OCS Report 

MMS 2007-029 

Oil-Spill Risk Analysis: 

Contingency Planning Statistics 

for Gulf of Mexico OCS Activities 

in the Walker Ridge Planning Area 

U.S. Department of the Interior 

Minerals Management Service 

Environmental Division 

OCS Report 

MMS 2007-029

Oil-Spill Risk Analysis: 

Contingency Planning Statistics 

for Gulf of Mexico OCS Activities 

in the Walker Ridge Planning Area 

By: 

Walter R. Johnson 

Zhen-Gang Ji 

Charles F. Marshall 

Eileen M. Lear (Editor)

U.S. Department of the Interior 

Minerals Management Service 

Environmental Division April 2007 

Contents

List of Figures and Tables................................................................................................................ ii 

Introduction....................................................................................................................................... 1 

Framework of the Analysis ............................................................................................................... 1 

Domain/Study Area....................................................................................................................... 1 

Hypothetical Spill Locations......................................................................................................... 2 

Environmental Resources ............................................................................................................. 2 

Oil-Spill Risk Analysis ..................................................................................................................... 3 

Oil-Spill Trajectory Simulations................................................................................................... 3 

Conditional Probabilities of Contact............................................................................................. 6 

Discussion ......................................................................................................................................... 6 

References Cited ............................................................................................................................... 7 

i 
List of Figures

 Figure Page 

1. Location of the oil-spill launch area for the Cascade and Chinook Projects 

in the Walker Ridge Planning Area ....................................................................... 9 

2. Locations of Gulf of Mexico counties/parishes (set 1) ........................................ 10 

3. Locations of Gulf of Mexico counties/parishes (set 2) ........................................ 11 

4. Locations of the U.S./Mexico international boundary segments in the Gulf 

of Mexico ............................................................................................................. 12 

List of Tables

 Table Page 

1. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area will contact a 

county/parish land segment within 30 days ........................................................ 13 

2. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area will contact an 

international boundary sea segment within 3, 10 and 30 days ............................ 14 

3. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area in the winter 

season will contact an international boundary sea segment within 3, 10 and 

30 days ................................................................................................................. 15 

4. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area in the spring 

season will contact an international boundary sea segment within 3, 10 and 

30 days ................................................................................................................. 16 

5. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area in the summer 

season will contact an international boundary sea segment within 3, 10 and 

30 days ................................................................................................................. 17 

6. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area in the fall season

will contact an international boundary sea segment within 3, 10 and 30 days 

 18 

ii 
Introduction 

The Federal Government offers U.S. Outer Continental Shelf (OCS) lands in the Gulf of 

Mexico (GOM) for oil and gas leasing. Because oil spills may occur from activities associated 

with offshore oil exploration, production, and transportation resulting from these lease sales, 

the Minerals Management Service (MMS) has conducted a formal oil-spill risk analysis 

(OSRA) to provide spill statistics that can be used in contingency planning for these areas. This 

report summarizes the results of that analysis, the objective of which was to estimate the risk of 

oil-spill contact to coastal resources in the GOM from oil spills accidentally occurring from the 

OCS activities (LaBelle, 2001). 

The occurrence of oil spills is fundamentally a matter of probability. There is no certainty 

regarding the amount of oil that would be produced, or the size or likelihood of a spill that 

would occur, during the estimated life of a given lease sale. Neither can the winds and ocean 

currents that transport oil spills be known for certain. A probabilistic event such as an oil-spill 

occurrence or oil-spill contact to an environmentally sensitive area cannot be predicted, only an 

estimate of its likelihood (its probability) can be quantified. 

This report provides the contingency planning statistics for the OCS activities in the GOM. The 

probabilities of oil spill occurrence and the combined probabilities of contact in the GOM are 

already presented in previous reports (Ji et al. 2002a, 2002b). This report is available from the 

MMS’s Internet site (http://www.mms.gov). 

Framework of the Analysis

Domain/Study Area 

The domain (shown in fig.1) defines the geographic boundaries that encompass the 

environmental resources at risk of contact by a hypothetical oil spill from OCS operations in 

the lease areas. Although few hypothetical oil spills were likely to extend beyond the borders of 

the domain within 30 days after release (the maximum elapsed time considered), we have 

tracked and tabulated spills that would travel beyond the open-ocean boundaries. These spills 

could contact land or other environmental resources outside the domain. 

