OCS Study 

MMS 2004-047 

 

Supply Network for Deepwater Oil and 

Gas Development in the Gulf of Mexico: 

An Empirical Analysis of Demand 

for Port Services 

Final Report 

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 2004-047 

Supply Network for Deepwater Oil and 

Gas Development in the Gulf of Mexico: 

An Empirical Analysis of Demand 

for Port Services 

Final Report 

Authors 

Jay Jayawardana 

Anatoly Hochstein 

Prepared under MMS Contract 

1435-01-01-CA-31154 

by 

UNO National Ports and Waterways Institute 

University of New Orleans 

College of Urban & Public Affairs 

New Orleans, Louisiana 70148 

Published by 

New Orleans

June 2004 
iii

DISCLAIMER 

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

and UNO National Ports and Waterways Institute. This report has been technically reviewed by 

MMS, and has been approved for publication. Approval does not signify that the contents 

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

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

from review and compliance with the 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: (504) 736-2519 or 

1-800-200-GULF 

CITATION 

Suggested citation: 

Jayawardana, J. and A. Hochstein. 2004. Supply Network for Deepwater Oil and Gas 

Development in the Gulf of Mexico: An Empirical Analysis of Demand for Port 

Services; Final Report. Prepared by UNO National Ports and Waterways Institute. U.S. 

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

Orleans, LA. OCS Study MMS 2004-047. 98 pp. 
v

ABSTRACT 

This report presents an empirical analysis of the demand for port services generated by the 

deepwater oil and gas industry during its phenomenal growth during the last decade. During this 

period, the deepwater oil production registered a nine-fold increase while the gas production 

increased sixteen fold. In addition, technological developments in seismic data acquisition, large 

deepwater field discoveries, and the innovative production systems have completely transformed 

the industry and the logistical support network. Although the logistical support system is a vital 

component of the industry, empirical studies analyzing the supply network adjustments from the 

perspective of port services are currently not available. Therefore, the demand analysis in this 

report will fill that void and is expected to be useful for port planning and investment decisions. 

The methodological approach followed in the analysis was determined by the nature of port 

activities at each port and data availability. For example, for Port Fourchon the demand for port 

services was estimated using time-series data from 1992 to 2001. The variable relationships 

between several industry variables and port services such as port tonnage, truck traffic and inland 

barge traffic were estimated using regression analysis. Similarly, for the Port of Morgan City 

specializing in shipbuilding, the demand relationships for vessel traffic on the Atchafalaya River 

and the industry variables were estimated. 

The regression models for Port Fourchon indicated that for every additional OCS well drilled 

the truck traffic at the port will increase by about 673 trips a year, inland barge traffic by 7 trips, 

and the tonnage handled at the port by 11,400 tons. Similarly, another model predicted that for 

every mile of pipeline approved, truck traffic will increase by 217 trips, barge traffic by 3 trips, 

and port tonnage by 46,000 tons. 

Using the above empirical estimates, demand forecasts were developed through 2010 for 

each variable. According to these estimates, truck traffic is expected to grow by 67 percent 

between 2001 and 2010, barge traffic by 25 percent and the port tonnage by 100 percent. 

The regression models estimated for the Port of Morgan City indicated that for every 

additional OCS well rigged the number of non-self propelled vessels on the Atchafalaya will 

increase by about 12 trips. The traffic forecasts through 2010 indicated a 62 percent growth for 

the period 2001 to 2010. 

With more than 60 percent of the port tenants engaged in OCS related services, the Port of 

Iberia experienced continuous growth in the 1990’s. Since activities at the Port of Iberia are 

concentrated on the assembly of prefabricated structures, repair and maintenance, a quantitative 

database with relevant demand and supply was not available. However, analytical models 

developed on port financial performance and infrastructure expansion indicated increasing 

demand for offshore services. The OCS service activities at the Port of Galveston have emerged 

as an important sector with an increasing share of waterfront land devoted to offshore activities 

and the location of several large-scale tenant operations in recent years. 

