1992).

1998, an additional well was drilled at this production site (dry well). To date, the production of oil

and gas in the near vicinity has not been demonstrated to be detrimental to the health and

productivity of the FGB.

METHODS

Sampling was conducted 27 September – 1 October 1998 and 12-16 September 1999. The methods

are a continuation of protocols established in 1989 by Gittings et al. (1992). Non-destructive

photographic sampling was the primary methodology (Dokken et al. 1999).

Fourteen 10 m random photographic transects at each bank were conducted to provide data on coral

community diversity and cover (Dokken et al. 1999). Transects were run both inside the designated

100 m2 study area and outside the study area to test the consistency of habitat conditions within and

outside the study area.

Sclerochronology was used to measure annual accretionary growth of Montastraea faveolata over

extended time periods. Encrusting growth of Diploria strigosa was measured at 60 close-up

photographic stations on each bank.
383

Figure 1G.2. Biotic zonation and topography of East Flower Garden Bank. The dark area

depicts the high diversity coral reef zone (from Rezak et al. 1985).
384

Figure 1G.3. Biotic zonation and topography of the West Flower Garden Bank. The darkest

area depicts the high-diversity coral reef zone (from Rezak et al. 1983).
385

Forty repetitive quadrats were photographed at each bank to monitor changes in community

structure. Permanent photographic stations were established in 1989 (Gittings et al. 1992). Each

quadrat photographic was repeated in 1998 and 1999 to compare and contrast with prior years.

Video transects (100 m) were recorded along the boundary lines of the study area. These were

compared to previous video transects and archived for historical record.

Temperature, insolation, and hydrocarbons within the water column were measured. Continuous

recording thermistors were used to record temperature and Li-Cor spherical light sensor measure

photosynthetically active radiation (PAR). Semi-permeable Membrane Devices (SPMD) were

deployed to sample the water column for polycyclic aromatic hydrocarbons, PCB, and pesticides.

Transect surveys of herbivorous sea urchins, Diadema sp., were conducted. Additionally, visiting

scientists conducted studies of algal ecology, carbon distribution and flow, micromollusc

populations, and pore water quality.

RESULTS

The results were generally unremarkable and consistent with past data. The one notable occurrence

was the increase in algal biomass at the expense of bare reef rock. The cause of this is not known.

Population densities of Diadema sp., a primary control of algal biomass, remained very low. 

The results of the SPMD (water quality) were possibly compromised due to juvenile crustaceans

tearing pinholes in the membranes. Shorter deployments will be required to eliminate this

occurrence. Contaminants recovered were in very small concentrations.

Guest scientists recorded 72 species of algae, more than 100 new species of micromolluscs for the

FGB, and described the FGB as “autogenous” with blue-green algae the primary source of nitrogen.

And, based on laboratory studies of toxicity, the pore water of the FGB sediments was found not to

contain toxic levels of any contaminants.

CONCLUSION

The FGB continue to be healthy and productive. The monitoring program continues to expand one

of the longest continuous databases for coral reefs in existence. Through the monitoring and

associated research efforts understanding of the dynamics of the FGB is increasing.

REFERENCES

Bright, T.J., D.W. McGrail, R. Rezak, G.S. Boland, and A.R. Trippet. 1985. The Flower Gardens:

A compendium of information. U.S. Dept. of Int. Minerals Mgmt. Service, Gulf of Mexico. OCS

Regional Office, New Orleans, Louisiana. OCS Study MMS 85-0024. 103 p.

Bright, T.J., G.P. Kraemer, G.A. Minnery, and T.S. Viada. 1984. Hermatypes of the Flower Garden

Banks, northwestern Gulf of Mexico: a comparison to other western Atlantic reefs. Bull. Mar.

Sci. 24(3):461-476.
386

Dokken, Q.R., I.R. MacDonald, J.W. Tunnell, C.R. Beaver, G.S. Boland, and D.K. Hagman. 1999.

Long-term monitoring of the East and West Flower Garden Banks 1996-1997. U.S. Dept. of Int.

Minerals Mgmt. Service, Gulf of Mexico. OCS Region, New Orleans, Louisiana. OCS Study

99-0005. 101 p.

Gittings, S.R., G.S. Boland, K.J.P. Deslarzes, D.K. Hagman, and B.S. Holland. 1992. Long-term

monitoring at the East and West Flower Garden Banks. U.S. Dept. of the Int. Minerals Mgmt.

Service, Gulf of Mexico. OCS Regional Office, New Orleans, Louisiana. OCS Study MMS 92-

0006. 206 p.

Rezak, R. 1981. Geology pp. 23-59. In R. Rezak and T.J. Bright, eds. Northern Gulf of

MexicoTopographic Features Study. Final Report to the U.S. Dept. of Int., Bureau of Land

Mgmt. Contract #AA551-CT8-35. Vol. 1. NTIS Order No. PB81-248650:23-59.

Rezak, R.,T. J. Bright, and D.W. McGrail. 1985. Reefs and banks of the northwestern Gulf of

Mexico: Their geological, biological, and physical dynamics. John Wiley and Sons, New York,

NY. 259 p.
387

SURVEYS AND SATELLITE TRACKING LOGGERHEAD SEA TURTLES

(CARETTA CARETTA) IN AND AROUND THE FLOWER

GARDEN BANKS, NORTHWEST GULF OF MEXICO

Ms. Emma L. Hickerson

Flower Garden Banks National Marine Sanctuary

Texas A&M University

ABSTRACT

More than five years of underwater/above water surveys resulted in 140 reports documenting 153

sea turtle sightings within the boundaries of the Flower Garden Banks National Marine Sanctuary

(FGBNMS) in the northwestern Gulf of Mexico (GOM). Six large immature loggerhead sea turtles

(Caretta caretta) with carapace lengths (CCL) ranging from 70.5-101cm were captured at depth by

SCUBA divers. Five of the six were outfitted with satellite transmitters. Five of the six animals were

females. Over 40% of the satellite locations fell within the Sanctuary boundaries. Geographic

Information System (GIS) analysis revealed an average core range of 133.6 km2

 and an average

home range of 1,074 km2. These ranges are not significantly different from satellite tagged C.

caretta captured underneath oil and gas platforms in the GOM. The average core ranges fell within

one kilometer of the sanctuary boundaries, and the home range within 30 km of the sanctuary

boundaries. Management recommendations are made to the National Oceanic and Atmospheric

Administration’s (NOAA’s) Marine Sanctuary Division.

INTRODUCTION

This data is the result of sea turtle satellite tracking conducted at the Flower Garden Banks National

Marine Sanctuary from June 1995 – August 1999.

The East and West Flower Garden Banks are located over 180km SSE of Galveston, Texas. They

are separated by about 20km of open ocean - of depths around 130m. The Flower Garden Banks are

the northernmost coral reefs on the North American continental shelf. The Sanctuary is one of 13

Federal Marine Sanctuaries within National Oceanic and Atmospheric Administration (NOAA). The

Flower Garden Banks National Marine Sanctuary designated as a sanctuary in 1992. Stetson Bank

was added to the FGBNMS in 1996. The banks themselves are the surface expression of salt diapirs

capped by living coral reefs. The reefs are estimated to have been in existence for 10-15,000 years.

The West Bank is approximately 90 square km in size, with a reef crest covering 0.4 square km,

rising to within 20m of the surface. The East Bank is a pear shaped dome approximately 5 km in

diameter, with a square kilometer of reef crest rising from over 100m depth to within 18m of the sea

surface.

Stetson Bank is composed of claystone outcroppings that have been pushed up to within 17m of the

sea surface. The most conspicuous features of this bank are the pinnacles, which stretch along the

northwest face for a distance of approximately 500m. They rise from about 65m on the northwest
388

side and slope off to around 23m on the southeast side where a large, flat area dotted with small

rocky outcroppings stretches out behind the pinnacles region.

At the East and West FG Banks, above 36m in depth, the hermatypic corals—four species of

Montastrea (a star coral), and two brain corals - Diploria strigosa and Colpophyllia natans,

dominate the landscape along with approximately 17 other species. These corals represents

approximately one-third the number of species of coral found in other Caribbean reef systems such

as Bonaire and Florida Keys. Monitoring efforts report over 50% coral coverage. (Similar to

Bonaire, but higher than most areas of the Florida Keys).

Monitoring efforts over the past 20 years have shown that this is a very healthy reef system. It is

home to many of the typical Caribbean assemblages of invertebrates and fish, but has fewer species

than some: just over 200 species of fish. Usual visibility in winter is around 20m with summer

visibility averaging round 30m. Seasonal occurrence of pelagic elasmobranchs at the Flower

Gardens has been documented by Jeff Childs of the Wildlife and Fisheries Department at Texas

A&M University. Around 27 species of elasmobranchs occur at the sanctuary, including the wintertime species. Whale sharks occur during the late summer months. These animals we refer to as the

charismatic megafauna of the Sanctuary, included in this category are the sea turtles. Sea turtles are

endangered and threatened species.

Life Cycle of Sea Turtles

1. The majority of sea turtle research is conducted on nesting beaches where hundreds, and

sometimes thousands, of animals converge to dig holes and lay their eggs. This life history

stage of sea turtles is the best documented. Unfortunately, the nesting represents but a

fleeting visit by the animals—their home is in the water—where the females will spend over

95% of their time. Males may never return to land once they have left their beach of origin.

The ocean environment is a difficult place to conduct research, and therefore, limited studies

have been undertaken there.

2. Offshore from the nesting beach, males congregate to meet the incoming migrating females.

Mating takes place either here or in unknown oceanic areas along the migration route. 

3. The males head back to their adult feeding grounds after a period of mating, leaving the

females to their nesting cycle. After this cycle is completed, they too head to the adult

feeding grounds. 

4. After 8 – 10 weeks of incubation, the eggs hatch and the hatchlings make their mad dash

to the ocean. At this time, they enter a period in their lives that referred to as the “lost

year”—actually, it is many years. During this period very little is known of the animals’

whereabouts. It is generally accepted that hatchlings are associated with drifting Sargassum

mats. After possibly as many as 20 years, the animals reappear as juveniles on juvenile

feeding grounds. The Flower Gardens, I believe, is one of these grounds, but for large

juveniles. We have, however, documented one adult animal. 
389

After going through several years of puberty, the now-adult animals migrate for reproduction and

return to an adult feeding ground or perhaps to the same feeding ground they utilized as large

juveniles.

Project Objectives

1. Determine what species of sea turtles occur at the study site;

2. Attach radio transmitters to turtles to determine whether they are resident animals and learn

about their use of the Sanctuary (we are also able to learn something about how much time

they spend on the surface by using transmitters);

3. Attach satellite transmitters to turtles to learn to what depths the animals descend during

their dives to determine their core and home ranges and migratory routes;

4. Recommend management strategies, if needed, to the Sanctuary for necessary protection of

the animals.

METHODS

Sighting Data

I relied on volunteer divers to provide much of the sighting data. To encourage recreational divers

to report their sightings, I placed informational posters onboard in the galley area and other strategic

places. The posters had descriptions and pictures of the five species of turtle found in the GOM,

description of how to sex a turtle, and explanations of how divers could participate in the study.

I placed sea turtle information sheets onboard and provided slates for their use underwater by those

taking notes of their sea turtle observations—e.g. if the turtles had barnacles on their carapaces, they

could document the location directly onto the slate. Census forms were also placed on board for the

divers to report their observations. I asked them to attempt to identify the species and sex, to

estimate carapace length and width, and to note any identifying characteristics such as barnacle

patterns, missing/notched flippers and scutes. Divers were also asked to provide some details such

as date, time, location, weather conditions, and their contact information. These forms were left

onboard for my collection.

I encouraged the divers to provide any available photographs or videos of the turtles they

encountered. With these I created a catalog of individual sea turtles—using the identifying

characteristics. This is a short-term way of documenting the persistence of individuals, as barnacles

are not permanent features on the shells of the animals. I hope to test this method of identification

over time as I intend to place the catalog on the Sanctuary website and onboard the recreational dive

vessels so that people can refer to them. Of course, missing flippers and notching of carapaces are

more of a long-term identification characteristic.
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Satellite Telemetry

The most challenging part of this project was finding an animal and capturing it. Both volunteers

and I spent many hours for an animal to put in the net.

In the event that a resting animal was found, a designated diver would immobilize the animal by

tipping it slightly forward to stop it from using its strong front flippers to start swimming. (If the

animal is large enough and is allowed to start swimming forward, there is nothing to do but to let

go.) A second diver was assigned to be ready with the capture net to receive the animal. 

Once the turtle was in the net, ropes were tied onto the metal mouth of the bag and used by the

divers to carry the net and turtle as they made their slow ascent, including a safety stop, to keep their

hands out of reach of the turtle’s powerful jaws.

Once the animal was safely on deck, it was checked for any injuries. Then the carapace was cleaned

off and dried, biological measurements taken, including measurements of carapace and plastron

length and width, size of head, tail, and claws. The animals were usually PIT tagged, as well as

flipper tagged. Blood was sampled from a dorsal sinus located in the neck. The serum was used to

determine the sex of the animal, and the red blood cells were stored for genetic analysis. The

satellite transmitter was either fiberglassed or epoxied onto the carapace. It usually took around two

hours to completely process an animal before it was released. 

Several factors have to come into play for a transmission to occur. The transmitters only send a

signal when the animal is on the surface and the transmitter is turned “on.” The transmitters were

preprogrammed with a duty cycle: some of them were set for 8 hours on, then 52 hours off, and two

of them were set to transmit constantly, that is, 24 hours on. Also, the transmitters were equipped

with saltwater switches that prevent transmissions when they are submerged (or, in some cases,

when the animal is on the surface but the transmitter is being affected by high seas). The animals

only surface for perhaps two to three minutes per hour, if that. For location information to be

obtained, the animal must remain on the surface for at least that time to send off several signals. One

of the two NOAA satellites must be within range of the animal—about eight minutes per satellite

pass. When these factors all come together, the satellite receives several messages and relays them

to the ground in real time. The satellites record the data and dump the messages as they pass over

of the receiving stations. The receiving stations then pass on the raw Argos data to the processing

centers, which then process the data and pass it on to the Argos user.

Argos locations are calculated by measuring the Doppler shift on the transmitter signals. The

Doppler shift change in frequency of a sound wave or electromagnetic wave when a source of

transmission and an observer are in motion relative to each other. Each time the satellite receives

a message from a transmitter, it measures the frequency and time-tags the arrival. Argos assesses

the data and allocates a Location Class to each fix, depending upon the number of messages

received, the satellite and transmitter geometry during the message reception and the transmission

stability. 
391

I assessed the location data using two methods - the first was looking at core and home ranges using

an extension to Arcview called Animal Movements - developed by USGS at the Alaska Biological

Science Center. Based on the location points I input, this program calculated an area within which

a 50% probability exists that a given point will fall—called the core range—and an area within

which a 95% probability exists that a given point will fall—the home range.

The second way I assessed the location data is by a method I call the Satellite Fix Proximity

Relationship. I created this method because I wanted to look at the data in relation to the National

Marine Sanctuary boundaries. For this reason, I created several zones. The center of each zone is

the area within the Sanctuary. Radiating outwards from the banks are the other zones, out to 1km,

5km, then 6.44km, a distance that equals 4 miles. The Flower Garden Banks lie within one of the

most active petroleum fields in the world. There is an active gas platform within the Sanctuary

boundaries on the East Bank, within 1 mile of the reef crest. Minerals Management Service created

regulatory zones to protect many biological hardbottoms within the GOM. There is a 4-mile

regulatory zone around the banks of the Flower Gardens. The oil and gas industry must adhere to

special regulations within these areas, for example, they are required to shunt drilling muds to within

approximately 10m of the sea floor during drilling operations. Other zones created for the purpose

of this study are at 10km and 30km.