The study area (shown in fig. 1) is the Walker Ridge Planning Area that encompasses a portion 

of the offshore waters within the Gulf of Mexico. The subarea of Walker Ridge that contains 

the Cascade and Chinook Projects is approximately 140 to 160 nautical miles offshore and is 

close to the limits of the Exclusive Economic Zone–the maritime region extending 200 nautical 

miles from the baseline of the territorial sea, in which the United States has exclusive rights 

and jurisdiction over living and nonliving natural resources. The study area was created as a 

hypothetical oil-spill launch area, which is used to represent oil-spill risks from platforms in the 

Cascade and Chinook Projects (fig. 1). 

1 
Hypothetical Spill Locations

The OSRA Model initiated hypothetical oil spills uniformly in space and time from within the 

study area, as shown in figure 1. At 1/10o intervals in the north-south direction (about 

11 kilometers [km]) and 1/10o intervals in the east-west direction (about 10 km), the model 

launched an oil spill every 1.0 day. At this resolution, there were 15 total launch points in 

space, and a total of 5,760 oil-spill trajectories were launched from each spatial grid point over 

two time periods, 9 years and 7 years, as described below (see “Oil Spill Trajectory 

Simulations”). The spatial resolution of the spill simulations was well within the spatial 

resolution of the input data, and the interval of time between releases was sufficiently short to 

sample weather-scale changes in the input winds (Price et al., 2003). 

The sensitivity tests on the OSRA Model (Price et al., 2002) indicated that, statistically, the 

above-mentioned spatial resolution (1/10o by 1/10o

) and time resolution (1.0 day) are sufficient 

to represent the spatial and time variations of the particle trajectories in the area. 

Environmental Resources 

The environmental resources considered in this analysis include the counties and parishes along 

the coast of the Gulf of Mexico. Figures 2 and 3 depict locations of these counties and parishes. 

The MMS used data derived from the Coastal Offshore Resource Information System (CORIS) 

and other databases (USDOI, MMS, 1999). The CORIS data were developed and supported by 

State and Federal Agencies and the oil industry operating along the Gulf Coast. The 

environmental resources considered also include 17 U.S./Mexico international boundary 

segments (fig. 4). 

All onshore, coastal environmental resource locations were represented by one or more 

partitions of the coastline, herein called land. The study area coastline was partitioned into 

162 equidistant land segments of approximately 10-mile (16-km) length. The partitions were 

formed by creating straight lines between two points projected onto the coast; therefore, the 

actual miles of shoreline represented by each land segment may be greater than 10 miles, 

depending upon the complexity of the coastal area. 

The counties and parishes examined in this OSRA are shown below. 

Counties/Parishes (set 1)--shown on Figure 2

C1-Cameron, TX C25-Baldwin, AL 

C3-Kenedy, TX C27-Santa Rosa, FL 

C5-Nueces, TX C29-Walton, FL 

C7-Calhoun, TX C31-Gulf, FL 

C9-Brazoria, TX C33-Wakulla, FL 

C11-Chambers, TX C35-Taylor, FL 

C13-Cameron, LA C37-Levy, FL 

C15-Iberia, LA C39-Hernando, FL 

C17-Terrebonne, LA C41-Pinellas, FL 

C19-Jefferson, LA C43-Manatee, FL 

C21-St. Bernard, LA C45-Charlotte, FL 

2 
C23-Jackson, MS C47-Collier, FL 

Counties/Parishes (set 2)--shown on Figure 3

C2-Willacy, TX C26-Escambia, FL 

C4-Kleberg, TX C28-Okaloosa, FL 

C6-Aransas, TX C30-Bay, FL 

C8-Matagorda, TX C32-Franklin, FL 

C10-Galveston, TX C34-Jefferson, FL 

C12-Jefferson, TX C36-Dixie, FL 

C14-Vermilion, LA C38-Citrus, FL 

C16-St. Mary, LA C40-Pasco, FL 

C18-Lafourche, LA C42-Hillsborough, FL 

C20-Plaquemines, LA C44-Sarasota, FL 

C22-Hancock & Harrison, MS C46-Lee, FL 

C24-Mobile, AL C48-Monroe, FL 

Oil-Spill Risk Analysis 

In this report, the OSRA was conducted to calculate the trajectories of oil spills from 

hypothetical spill locations to various environmental resources. 

Risk analyses may be characterized as “hazard-based” or “risk-based.” A hazard-based 

analysis examines possible events regardless of their low (or high) likelihood. For example, a 

potential impact would not lose significance because the risk has been reduced due to an 

increase in the level of control, such as engineering standards. A risk-based analysis, on the 

other hand, does take into account the likelihood of the event occurring or the measures that 

can be taken to mitigate against its potential impacts. This OSRA is designed for use as a 

hazard-based assessment. Therefore, the likelihood of oil spills occurring on the OCS was not 

considered in the analysis. 