A qualitative analysis of different port variables also indicate the extent of adjustments made 

by the ports during the period. For example during the 1992-2001 period, port tonnage handled 

increased seven-fold and port operating revenues increased by 82 percent at Port Fourchon. The 

operating revenues at the Port of Iberia increased three-fold during 1992-2000 the period. The 

amount of waterfront land allotted to OCS activities at the Port of Galveston increased twentyfold during the same period. 

Based on all the information in this report, it is evident that the ports have expanded 

infrastructure investment to meet the growing needs of the deepwater oil and gas industry. As 
vi

the industry grew at a faster pace than the supply of port services during the period, the ports 

have enjoyed higher returns resulting in better financial performance. However, as the 

deepwater oil and gas industry reaches a plateau, more information is needed in port investment 

and planning decisions. This report is an attempt to provide such information. 
vii

TABLE OF CONTENTS 

Page

Abstract ------------------------------------------------------------------------------------------------ v 

List of Figures ----------------------------------------------------------------------------------------- xi 

List of Tables ------------------------------------------------------------------------------------------ xiii 

Abbreviations, Acronyms, and Symbols----------------------------------------------------------- xv 

1 Executive Summary---------------------------------------------------------------------------- 1 

1.1. Ports and the OCS Supply Network--------------------------------------------------- 1 

1.1.1. Study Approach and Outline --------------------------------------------------- 1 

1.1.2. Major Components of the System --------------------------------------------- 1 

1.2. Port Fourchon ---------------------------------------------------------------------------- 1 

1.2.1. Demand for Port Services------------------------------------------------------- 1 

1.2.2. Empirical Analysis and Forecasts---------------------------------------------- 5 

1.3. Port of Morgan City--------------------------------------------------------------------- 6 

1.3.1. Profiles of Major Operators----------------------------------------------------- 6 

1.3.2. Demand for Port Services------------------------------------------------------- 6 

1.3.3. Empirical Analysis and Forecasts---------------------------------------------- 7 

1.4. Port of Iberia ----------------------------------------------------------------------------- 8 

1.4.1. Demand for Port Services------------------------------------------------------- 9 

1.5. Port of Galveston ------------------------------------------------------------------------ 11 

1.5.1. Offshore Service Activities and Major Operators --------------------------- 11 

1.5.2. Growth Trends in OCS Services ----------------------------------------------- 12 

1.5.3 Long-term Industry Adjustments --------------------------------------------- 13 

1.6. Conclusions ------------------------------------------------------------------------------ 13 

2 Ports and the OCS Supply Network --------------------------------------------------------- 15 

2.1. Introduction ------------------------------------------------------------------------------ 15 

2.2. Study Approach and Outline ----------------------------------------------------------- 15 

2.3. Major Components of the System----------------------------------------------------- 16 

2.3.1. Inland Transport Sector --------------------------------------------------------- 18 

2.3.2. Offshore Sector------------------------------------------------------------------- 18 

2.3.3. Port Sector ------------------------------------------------------------------------ 18 

3 Port Fourchon----------------------------------------------------------------------------------- 21 

3.1. Framework for Analysis ---------------------------------------------------------------- 21 

3.2. Port Infrastructure and Operations ---------------------------------------------------- 21 

3.2.1. Location and Transportation Links -------------------------------------------- 21 

3.2.2. Port Infrastructure---------------------------------------------------------------- 22 

3.3. Data and Definition of Variables ------------------------------------------------------ 23 

3.3.1. Historical Trends ----------------------------------------------------------------- 24 

3.4. Estimating the Demand for Port Services -------------------------------------------- 27 

3.4.1. Model Specification ------------------------------------------------------------- 27 
viii

3.4.2. Truck Traffic Demand----------------------------------------------------------- 29 