RESULTS

Sighting Data

Both untrained and trained recreational and scientific divers collected the sighting data between

August 1994 and April 2000. 

A total of 153 sea turtle sightings were gathered, reporting three different species, Caretta caretta,

the loggerhead sea turtle, Eretmochelys imbricata, the hawksbill, and Dermochelys coriacea, the

leatherback sea turtle. 

Loggerheads comprised 87% of the animals identified. More sightings took place underwater than

on the surface (where the animals are often sighted as they surface for air). The majority of the

sightings took place at the East Bank. The average estimated carapace length reported by observers

was around 1m. Around one-quarter of the animals reported at Stetson Bank were hawksbills. Four

post-hatchlings associated with Sargassum were observed. Unfortunately, one of these animals was

eaten by a jack while passing by the dive platform. six animals were observed on multiple occasions.

According to records from one dive charter operator, diving pressure is greatest at the East Bank and

the least at the West Bank. From diver usage information I have determined that there are similar

numbers of turtles at both of the Flower Garden Banks and fewer turtles at Stetson Bank. A large

percentage of the observations were made during the summer season because the boats are on a

more rigorous schedule during this season.
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Satellite Telemetry

Over the course of the study, 6 animals with carapace lengths ranging from around 70 and 100 cm

were captured, and all but one of these animals were females. The male (whom we named Triton)

was captured on three occasions over a period of twenty months. Most captures were conducted at

night. Three animals were captured on each of the Flower Garden Banks. 

The five functioning transmitters received a total of 771 messages—426 of which did not provide

a location. A total of 278 of the remaining 345 satellite fixes were accepted for analysis.

Transmission days totaling 1,450 days were obtained in fairly equal portions between the seasons.

Most of the accepted fixes were received during the summer and fall because the sea conditions

during the winter and spring tended to be rougher than summer and fall, not allowing for quality

transmissions.

The average core range for the five turtles was around 134 km2

 and encompassed nearly the entire

Flower Garden Banks National Marine Sanctuary. The average home range was 1,074 km2

.

We can use this data to assist with management decisions. For example, we can determine what

percentage of the core and home ranges we are protecting now. We can see that about 72 % of the

core ranges of the animals are now protected within the Sanctuary boundaries, but only 44% of the

home ranges are protected within the boundaries.

During the next couple of years, the Flower Garden Banks National Marine Sanctuary will be

reviewing its management plan, including regulations. It will be reviewing, for example, the current

boundaries and fishing regulations. 

The data collected in this study suggest that if, for example, long-line fishing regulations were

implemented, or the Sanctuary boundaries were extended to the MMS 4-mile zone, nearly all of the

core ranges for these animals would be protected, as well as substantially more of the home ranges.

The core range protection would increase by 25% and home range by nearly 37%.

I selected the MMS 4-mile zone as it is already in place and may perhaps provide a foundation for

establishing further regulations.

Renaud and Carpenter, from the National Marine Fisheries Service in Galveston, captured four

loggerhead sea turtles as the animals slept underneath oil and gas platforms in the GOM. They

attached satellite transmitters to their carapaces and determined their core and home ranges (using

a different type of analysis than was used in this study).

One of the animals apparently responded to a cold front by moving farther offshore in search of

warmer water. After the cold front passed, the animal moved east into waters off Louisiana. I

considered this animal to be an outlier and did not use it in the analysis, leaving three animals in the

analysis.
393

When I compared the core and home ranges for both sets of animals, one living in an artificial

habitat and the other living on natural reef, I found that there was no significant difference between

the two. 

I am wary of these data because the numbers of animals are very low (5 and 3), but I felt compelled

to include them in my report, as they represent information not easily obtained and not reported

previously.

CONCLUSIONS

• A population of resident loggerhead sea turtles utilizes the resources of the FGBNMS.

• Female loggerheads are the most often observed turtles at the Flower Garden Banks. It is

interesting to note the sex ratio of the captured animals (five females and one male), as this

is the same sex ratio of the South Florida loggerhead nests (see preliminary genetic data).

• Large juvenile animals are the dominant life history stage reported, and on occasion,

hatchlings and post-hatchlings pass through in Sargassum mats. One adult female animal

was documented.

• Hawksbills occurred at Stetson Bank at a higher ratio than either the East and West Bank ,

probably because the available sponges growing there.

• Over the course of this study, more turtles were observed at the Flower Garden Banks than

Stetson Bank. 

• The carapace length reported by observers is overestimated. I believe the captured animals

(average carapace length of approximately 83 cm) is a representative group of the population

of loggerhead sea turtles at the Flower Garden Banks. This overestimation is probably due

to the fact that observers report the entire length of the animal, including the head.

• Hatchling and post-hatchlings found in Sargassum are susceptible to predation by chubs and

jacks that come off the reef to feed or are associated with the moored vessels. I have

witnessed this feeding behavior adjacent to oil and gas platforms. It is my prediction that

increased platform installations and creation of artificial submerged habitat increases the

predation of hatchlings on the surface.

• This study suggests that loggerheads living at natural and artificial reef structures (oil and

gas platforms) exhibit similar core and home ranges.

• Two methods of location data analysis may be used to evaluate the effectiveness of current

protection and make recommendations for management and protection decisions.
394

REFERENCES

Argos. 1984. Location and data collection satellite system user’s guide. Toulouse, France: Service

Argos. 36 pp.

Argos. 1996. User’s Manual. Largo, Maryland: Service Argos. 176 pp. 

Elvers, D.J. and C.W. Hill. 1985. History of Activities at the Flower Garden Banks. In The Flower

Gardens: a compendium of information. T.J. Bright, D.W. McGrail, R. Rezak, G.S. Boland, and

A.R. Tripett, eds. Minerals Mgmt. Service, OCS Studies/MMS 85-0024.

Hickerson, E.L. 2000. Assessing and tracking resident, immature loggerheads (Caretta caretta) in

and around the Flower Garden Banks, northwest Gulf of Mexico. Master’s Thesis. Biology

Department. Texas A&M University.

Hooge, P.N. and B. Eichenlaub. 1997. Animal movement extension to arcview. Ver. 1.1. Alaska

Biological Science Center, U.S. Geological Survey, Anchorage, Alaska.

Lutz, P.L. and J.A. Musick, eds. 1997. The biology of sea turtles. Boca Raton, Florida: CRC Press,

Inc.

Musick, J.A. and C.J. Limpus. 1996. Habitat Utilization and Migration in Juvenile Sea Turtles. In

The Biology of Sea Turtles. Lutz, P.L. and J.A. Musick, eds. Boca Raton, Florida: CRC Press,

Inc. 137-163.

Owens, D.W. and G. J. Ruiz. 1980. New methods of obtaining blood and cerebral spinal fluid from

marine turtles. Herpetelogica. 36:17-20.

Renaud, M.L. and J.A. Carpenter. 1994. Movements and submergence patterns of loggerhead turtles

(Caretta caretta) in the Gulf of Mexico determined through satellite telemetry. Bull. Mar. Sci.

55(1):1-15.

Rezak, R. 1985. Geology of the Flower Garden Banks area, pp. 31-50. In The Flower Gardens: a

compendium of information. T.J. Bright, D.W. McGrail, R. Rezak, G.S. Boland, and A.R.

Tripett, eds. Minerals Mgmt. Service, OCS Studies/MMS 85-0024.
395

PLATFORMS FOR RESEARCH: THE “MIGRATION OVER THE GULF” PROJECT

Dr. Robert W. Russell

Center for Coastal, Energy, and Environmental Resources (CCEER)

Louisiana State University

Each spring, roughly a billion landbirds migrate northward across the Gulf of Mexico, en route to

breeding habitats from their wintering quarters in the tropics. Following a short breeding season in

the north, most of these birds return southward across the Gulf, their numbers then augmented by

offspring produced over the summer. Although these massive trans-Gulf migrations (TGMs)

represent one of the great behavioral events of the world, basic aspects of TGM (such as species

composition, flight routes, orientation tactics, and responses to weather) have been poorly known.

The flight pathway of a large proportion of trans-Gulf migrants is directed over Gulf waters in which

are located about 4,000 offshore oil and gas production platforms. These platforms make up the

largest artificial island system in the world. In light of the absence of natural islands or other

terrestrial habitats during crossings of the Gulf of Mexico, it seems inevitable that the installation

of an expansive artificial archipelago in the northern Gulf must affect migrants in some fashion.

However, until recently, no systematic studies had examined the interaction between platforms and

migrating birds. 

Our MMS-sponsored study of TGM and migrant-platform interactions began in spring 1998, and

fieldwork concluded in November 2000. The study is currently based at the LSU Center for Coastal,

Energy, and Environmental Resources (CCEER), and is funded by MMS through a cooperative

agreement with the LSU Coastal Marine Institute. Six major petroleum companies (BP,

ExxonMobil, Newfield, Phillips, Shell, and Texaco) have made platforms available to the study and

have provided in-kind support in the form of helicopter transportation of personnel, boat

transportation of equipment, offshore housing and meals for personnel, and other forms of logistical

assistance.

The large-scale design of the study evolved over the course of the fieldwork as we discovered more

about TGM. During the first three field seasons (spring and fall 1998, spring 1999), we operated on

five platforms off the Louisiana coast. During that initial exploratory phase, we discovered that the

largest migratory flights often occur to the east (fall) or west (spring) of Louisiana. With the aid of

a second MMS contract and additional assistance from our cooperating companies, we expanded

to ten platforms in fall 1999 and nine platforms in spring 2000, and also expanded the field seasons

temporally to cover the migration periods more completely. This second “confirmatory” phase of

the study enabled us to achieve a more Gulf-wide perspective on migration and to test some of our

radar-derived hypotheses concerning flight routes and platform influences. During the concluding

phase of the study (fall 2000), we reduced our coverage to three platforms where we conducted

several focused studies on migrant behavior. Over the course of the study, our field team

has completed the equivalent of about eight continuous platform-years of monitoring (i.e., the

equivalent in effort to one observer monitoring a single platform for eight years continuously with

no breaks).
396

Our work has demonstrated that platforms constitute a significant component of the en route

environment of trans-Gulf migrants. Although a small proportion of the total numbers of birds

migrating over the Gulf stops on platforms, platform use varies dramatically among species, and in

some cases is of great ecological significance. The diversity of impacts is too great to summarize

here, so four specific examples follow:

1. Large numbers of Peregrine Falcons—perhaps the majority of the North American breeding

population of this species—use oil platforms in the northern Gulf during the fall for resting

and hunting. The species was federally listed as endangered until recently. Peregrines often

appeared on platforms immediately before weather events that induced large landbird

movements. Because of their high subsequent success preying on migrants, it seems that

Peregrines are now “anticipating” ephemeral periods of high resource availability. This

adaptive behavior may be a precursor to more dramatic evolutionary changes in the life

history of the species, since an ecologically similar species—Eleonora’s Falcon—has

evolved a strategy of breeding on islands in the Mediterranean during the fall,

when abundant trans-Mediterranean migrant landbird prey are available for provisioning

young.

2. The archipelago of offshore oil platforms may be facilitating the natural selection of a TGM

strategy in several species. One of the most common birds on platforms is the Cattle Egret,

a species that colonized eastern North America in the last half-century. A rapid evolution of

TGM may be implicated in what appears to be a population explosion and major range

expansion of White-winged Doves into the southeastern United States. Another dove

species—the Eurasian Collared-Dove—has recently colonized North America, and it began

showing up on platforms in fall 1999. Platforms may facilitate the evolution of TGM

strategies in certain species by providing “steppingstones” that allow incipient migrants to

cross the Gulf successfully via a series of shorter flights.

3. During the fall, many short-distance migrants that spend the winter along the Gulf Coast

(such as wrens, kinglets, and sparrows) inadvertently “overshoot” the coastline during

nocturnal migratory flights and end up over Gulf waters. These overshoot migrants, which

are evolutionarily ill-equipped to deal with the rigors of overwater migration, are among the

heaviest users of platforms during the fall, and the availability of platform rest stops

probably enables many individuals to return to land successfully. This reduction in selection

pressure may in turn be implicated in large-scale shifts in the wintering distributions of some

of these species.

4. Because platforms in the northern Gulf are located toward the tail end of a northbound transGulf flight, the existence of the platform archipelago reduces the distance that a spring

migrant must cross over water during one leg. Under normal weather circumstances, many

spring trans-Gulf migrants do not stop when they reach the northern Gulf coast, but instead

proceed inland variable distances to suitable stopover habitats or even to the breeding

grounds. However, sometimes migrants unexpectedly encounter poor weather en route

across the Gulf, and many individuals are then forced down and perish in the Gulf. The

refuge provided by platforms can ameliorate high weather-induced mortality and can
397

theoretically have important population-level impacts on species with small continental

populations, due to the disproportionate impact of stochastic effects on small populations.

During our first two field seasons, we discovered an unexpected abundance of terrestrial insects

offshore and expanded our focus to include insect monitoring via both visual censuses and

quantitative sampling with ultraviolet light traps. During both spring and fall, a large blanket of

terrestrial insects—the “aerial plankton”—is transported offshore by north winds. This aerial

plankton represents a significant food resource for birds that stop to rest on platforms. Many of the

birds are able to forage successfully, and in fact, energy intake rates of birds on platforms have

sometimes been observed to be higher than generally observed in “natural” habitats onshore. The

frequent abundance of migratory moths and other insects on platforms is especially important to

fuel-depleted migrant birds forced down by foul weather during the spring and to the overshoot

migrants during the fall.

In addition to the passively transported insect fauna, we have found that several species of

dragonflies and moths are active trans-Gulf migrants. Trans-Gulf migration in insects has important

implications for understanding large-scale biogeographic patterns as well as life-history strategies

of the species involved. 

We have also been monitoring the occurrence and behavior of fishes and seabirds in the vicinity of

our platforms. This more opportunistic work has suggested a complex series of ecological

interactions centered around platforms. Platforms appear to attract macrozooplankton and “baitfish,”

either by behavioral attraction or by mechanical entrainment in convergent flows induced by the

platform substructures. This fauna in turn attracts predatory fishes such as Blue Runners and tunas.

Obligate surface-feeding seabird species are in turn attracted to the vicinity of the schools of

predatory fish, where they take buoyant scraps from the fish feeding frenzies. These relationships

merit further attention, because concentration of marine bird populations in the vicinity of platforms

may be a conservation concern in the event of oil spills.

Our study has yielded many new discoveries concerning TGM and has provided important

information about the effects of offshore platforms on trans-Gulf migrants. Our observations also

suggest that the platforms have altered the ecology of the Gulf in diverse ways, facilitating a variety

of complex and multi-trophic ecological interactions among marine plankton, fish, seabirds,

landbirds, and terrestrial aerial plankton. While platforms may be beneficial to some organisms, a

more important impact may prove to be their tremendous value to scientists as research platforms

for learning more about the ecology of the Gulf. Our study serves as a successful model for how

private industry, government, and academia can join forces and work cooperatively to achieve

important research and environmental goals. As we shift into the writeup phase of the program, we

will highlight the issues relevant to managing the “platform archipelago” as a resource for migrating

birds, and the value of platforms for research and ecological monitoring.
398

Robert W. Russell received his Ph.D. in ecology and evolutionary biology at the University of

California at Irvine in 1994. His dissertation work involved using radars to quantify spatial

distributions of birds and insects in the atmosphere and their relationships to atmospheric structure.