Oil-Spill Trajectory Simulations 

The OSRA Model, originally developed by Smith et al. (1982) and enhanced by MMS over the 

years (LaBelle and Anderson, 1985; Ji et al., 2003, Ji et al. 2004), simulates oil-spill transport 

using realistic data fields of winds and ocean currents in the GOM. An oil spill on the ocean 

surface moves around by the complex surface ocean currents exerting a shear force on the 

spilled oil from below. In addition, the prevailing wind exerts an additional shear force on the 

spill from above, and the combination of the two forces causes the transportation of the oil spill 

away from its initial spill location. In the OSRA Model, the velocity of a hypothetical oil spill 

is the linear superposition of the surface ocean current and the wind drift caused by the winds. 

The model calculates the movement of hypothetical spills by successively integrating time 

sequences of two spatially gridded input fields: the surface ocean currents and the sea-level 

winds, both of which were generated by other computer models using many observations of 

relevant physical parameters. In this fashion, the OSRA Model generates time sequences of 

hypothetical oil-spill locations–essentially, oil-spill trajectories. 

3 
At each successive time step, the OSRA Model compares the location of the hypothetical spills 

against the geographic boundaries of shoreline and designated offshore environmental 

resources. The model counts the occurrences of oil-spill contact to these areas during the time 

periods that the habitat is known to be used by the resource. Finally, the frequencies of oil-spill 

contact are computed for designated oil-spill travel times (e.g., 3, 10, or 30 days) by dividing 

the total number of oil-spill contacts by the total number of hypothetical spills initiated in the 

model from a given hypothetical spill location. The frequencies of oil-spill contact are the 

model-estimated probabilities of oil-spill contact. The OSRA Model output provides the 

estimated probabilities of contact to all identified offshore environmental resources and 

segments of shoreline from locations chosen to represent hypothetical oil spills from oil 

production and transportation facilities, at several selected oil-spill travel times. 

There are factors not explicitly considered by the OSRA Model that can affect the transport of 

spilled oil as well as the dimensions, volume, and nature of the oil spills contacting 

environmental resources or the shoreline. These include possible cleanup operations, chemical 

composition or biological weathering of oil spills, or the spreading and splitting of oil spills. 

The OSRA analysts have chosen to take a more environmentally conservative approach by 

presuming persistence of spilled oil over the selected time duration of the trajectories. 

In the trajectory simulation portion of the OSRA Model, many hypothetical oil-spill trajectories 

are produced by numerically integrating a temporally and spatially varying ocean current field, 

and superposing on that an empirical wind-induced drift of the hypothetical oil spills (Samuels 

et al., 1982). Collectively, the trajectories represent a statistical ensemble of simulated oil-spill 

displacements produced by a field of winds derived from observations and numerically derived 

ocean currents. The winds and currents are assumed to be statistically similar to those that will 

occur in the Gulf during future offshore activities. In other words, the oil-spill risk analysts 

assume that the frequency of strong wind events in the wind field is the same as what will 

occur during future offshore activities. By inference, the frequencies of contact by the 

simulated oil spills are the same as what could occur from actual oil spills during future 

offshore activities. 

Another portion of the OSRA Model tabulates the contacts by the simulated oil spills. The 

model contains the geographical boundaries of a variety of identified environmental features. 

At every integration time step, the OSRA Model tracks the locations of the simulated spills and 

counts the number of oil-spill contacts to segments of shoreline (counties/parishes). A contact 

to shore will stop the trajectory of an oil spill; no re-washing is assumed in this model. After 

specified periods of time, the OSRA Model will divide the total number of contacts to the 

coastline segments by the total number of simulated oil spills from a given geographic location. 

These ratios are the estimated probabilities of oil-spill contact from offshore activities at that 

geographic location, assuming spill occurrence. 

Conducting an oil-spill risk analysis needs detailed information on ocean currents and wind 

fields (Ji, 2004). The ocean currents used are numerically computed from an ocean circulation 

model of the GOM driven by analyzed meteorological forces (the near-surface winds and the 

total heat fluxes) and observed river inflow into the GOM (Herring et al., 1999; Oey et al., 

4 
2004; Oey, 2005). The models used are versions of the Princeton Ocean Model (POM), which 

is an enhanced version of the earlier constructed Mellor-Blumberg Model. It is a threedimensional, time-dependent, primitive equation model using orthogonal curvilinear 

coordinates in the horizontal and a topographically conformal coordinate in the vertical. The 

use of these coordinates allows for a realistic coastline and bottom topography, including a 

sloping shelf, to be represented in the model simulation. The model incorporates the MellorYamada turbulence closure model to provide a parameterization of the vertical mixing process 

through the water column. 