3.4.3. Inland Barge Traffic Demand -------------------------------------------------- 31 

3.4.4. Cargo Activities Demand ------------------------------------------------------- 31 

3.5. Demand Forecasts ----------------------------------------------------------------------- 32 

3.5.1. Forecasting Approach ----------------------------------------------------------- 32 

3.5.2. Growth Projections -------------------------------------------------------------- 32 

3.6. Structural Analysis and Policy Implications ----------------------------------------- 33 

4 Port of Morgan City---------------------------------------------------------------------------- 37 

4.1. Location and Transportation Infrastructure ------------------------------------------ 37 

4.2. The Public Port -------------------------------------------------------------------------- 38 

4.2.1. Port Organization, Location, and Facilities----------------------------------- 38 

4.2.2. Port Operations and Financial Performance ---------------------------------- 40 

4.3. Private Sector Operators---------------------------------------------------------------- 40 

4.3.1. Profiles of Major Operators----------------------------------------------------- 41 

4.4. Data and Definition of Variables ------------------------------------------------------ 43 

4.4.1. Industry Variables and Port Activity Levels---------------------------------- 43 

4.4.2. Historical Trends ----------------------------------------------------------------- 43 

4.5. Estimating the Demand for Port Services -------------------------------------------- 47 

4.6. Model Forecasts ------------------------------------------------------------------------- 48 

4.7. Structural Analysis and Policy Implications ----------------------------------------- 48 

5 Port of Iberia ------------------------------------------------------------------------------------ 51 

5.1. Port Location and Transportation Links ---------------------------------------------- 51 

5.2. Port Infrastructure ----------------------------------------------------------------------- 53 

5.2.1. Port Layout and Land Use ------------------------------------------------------ 53 

5.2.2. Public Port Organization and Operations ------------------------------------- 55 

5.2.3. Tenant Activities ----------------------------------------------------------------- 56 

5.2.4. Profile of a Port Tenant---------------------------------------------------------- 57 

5.3. Historical Trends ------------------------------------------------------------------------ 60 

5.3.1. Port Capital Investments -------------------------------------------------------- 60 

5.3.2. Port Financial Performance ----------------------------------------------------- 61 

5.3.3. Port Employment----------------------------------------------------------------- 65 

5.4. Conclusions ------------------------------------------------------------------------------ 65 

6 Port of Galveston------------------------------------------------------------------------------- 67 

6.1. Port Location and Transportation Links ---------------------------------------------- 67 

6.2. Port Infrastructure ----------------------------------------------------------------------- 68 

6.2.1. Container and Break-bulk Cargo Terminals---------------------------------- 68 

6.2.2. Bulk Cargo Terminals ----------------------------------------------------------- 70 

6.2.3. Industrial Terminals ------------------------------------------------------------- 70 

6.2.4. Cruise Ship Terminals----------------------------------------------------------- 70 

6.3. Offshore Supply Activities and Major Operators ----------------------------------- 71 

6.3.1. Smith-Hamm, Inc. --------------------------------------------------------------- 71 

6.3.2. Cooper Cameron Corp-Deep Flex Division. --------------------------------- 72 

6.3.3. First Wave/Newpark Shipbuilding-Pelican Island, Inc. -------------------- 72 
ix

6.3.4. Edison Chouest Offshore/C Port Galveston LP ------------------------------ 72 

6.4. Development Trends -------------------------------------------------------------------- 74 

 6.4.1. Structural Changes in the Industry--------------------------------------------- 75 

 6.4.2. Analysis of Industry Trends In Louisiana and Texas------------------------ 75 

 6.4.3. Port of Galveston and Industry Trends---------------------------------------- 77 

6.5. Conclusions ------------------------------------------------------------------------------ 78 

References --------------------------------------------------------------------------------------------- 79 

Appendices--------------------------------------------------------------------------------------------- 

Appendix A - Data and Regression Model Output - Port Fourchon--------------------- 81 