He spent several years as a research scientist with NOAA in Seattle before moving to the Louisiana

State University in January 1998 to lead the new MMS-sponsored study of bird migrations and

offshore platforms in the Gulf of Mexico. His primary research interests concern the ecology of bird

and insect migrations, but he has also been active in biological oceanography, studying relationships

between ocean physics, zooplankton distributions, and seabird ecology in both Arctic and Antarctic

seas.
399

EFFECTS OF OIL AND GAS EXPLORATION AND DEVELOPMENT AT SELECTED

CONTINENTAL SLOPE SITES IN THE GULF OF MEXICO

Dr. Alan D. Hart

Continental Shelf Associates, Inc.

Jupiter, Florida

Continental Shelf Associates, Inc. and its subcontractors/consultants are conducting a multiyear

study to assess the impacts of oil and gas exploration and development at selected sites on the

continental slope in the Gulf of Mexico (GOM). These sites are two exploration sites, which are

being sampled before and after drilling, and three post-development sites, which are being studied

once after drilling. In addition, a single site where approximately 800 barrels of synthetic based mud

was spilled is also being studied. The two exploration sites, Garden Banks Area Block 516 and

Viosca Knoll Area Block 916, are located in water depths of about 1,000 m. The three postdevelopment sites are Mississippi Canyon Block Area 292, Mississippi Canyon Area Block 934, and

Garden Banks Area Block 602. Water depths at these post-development sites are about 1,100 m. The

water depth at the spill site, Mississippi Canyon Area Block 592, is approximately 670 m. Both

water based and synthetic based muds were used in the drilling of the development wells and will

be used in the drilling of the exploration wells. 

The program consists of two components: physical characterization and chemical/biological

characterization. The objective of the physical characterization is to determine the physical impacts

of the operations including

1. areal extent and accumulation of muds and cuttings;

2. physical modification/disturbance of the sea bed due to anchors and their mooring systems;

and

3. accumulation of debris due to operations.

These physical impacts will be determined from acoustic reflectivity maps produced from data

collected with a deep-towed side-scan sonar and subbottom profiling system. 

The objectives of the chemical/biological characterization are 

1. to determine the extent of physical/chemical modification of sediments in the immediate

area of the wellsites compared to sediment conditions at reference sites (and before drilling

in the case of exploration sites) and

2. to conduct limited biological collections to determine biological effects related to chemical

and physical impacts.
400

Box core samples will be collected at 12 locations within 500 m of each exploration/development

site, and two box cores will be collected at each of six reference sites located at least 10 km from

each exploration/development site. Sediment grain size, mineralogy, texture, radionuclides, metals,

total organic carbon, and hydrocarbons will be analyzed. Samples for pore water, redox chemistry,

and sediment toxicity (10 day acute test) also will be collected. Sediment profiling imagery transects

will be performed near each site and at two of the corresponding reference sites. The biological

community will be sampled using a box core, still photographs, and bottom traps. A number of

biological parameters will be measured:

1. microbiotal activity, biomass, and community structure;

2. meiofauna taxonomy including harpacticoid taxonomy/genetic diversity/reproductive status

and nematode feeding groups; and

3. megafaunal taxonomy and metal/hydrocarbon concentrations in tissues of selected animals.

Interpretation and synthesis of the data will include the testing of hypotheses concerning differences

in chemical and biological parameters between areas in the vicinity of exploration, development,

and spill sites and reference areas. The tests of hypotheses will provide insight into the effects on

the continental slope biota. Relationships between physical/chemical variables and biological

variables will also be examined. The data will be used to provide first-order estimates of the extent

of impact. A screening level ecological risk assessment for the activities will also be performed.

Dr. Alan Hart is the Science Director of Continental Shelf Associates, Inc. located in Jupiter,

Florida. He has 19 years of experience in marine environmental science, including major research

programs for federal, state, and industrial clients. He has been involved in characterization and

monitoring studies covering a wide range of human activities in the marine environment, including

oil and gas operations, dredged material disposal, beach restoration, and sewage outfalls. Dr. Hart

received his B.S. degree in zoology from Texas Tech University in 1973 and his Ph.D. Degree in

biological oceanography from Texas A&M University in 1981.
401

BLUEWATER FISHING AND DEEPWATER OCS ACTIVITY: INTERACTIONS

BETWEEN THE FISHING AND PETROLEUM INDUSTRIES IN

DEEPWATERS OF THE GULF OF MEXICO

Mr. David B. Snyder

Continental Shelf Associates, Inc.

Jupiter, Florida

INTRODUCTION

The fishing and offshore energy industries have coexisted amicably for many years in shelf waters

of the northern Gulf of Mexico (GOM). Recently, the offshore energy industry in the (GOM) has

shifted its interest beyond the shelf and into deeper waters (>200 m). This shift is evidenced by over

3,800 active leases and about 50 development/production facilities in water depths greater than 200

m. Existing and future structures represent new and evolving technology that could interact with

deepwater (bluewater) fisheries. All phases of industry—geophysical surveys, exploratory drilling,

development/production, and abandonment—could interact with current deepwater fishing practices.

In the northern GOM these practices include trapping for golden crab, trawling for royal red shrimp,

bottom longlining for groupers, snapper, and tilefishes, and surface longlining for sharks, swordfish,

and tunas.

The potential for interactions between bluewater fishing and deepwater energy industry was raised

as a primary concern by a fisheries subcommittee during a recent deepwater workshop (Carney

1998) sponsored by the Minerals Management Service (MMS). In 1999, Continental Shelf

Associates, Inc. was awarded a contract to investigate this problem for MMS. The project team

consists of independent consultants with experience in fisheries, oil and gas technology, space-use

problems, and Geographical Information Systems (GIS).

OBJECTIVES

We are assessing actual and potential interactions between the two industries through the following

objectives:

• Determine bluewater fishing endeavors and practices and deepwater outer continental shelf

(OCS) energy development activities;

• Describe and map bluewater fishing and deepwater OCS energy development activities;

• Describe current GOM and relevant world wide interactions and predict future situations that

may occur in the GOM between bluewater fishing and deepwater OCS energy development

activities; and

• Recommend proactive mitigation measures for MMS and for the fishing and OCS energy

industries.
402

METHODS

The first two objectives are being addressed by gathering descriptive information and “mappable”

data from a variety of sources for the two industries. Past and current information on the OCS

energy industry will be obtained from MMS data sets that contain active leases, filed Plans of

Exploration (POEs), existing development facilities, and existing pipelines. Existing facility

descriptions will come from filed Development Operations Coordination Documents (DOCDs) or

POEs, U.S. Coast Guard files, and industry operators. Descriptions of exploratory drilling rigs will

come from various drilling rig contractors. Future OCS activity will be projected from the MMS

data sets that include active leases with filed POEs or DOCDs, announced discoveries with filed

POEs or DOCDs, and future pipelines. In addition, an analysis of lease bonuses paid on existing

leases will be made to determine which lease block received high bids.

The bluewater commercial fishing industry will be described from data obtained from National

Marine Fisheries Service (NMFS) data sets. Several data sets will be examined, including the

longline logbook data set, the shrimp data set, and the reef fish logbook data set. These data sets

provide varying levels of spatial resolution, ranging from latitude/longitude (degrees and minutes)

to large scale (kms) NMFS statistical grids. Catch and effort information will be extracted from the

data sets to characterize spatial and temporal patterns in the northern Gulf of Mexico. Species

composition and life-history characteristics will be described for primary deepwater fisheries

species.

Current domestic conflicts are being gathered from U.S. Coast Guard, Fishermen’s Contingency

Fund, and California Fisheries Liaison Office. Information on international interactions will be

compiled from a variety of sources including Canada-Nova Scotia Offshore Petroleum Board,

Fisheries and Offshore Consultative Group (North Sea), United Kingdom Offshore Operators

Association Compensation Fund, and Department of Fisheries Malaysia.

RESULTS

The most common facilities used in deepwater operations are fixed platforms, semi-submersible

floating production systems, compliant towers, tension leg platforms, spars, and subsea completions

(Figure 1G.4). The spatial preclusion of seafloor or water column by these facilities depends upon

the type of mooring system used and the water depth. For example, catenary moored systems cover

much greater portions of the seafloor than do tension leg systems.

Presently there are about 3,800 active leases in waters greater than 200 m deep, with approximately

50 platforms currently operating in these water depths. Areas with the future activity are in

Mississippi Canyon, Green Canyon, Garden Banks, and Viosca Knoll lease block areas. Of the 3,800

leases, about 800 received bonus bids exceeding $1 million. With the exception of Corpus Christi

and Port Isabel, where there has been little if any drilling success to date, all OCS areas with less

than 60% eased blocks are either relatively small in overall extent in the deepwater study area or

have experienced legal constraints on leasing. The remaining eight areas have hundreds of leased

blocks each. In most of these areas, between approximately 3and 6% of leased blocks received

bonus bids in excess of $500 per acre. Interestingly, these include both the relatively nearshore area
Figure 1G.4. Deepwater production systems in the Gulf of Mexico.
Figure 1G.5. Spatial distribution of surface longline sets made in the Gulf of Mexico during 1998 (Source: Nati

Fisheries Service longline logbook data 1999).
405

of East Breaks and Green Canyon, as well as the more distant and deeper water areas of Alaminos

Canyon, Atwater Valley, Keathley Canyon, and Walker Ridge. In fact, the two bluewater blocks

which received bonus bids in excess of $5,000 per acre are of recent vintage (1998) and are in water

depths of approximately 1,500 and 3,000 m. In the Garden Banks area, which saw the first

development in over 600 m, and Mississippi Canyon, which boasts several developments beyond

900 m, twice the percentage of leases received bonus bids in excess of $500 per acre.

Current deepwater fishing practices in the northern GOM include trapping for golden crab; trawling

for royal red shrimp; bottom longlining for groupers, snappers, and tilefishes; and surface longlining

for sharks, swordfish, and tunas. The areal extent of these fisheries varies greatly, from widespread

to localized. The royal red shrimp fishery appears to be concentrated in the area south of

Alabama/Mississippi corresponding to statistical grid 10, with minimal effort expended in areas off

the Florida Keys and Texas. Golden crab trapping is most prevalent off southwestern Florida and

the Florida Keys, with very few fishers actually participating in this fishery. There is some

speculation that the deepwater crab fishery will expand in the future. The bottom longline fishery

occurs near the shelf break and is legislatively mandated to remain offshore of the 102 m depth

contour. Most effort by reef fish permit holders for deepwater groupers and tilefishes occurs

offshore west Florida; however, appreciable effort has been expended offshore of Louisiana and

Texas as well. The pelagic longline fishery is widespread in the open GOM (Figure 1G.4). Of these

gear types, the pelagic longline presents the greatest possibility for interactions or space-use

conflicts.

REFERENCES

Carney, R.S. 1998 Workshop on Environmental Issues Surrounding Deepwater Oil and Gas

Development: Final Report. U.S. Department of the Interior, Minerals Mgmt. Service, Gulf of

Mexico OCS Region, New Orleans, LA. OCS Study MMS 98-0022.163 pp.

Mr. David B. Snyder is a senior staff scientist with Continental Shelf Associates, Inc. He has 18

years of experience with aquatic environmental assessment and research programs for federal, state,

and industrial clients. He has participated as Research or Chief Scientist on over 50 scientific cruises

conducted in domestic and international waters. Mr. Snyder has managed several fishery-related

projects including bycatch studies, life history studies, and ichthyofaunal assessments in a variety

of marine and freshwater habitats Mr Snyder received his B.S. in zoology from the University of

Florida in 1978 and his M.S. in ichthyology/marine biology from Florida Atlantic University in

1984.
406

EVALUATION OF OIL AND GAS PLATFORMS ON THE LOUISIANA CONTINENTAL

SHELF FOR ORGANISMS WITH BIOTECHNOLOGY POTENTIAL

Dr. Lawrence J. Rouse

Department of Oceanography and

Coastal Studies Institute

Louisiana State University

In 1998, President Clinton convened the National Ocean Conference (NOC) in Monterey, California.

The report of this conference, Turning to the Sea: America’s Ocean Future, identified biotechnology

as a high-priority issue for the nation. The report identifies a lack of information about baseline

conditions of the marine environment which makes it difficult to assess the environmental impacts

of biotechnology, listing among its key recommendations:

• Increase support for sustainable harvesting and testing of marine compounds by both

government agencies and commercial pharmaceutical companies as possible treatments for

AIDS, inflammatory or infectious diseases, and cancers; and

• Support research on the environmental effects of extracting marine organisms for

biotechnology purposes.

In response to the Minerals Management Service’s recognition that offshore oil and gas platforms

may serve as a harvestable source of organisms with pharmaceutical or other commercial

application, this proposal will address the NOC report’s recommendations. Our initial effort will be

to answer the following questions:

• What organisms make up the biofouling communities on the platforms?

• Are any of these organisms potential sources of pharmaceuticals or other natural products?

• How do the organisms populate the platforms? What is the distribution and relative

abundance of the organisms on a platform and how does this distribution vary between

platforms and with depth and time?

The Investigators assembled for this project have expertise in a number of organisms that are

potential sources of useful natural products. Our effort will, therefore, focus on a specific set of

organisms. The team of scientists and their expertise includes:

• Dr. Fred Rainey – Bacteria

• Drs. Russell Chapman and Suzanne Fredericq – Algae 

• Dr. Michael Hellberg – Bryozoans
407

• Dr. Barun Sen Gupta – Benthic foraminifers

• Dr. Laurie Anderson – Molluscs

• Dr. Dave Foltz – Genetic analysis: foraminifers and molluscs

Dr. Larry Rouse will be the project director and oversee the collection of samples from the offshore

platforms. 

The sampling scheme will be to obtain samples at six to seven oil and gas platforms east and west

of the Mississippi River delta. The platforms will be in a variety of water environments: a blue-, a

green-, and a brown-water. At each platform samples will be acquired from an easternmost and a

westernmost leg at or near the surface, 10 meters, and 20 meters. At each level, all the encrusting

organisms in three 25 by 25 cm squares will be scraped off and stored in plastic bags. The samples

will be sorted and preserved as appropriate. Laboratory analysis will identify the organisms by

morphology and/or by DNA sequencing techniques.

At the present time, we expect to carry out the first field sampling in the spring of 2001. A second

sampling effort is scheduled for 2002. The specific program for the second year will be determined

based on the results of the first year’s study.
409

SESSION 1H

MMS SPONSORED OIL SPILL RESEARCH

Chair: Ms. Darice Breeding, Minerals Management Service

Date: December 7, 2000

Presentation Author/Affiliation

DeepSpill 2000: Experimental Deepwater

Blowouts

Dr. Mark Reed

SINTEF Applied Chemistry, Norway

In-Situ Burning of Oil Spills in the

Marshland Environment

Mr. Nelson P. Bryner

Mr. William D. Walton

Mr. Laurean A. DeLauter

Mr. W. H. Twilley

National Institute of Standards & Technology

U.S. Department of Commerce

Dr. Irving A. Mendelssohn

Dr. Qian Xin Lin

Dr. Kenneth R. Carney

Wetland Biogeochemistry Institute

Louisiana State University

Mr. Joseph V. Mullin

Technology Assessment and Research Branch

Minerals Management Service

Technology Assessment of the Use of

Dispersants on Spills from Drilling and

Production Facilities in the Gulf of Mexico

Outer Continental Shelf

Dr. Ken Trudel

Dr. Sy Ross

Mr. Randy Belore

S.L. Ross Environmental Research Ltd.