The prognostic variables of the model are velocity, temperature, salinity, turbulence kinetic 

energy, and turbulence macroscale. The momentum equations are nonlinear and incorporate a 

variable Coriolis parameter. Prognostic equations governing the thermodynamic quantities 

(temperature and salinity) account for water mass variations brought about by highly timedependent coastal upwelling processes. The processes responsible for eddy production, 

movement, and eventual dissipation are also included in the model physics. Other computed 

variables include density, vertical eddy viscosity, and vertical eddy diffusivity. 

Two separate model runs were used to calculate the trajectories for this statistical report. The 

first was a 9-year simulation performed by Dynalysis of Princeton (Herring, et al., 1999). The 

POM was driven by winds and heat fluxes over the 9-year period, 1986 through 1994, which 

were analyzed by the European Center for Medium-Range Weather Forecasts (ECMWF). The 

second ocean model calculation was performed by Princeton University (Oey, 2003; Oey, et 

al., 2004). This simulation covered the 7-year period, 1993 through 1999, and the results were 

saved at 1-hour intervals. This run included the assimilation of sea surface altimeter 

observations, to improve the ocean model results. The surface currents were then computed for 

input into the OSRA Model along with the concurrent wind field. The OSRA Model used the 

same wind field to calculate the empirical wind drift of the simulated spills. The statistics for 

the contacts by the trajectories forced by the two model runs were combined for the average 

probabilities. 

The ocean model simulations were extensively skill-assessed with many observations from the 

GOM (Herring et al., 1999; Oey, et al., 2004, Oey, 2005). These extensive sets of observations 

afford a rigorous test of the model’s ability to reproduce ocean transport as well as prominent 

features of the Gulf, such as the Loop Current and strong mesoscale eddies, which are easily 

observed from satellite-borne instrumentation. With these observations and other current 

measurements from moored current meters, a good determination of the model’s veracity was 

made. Both the POM models did an excellent job in reproducing the characteristics of the 

GOM surface currents both on and off the continental shelf. The surface current field manifests 

all the dominant structures in time and space as the observed currents and is, therefore, 

applicable in the statistical estimation of future spill risk that the OSRA Model makes. 

Trajectories of hypothetical spills were initiated every 1.0 day from each of the 15 launch 

points in space—3,240 trajectories per launch point over the 9-year simulation period and 

2,520 over the 7-year simulation period. The chosen number of trajectories per site (5,760) was 

small enough to be computationally practical and large enough to reduce the random sampling 

5 
error to an insignificant level. Also, the weather-scale changes in the winds are at least 

minimally sampled with simulated spills started every 1.0 day. 

The OSRA Model integrates the spill velocities (a linear superposition of surface ocean 

currents and empirical wind drift) by integrating in time to produce the spill trajectories. The 

time step selected was 1 hour to fully utilize the spatial resolution of the ocean current field and 

to achieve a stable set of trajectories. The velocity field was bilinearly interpolated from the 3-

hourly or 1-hourly grid to get velocities at 1-hour intervals. Smaller time steps did not produce 

significant differences in the simulated trajectories after 30 model days, so the 1-hour time step 

was chosen for this analysis. Ji et al. (2004) summarized the latest improvement on the OSRA 

Model and the model sensitivity tests. 

Conditional Probabilities of Contact 

The probability that an oil spill will contact a specific environmental resource within a given 

time of travel from a certain location or spill point is termed a conditional probability, the 

condition being that a spill is assumed to have occurred. Each trajectory was allowed to 

continue for as long as 30 days. However, if the hypothetical spill contacted shoreline sooner 

than 30 days after the start of the spill, the spill trajectory was terminated, and the contact was 

recorded. On the other hand, the international boundary segments do not terminate the 

trajectories, so that one trajectory could contact more than one segment, based on changing 

wind and current histories. 