Appendix B - Data and Regression Model Output - Port of Morgan City-------------- 95 
xi

LIST OF FIGURES 

Figure Page

1.1. OCS Supply Network – Major Components ----------------------------------------------- 2 

1.2. Model Specifications and Variable Relationships Estimated, Port Fourchon ---------- 3 

1.3. Variable Trends, Port Fourchon-------------------------------------------------------------- 4 

1.4. Variable Trends, Morgan City---------------------------------------------------------------- 7 

1.5. Capital Expenditures, Cumulative Trend (1990-2000), Port of Iberia ------------------ 10 

1.6. Land Leased to OCS Industries (1993, 1999, and 2000), Port of Galveston ----------- 12 

2.1. OCS Supply Network – Major Components ----------------------------------------------- 17 

2.2. Sequence of Intermodal Cargo Transfer at Ports------------------------------------------- 20 

3.1. Cumulative Port Investments on Bulkhead Extensions (1990-2002)-------------------- 23 

3.2. OCS Wells Drilled, Pipeline Miles Approved, and Truck and Barge Traffic Trends - 25 

3.3. Port Tonnage Trends--------------------------------------------------------------------------- 26 

3.4. Monthly Variations for Bulk Cargo (1996-2000 Average) ------------------------------- 27 

3.5. Model Specification and Variable Relationships Estimated------------------------------ 28 

3.6. Truck Traffic, Barge Traffic, and Tonnage Forecasts Using 

Three Alternative Models --------------------------------------------------------------------- 34 

4.1. Self-Propelled and Non Self-Propelled Vessel Trips on the Atchafalaya 

River from Morgan City to the Gulf of Mexico and on Other Louisiana 

Waterways -------------------------------------------------------------------------------------- 45 

4.2. Variable Trends -------------------------------------------------------------------------------- 46 

5.1. Port Layout and Plan Use --------------------------------------------------------------------- 54 

5.2. Functional Zones ------------------------------------------------------------------------------- 55 

5.3. Layout of a Typical Prefabrication Terminal----------------------------------------------- 58 

5.4. Capital Expenditures, Cumulative Trend (1990-2000)------------------------------------ 61 

5.5. Financial Performance Trends (1992-2000) ------------------------------------------------ 63 

5.6. Financial Indicators, Sources, and Uses of Funds (2000)--------------------------------- 64 

6.1. Tonnage by Major Categories (2001) ------------------------------------------------------- 71 

6.2. Port Owned Waterfront Land----------------------------------------------------------------- 75 

6.3. Land Leased to OCS Industries (1993, 1999, and 2000)---------------------------------- 76 
xiii

LIST OF TABLES 

Table Page

1.1. Regression Estimates for Truck Traffic, Inland Barge, and Cargo 

Tonnage, Port Fourchon----------------------------------------------------------------------- 5 

1.2. Major Offshore Oil and Gas Firms, Morgan City------------------------------------------ 6 

1.3. Regression Estimates for Vessel Traffic and Technical Relationships 

Between Different Variables, Morgan City------------------------------------------------- 8 

1.4. Classification of Businesses (1999), Port of Iberia ---------------------------------------- 9 

1.5. Analysis of Lease Operations, Port of Iberia ----------------------------------------------- 10 

1.6. Number Employed in Oil and Gas Industry- Louisiana and Texas 1992-2000 -------- 13

2.1. Major Characteristics of Public and Private Ports ----------------------------------------- 19 

3.1. Data Series on OCS- and Port-Related Variables------------------------------------------ 24 

3.2. Monthly Variations in Cargo Handled (1996-2000 Average) ---------------------------- 26 

3.3. Regression Estimates for Truck Traffic, Barge Traffic, and Port Tonnage------------- 30 

3.4. Technical Relationships Between Variables: Estimated Annual Growth 

Rates for Truck Traffic, Barge Traffic, and Port Tonnage-------------------------------- 32 