Study to Compare the Effectiveness of

Chemical Dispersants When Applied Neat

vs. Dilute: Mesoscale Tests

Mr. Randy Belore

Dr. Sy Ross

Dr. Ken Trudel

S.L. Ross Environmental Research Ltd
411

DeepSpill Experiment

June 2000

Objectives

hto obtain data for verification and testing of

numerical models for simulating accidental

releases in deep waters;

hto test equipment for monitoring and

surveillance of accidental releases in deep

waters;

hto evaluate the safety aspects of accidental

releases of gas and oil in deep waters.

Deepwaters:

High pressures: 1000 m = 101 atmospheres

Low temperatures: -1 to 5oC

• Non-ideal gas behavior

• Increased solubility of gas in sea water

• More gas dissolved in oil

• Gas may combine with sea water to form hydrates

• Cross-flow important for determining surface oil

distribution

DEEPSPILL 2000: EXPERIMENTAL DEEPWATER BLOWOUTS

Dr. Mark Reed

SINTEF Applied Chemistry, Norway
412

Example

Computed

Surface Slick

-5

0

5

10

-5 0 5 10

Distance East, km

Distance North, km

> 0 micron

> 5 micron

> 10 micron

> 50 micron

> 100 micron

> 200 micron

Discharge 

location

Deepwater blowouts

Oil droplets surface

Outflow of oil and gas

Sea water temperature

Plume of entrained

water, oil and hydrate

Gas converted to hydrate

Hydrate

line
413

DeepSpill JIP

Background

hFeasibility study conducted by SINTEF on behalf of Chevron:

June - September 1999

hJoint Industry Project initiated by Chevron: September 1999

hDecisive participation by MMS

hEventual participation from 22 oil companies and MMS

hTotal budget ∼ $2 million

hSINTEF Applied Chemistry acted as principal contractor

hVarious subcontractors: design and operation of gas and oil

transport, pumping systems, equipment for subsea monitoring,

research ships

hFour experimental discharges conducted in the Norwegian sea

June 2000

Participating Units

WROV

OROV

Håkon Mosby

Far Grip

Johan Hjort and

sampling boats

Surveillance

aircraft

UV fluorescence

meter

ADCP with

acoustic

transmitter

Rosette with

sampling flasks, CTD

and fluorimeter

SINTEF lab

container
414

Discharge platform at sea bed

Observing plume by echo-sounder
415

Echo-sounder image from Håkon Mosby (38 kHz)

Example from start of LNG discharge

Gas and oil droplets from marine diesel experiment
416

Oil slick from marine diesel experiment

Major findings

• Oil discharges

– Oil surfaced and started forming a slick about one

hour after start of experiment;

– Surface slick built up in area with time as oil

droplets of diminishing size arrived at the surface;

– Surface slick of variable thickness with patches of

thicker oil;

– Water - in - oil emulsion formed in the thicker

patches of the crude oil slick.

• Gas discharges

– Gas bubbles did not reach surface probably due to

dissolution of gas in seawater;

– No hydrate formation was observed (!)
417

DeepBlow: Lagrangian integral

plume model for deep waters

u, v, w

h

b

Qi,T, S

Lagrangian plume element

Plume trajectory

0

200

400

600

800

1000

1200

-1600 -1400 -1200 -1000 -800 -600 -400 -200 0 200

D istance East, m

Depth, m
418

Dr. Mark Reed is Senior Scientist at SINTEF Applied Chemistry, Division of Environmental

Engineering in Trondheim, Norway, where he has been since 1992. Prior to that, he worked at ASA

in Rhode Island. His area of specialization is marine environmental modeling. Dr. Reed received

his Ph.D. from the University of Rhode Island in 1980 in oil spill-fishery interactions and did postdoctoral work in Trondheim, Norway in fish migration modeling.
419

IN-SITU BURNING OF OIL SPILLS IN THE MARSHLAND ENVIRONMENT

Mr. Nelson P. Bryner

Mr. William D. Walton

Mr. Laurean A. DeLauter

Mr. W. H. Twilley

National Institute of Standards & Technology

U.S. Department of Commerce

Dr. Irving A. Mendelssohn, 

Dr. Qian Xin Lin

Dr. Kenneth R. Carney

Wetland Biogeochemistry Institute

Louisiana State University

Mr. Joseph V. Mullin

Technology Assessment and Research Branch

Minerals Management Service

BACKGROUND

Oil spills of crude or refined hydrocarbons in environments such as salt marshes provide unique

challenges for oil spill response teams. If the oil is not removed from the marsh, the toxic properties

of crude oil and many refined oil products are likely to kill a majority of the plants within the initial

spill boundary. However, access to spills in wetlands can be difficult and may force oil spill

response teams to utilize heavy equipment to gain access to the affected wetlands. It has been noted

that mechanical remediation techniques can do more damage to these highly fragile wetland

systems than the oil toxicity itself. The oil spill response community, including the Minerals

Management Service, US Coast Guard, NOAA, EPA, and private oil spill remediation companies,

is constantly seeking cleanup technologies that are less intrusive to the environment. In-situ burning

of oiled wetlands potentially provides such a technique. Wetlands, both inland and coastal, are often

burned on an annual cycle to provide better wildlife habitat. However, the effects of burning on

wetland recovery have been variable, and the factors controlling this differential response to

burning have not been adequately addressed. Even less is known about the primary variables

determining the successful recovery of wetland subjected to in-situ burning after an oil spill. Yet,

this information is essential if we are to consider, on a regular basis, in-situ burning for the

remediation of oil contaminated wetlands. The data collected by this project will help fill this

information gap. 

EXPERIMENTAL METHOD

A series of 22 tests burning diesel fuel and Louisiana crude oil were conducted in a 6 m diameter

tank to examine the effects of water level, duration of burn, and pre-oiling on Spartina Alterniflora,

Spartina Patens, and Sagittaria Lancifolia, all common marsh species. Over 300 plant sods, each
420

Figure 1H.1. Plants in tank at different elevations.

30 cm in diameter and 30 cm of soil depth, were harvested from south Louisiana wetlands.

Thermocouple arrays were inserted into 100 sods in order to track soil temperatures. During the burn

tests, marsh sods with intact soil and vegetation, were positioned at -10 cm, -2 cm, 0 cm, + 2 cm,

and + 10 cm relative to the water level (Figure 1H.1). To simulate initial exposure to oil before the

arrival of oil spill response teams, half of the sods were pre-oiled with either diesel fuel or crude oil

24 hours before the test burn. Diesel fuel or crude oil was added to the surface of water, ignited, and

allowed to burn (Figure 1H.2) for periods of either 400 s, 700 s, or 1,400 s. Once the plant sods were

exposed to an in-situ burn, the specimens were returned to Louisiana State University greenhouses

and monitored for plant response and soil physical-chemistry. The effects of water level, burn

duration, and pre-oiling on burn dynamics and wetland vegetation recovery were assessed. 

RESULTS

Soil temperatures versus time are plotted for 400s (diesel) exposures for Spartina Alterniflora in

Figures 1H.3a, 1H.4a, 1H.5a, and 1H.6a, for soil elevations of +10 cm, 0 cm, -2 cm, and –10 cm,

respectively. Soil temperature plots for 1,400 s (diesel) exposures for Spartina Alterniflora are

plotted in Figures 1H.3b, 1H.4b, 1H.5b, and 1H.6b, for soil elevations of +10 cm, 0 cm, -2 cm, and
421

Figure 1H.2. Plants exposed to in-situ burning of diesel/crude oil.

–10 cm, respectively. All sod elevations are relative to water level; for example + 10 cm indicates

that the soil line was 10 cm above the water surface and -10 cm indicates that the soil line was 10

cm below the water surface. For each plot, ignition occurred at 600 s and the fire extinguished itself

at 1,000 s for the 400 s exposure and at 2,000 s for the 1,400 s exposure. Ten centimeters of water

overlying the soil surface was sufficient to buffer soil temperature even during a 1,400 s burn (peak

soil temperatures of 40°C (Figure 1H.6b). In contrast, a water table 10 cm below the soil surface

resulted in peak soil temperatures of 580 o C at the surface (Figure 1H.3b). Since lethal temperatures

to vascular plants have been cited in range of 60°C to 65°C, the temperature data suggests that 2 cm

of water probably provides sufficient protection from temperatures higher than 60°C. Even 0 cm or

+ 2 cm of water appears to prevent the 60°C isotherm from penetrating more than 1cm or 2 cm down

into the soil. It is not clear whether 60°C temperatures for brief periods of time 2 cm below the soil

surface are sufficient to prevent the plant from recovering from the thermal exposure.The plant

survival and growth responses (plots not included in this presentation) to the water level treatments

support the temperature data although the presence of diesel fuel in the soil made
422

Figure 1H.3a. Soil evaluation + 10 cm 400 s burn exposure.

Figure 1H.3b. Soil evaluation + 10 cm 1,400 s burn exposure.
423

Figure 1H.4b. Soil evaluation 0 cm 1,400 s burn exposure.

Figure 1H.4a. Soil evaluation 0 cm 400 s burn exposure.
424

Figure 1H.5a. Soil evaluation -2 cm 400 s burn exposure.

Figure 1H.5b. Soil evaluation -2 cm 1,400 s burn exposure.
425

Figure 1H.6a. Soil evaluation -10 cm 400 s burn exposure.

Figure 1H.6b. Soil evaluation -10 cm 1,400 s burn exposure.
426

analysis more difficult. In year 1, diesel fuel was allowed to mingle with the sods during the burn.

A significant number of plants at the 0 cm and - 2cm levels appeared to suffer negative effects

because of diesel fuel within the soil. In year 2, the diesel fuel was prevented from mingling with

the plant sods during the burn exposure and plants at the + 2 cm, -2 cm and -10 cm are recovering

much better than in year 1. Exposing the plant sods to burning diesel fuel (year 1) and burning diesel

fuel and South Louisiana crude oil (year 2) appeared to produce similar temperature profiles in the

soil. 

CONCLUSIONS

Peak soil temperatures in excess of 550°C were recorded at the soil surface in plant sods located at

10 cm above the water surface. A water thickness of 2 cm provided sufficient protection to prevent

peak soil temperatures from exceeding 60°C. Spartina alterniflora exhibited good vegetative regrowth at - 2cm and -10 cm water levels as long as diesel fuel had not entered the soil.

ACKNOWLEDGMENTS

Funding was provided by the U.S. Minerals Management Service and the Louisiana Applied

Research and Development Program. We extend our appreciation to LSU’s Fire and Emergency

Training Institute for insuring safe and successful burns at their facility and to graduate students at

LSU for their assistance.
427

TECHNOLOGY ASSESSMENT OF THE USE OF DISPERSANTS ON SPILLS FROM

DRILLING AND PRODUCTION FACILITIES IN THE GULF OF MEXICO

OUTER CONTINENTAL SHELF

Dr. Ken Trudel

Dr. Sy Ross

Mr. Randy Belore

S.L. Ross Environmental Research Ltd.

INTRODUCTION

This paper briefly summarizes this S.L. Ross (2000) project. The project examined the technical

issues surrounding the use of dispersants to clean up spills from U.S. MMS-regulated facilities in

the Gulf of Mexico Region (GOMR). Issues included: a) amenability of GOMR oils to chemical

dispersion; b) logistic capabilities and limitations of existing dispersant spraying platforms: and c)

the net environmental benefits or environmental trade-offs associated with chemical dispersion of

spills in the GOMR. This project was sponsored by Engineering and Research, Minerals

Management Service.

DISPERSIBILITY OF GOMR OILS

An analysis was performed to assess the general applicability of dispersants on spills involving oils

that are produced in the GOMR. Many distinct oils must be considered because thousands of wells

are in operation. A publicly available MMS database, which provides average API oil gravities for

all plays in the GOMR, shows that the vast majority of GOMR oils are relatively light (average API

gravity is about 33° = 0.86 specific gravity). This is generally favorable, but more information is

required to evaluate an oil’s likely chemical dispersibility, especially data on the tendency of the oil

to emulsify as a function of weathering (evaporation). Although such information is generally not

available, it is for 28 specific GOMR oils that were thoroughly analyzed and modeled in previous

projects funded by MMS. The oils are listed in Table 1H.1, ranked according to emulsion formation

tendency. Batch spills of size 1,000 barrels and 10,000 barrels are used as examples to calculate

windows of opportunity for using dispersant. 

If these 28 oils are representative of the Gulf oils in general, the following conclusions can be made

regarding the dispersibility of GOMR oils with respect to batch spills in the size range shown.

Fourteen percent of GOMR-OCS oils ( four of the 28 oils) are highly emulsifiable and will have a

very narrow “window of opportunity” for treatment with chemical dispersants. These are called Hi-E

oils in this study. They are defined as oils that will start to emulsify either immediately or after up

to 10% of the spill has evaporated. The next category is for Av-E oils (29% of total). For these, there

is a relatively narrow time-window for effective dispersant response, but still significantly more time

available than the Hi-E oils. For Low-E oils (32% of total) the “window of opportunity” for effective

dispersant use becomes wide, and one has several days to respond to the spill. Finally, No-E oils
Table 1H.1. GOMR crude oils that have undergone spill-related testing (1 of 2 pages).

Crude Oil Name API Gravity

Fresh Oil

Pour

Point

EF

Oil Viscosity @ 60EF

at Various Weathered

States Emulsion

Formation

Tendency*

Size of "Window

of Opportunity"

 for Successful

Dispersant Use 

Hours for Oil to reach Specified V

6 m/s (12 kt) winds

0% ~ 15% ~ 25%

1,000 Barrel Batch Spill 10,000 Ba

2,000 cP 5,000 cP 20,000 cP 2,000 cP 

HIGHLY EMULSIFIABLE OILS (Hi-E Oils) (Emulsion forms at 0 to10 % spill evaporation)Green Canyon 65 20 -18 177 800 4250 yes @ 0 % very narrow 3.3 5 11 3.9 Miss. Canyon 807(1999) 28 ? 33 404 2237 yes @ 8% very narrowMiss. Canyon 807(1998) 28 -29 41 491 3454 yes @ 0% very narrow 3.2 4 9 3.7 West Delta 143 29 ? 32 - 1572 yes @ 6 % very narrow 5 7 30 5.9 MEDIUM EMULSIFIABLE OILS (Av-E Oils) (Emulsion forms at 11 to 29 % spill evaporation)Green Canyon 205 29 ? 26 157 543 yes @ 23% narrowGreen Canyon 109 27 -33 39 225 690 yes @ 22 % narrow 33 35 45 53 Garden Banks 387 30 -38 29 181 579 yes @ 23% narrow 15.5 17 28 23 West Delta 30 11-23? -9 1180 - 1350 yes @ 24 % narrow 67 68 73 109 Mississippi Canyon72 32 -18 16 34 195 yes @ 18% narrowMain Pass 69/225 34 ? 13 - 118 yes @ 25 % narrow Viosca Knoll 826 #1 32 25 16 132 325 yes @ 24% narrowViosca Knoll 826 #2 31 ? 17 84 186 yes @ 15% narrow

* The percentage value refers to the amout of oil evaporation that must occur to start the emulsification process.
Table 1H.1.(continued). GOMR crude oils that have undergone spill-related testing (2 of 2 pages).