The trajectories simulated by the model represent only hypothetical pathways of oil slicks; they 

do not involve any direct consideration of cleanup, dispersion, or weathering processes that 

could alter the quantity or properties of oil that might eventually contact the environmental 

resource locations. However, an implicit analysis of weathering and decay can be considered 

by choosing a travel time for the simulated oil spills when they contact environmental resource 

locations that represent the likely persistence of the oil slick on the water surface. The MMS 

performed an analysis of the likely weathering and cleanup of a typical offshore oil spill of 

1,000 bbl or greater occurring under the proposed action scenarios (USDOI, MMS, 2002). The 

analysis of the slick’s fate showed that a typical GOM oil slick of 1,000 bbl or greater, exposed 

to typical winds and currents, would not persist on the water surface beyond 10 days. 

Therefore, OSRA Model trajectories were analyzed on an annual basis for 3, 10, and 30 days, 

and the probabilities of oil-spill contact occurring within these time periods are reported in 

tables 1 and 2. The probabilities of oil-spill contact were also analyzed on a seasonal basis, 

and these probabilities are reported in tables 1 (counties/parishes), and tables 3 through 6 (sea 

segments). The counties and parishes with all probabilities of less than 0.5 percent are not 

shown. 

Discussion 

As one might expect, the environmental resource locations closest to the spill sites had the 

greatest risk of contact. As the model run duration increases, more of the identified 

environmental resources could have meaningful probabilities of contact (> 0.5%). The longer 

6 
transit times (up to 30 days) allowed by the model enable more hypothetical spills to reach the 

environmental resources from more distant spill locations. With increased travel time, the 

complex patterns of wind and ocean currents produce eddy-like motions of the oil spills and 

multiple opportunities for a spill to make contact with any given environmental resource. The 

hypothetical oil-spill launch area for this analysis is between 140 and 160 nautical miles from 

the coast, which resulted in no probabilities of contact to county/parish land segments of 

greater than 0.5 percent for 3 to 10 days and an annual average maximum of 2 percent (table 1). 

Due to the climatology of the wind, the spring season had the higher average probabilities of 

contact to these segments (the highest being 8 percent), and the fall season had the lowest 

(none greater than 0.5 percent). The hypothetical launch area was approximately 40 to 55 

nautical miles from the international boundary segments, thus these segments have annual 

average contact probabilities of up to 16 percent within 10 days (table 2). The international 

boundary segments do not terminate the trajectories, so that one trajectory could contact more 

than one segment, based on changing wind and current histories. 

References Cited 

Herring, H. J., M. Inoue, G. L. Mellor, C. N. K. Mooers, P. P. Niiler, L-Y. Oey, R. C. Patchen, 

F. M. Vukovich, and W. J. Wiseman, Jr. 1999. Coastal Ocean Modeling Program for the 

Gulf of Mexico. Report Numbers 115.1, 115.2, and 115.3 with appendices 115A through 

115O-P. Prepared for the Minerals Management Service. 

Ji, Z.-G. 2004. Use of Physical Sciences in Support of Environmental Management. 

Environmental Management. Environmental Management 34(2):159-169. 

Ji, Z.-G., W.R. Johnson, C.F. Marshall, G.B. Rainey, and E.M. Lear. 2002a. Oil-Spill Risk 

Analysis: Gulf of Mexico Outer Continental Shelf (OCS) Lease Sales, Central Planning 

Area and Western Planning Area, 2003-2007, and Gulfwide OCS Program, 2003-2042. 

OCS Report 2002-032. Minerals Management Service, Herndon, Virginia. 

Ji, Z.-G., W.R. Johnson, C.F. Marshall, G.B. Rainey, and E.M. Lear. 2002b. Oil-Spill Risk 

Analysis: Gulf of Mexico Outer Continental Shelf (OCS) Lease Sales, Eastern Planning 

Area, 2003-2007, and Gulfwide OCS Program, 2003-2042. OCS Report 2002-069. 

Minerals Management Service, Herndon, Virginia. 

Ji, Z.-G., W.R. Johnson, J.W. Price, and C.F. Marshall. 2003. Oil-Spill Risk Analysis for 

Assessing Environmental Impacts. In Proceedings of the 2003 International Oil Spill 

Conference, Vancouver, Canada. 

Ji, Z.-G., W.R. Johnson, and C.F. Marshall. 2004. Deepwater Oil-Spill Modeling for Assessing 

Environmental Impacts. Proceedings of the 2004 Oil Spill Conference, Alicante, Spain. 

LaBelle, R.P. 2001. Overview of U.S. Minerals Management Service Activities in Deepwater 

Research. Marine Pollution Bulletin 43(7-12): 256-261. 

7 
LaBelle, R.P., and C. M. Anderson. 1985. The Application of Oceanography to Oil-Spill 

Modeling for the Outer Continental Shelf Oil and Gas Leasing Program: Marine 

Technology Society Journal 19(2):19-26. 