3.5. Truck Traffic, Barge Traffic, and Port Tonnage Forecasts Using Three 

Alternative Models----------------------------------------------------------------------------- 33 

3.6. Correlation Matrix for Analysis Variables – Port Fourchon------------------------------ 35 

4.1. Waterways Network and Traffic (2000) ---------------------------------------------------- 38 

4.2. Capital Investment Program (1990-2002) -------------------------------------------------- 39 

4.3. Oil and Gas Industry Related Cargo (1996-2000 Average) ------------------------------ 40 

4.4. Analysis of Revenue Sources (2000) -------------------------------------------------------- 41 

4.5. Major Offshore Oil and Gas Service Firms------------------------------------------------- 41 

4.6. Infrastructure Facilities at Selected Private Sector Shipyards---------------------------- 42 

4.7. Data and Analysis Variables------------------------------------------------------------------ 44 

4.8. Regression Estimates for Vessel Traffic and Technical Relationships 

Between Variables ----------------------------------------------------------------------------- 47 

4.9. Model Forecasts of Vessel Traffic ----------------------------------------------------------- 49 

4.10. Correlation Matrix for Analysis Variables – Morgan City ------------------------------- 50 

5.1. Access Channels and Constraints ------------------------------------------------------------ 52 

5.2. AADT Counts on Highway 90 --------------------------------------------------------------- 53 
xiv

5.3. Analysis of Lease Operations----------------------------------------------------------------- 56 

5.4. Classification of Businesses (1999)---------------------------------------------------------- 57 

5.5. Profile of a Tenant ----------------------------------------------------------------------------- 59 

5.6. Fabrication Building: A New Project-------------------------------------------------------- 60 

5.7. Financial Performance Trends, Selected Years -------------------------------------------- 62 

5.8. Employment by Job Categories -------------------------------------------------------------- 65 

6.1. Analysis of Vessel Traffic on Galveston Ship Channel, 2001---------------------------- 67 

6.2. Port Tonnage (2001) --------------------------------------------------------------------------- 68 

6.3. Classification of Cargo Terminals ----------------------------------------------------------- 69 

6.4. Cooper Cameron Corp-Deep Flex Division Planned Development --------------------- 72 

6.5. Newpark Shipbuilding, Pelican Island Inc., Profile of a Marine 

Repair Facility ---------------------------------------------------------------------------------- 73 

6.6. Edison Chouest Offshore Service Center, Major Stages of Planned Development --- 74 

6.7. Analysis of Long-term Trends in the Oil and Gas Industry in Louisiana 

and Texas, 1992-2000 ------------------------------------------------------------------------- 77 

6.8. Analysis of Long-term Trends in the Oil and Gas Industry for Louisiana 

and Texas, Three-Year Moving Averages, 1992-2000------------------------------------ 78 
xv

ABBREVIATIONS, ACRONYMS, AND SYMBOLS 

AADT Average Daily Traffic 

ac acre 

BNSF Burlington Northern and Santa Fe Railroads 

Chouest Edison Chouest Offshore (ECO)/C Port Galveston, LP 

CPA Central Planning Area 

COE U.S. Army Corps of Engineers 

DOCD Development Operations Coordination Document 

EPA Eastern Planning Area 

EP Exploration Plans 

ft feet 

ft2 square feet 

GIWW Gulf Intracoastal Waterway 

GOM Gulf of Mexico 

GVSR Galveston Railroad, L.C. 

LOOP Louisiana Offshore Oil Port 

LOS Level of Service 

mi miles 

MMS U.S. Minerals Management Service 

OCS Outer Continental Shelf 

PCDP Louisiana Port Construction and Development Priority Program 

POI Port of Iberia 

R-square (R2) Coefficient of Determination 

RO/RO Roll-on/Roll-off Vessels 

UNO University of New Orleans 

UP Union 

V/C Vehicle/Capacity Ratio 

WPA Western Planning Area 
1

1. Executive Summary 

1.1. Ports and the OCS Supply Network 

An effective logistical support system is an important prerequisite for deepwater oil and gas 

exploration and development. In this intermodal transportation system, ports have emerged as 

pivotal activity centers connecting the onshore network with the waterborne offshore segment. 