Crude Oil Name API Gravity

Fresh Oil

Pour

Point

EF

Oil Viscosity @ 60EF

at Various Weathered

States Emulsion

Formation

Tendency*

Size of "Window

of Opportunity"

 for Successful

Dispersant Use 

Hours for Oil to reach Specified V

6 m/s (12 kt) winds

0% ~ 15% ~ 25%

1,000 Barrel Batch Spill 10,000 Ba

2,000 cP 5,000 cP 20,000 cP 2,000 cP 

SLOWLY EMULSIFIABLE OILS (Low-E Oils)(Emulsion forms at 30 to 50+ % spill evaporation)Garden Banks 426 39 -8 6 13 34 yes @ 38% wide 48 52 246 78 Green Canyon 184 39 -47 5 11 31 yes @ 38% wide 141 143 162 234 Main Pass 37 39 27 7 16 36 yes @ 50 % wide disperse @117 disperse @186

Ship Shoal 239 26 5 34 70 74 yes @ 50 % wideSouth Pass 49 29 ? 23 - 146 yes @ 30 % wide South Pass 93 33 5 19 23 32 yes @ 34 % wideSouth Pass 67 16 16-55? 39 - 110 yes @ 45 % wideSouth Pass 60 36 16 1 22 41 yes @ 38 % wide 40 45 215 65 Viosca Knoll 990 38 ? 7 12 31 yes @ 35% wideOILS THAT DO NOT EMULSIFY (No-E Oils) (Emulsion does not form)Main Pass 306 33 -63 9 19 54 no very wide 341 >360 >360 >360 Eugene Island 43 37 32 13 36 65 no very wide 306 >360 >360 >360 Eugene Island 32 37 45 10 16 21 no very wide 231 >360 >360 >360 Mississippi Canyon194 35 -40 7 15 21 no very wide disperse @117 disperse @197

Ship Shoal 269 39 -44 5 7 18 no very wideSouth Timbalier 130 35 -17 7 10 19 no very wideWest Delta 97 50 -17 1 1 no very wide
430

(25% of total) are ideal dispersant-use candidates because they do not emulsify regardless of the

extent of evaporation. This class of oils would also include diesel oils.

In summary, the opportunity for using dispersants effectively on the example oils shown in the table

is very good. Only the Hi-E oils, representing 14% of the total, present problems due to their

tendency to emulsify rapidly, thus quickly closing the window of opportunity for effective dispersant

use. The remaining 86% offer a reasonable chance of being good targets for a dispersant response

program. Indeed, both Low-E oils and No-E oils, representing 57% of all spill possibilities, are

excellent candidates for responding with dispersants. There is generally much time available for

dispersing such spills before the oils become too viscous, at least when considering batch spills in

the spill size range of 1,000 bbl to 10,000 bbl. 

For other spills the dispersant-use time window will vary as a function of spill type (e.g., blowout

vs. batch spill), spill size and environmental conditions. To analyze this variation, a detailed

modeling exercise was initiated. 

SPILL SCENARIO MODELING

This analysis assessed the potential influence of the spill conditions on the weathering, emulsion

formation and time window for chemical dispersion in spills that are typical of GOMR conditions.

Representatives of each oil category in Table 1H.1 were selected for modeling purposes (these are

highlighted) and a number of spill scenarios were developed to reflect the range of spill possibilities

associated with OCS installations. These scenarios are shown in Table 1H.2. The following

describes the predicted effects of spill conditions and oil types on the time windows in GOMR spills.

Batch Spills: Scenarios 1 through 3

Batch spills involving diesel oil and No-E oils (scenarios 1a, 1b and 2a) have large windows of

opportunity for the use of dispersants because of the low tendency of these oils to form emulsions.

The batch spill involving Av-E oil (scenario 2b) is a good candidate for dispersant use because it

is relatively persistent (> 30 days)—and, thus, a threat to even distant shorelines—and yet it does

not emulsify quickly (96 hours), allowing ample time to implement a spraying operation. Such time

is not available in scenarios 2c and 3 where emulsion viscosities for the batch spills involving Hi-E

oil will exceed chemically dispersible levels within only 10 to 15 hours.

Above-Sea Blowouts: Scenarios 4 and 5

The primary difference between the above-sea blowout results and the batch spills of similar oil and

total spill volume is the initial small thickness and widths of the oil slicks and the long-term release

characteristics of the blowouts. An above-sea, low-flow blowout involving Lo-E oil (scenario 4a)

will disperse quickly on its own (within 15 hours). The same blowout involving an Av-E oil (4b)

will emulsify relatively rapidly (10 to 15 hours), as it did in the batch spills, but because this spill

is continuous and lasts over a period of four days it is possible to mount a spraying operation to treat

the freshly released oil during daylight hours. 
431

Table 1H.2 GOMR spill scenarios.

# Spill Description Spill Volume Model Oil Comments

1 Batch Spill (1a) 2000 bbl and

(1b) 20,000 bbl

(1a) Diesel

(1b) No-E Oil

Demonstrates the large dispersantuse time window for spills of diesel

and crude oils that do not emulsify. 

2 Batch Spill 20,000 bbl (2a) Lo-E Oil

(2b) Av-E Oil

(2c) Hi-E Oil

Could be tank rupture on platform or

"dead crude" pipeline spill. Shows

the effect of oil type on time window,

as compared to Spill#1.

3 Batch Spill 100,000 bbl (3) Hi-E Oil Could be worst-case FPSO spill or

shuttle tanker spill. 

4 Surface Blowout,

average rate,

short duration

20,000 bbl =

5,000 BOPD* x

4 days

(4a) Lo-E Oil

(4b) Av-E Oil

Demonstrates the fast initial

evaporation of oil in air, and its effect

on time window.

5 Surface Blowout,

high flow rate

1,400,000 bbl =

100,000 BOPD x

14 days

(5a) Hi-E Oil

(5b) Av-E Oil

Extremely large spill that will

challenge all countermeasures

methods for Hi-E oils and even AvOils and lighter.

6 Subsurface

Blowout, shallow

water, low flow 

20,000 bbl =

5,000 BOPD x

4 days

Av-E Oil

(6a) 35 m deep

(6b) 50 m deep

(6c) 150 m 

Shows the differences between

same-sized batch spill (Spill#2) and

surface blowout (Spill#4). Could also

represent Alive crude@ pipeline spill.

7 Subsurface

Blowout, shallow

water, high flow 

100,000 bbl =

7,200 BOPD x

14 days

Av-E Oil

(7a) 35 m deep

(7b) 50 m deep

(7c) 150 m 

Worst-case, but more manageable

than surface blowout (Spill#5)

because no fast initial evaporation in

air. 

8 Subsurface

Blowout, deep

water, high flow 

9,000,000 bbl =

100,000 BOPD x

90 days

(8a) HI-E Oil

(8b) Av-E Oil

Represents worst-case blowout in

deep water, and 90 days to drill relief

well

* BOPD = barrels of oil per day

 The above-surface, high-flow blowout involving Hi-E oil (scenario 5a) emulsifies very quickly and

provides a window of opportunity for dispersant application of only five hours. Much of the oil that

is released overnight during this blowout will not be amenable to effective dispersant treatment the

next day. The fresh oil released will be relatively thick (2.5 to 4 mm) and narrow (<100m) making

this spill a good candidate for vessel-based dispersant application as long as the dispersant is applied

very close to the source. 

Scenario 5b has the same high flow rate as 5a, but the lighter oil (Av-E) results in a larger window

of opportunity for dispersant application (up to 36 hours). This scenario is also a good candidate for

dispersant use because the slicks will survive a long time if left untreated (> 30 days), but

dispersants should be effective on all of the oil, even that discharged over night.
432

Subsea Blowouts: Scenarios 6 and 7

In these scenarios the a, b and c designations refer to the different release depths of 35, 50 and 150

m, respectively. As the release point gets deeper, the surface slick becomes wider (increasing from

approximately 300 m to 750 m) and thinner (decreasing from about 0.15 mm to 0.05 mm). The

higher flow rates of scenario 7 increase the slick widths and thicknesses somewhat, but not radically.

The window of opportunity for dispersant application in these scenarios is between four to seven

hours. Because these spills are all continuous releases, the fresh oil emanating from the blowout site

during the day will be treatable as long as it can be dosed within about six hours of its release.

However, much of the oil released overnight will not be chemically dispersible the following

morning. The dispersant application system used to apply the dispersant will have to be designed

to properly dose the relatively thin slicks that result from these blowouts.

ANALYSIS OF DISPERSANT LOGISTICS

A detailed analysis of the above scenarios was performed with respect to dispersant-use logistics

and factors that affect operational efficiency. The objective was to assess the current level of

dispersant capability in the Gulf as tested against the selected spill scenarios. Two key factors are

the availability of dispersant and the capability of various platforms for delivering and applying the

dispersant. 

Dispersant Availability

The quantities of dispersant immediately available to fight spills in the GOM area are of the order

of 183,000 gallons (147,000 gallons from Region 6 and 36,000 gallons from Region 4). At least a

portion of the remaining 222,000 gallons of dispersant located elsewhere could be made available

for use on spills in the Gulf within 24 hours. In addition to the stockpiles already in place, dispersant

manufacturers claim to be capable of producing approximately 44,000 gallons per day on an

emergency basis.

Application Platforms

A crucial component of the dispersant response system is the spraying platform used to apply

dispersants. Key features of the available platforms are outlined as follows.

C-130/ADDS Pack. The C-130 aircraft, equipped with the ADDS Pack (Airborne Dispersant

Delivery System) has the greatest overall dispersant delivery capacity of any existing platform. This

is by virtue of its high payload, spray rate, swath width and transit speed. At present, its main

drawback in the Gulf of Mexico is that start-up times may be lengthy. At present (December 2000),

spraying would not begin until the morning of the second day of the spill, in most cases.

DC-4. This platform is modeled after the dedicated dispersant spraying aircraft owned by Airborne

Support Incorporated of Houma, LA. This aircraft has the greatest delivery capacity of any dedicated

aircraft application system currently available in the U.S. The key feature of the system is that it
433

operates on a “firehouse” basis, meaning that it is dedicated to the task of dispersant spraying and

is in a constant state of readiness. Its start-up time is one hour or less.

DC-3. This platform is also modeled after the dedicated dispersant spraying aircraft owned by

Airborne Support Incorporated. The aircraft has the second greatest delivery capacity of the

dedicated aircraft systems. This system also reports a start-up time of one hour or less. 

Cessna AT-802 (Agtruck). These are small, single engine aircraft that are purpose-built for aerial

spraying. In the U.S., a group of operators have organized to offer a dispersant spraying service

using this aircraft. A number of these are available in the Gulf area. These operators guarantee a

start-up time of four hours or less. These have a lesser payload capacity than certain of the larger

aircraft, but this deficiency is somewhat compensated for by availability of multiple platforms.

These have a somewhat more limited range over water than the large, multi-engine aircraft.

Helicopter. Helicopters equipped with spray buckets have the advantage of availability. They are

limited by their small payload and limited range. They are highly maneuverable and capable of

being re-supplied near a spill site, which greatly increases their operational efficiency.

Vessels. There are a number of vessel systems currently available in the Gulf area. These vary

widely in terms of their payloads, pump rates and swath widths. Certain of the response vessels have

relatively low payloads, which severely limits their capabilities. However, the recent addition of

larger, high-speed crew-cargo vessels, equipped with portable dispersant spray systems and deckmounted marine portable tanks have greatly improved the response capability of this group.

RESULTS OF ANALYSIS

The following are the main results of the logistics analysis:

 1. In the batch spill scenarios, the rate of emulsification exerts a very strong influence over

dispersion efficiency. In scenarios involving oils that have little tendency to emulsify, the

oil dissipates naturally within hours or days and dispersants reduce the persistence of oil only

slightly. In scenarios involving oils with a high tendency to emulsify, the time windows are

very short, approximately seven hours. For some platforms, this interval allows time for one

or two sorties at most, while for others the time window is too brief to complete even a

single sortie. Even systems with the largest payloads (e.g., C-130) reduced the volume of

persistent oil present by a few tens of percentage points in the smallest spill scenario (20,000

bbl scenario).

 2. The impact of dispersants is most evident in scenarios with oils that do emulsify, but also

do have a relatively long time window, up to 58 hours. In the smallest of these scenarios

(Scenario 2b, 20,000 bbl), the platforms with the highest delivery capacities (C-130 and DC4) are capable of dispersing the entire spill, but the smaller platforms are capable of

dispersing only a portion of the spill. When the capacities of all platforms to deliver

dispersant over a 12-hour period and a 30-mile distance were compared to the C-130, their
434

relative performances would be as follows: DC-4, 0.57 times the C-130, DC-3, 0.23;

Agtruck AT-802, 0.25; helicopter,0.12; and surface vessels , 0.08 to 0.73.

 3. Both helicopter and vessel systems have the advantage of being capable of being re-supplied

at the spill site, thus avoiding the necessity of traveling to their base of operations. Because

they can re-supply at the spill site, their performance can be improved by factors of 2.7

(helicopter) and 4.5 (vessel). The performance of these platforms relative to the C130, when

supplied at site, would be 0.32 and 0.36, respectively.

 4. The distance from the spill site to the base of re-supply influences performance. Increasing

the operating distance from 30 miles to 100 miles reduces performance of most platforms

to 50 to 75% of their capacities at 30 miles. By increasing the operating distance to 300

miles, delivery capacities are reduced to 40 to 60% of their capacities at 30 miles. The

helicopter system could not be used for responses at 100 miles, nor the AT-802 at 300 miles

because of range limitations.

 5. For blowout spills, as with batch spills, the effects of dispersant use on oil fate depend on

the properties and behavior of the oil. Blowouts of oils that do not emulsify or that emulsify

very slowly will disperse quickly by natural means, and dispersants may not affect their

persistence greatly. Other oils which emulsify relatively quickly can be strongly affected by

dispersant operations.

 6. Blowouts that emulsify quickly cannot be fully dispersed because dispersant operations must

be suspended at night and a portion of the oil spilled overnight will emulsify to undispersible

levels. When a blowout and batch spill of identical size (20,000 bbl) and oil type (Av-E) are

compared, the batch spill can be fully dispersed, but the blowout cannot because of the

“overnight effect.” The more quickly the oil emulsifies, the greater the proportion that will

become undispersible.

 7. When surface and subsea blowouts of identical size and oil type are compared, dispersion

of the subsea blowout is much less effective operationally than the surface blowout due to

its larger width, smaller oil thickness and more rapid emulsification.

 8. Payload and operating distance control overall operational effectiveness in blowout spills

as in batch spills, but these influences are less evident when blowout rates are of the order

of 5,000 BOPD or less. At these discharge rates, the larger platforms have excess capacity:

therefore, their logistic advantage over the smaller platforms is less pronounced. 

 9. Overall, the results of the scenarios analyzed suggest that the largest spill that can be fully

treated using existing response capabilities lies in the area of 3180 m3

 for batch spills or 800

m3 /day for 4 days for continuous spills. 