Oey, L.-Y., 2003: A Circulation Model of the Gulf of Mexico and the Caribbean Sea: 

Development of the Princeton Regional Ocean Forecast (& Hindcast) System - PROFS, 

and Hindcast Experiment for 1992-1999. Final Report, OCS Study MMS 2005-049, U.S. 

DOI Minerals Management Service, Herndon, Virginia. 174 pp. 

Oey, L.-Y., P. Hamilton, and H.-C. Lee. 2004. Modeling and Data Analyses of Circulation 

Processes in the Gulf of Mexico: Final Report. OCS Study MMS 2003-074. U.S. Dept. 

of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New 

Orleans, LA. 140 pp. 

Oey, L.-Y. 2005. A Circulation Model of the Gulf of Mexico and the Caribbean Sea: 

Development of the Princeton Regional Ocean Forecast (& Hindcast) System - PROFS, 

and Hindcast Experiment for 1992-1999. Final Report. OCS Study MMS 2005-049. 

U.S. Dept. of the Interior, Minerals Management Service, Environmental Division, 

Herndon, Virginia. 174 pp. 

Price, J.M., W.R. Johnson, Z.-G. Ji, C.F. Marshall, and G.B. Rainey. 2002. Sensitivity Testing 

for Improved Efficiency of a Statistical Oil Spill Risk Analysis Model. Environmental 

Modelling & Software 19(2004):671-679. 

Price, J. M., W. R. Johnson, C. F. Marshall, and Z.-G. Ji. 2003. Overview of the Oil Spill Risk 

Analysis (OSRA) Model for Environmental Impact Assessment. Spill Science & 

Technology Bulletin 8(5-6):529-533. 

Samuels, W. B., N. E. Huang, and D.E. Amstutz. 1982. An Oil Spill Trajectory Analysis Model 

with a Variable Wind Deflection Angle. Ocean Engineering 9:347-360. 

Smith, R. A., J. R. Slack, T. Wyant, and K. J. Lanfear. 1982. The Oil Spill Risk Analysis Model 

of the U.S. Geological Survey. U.S. Geological Survey Professional Paper 1227. 

U.S. Department of the Interior, Minerals Management Service. 1999. Relational Database 

Design for Coastal and Offshore Resource Information System ( CORIS ). Version 1.2. 

U.S. Dept. of the Interior, Minerals Management Service, Information Technology 

Division, Systems Application Branch. April 1999. 

U.S. Department of the Interior, Minerals Management Service. 2002. Gulf of Mexico OCS Oil 

and Gas Lease Sales: 2003-2007, Central Planning Area Sales 185, 190, 194, 198, and 

201; Western Planning Area Sales 187, 192, 196, and 200 Draft Environmental Impact 

Statement. OCS EIS/EA MMS 2002-015. U.S. Dept. of the Interior, Minerals 

Management Service, Gulf of Mexico OCS Region, New Orleans, LA. 2 vols. 

8 
TX

AL MS

LA

31o30o29o28o27o26o25o24o

97o 96o 95o 94o 93o 92o 91o 90o 89o 88o 87o 86o 

Figure 1. Location of the oil-spill launch area for the Cascade and Chinook projects in 

Area.

9

MEX
Figure 2. Locations of Gulf of Mexico counties/parishes (set 1). (Shading is not to scal

31o30o29o28o27o26o25o24o

97o 96o 95o 94o 93o 92o 91o 90o 89o 88o 87o 86o 

C1

C11

C9

C7

C5

C3

C13

C15

C17 C19

C1 - Cameron, TXC3 - Kenedy, TXC5 - Nueces, TXC7 - Calhoun, TXC9 - Brazoria, TX

C11 - Chambers, TXC13 - Cameron, LAC15 - Iberia, LAC17 - Terrebonne, LAC19 - Jefferson, LAC21 - St. Bernard, LAC23 - Jackson, MS

C23 C25 C27C29

C21 C3

C25 - Baldwin, ALC27 - Santa Rosa, FLC29 - Walton, FLC31 - Gulf, FLC33 - Wakulla, FLC35 - Taylor, FLC37 - Levy, FLC39 - Hernando, FLC41 - Pinellas, FLC43 - Manatee, FLC45 - Charlotte, FLC47 - Collier, FL