10. Response to the large, deepwater blowout scenarios (Scenarios 8a and 8b) is difficult for

several reasons. First, these spills occur farthest from any base of operations. At this long
435

distance, a spill of even modest size is beyond the capabilities of single units of most aerial

systems, except the C-130/ADDS Pack system. In theory, the amount of oil discharged each

day, 100,000 barrels, is within the operating capacity of all of the large fixed-wing response

resources in the GOMR, provided this were supplemented with two, preferably three, of the

ADDS Pack systems from outside the region. This assumes that the operation achieves both

a very high level of dispersant effectiveness and operational efficiency. Second, these two

scenarios involve extremely large amounts of oil. The daily discharge rates for oil are so

large that they would exhaust the North American stockpiles of dispersant within the first

two to six days of the spill, assuming that the dispersant could be delivered to the spill that

quickly. The operation would prove extremely difficult because the daily dispersant

requirements vastly exceed the available delivery capability by many times (from 5 to 19 C130/ADDS Pack systems would be needed). 

NET ENVIRONMENTAL BENEFIT OF DISPERSANT USE

A detailed analysis of selected scenarios was conducted to study the environmental risks associated

with untreated and chemically dispersed spills from offshore MMS-regulated facilities in the Gulf

of Mexico. The objective was to determine whether or not dispersants offered a net environmental

benefit in treating spills from these facilities. The key variables in these assessments were spill

location, distance from shore, and the type of spill (i.e., batch spill versus blowout spill).

An important variable in the environmental assessment was the location of the spill. At the initiation

of the project, six launch sites were suggested by Minerals Management Service for consideration,

including: a) shallow water off Texas; b) shallow water off Louisiana; c) a mid-shelf site part-way

between sites a) and b); d) the Flower Gardens Area; e) a deepwater offshore site; and f) the Destin

Dome Area. Upon consideration of the fate and movement of oil and a preliminary assessment of

environmental issues, spills from three sites; a), c) and f) were considered in detail.

RESULTS OF THE ANALYSIS 

From the perspective of environmental risk and potential net environmental benefit of dispersantuse, the scenarios analyzed here fall into three categories.

a. One group includes oils that disperse very quickly, by natural means. Regardless of launch

point, these spills disperse naturally in offshore waters; do not threaten shorelines or

nearshore waters; and pose only very modest environmental risks. Chemical dispersion does

little to reduce the impact of these spills and therefore offers little in the way of a net

environmental benefit.

b. A second group of scenarios includes those in which the oils are persistent and could cause

significant impact if untreated, but in which spills are small enough and time windows are

long enough to permit dispersant operations to disperse all or most of the oil. In these spills,

dispersants can greatly reduce the risks associated with the untreated slick and can offer a
436

net environmental benefit provided the risks posed by the dispersed oil are low. Net

environmental benefit issues are clearest in these scenarios.

c. The last group includes all of the spills in which oils emulsify too quickly for dispersant

operations to be mounted or in which spill volumes greatly exceed the capability of

platforms. In these scenarios, dispersants do little to reduce the impact of the untreated spill

and therefore offer little net environmental benefit. 

The main conclusion from this work is that if dispersants are used to treat spills from MMSregulated offshore facilities in the Gulf of Mexico, there will be a net environmental benefit in

almost every case. The reason for this is that the launch sites considered in this study are all

offshore. If spills from these sites are sprayed with dispersants near the spill site (as they must be

if the dispersant is to be effective), the spraying will take place offshore and the environmental risks

from the dispersed oil will be very low or at least lower than the risks from the untreated spill.

The detailed analysis of a spill from an offshore launch site, Mid-Point, showed that there was a net

environmental benefit of dispersant use. In this case, the untreated slick persisted to reach the

shoreline and caused damage, while the same spill dispersed offshore caused far less damage. This

situation is likely to hold in many other locations in the Gulf, even near the shallowest of the

offshore hard-bottom communities, such as the Flower Garden Banks. The latter are deep enough

to be relatively safe from damage in cases where dispersants are used nearby.

The spill from a near-shore launch site, Texas Nearshore, was unique because only in this scenario

were there significant drawbacks from using dispersants. However, despite this, dispersants still

offered a net environmental benefit. In this case, the untreated spill posed important risks to both

economic and biological resources. However, unlike all other scenarios in which the dispersed case

posed very few risks, in the Texas Nearshore case, the dispersed case posed a significant risk to at

least one major economic resource, namely the shrimp fishery. On balance dispersants still appeared

to offer a net environmental benefit, but there is some uncertainty surrounding this result. The risk

posed by the dispersed case involved the shrimp fishery. The dispersed spill posed no biological risk

to the shrimp stock, but the cloud of dispersed oil might result in a temporary and localized closure

to the fishery. The local policies toward fishery closures and local attitudes toward the valuation of

economic and biological resources could have a bearing on the analysis of net benefit. 

The Destin Dome scenario demonstrated that the benefits of dispersants vary from place to place

in the Gulf. This is because there are wide variations in the sensitivities of coastal zones to the

effects of untreated oil. There are also spatial variations in the sensitivity of the offshore community

to dispersed oil, as well, but these differences appear to be less dramatic. This supports the

conclusion that there will be a net benefit of using dispersants on offshore spills throughout most

of the study area. The only variation appears to be in the size of the benefit. 

The blowout scenario showed that the net environmental benefit of using dispersants is far greater

in blowout spills than in batch spills of the same size. This is because the impact of an untreated

blowout spill can be far greater than for a batch spill. The damage caused by an untreated batch spill
437

will involve only a small, localized area, while that from a blowout will cover a larger area and be

greater as a consequence. On the other hand, when a blowout is treated with dispersants, any

resulting damage is restricted to the vicinity of the spill site and is no greater than in the case of the

batch spill.

While spills will certainly fall into these categories, at present the behavior of any given spill cannot

be accurately predicted. It is important to recognize that the results of the scenarios analyzed here

were based on computer simulations and assumptions concerning dispersant effectiveness rates and

rates of emulsification. Many of the processes involved cannot be estimated precisely enough to

allow a prediction of the effectiveness of a dispersant operation in advance. Rather, during an actual

spill, it will be necessary to make decisions about the potential usefulness of dispersants and the

effectiveness of dispersant applications based on direct real-time observations rather than on

computer simulations. For this reason, it will be necessary to have these monitoring capabilities in

place to use dispersants effectively.

For purposes of future work, it is important to recognize that natural resource databases such as

Gulf-Wide Information System and Texas Coastal Oil Spill Planning and Response Toolkit contain

little information concerning resources, such as fish, shellfish and fisheries, that are at risk from

chemically dispersed oil. As a consequence, assessments of risk and net environmental benefit that

are based solely on these sources would under-represent risks to these groups and would be biased

in favor of dispersants.

REFERENCES

S.L. Ross Environmental Research Ltd. 2000. Technology Assessment of the Use of Dispersants

on Spills from Drilling and Production Facilities in the Gulf of Mexico Outer Continental Shelf,

Report to Minerals Mgmt. Service, Engineering and Research Branch, Herndon, VA.
438

STUDY TO COMPARE THE EFFECTIVENESS OF CHEMICAL DISPERSANTS

WHEN APPLIED NEAT VS. DILUTE: MESOSCALE TESTS

Mr. Randy Belore

Dr. Sy Ross

Dr. Ken Trudel

S.L. Ross Environmental Research Ltd

Many of the dispersants currently available in North America are “concentrate” products. These

dispersants are suitable for spraying from all types of application platforms, including aircraft and

surface vessels. They are invariably sprayed neat (undiluted) from aircraft, but a number of vesselbased systems dilute the dispersant before spraying. This dilution is done by educating the dispersant

into a water stream during the spraying operation. The present study was undertaken to determine

whether dilution had any effect on dispersant effectiveness. This project was one of a series

undertaken to improve dispersant spraying technology for vessel systems.

Effectiveness testing was conducted in a test tank to simulate real-world conditions, as closely as

possible, as described below. The following variables were examined:

1. effect of oil-to-dispersant ratio;

2. effect of dispersant type (Corexit 9500 and Corexit 9527);

3. method of diluting the dispersant (premixing vs. educting); and

4. type of oil.

Other conditions in the test were controlled, including: water-to-dispersant dilution rate; slick

thickness; and mixing energy.

METHODS

Details of the methods are provided in Belore et al. (2000a,b,c) and SL Ross (1999).

The method was as follows: 

• All tests were conducted in a wave-tank at SL Ross facilities.

• In each test run, a slick of known volume and thickness was laid down on the surface of the

water in the tank.

• Dispersant was applied at a known dose rate using a spray boom apparatus. 
439

• The wave generator was then engaged. Slicks dispersed rapidly initially, but after a few

minutes of agitation, dispersion slowed and then ceased entirely.

• After 30 minutes of agitation, the test was stopped and the oil remaining on the surface was

collected using sorbants and was weighed.

• Dispersant effectiveness was expressed as the percent of the oil that dispersed during the

test.

In all studies, pre-tests were undertaken in which the dispersant was pre-mixed with the oil at a

range of oil-to-dispersant ratios (DOR). Dispersion rates were measured using these pre-mixed oils

to determine the critical minimum DOR at which the test slick was 100% dispersed. The minimum

effective DOR was referred to as the “target” and this DOR was used for most subsequent testing.

COMPARISON OF COREXIT 9500 and COREXIT 9527

The first set of tests determined whether dilution of the dispersant with seawater prior to spraying

had any effect on dispersant effectiveness. Tests were conducted using Alaska North Slope crude

oil, dispersed with Corexit 9500 or Corexit 9527. The “target” DOR was determined for each

dispersant, as described above, and all subsequent testing was performed at that DOR. In both cases

the “target” DOR was 1:75. All “diluted” runs were conducted at a dilution ratio of 1 part dispersant

to 10 parts water. 

The results of these tests showed that the effectiveness of Corexit 9527 was not affected by dilution

with water prior to spraying. However, the performance of Corexit 9500 was significantly reduced

under the same conditions (Table 1H.3).

It must be noted that in the above tests, the “diluted” dispersant was prepared by pre-mixing

dispersant with seawater in a reservoir several minutes prior to spraying, rather than educating it into

the water stream during the spraying operation. A second set of tests was conducted to verify that

the influence of dilution on the effectiveness of Corexit 9500 was the same whether the dispersant

was educted or pre-mixed with water. The tests showed that effectiveness of Corexit 9500 was

reduced to the same degree whether dilution was by education or pre-mixing.

Table 1H.3. Influence of dilution on effectiveness of dispersant on ANS crude oil.

Dispersant

Effectiveness of Treatment

Neat Diluted (1:10)

Corexit 9527 99 97

Corexit 9500 97 17
440

0

20

40

60

80

100

0 20 40 60 80 100 120 140 160

Oil to Dispersant Ratio

% Dis

persed

Neat 9500

dilute 9500

dilute 9527

Figure 1H.7. Effect of oil-to-dispersant ratio on neat and dilute dispersants.

EFFECT OF DISPERSANT-TO-OIL RATIO (DOR)

A further series of tests was conducted to determine whether the effect of dilution on effectiveness

of Corexit 9500 was influenced by the DOR. Tests were conducted using ANS crude oil. Dispersant

effectiveness was tested at DORs of 1:25 and 1:40, as well as 1:75. The results of these tests are

summarized in Figure 1H.7 below. These tests showed that the effectiveness of diluted Corexit 9500

increased when the DOR was increased, to the point that diluted Corexit 9500 was 100% effective

at a DOR of 1:25. 

EFFECT OF OIL TYPE

This series of tests was conducted to determine whether diluting Corexit 9500 reduced its effectiveness on oils other than ANS crude oil. Tests were run on five additional crude oils, including:

Gulfaks, Green Canyon, Bonny Light, Hibernia and South Louisiana. The target DOR for each oil

was determined in pre-mixed tests, as described above. The target DOR or minimum DOR required

to cause 100% dispersion in premixed tests, differed markedly among the oils (Table 1H.4).

The results of the study showed that dilution had little effect on the effectiveness of Corexit 9527

on any oil (Figure 1H.8). It also showed that while the effectiveness of Corexit 9500 was reduced

by dilution in tests with certain oils (Gulfaks, Green Canyon and Bonny Light), its effectiveness was

undiminished in tests with other oils, such as Hibernia and South Louisiana crude (Figure 1H.9).
441

Gulfaks Green

Canyon Bonny Light Alaska North

Slope Hibernia South

Louisiana

Dilute @ Target DOR

Neat @ Target DOR

0

10

20

30

40

50

60

70

80

90

100

Percent Dispersed

(note : test DORs deviated slightly from target values

% dispersed results shown are averages 

Figure 1H.8. Dispersing efficiency neat vs. dilute: Corexit 9527.

Table 1H.4. Target DORs as determined in pre-mixed tests.

Oil Type

Target DOR

Corexit 9500 Corexit 9527

Gulfaks 1:80 1:85

Green Canyon 1:60 1:50

Bonny Light 1:80 1:75

Hibernia 1:120 1:110

South Louisiana 1:100 1:80

CONCLUSIONS

In conclusion, these test results showed that the operational effectiveness of Corexit 9500 may be

diminished somewhat by diluting it prior to application. The effect of dilution varied with the type

of oil being treated. With Corexit 9500, the effect of dilution depended on the dispersant dose rate,

and with some oils, increasing the dispersant dose rate could compensate for the loss of effectiveness

caused by dilution. Effectiveness of Corexit 9527 was not affected by dilution.

ACKNOWLEDGMENTS

Funding for this work was provided by the U.S. Minerals Management Service, Herndon VA and

by ExxonMobil Research and Engineering Company, Florham Park, NJ.
442

Gulfaks Green

Canyon Bonny

Light Alaska

North

Slope

Hibernia South

Louisiana

Dilute @ Target DOR

Dilute @ ~1:25 DOR

Neat @ Target DOR 0

10

20

30

40

50

60

70

80

90

100

Percent Dispersed

(note: test DORs deviated slightly from 

target values 

% dispersed results shown are averages)

Figure 1H.9. Dispersing efficiency near vs. dilute: Corexit 9500.

REFERENCES

Belore, R.C. and S.L. Ross. 2000a. Laboratory study to compare the effectiveness of chemical

dispersants when applied dilute versus neat. Proceedings of the Arctic and Marine Oil Spill

Program Technical Seminar, Environment Canada.

Belore, R.C. 2000b. Laboratory study to compare the effectiveness of chemical dispersants when

applied dilute versus neat: part 2. ExxonMobil Research and Engineering Company, Florham

Park, N.J.

Belore, R.C. 2000c. Laboratory study to compare the effectiveness of chemical dispersants when

applied dilute versus neat: part 3. ExxonMobil Research and Engineering Company, Florham

Park, N.J.

Ross, S.L. Environmental Research Ltd. 1999. Laboratory study to compare the effectiveness of

chemical dispersants when applied dilute vs. Neat. Project Report prepared for Minerals Mgmt.

Service, Herndon, VA, 26 pp.
443

INDEX TO AUTHORS

Aharon, Dr. Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321

Anderson, Mr. Eric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326

Andras, Dr. J. P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Anuskiewicz, Dr. Richard J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161, 162

Arvidson, Dr. Rolf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Ball, Mr. David A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161, 167

Bates, Mr. Thomas W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Bean, Mr. Dan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

Beaver, Mr. Carl R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Beggs, Dr. John J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

Begly, Dr. B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Belore, Mr. Randy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427, 438

Bender, Dr. Les C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Bergquist, Dr. D. C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Boyer, Mr. Brian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

Brooks, Mr. Steve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

Bryant, Dr. William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

Bryner, Mr. Nelson P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Burd, Mr. Jim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

Carey, Mr. R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Carney, Dr. Kenneth R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Carney, Ms. S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Chen, Mr. Fanghui . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301

Childs, Ms. Susan A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Chinkin, Mr. Lyle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Cifuentes, Dr. Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Coe, Ms. Dana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Coffman, Mr. Kim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
444

Cooper, Dr. Craig . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Cranswick, Ms. Deborah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Cushing, LCDR John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130

DeCort, Mr. Thierry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371

DeLauter, Mr. Laurean A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Dellapenna, Dr. Tim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

Dismukes, Dr. David E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254, 341

Dokken, Dr. Quenton R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Dupont, Dr. Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359

Dye, Mr. Timothy S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Eschbach, Dr. Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

Escobar-Briones, Dr. Elva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190

Escoricia, Ms. Susie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Fisher, Dr. C. R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Freytag, Dr. J. K. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Fu, Dr. Baoshun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321

Gambino, Ms. Stephanie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371

Gettrust, Dr. Joe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Gill, Dr. Duane A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

Graham, Mr. Bruce D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Grossman, Dr. Ethan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Guinasso, Jr., Dr. Norman L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Hanna, Dr. Steven R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Hardin, Mr. Dane D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Hart, Dr. Alan D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 399

Hickerson, Ms. Emma L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387

Hochstein, Dr. Anatoly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

Horn, Dr. M. Van . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Hsu, Dr. S. A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

Iledare, Dr. Omowumi O. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
445

Irion, Dr. Jack B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174

Ji, Dr. Zhen-Gang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

Johnson, Dr. Walter R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

Joye, Dr. Samantha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Kelly, Mr. F. J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

King, Dr. William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372

Lin, Dr. Qian Xin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Luke, Dr. Ron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

MacAvoy, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

MacDonald, Mr. Clinton P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

MacDonald, Dr. Ian R.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16, 197, 285, 295, 381

Macko, Dr. Steve ........................................................ 285, 289

Marshall, Mr. Charles F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

McCay, Dr. Deborah French . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331

McMullin, Ms. E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Mendelssohn, Dr. Irving A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Mesyanzhinov, Dr. Dmitry V. .............................................. 254, 359

Mobley, Mr. Steve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

Morin, Mr. Jeffrey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Morris, Ms. Kristi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Morse, Dr. John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Mullin, Mr. Joseph V. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Nelson, Dr. K. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Olatubi, Williams O. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341

Parisi, Dr. Domenico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

Parker, Ms. Wanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

Payton, Ms. Debbie ...................................................... 207, 324

Peccini, Mr. Michael B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Petterson, Dr. John S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

Phillips, Dr. Neal W. ...........................................................3
446

Price, Dr. James M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

Pulsipher, Dr. Allan G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359

Rainey, Ms. Gail B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

Reed, Dr. Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210, 217, 307, 411

Regg, Mr. James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Reidenauer, Dr. Jeffrey A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

Roberts, Dr. Harry H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Roberts, Dr. Paul T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Ross, Dr. Sy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427, 438

Rouse, Dr. Lawrence J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406

Rowe, Dr. Gilbert T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Russell, Dr. Robert W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395

Sager, Dr. William W. ..................................................... 16, 281

Sassen, Dr. Roger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Scalfano, Mr. David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Schaeffer, Dr. S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Schroeder, Dr. William W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281

Scott, Mr. Erik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

Scott, Dr. L. Max . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321

Shrimpton, Mr. Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

Slowey, Dr. Niall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

Snyder, Mr. David B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 401

Spring, Mr. Keith D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Storey, Dr. Keith . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

Stuebe, Mr. C.G. (Chuck) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

Sulak, Dr. Kenneth J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Tolbert, Dr. Charles M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

Tootle, Dr. Deborah M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

Trudel, Dr. Ken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427, 438

Tunnell, Dr. John W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381
447

Twilley, Mr. W. H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

VanGent, Mr. Dan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321

Verret, Mr. Allen J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

Viada, Mr. Stephen T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Vigil, Ms. Debra L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix

Wade, Dr. Terry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Wallace, Ms. Barbara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233

Walton, Mr. William D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419

Ward, Dr. R. T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Weaver, Mr. Douglas C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Wilson, Ms. Darcy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

Withers, Dr. Kim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Woolsey, Dr. J. Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Yapa, Dr. Poojitha D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301

Yocke, Dr. Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Zatarain, Ms. Vicki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351

Zeigler, Mr. Gary S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Zheng, Mr. Li . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301

Zhu, Ms. Qiaozhen “Lucy” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
449

ATTENDEES

Aharon, Paul

LSU

Baton Rouge, LA 70893

Ahlfeld, Tom

MMS

381 Elden St MS 4023

Herndon, VA 20170

Allen, Dan

Chevron USA Production Co.

935 Gravier St.

New Orleans, LA 70112

allj@chevron.com

Amato, Richard A

NAVION

5151 San Felipe #1390

Houston, TX 77056

Anderson, Eric

Applied Science Assoc.

70 Dean Knauss Drive

Narragansett, RI 02882

Anuskiewicz, Rick

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Archer, Judy

Walter Oil & Gas Corp

1100 Louisiana #200

Houston, TX 77002

archer@walteroil.com

Austin, Diane E

University of Arizona

P.O. Box 210030

Tucson, AZ 85721

daustin@u.arizona.edu

Avent, Robert M

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Ball, David

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Barton, Warren J

MMS

1201 Elmwood Park MS 5440

New Orleans, LA 70123

warreb.barton@mms.gov

Bates, Alton

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

alton.bates@mms.gov

Bean, Daniel A

Texas A&M University

727 Graham Rd

College Station, TX 77845

dabean@oceon.tamu.edu

Bender, Les

Texas A&M University

727 Graham Rd

College Station, TX 77845

les@gerg.tamu.edu

Blanchard, Brian

LSU

Baton Rouge, LA 70803

bblanc5@lsu.edu
450

Boatman, Mary

MMS

1201 Elmwood Prk Blvd MS 5433

New Orleans, LA 70123

mary.boatman@mms.gov

Boland, Greg

MMS

2164 Champions Dr

La Place, LA 70068

gregory.boland@mms.gov

Bornholdt, Dave

USGS Bio. Resources

1700 Leetown Rd

Kearneysville, WV 25430

Bosch, Julie

Neptune Sciences Inc

40201 Hwy 190 East

Slidell, LA 70460

bosch@neptunesci.com

Boyer, Brian

COMM Engineering Inc.

P.O. Box 53463

Lafayette, LA 70508

Bradford, Cary V

Kerr-McGee Oil& Gas Corp.

16666 Northchase

Houston, TX 77060

cbradford@kmg.com

Bradford, Vanessa

Shell Offshore Inc

P.O. Box 61933

New Orleans, LA 70161-1933

Brassieur, C. Ray

University of New Orleans

1118 Royal Street

New Orleans, LA 70116

cbrassie@uno.edu

Breeding, Darice

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Brewer, Gary

USGS Bio. Resources

1700 Leetown Rd

Kearneysville, WV 25430

gary_brewer@usgs.gov

Brooks, Steve

ExxonMobil

P.O. Box 61707

New Orleans, LA 70161

steve.brooks@upstream.eom.com

Broussard, T.J.

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

tommy.broussard@mms.gov

Bruce, Patricia

Devon Energy Corp.

P.O. Box 4616

Houston, TX 77212

patricia.bruce@dvn.com

Bryant, Wiliam R

Dept. of Oceanography

Texas A&M University

College Station, TX 77843-3146

wbryant@ocean.tamu.edu

Bryner, Nelson

National Inst. of Standards and Tech. 

Buch, Kevin

Flower Garden Banks

National Marine Sanctuary

216 W 26th St #104

Bryan, TX 77803

kevin.buch@noaa.gov
451

Buchannon, Robin C

Univ. of MS - Center for Marine Res. & Env.

220 Old Chemistry Bldg.

University, MS 38677

inst@mmri.olemiss.edu

Bugg, David

BP

501 Westlake Blvd 20.198

Houston, TX 77079

buggd@bp.com

Burd Jr., James J

The Louis Berger Group Inc

1819 H Street NW #900

Washington, DC 20006

jburd@louisberger.com

Carlson, Jane M

MMS

381 Elden St., MS-4022

Herndon, VA 20170

Chen, Fanghui

Clarkson University

CEE 5710

Clarkson University

Potsdam, NY 13699

chenf@clarkson.edu

Cheramie, Mark

Dominion E&P, Inc

1450 Poydras St.

New Orleans, LA 70112

mark_p_cheramie@dom.com

Chew, Dennis

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Cho, Hyunjung

University of New Orleans

2000 Lakeshore Drive

New Orleans, LA 70148

hcho1@uno.edu

Christopher, Joe

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

joseph.christopher@mms.gov

Church, Robert A

C & C Technologies, Inc.

730 E. Kaliste Saloom Rd

Lafayette, LA 70508

robert.church@cctechnol.com

Cimato, James

MMS

381 Elden St (MS 4041)

Herndon, VA 20170

james.cimato@mms.gov

Cluck, Rodney E

MMS

381 Elden St

Herndon, VA 20170

rodney.clark@mms.gov

Codina, Caron

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

caron.codina@mms.gov

Coffman, Kim

MMS

381 Elden St., MS-4010

Herndon, VA 20170

kim.coffman@mms.gov
452

Cole, John G

LGL

1410 Court St

Bryan, TX 77801

Cottone, Vincent F

Texaco E&P

400 Poydras St

New Orleans, LA 70130-3245

cottovf@texaco.com

Cox, Jeff

Evans-Hamilton, Inc.

4608 Union Bay Pine

Seattle, WA 98105

jeff@evanshamilton.com

Cranswick, Deborah

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Current, Carole L

MMS

1201 Elmwood Prk Blvd

MS 5433

New Orleans, LA 70123

carole.current@mms.gov

Cushing, Jr., LCDR John M

U.S. Coast Guard

501 Magazine #1341

New Orleans, LA 70130

jcushing@d8.uscg.mil

Dauterive, Les

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

lester.dauterive@mms.gov

Davis, Donald W

LA Oil Spill R&D Program

258A Military Science Bldg

LSU

Baton Rouge, LA 70803

osradp@ibm.net

Defenbaugh, Rick

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Delacruz, Desiree

Dominion E&P, Inc

1450 Poydras St

New Orleans, LA 70112

desiree_g_delacruz@dom.com

Dennis, George

USGS

7920 NW 71st St

Gainesville, FL 32653

george_dennis@usgs.gov

Desai, Yeshavant

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

yeshavant.desai@mms.gov 

Desmond, Chris

LOOP, LLC

155 Rue Charlemagne

Slidell, LA 70461

ctdesmond@loopllc.com

Dismukes, David

Econ One 

Dokken, Quenton

Texas A&M - Corpus Christi

Center for Coastal Studies

6300 Ocean Dr

Corpus Christi, TX 78412
453

Dougherty, Barbara

Devon Energy Corp.

840 Gessner

Houston, TX 77024

bdougherty@santafe-snyder.com

Dunn, Jon

ATP Oil & Gas Corp.

4600 Post Oak Place #230

Houston, TX 77027-9726

jdunn@atpog.com

Ebbesmeyer, Curt

Evans-Hamilton, Inc.

4608 Union Bay Place NE

Seattle, WA 98105-4026

curt@evanshamilton.com

Elterman, Joan A

Dominion E&P, Inc

1450 Poydras St

New Orleans, LA 70112

joan_a_elterman@dom.com

Eschbach, Karl

Impact Assessment Inc.

2166 Aveneu De La Playa #F

La Jolla, CA 92037

Escobar-Briones, Elva

Universidad Nacional Autonoma Mexico 

Fagot, Caryl

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

caryl.fagot@mms.gov

Farace, Nolan

USDA

Box 71

Husser, LA 70442

Field, Stu

University of New Orleans

Dept of Biological Sciences

New Orleans, LA 70148

sgfield@uno.edu

Finney, Scott S

Acculab Inc

5041 Taravella Rd

Marrero, LA 70072

ssfinney@aol.com

Fisher, Charles R

Pennsylvania State University

State College, PA 16804

efisher@psu.edu

Foulcard, Shira A

Texaco

1111 Bagby Street

40th Floor

Houston, TX 77002

foulcsa@texaco.com

Francois, Darryl

MMS

1849 C Street NW

Washington, DC 20240

Franze, Carol

University of New Orleans

Dept of Biological Sciences

New Orleans, LA 70148

cfranze@uno.edu

French McCay, Deborah

Applied Science Assoc.

4749 Bennett Drive #L

Livermore, CA 94550

Frickey, Stacey

Shell E&P Co.

701 Poydras St #2076

New Orleans, LA 70139
454

Fuentes, Gustavo

University of New Orleans

823 Adams St

New Orleans, LA 70118

choupik@hotmail.com

Gallagher, Gerard A

Ecology & Environment Inc.

1950 Commonwealth Lane

Tallahassee, FL 32303

gagallagher@ene.com

Gambino, Stephanie

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

stephanie.gambino@mms.gov

Gettrust, Joe

Naval Research Lab 

Gill, Duane

MSU

Oxford, MS 38655

Gitschlag, Gregg

NOAA/NMFS

4700 Avenue U

Galveston, TX 77551

gregg.gitschlag@noaa.gov

Goers, Connie

J. Connor Consulting Inc

16225 Park Ten Place #700

Houston, TX 77084

connie@jcc.team.com

Good, Keith

MMS

381 Elden St.

Herndon, VA 20170

keith.good@mms.gov

Gounah, Tony

Anadarko Petroleum Corp.

201 Energy Parkway #310

Lafayette, LA 70508

tonygounah@upr.com

Graham, Bruce

Marine Resources Inc

10 Central Parkway

Stuart, FL 34994

bgrchammrie@aol.com

Gregg, Kurtis

Florida Dept of Environ. Protection

3900 Commonwealth Blvd, MS 47

Tallahassee, FL 32399-3000

kurtis.gregg@dep.state.fl.us

Grimsley, Rusty

Chevron USA Production Co.

935 Gravier St

New Orleans, LA 70112

jgri@chevron.com

Guidry, Roland

Governor's Office

625 N. 4th Street

Baton Rouge, LA 70802

losco@linknet.idt.net

Hamilton, Bob

Evans-Hamilton, Inc.

7214 S Kirkwood

Houston, TX 77072

bob@evanshamilton.com

Hardin, Dane

Applied Marine Sciences Inc.

P.O. Box 8346

Santa Cruz, CA 95061-8346

hardin@amarine.com

Hart, Al

Continental Shelf Assoc. Inc. 
455

Hathcock, Susan

Anadarko Petroleum Corp.

17001 Northchase Dr

Houston, TX 77251-1330

susan_hathcock@anadarko.com

Hebert, Carl

Kerr-McGee Oil& Gas Corp.

16666 North Chase

Houston, TX 77060

chabert@kmg.com

Henry, Charlie

NOAA

501 Magazine St

New Orleans, LA 70130

charlie.henry@noaa.gov

Herkhof, Dirk

MMS

381 Elden St

Herndon, VA 20170

dirk.herkhof@mms.gov

Hickerson, Emma

Flower Garden Banks

National Marine Sanctuary

216 W 26th St #104

Bryan, TX 77803

ema.hickerson@noaa.gov

Hill, Charles

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

charles.hill@mms.gov

Holder Jr., Samuel

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

samuel_holder@mms.gov

Hsu, S.A.

LSU Coastal Studies Inst.