TX

LA

MS AL 

Mex ci o

10
Figure 3. Locations of Gulf of Mexico counties/parishes (set 2). (Shading is not to scal

97o 96o 95o 94o 93o 92o 91o 90o 89o 88o 87o 86o 

C2 - Willacy, TXC4 - Kleberg, TXC6 - Aransas, TXC8 - Matagorda, TX

C10 - Galveston, TXC12 - Jefferson, TXC14 - Vermilion, LAC16 - St. Mary, LAC18 - LaFourche, LAC20 - Plaquemines, LAC22 - Hancock & Harrison, MSC24 - Mobile, AL

C26 - Escambia, FLC28 - Okaloosa, FLC30 - Bay, FLC32 - Franklin, FLC34 - Jefferson, FLC36 - Dixie, FLC38 - Citrus, FLC40 - Pasco, FLC42 - Hillsborough, FLC44 - Sarasota, FLC46 - Lee, FLC48 - Monroe, FL

C2

C12

C10

C8

C6

C4

C16

C14

C18 C20

C22 C24 C26

C28

C30

TX

LA

MS AL 

Mex ci o

31o30o29o28o27o26o25o24o

11
31o

30o29o28o27o26o25o24o

97o 96o 95o 94o 93o 92o 91o 90o 89o 88o 87o 86o 

TX

AL MS

LA

Figure 4. Locations of the U.S./Mexico international boundary segments in the Gulf o

12

MEX

12 3 4 5

6 7 8 9 10 11

12
Table 1. Probabilities (expressed as percent chance) that an oil spill starting within a 

particular launch area in the Walker Ridge Planning Area will contact a county/parish 

land segment within 30 days 

County/Parish Annual Winter Spring Summer Fall 

C7 n n 1 n n 

C8 1 2 2 n n 

C9 1 1 2 n n 

C10 2 2 6 1 n 

C12 1 n 3 n n 

C13 2 1 8 n n 

C14 1 n 4 n n 

C15 n n 2 n n 

C17 1 n 5 n n 

C18 1 n 2 n n 

C19 n n 1 n n 

C20 1 n 5 1 n 

Notes: ** = Greater than 99.5 percent; n = less than 0.5 percent. 

 Rows with all values less than 0.5 percent are not shown. 

Location of county/parish land segments

C7 (Calhoun, TX) C8 (Matagorda, TX) C9 (Brazoria, TX) 

C10 (Galveston, TX) C12 (Jefferson, TX) C13 (Cameron, LA) 

C14 (Vermilion, LA) C15 (Iberia, LA) C17 (Terrebonne, LA) 

C18 (LaFourche, LA) C19 (Jefferson, LA) C20 (Plaquemines, LA) 

13
Table 2. Probabilities (expressed as percent chance) that an oil spill starting within 

a particular launch area in the Walker Ridge Planning Area will contact an 

international boundary sea segment within 3, 10 and 30 days 

International Boundary Number of Days 

Sea Segment 3 10 30 

1 n n n 

2 n n n 

3 n n 2 

4 n n 4 

5 n 1 9 

6 n 4 17 

7 2 13 26 

8 6 16 23 

9 1 7 12 

10 n 2 5 

11 n n 1 

12 n n 1 

13 n n 1 

14 n n n 

15 n n n 

16 n n n 

17 n n n 

Note: ** = Greater than 99.5 percent; n = Less than 0.5 percent. 

Location of boundary sea segments

1 ( to 97o

 W. long.) 2 (97-96o W. long.) 3 (96-95o W. long.) 

4 (95-94o W. long.) 5 (94-93o W. long.) 6 (93-92o W. long.) 

7 (92-91o

 W. long.) 8 (91-90o W. long.) 9 (90-89o W. long.) 

10 (89-88o

 W. long.) 11 (88-87o W. long.) 12 (87-86o W. long.) 

13 (86-85o W. long.) 14 (85-84o W. long.) 15 (84-83o W. long.) 

16 (83-82o

 W. long.) 17 (82-81o W. long.)

14
Table 3. Probabilities (expressed as percent chance) that an oil spill starting within 

a particular launch area in the Walker Ridge Planning Area in the winter season 

will contact an international boundary sea segment within 3, 10 and 30 days 

International Boundary Number of Days 

Sea Segment 3 10 30 

1 n n n 

2 n n n 

3 n n 4 

4 n n 5 

5 n 1 10 

6 n 2 18 

7 2 14 31 

8 10 23 29 

9 n 2 6 

10 n n 2 

11 n n 1 

12 n n n 

13 n n n 

14 n n n 

15 n n n 

16 n n n 

17 n n n 

Note: ** = Greater than 99.5 percent; n = Less than 0.5 percent. 