LSU

Baton Rouge, LA 70803

sahsu@antares.esl.lsu.edu

Huang, Chester

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Huffaker, Christine

MMS

949 E 36th Ave Rm 300

Anchorage, AK 99508

christine.huffakej@mms.gov

Hunt, Jesse

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

jesse.hunt@mms.gov

Iledare, Omowunmi

LSU/Center for Energy Studies

1 East Fraternity Circle

Baton Rouge, LA 70803

allan@enrg.lsu.edu

Irion, Jack B

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

jack.irion@mms.gov

Ji, Jeff

MMS

381 Elden St MS 4023

Herndon, VA 20170

jeff.gi@mms.gov
456

Johnson, Arthur H

Chevron USA Production Co.

935 Gravier St.

New Orleans, LA 70112

arhj@chevron.com

Johnson, Cherie

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Johnson, Walter

MMS

381 Elden St

Herndon, VA 20170-4817

walter.johnson@mms.gov

Johnston, James B

NWRC

700 Cajundome Blvd

Lafayette, LA 70506

jimmy_johnston@usgs.gov

Kartye, Craig

Texas Engineering Ext. Servce

8701 Tiechman Rd

Galveston, TX 77554

craig.kartye@teexmail.tamu.edu

Kelly, Frank

Texas A&M - Corpus Christi

6300 Ocean Dr

CBI

Corpus Christi, TX 78412

fkelly@cbi.tamucc.edu

Kennicutt II, M.C.

GERG/TAMU

833 Graham Rd

College Station, TX 77845

mck2@gerg.tamu.edu

Kenny, Jan

DEMEX

401 Whitney Ave

Suite 412

Gretna, LA 70056

demex-nola@msn.com

Kenny, John J

DEMEX

401 Whitney Ave Suite 412

Gretna, LA 70056

demex_nola@usa.com

King, Bill

MMS

381 Elden St., MS-4042

Herndon, VA 20170

bill.king@mms.gov

LaBorde Johnson, Bonnie

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

bonnie.johnson@mms.gov

Landry, Connie

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

connie.landry@mms.gov

Landry, Laura A

L. A. Landry & Assoc.

105 Bayou Vista Drive

Hitchcock, TX 77563

lala@ut.net

Landry, Paul A

COMM Engineering Inc.

P.O. Box 53463

Lafayette, LA 70508

lamp@commengineering.com
457

Lea, Reid

W & T Offshore

3900 N Causeway #1200

Metairie, LA 70003

reid@wtoffshore.net

Ledet, Stephen J

ExxonMobil

1555 Poydras

New Orleans, LA 70112

stephen_j_ledet@email.mobil.com

Lee, Griff C

Griff C. Lee Inc

6353 Carlson Dr

New Orleans, LA 70122

gcl@accesscom.net

LeLeux, David

MMS

620 Esplanade #200

Lake Charles, LA 70607

david.leleux@mms.gov

Leonard, Norman

University of New Orleans

Dept of Biological Sciences

New Orleans, LA 70148

sunseeks@earthlink.net

LePere, Gia

Matrix Oil & Gas

P.O. Box 2468

Covington, LA 70434-2468

gia@matrixoil.com

Libiez, Susan

Chevron USA

935 Gravier St

New Orleans, LA 70112

sumi@chevron.com

Locke, Stephen

UNO Estuarine Research Lab

Lakefront Campus

New Orleans, LA 70148

slocke@uno.edu

Lugo-Fernandez, Alexis

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Luton, Harry

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

harry.luton@mms.gov

MacDonald, Ian R

Texas A&M University

727 Graham Rd

College Station, TX 77845

ian@gerg.tamu.edu

Marse, Todd

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

todd.marse@mms.gov

Matthews, Justin

UNOCAL

P.O. Box 69200

Lafayette, LA 70508

Mauthner, Natasha

University of Aberdeen

Aberdeen, ABR4301L

McCelvey, Pat

Devon Energy Corp.

Box 4616

Houston, TX 77210

pat.mccelvey@dvn.com
458

McGee, Thomas M

Ctr for Marine Res. & Environmental Tech.

220 Old Chemistry Bldg

University, MS 38677

tmm@mmri.olemiss.edu

McGuire, Thomas R

University of Arizona

P.O. Box 310030

Tucson, AZ 85721-0030

McKee, James

SAIC

1140 Eglin Parkway

Shalimar, FL 32579

McKee, Lorna

University of Aberdeen

Aberdeen, ABR4301L

Meekins, Keith

MMS

381 Elden St MS 4023

Herndon, VA 20170

keith.meekins@mms.gov

Mesyanzhinov, Dmitry

LSU/Center for Energy Studies

1 East Fraternity Circle

Baton Rouge, LA 70803

dmesyan@lsu.edu

Meyer, Thomas

MMS

1201 Elmwood Park Blvd

New Orleans, LA 70123-2394

tom.meyer@mms.gov

Miles, Robert

The UK HSE

HSE Rose Court 2

Southpark Bridge

London, ENGLAND SE19HS

bob.miles@hse.gsi.gov.uk

Mobley, Steven M

RPC

7600 Chevy Chase

Austin, TX 78752

Moon, Gregory W

UNOCAL

14141 Southwest Frwy

Sugar Land, TX 77478

gmoon@unocal.com

Moran, David

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Moran, Robert J

NOIA

1120 G St NW #900

Washington, DC 20005

Morris, Kristi

USFWS 

Morse, John

Texas A&M University

727 Graham Rd

College Station, TX 77845

morse@astra.tamu.edu

Nelson, Mike

LSU

Baton Rouge, LA 70893

Nunez, Arlette

Shell Offshore Inc

P.O. Box 61933

New Orleans, LA 70161-1933

O'Connor, Patricia

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123
459

Olatubi, Williams

LSU

Baton Rouge, LA 70803

Parisi, Domenico

MSU

Oxford, MS 38655

Parker, Wanda

WJP Enterprises

1441 Baffin Bay

Plano, TX 75075

wanda.parker@wjpenterprises.com

Parkes, K.R.

Oxford University

Oxford

Oxford, OX 3UD

Payton, Debbie

NOAA

7600 Sand Point Way NE

Seattle, WA 98115

Peggion, Germana

Univ. of Southern Mississippi

Bldg 1103 Room 249

Stennis Space Ctr, MS 39529

germana.peggion@usm.edu

Petterson, John S

Impact Assessment Inc.

2166 Avenue de la Playa #F

La Jolla, CA 92037

Peuler, Elizabeth

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

elizabeth.peuler@mms.gov

Phillips, Neal W

Continental Shelf Assoc. Inc.

308 Southway

Baltimore, MD 21218

nwphillips@att.net

Pilie, Clay

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Poe, Billy

Explosive Svcs. Intl.

P.O. Box 45742

Baton Rouge, LA 70895

explosive@earthlink.com

Poirrier, Michael

University of New Orleans

2000 Lakeshore Drive

New Orleans, LA 70148

mpoirrie@uno.edu

Price, James M

MMS

381 Elden St., MS-4041

Herndon, VA 20170

pricej@mms.gov

Rainey, Gail B

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

gail.rainey@mms.gov

Ray, James P

Equilon Enterprises LLC

3333 Highway 6 South

Houston, TX 77082-3101

jpray@equilon.com
460

Reed, Mark

SINTEF Applied Chemistry

Trondheim, NORWAY 

mark.reed@chem.sintef.no

Regg, Jim

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Reggio, Jr., Villere

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

villere.reggio@mms.gov

Reidenauer, Jeffrey A

The Louis Berger Group Inc

100 Halsted St

East Orange, NJ 07018

jreiden@louisberger.com

Reinert, Lt. John V

USCG

609 Rosenberg #309

Galveston, TX 77550

Richardson, Ed

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Roberts, Harry

LSU

Baton Rouge, LA 70801

Roberts, Paul

Sonoma Technology Inc.

1360 Redwood Way #C

Petaluma, CA 94954-1169

Rodrigue Jr., Donald A

University of New Orleans

Dept of Biological Sciences

New Orleans, LA 70148

dasodrigue@uno.edu

Rogers, Claudia

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Rogers, Robert

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Romar, Mia

BP Amoco

501 Westlake Park Blvd

Houston, TX 77079

romar@bp.com

Roscigno, Pat

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Rouse, Lawrence

Coastal Marine Institute

CSI - LSU

Baton Rouge, LA 70803

lrouse@lsu.edu

Rouse, Mark

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

mark.rouse@mms.gov

Rowe, Gil

Texas A&M University

MS 3146 TAMU

College Station, TX 77843

growe@ocean.tamu.edu
461

Rubin, Mark

API

1220 L St NW

Washington, DC 20005

rubin@api.org

Sachitana, Susan

Dominion E&P, Inc

1450 Poydras St.

New Orleans, LA 70112-6000

susan-H.sachitana@

Sager, Will

Texas A&M University

727 Graham Rd

College Station, TX 77845

Sammarco, Paul W

LUMCON

8124 Hwy 56

Chauvin, LA 70344

psammarco@lumcon.edu

Sassen, Roger

Texas A&M University

727 Graham Rd

College Station, TX 77845

sassen@gerg.tamu.edu

Satterlee, Kent

Shell Offshore Inc

P.O. Box 61933

New Orleans, LA 70161-1933

Scalfano, David

Sonoma Technology Inc.

1360 Redwood Way #C

Petaluma, CA 94954-1169

Schmahl, G.P.

Flower Garden Banks

National Marine Sanctuary

216 W 26th St #104

Bryan, TX 77803

george.schmahl@noaa.gov

Scholten, Terry

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

terry.scholten@mms.gov

Schroeder, William

University of Alabama

101 Bienville Blvd.

Dauphin Island, AL 36258

wschroeder@disl.org

Shannon, Brian

2915 Sunset Ridge

McKinney, TX 75070-4217

b.e.shannon@att.net

Shedd, William W

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

william.shedd@mms.gov

Shrimpton, Mark

Community Resource Services Ltd 

Simmons, Robert A

Simmons Consulting

1418 Lake Village Blvd.

Slidell, LA 70461

rsimmons@gs.verio.net

Sinclair, James E

UNO Estuarine Research Lab

4425 Calumet St

Metairie, LA 70001

jsinclai@uno.edu
462

Smith, Jennifer

J. Connor Consulting Inc

16225 Park Ten Place #700

Houston, TX 77084

jennifer@jccteam.com

Smith, Jonathan

Shell E&P Co.

701 Poydras St #2076

New Orleans, LA 70139

Smith, Michael

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Snyder, David

Continental Shelf Assoc. Inc.

759 Parkway Street

Jupiter, FL 33477

dsnyder@conshelf.com

Soniat, Tom

Nicholls State University

NSU - Dept of Biology

Thibodaux, LA 70310

Spackman, Alan

Int'l Assoc. of Drilling Contractors

P.O. Box 4287

Houston, TX 77210-4287

alan.spackman@inadc.org

Steube, Chuck

Conoco Shipping Company

600 North Dairy Ashford

P.O. Box 2197, TR-2046

Houston, TX 77252-2197

chuck.g.steube@usa.conoco.com

Stong, Bea

J. Connor Consulting Inc

16225 Park Ten Place #700

Houston, TX 77084

bea@jccteam.com

Storey, Keith

Community Resource Services Ltd 

Strikmiller, Michael G

Environmental Enterprises USA

58485 Pearl Acres Rd #D

Slidell, LA 70461

mgseeusa@cmq.com

Thorton, Win

WINMAR Consulting

5700 Northwest Central Drive

Houston, TX 77092

win@winmarconsulting.com

Thurgate, Nicole

University of New Orleans

Dept of Biological Sciences

New Orleans, LA 70148

nythurga@uno.edu

Tidemann, Arlen

National Response Corp.

11200 Westheimer #850

Houston, TX 77042

Tilley, Jason

W & T Offshore

3900 N Causeway #1200

Metairie, LA 70002

jason@wtoffshore.net

Tolbert, Charles

Baylor University

300 Burleson Hall

Box 97326

Waco, TX 76798

charlie_tolbert@baylor.edu
463

Tolbert, Michael

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

michael.tolbert@mms.gov

Trosclair, Troy

MMS

Box 760

Bourg, LA 70343

troy.trosclair@mms.gov

Trudel, Ken

S.L. Ross 

Tsoflias, Sarah L

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

sarah.tsoflias

Verret, Allen J

DeepStar

131 S Robertson St

New Orleans, LA 70150

allen_verret@murphyoilcorp.com

Vigil, Debra

MMS

1201 Elmwood Prk Blvd

MS 5431

New Orleans, LA 70123

debra_vigil@mms.gov

Von Dullen, III, Philip

Chevron USA Production Co.

935 Gravier St.

New Orleans, LA 70112

pvon@chevron.com

Waddell, Van

SAIC

615 Oberlin Rd #300

Raleigh, NC 27605

vwaddell@raleigh.saic.com

Wallace, Barbara

Tech Law Inc

4340 East West Hwy #1120

Bethesda, MD 20814

bwallace@techlawinc.com

Warren, Daniel

C & C Technologies, Inc.

730 E. Kaliste Saloom Rd

Lafayette, LA 70508

djw@cctechnol.com

Weaver, Doug

U.S. Geological Survey

Florida Caribbean Science Ctr.

7920 NW 71st Street

Gainesville, FL 32653

doug_weaver@usgs.gov

Wetzel, Dana

Mote Marine Laboratory

1600 Ken Thompson Prkwy

Sarasota, FL 34236

dana@mote.org

Wilkinson, Laura Lee

University of New Orleans

4606 S Miso #C

New Orleans, LA 70125

llwilkin@uno,edu

Wilson, Darcy

Eastern Research Group Inc.

P.O. Box 2010

Morrisville, NC 27560

dwilson@erg.com
464

Winbush, Debra

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Witten, Mark

Chevron USA Production Co.

935 Gravier St.

New Orleans, LA 70112

mswi@chevron.com

Woolsey, Robert

Ctr Marine Res. Environ. Technology

USM

Oxford, MS 38655

Wright, Rusty

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Zatarain, Vicki

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

vicki.zatarain@mms.gov

Zeigler, Gary

Radian International LLC 
The Department of the Interior Mission

As the Nation's principal conservation agency, the Department of the Interior has responsibility

for most of our nationally owned public lands and natural resources. This includes fostering

sound use of our land and water resources; protecting our fish, wildlife, and biological diversity;

preserving the environmental and cultural values of our national parks and historical places;

and providing for the enjoyment of life through outdoor recreation. The Department assesses

our energy and mineral resources and works to ensure that their development is in the best

interests of all our people by encouraging stewardship and citizen participation in their care.

The Department also has a major responsibility for American Indian reservation communities

and for people who live in island territories under U.S. administration.

The Minerals Management Service Mission

As a bureau of the Department of the Interior, the Minerals Management Service's (MMS)

primary responsibilities are to manage the mineral resources located on the Nation's Outer

Continental Shelf (OCS), collect revenue from the Federal OCS and onshore Federal and Indian

lands, and distribute those revenues.

Moreover, in working to meet its responsibilities, the Offshore Minerals Management Program

administers the OCS competitive leasing program and oversees the safe and environmentally

sound exploration and production of our Nation's offshore natural gas, oil and other mineral

resources. The MMS Minerals Revenue Management meets its responsibilities by ensuring the

efficient, timely and accurate collection and disbursement of revenue from mineral leasing and

production due to Indian tribes and allottees, States and the U.S. Treasury.

The MMS strives to fulfill its responsibilities through the general guiding principles of: (1) being

responsive to the public's concerns and interests by maintaining a dialogue with all potentially

affected parties and (2) carrying out its programs with an emphasis on working to enhance the

quality of life for all Americans by lending MMS assistance and expertise to economic

development and environmental protection.