Location of boundary sea segments

1 ( to 97o

 W. long.) 2 (97-96o W. long.) 3 (96-95o W. long.) 

4 (95-94o

 W. long.) 5 (94-93o W. long.) 6 (93-92o W. long.) 

7 (92-91o W. long.) 8 (91-90o W. long.) 9 (90-89o W. long.) 

10 (89-88o

 W. long.) 11 (88-87o W. long.) 12 (87-86o W. long.) 

13 (86-85o

 W. long.) 14 (85-84o W. long.) 15 (84-83o W. long.) 

16 (83-82o W. long.) 17 (82-81o W. long.)

15
Table 4. Probabilities (expressed as percent chance) that an oil spill starting within 

a particular launch area in the Walker Ridge Planning Area in the spring season 

will contact an international boundary sea segment within 3, 10 and 30 days 

International Boundary Number of Days 

Sea Segment 3 10 30 

1 n n n 

2 n n n 

3 n n n 

4 n n 1 

5 n n 4 

6 n 1 4 

7 n 4 11 

8 n 2 6 

9 n 1 5 

10 n 2 3 

11 n n n 

12 n n 1 

13 n n 2 

14 n n n 

15 n n n 

16 n n n 

17 n n n 

Note: ** = Greater than 99.5 percent; n = Less than 0.5 percent. 

Location of boundary sea segments

1 ( to 97o

 W. long.) 2 (97-96o W. long.) 3 (96-95o W. long.) 

4 (95-94o

 W. long.) 5 (94-93o W. long.) 6 (93-92o W. long.) 

7 (92-91o W. long.) 8 (91-90o W. long.) 9 (90-89o W. long.) 

10 (89-88o

 W. long.) 11 (88-87o W. long.) 12 (87-86o W. long.) 

13 (86-85o

 W. long.) 14 (85-84o W. long.) 15 (84-83o W. long.) 

16 (83-82o W. long.) 17 (82-81o W. long.)

16
Table 5. Probabilities (expressed as percent chance) that an oil spill starting within 

a particular launch area in the Walker Ridge Planning Area in the summer season 

will contact an international boundary sea segment within 3, 10 and 30 days 

International Boundary Number of Days 

Sea Segment 3 10 30 

1 n n n 

2 n n n 

3 n n 2 

4 n n 5 

5 n 1 10 

6 n 7 21 

7 4 14 24 

8 2 5 12 

9 1 4 7 

10 n n 1 

11 n n n 

12 n n 1 

13 n n 1 

14 n n 1 

15 n n 1 

16 n n n 

17 n n n 

Note: ** = Greater than 99.5 percent; n = Less than 0.5 percent. 

Location of boundary sea segments

1 ( to 97o

 W. long.) 2 (97-96o W. long.) 3 (96-95o W. long.) 

4 (95-94o

 W. long.) 5 (94-93o W. long.) 6 (93-92o W. long.) 

7 (92-91o W. long.) 8 (91-90o W. long.) 9 (90-89o W. long.) 

10 (89-88o

 W. long.) 11 (88-87o W. long.) 12 (87-86o W. long.) 

13 (86-85o

 W. long.) 14 (85-84o W. long.) 15 (84-83o W. long.) 

16 (83-82o W. long.) 17 (82-81o W. long.)

17
Table 6. Probabilities (expressed as percent chance) that an oil spill starting within 

a particular launch area in the Walker Ridge Planning Area in the fall season will 

contact an international boundary sea segment within 3, 10 and 30 days 

International Boundary Number of Days 

Sea Segment 3 10 30 

1 n n n 

2 n n 1 

3 n n 1 

4 n n 4 

5 n 1 11 

6 n 8 23 

7 1 19 38 

8 14 32 44 

9 3 21 31 

10 n 5 13 

11 n n 2 

12 n n 1 

13 n n n 

14 n n n 

15 n n n 

16 n n n 

17 n n n 

Note: ** = Greater than 99.5 percent; n = Less than 0.5 percent. 

Location of boundary sea segments

1 ( to 97o

 W. long.) 2 (97-96o W. long.) 3 (96-95o W. long.) 

4 (95-94o

 W. long.) 5 (94-93o W. long.) 6 (93-92o W. long.) 

7 (92-91o W. long.) 8 (91-90o W. long.) 9 (90-89o W. long.) 

10 (89-88o

 W. long.) 11 (88-87o W. long.) 12 (87-86o W. long.) 

13 (86-85o

 W. long.) 14 (85-84o W. long.) 15 (84-83o W. long.) 

16 (83-82o W. long.) 17 (82-81o W. long.)

18
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.