In addition to cargo handling, ports also serve as industrial sites for large shipyards, equipment 

fabrication and repair, and value-added processing activities for both inputs and outputs of the 

industry. 

1.1.1. Study Approach and Outline 

The major objectives of this study are to define and analyze the nature of port services 

supporting the deepwater oil and gas exploration, and to estimate demand and supply 

adjustments made by both sectors in the 1990’s. For this purpose, a database on port activities 

was developed for four major Outer Continental Shelf (OCS) ports in the Gulf of Mexico 

(GOM): Port Fourchon, Port of Morgan City, and Port of Iberia, Louisiana, and Port of 

Galveston, Texas. Using empirical data, quantitative estimates of supply and demand were 

developed for several port activity variables. Based on the parameter estimates derived from 

econometric models, growth forecasts were made through 2010. 

The report is divided into five sections with an introduction in Chapter 2 and Chapters 3-6 

devoted to analyzing the activities at each of the four ports: Port Fourchon (Chapter 3), Port of 

Morgan City (Chapter 4), Port of Iberia (Chapter 5), and Port of Galveston (Chapter 6). 

1.1.2. Major Components of the System 

The OCS supply network consists of three major components: the inland transportation 

network, the offshore sector, and the port sector (Figure 1.1). The port sector consists of public 

port authorities and private sector service providers jointly operating to deliver the supply needs 

of the industry. 

1.2. Port Fourchon 

Port Fourchon has developed into the largest GOM supply base for offshore oil and gas 

services due to its central location with easy access to the GOM and the availability of port 

infrastructure.. Distinct advantages to the port are its proximity to offshore installations in the 

Central Planning Area (CPA) and Eastern Planning Area (EPA) and its 300-foot (ft) wide 

navigational channel with a 24 ft depth. Since 44 percent of pending exploration plans (EP) have 

indicated Port Fourchon as their supply base, the market share of the port is expected to expand 

with industry growth1

. 

1.2.1. Demand for Port Services 

A database consisting of both port and OCS activity variables was developed to estimate the 

demand for port services generated by the offshore industry. Using data for the period 1992 to 

2001, several regression models were specified to represent the demand for port services (Figure 

1.2). Different variables trends were examined (Figure 1.3) prior to proceeding with the 

empirical analysis. 

 

1 Deepwater Gulf of Mexico 2002: America’s Expanding Frontier. (U.S. Minerals Management Service, 2002) 
2 

and helicopters

Manufacturing:

Modes: Cargo Handling:

Inland barge

Storage

Transfer

Highway

Rail

Air

Shipbuilding

Inland Transport

Sector

Port Sector

Offshore Logistics System

Offshore Secto

Activities:

Equipment Fabrication

Transport of crew

and supplies 

by vessels

Figure 1.1. OCS Supply Network – Major Components. 
3

Independent Variables 

1. Total Number of OCS Wells Drilled 

2. Number of OCS Exploratory Wells Drilled 

3. Number of Pipeline Miles Approved 

↓

Dependent Variables 

1. Number of Trucks South Bound on LA 

HWY 1 

2. Number of Galliano Bridge Openings 

3. Total Tons at Port 

↓

Regression Models 

Model 

Number Independent Variable Dependent Variable 

1.1 Total OCS Wells Drilled Trucks South Bound on LA HWY 1 

1.2 Exploratory Wells Drilled Trucks South Bound on LA HWY 1 

1.3 Pipeline Miles Approved Trucks South Bound on LA HWY 1 

2.1 Total OCS Wells Drilled Galliano Bridge Openings 

2.2 Exploratory Wells Drilled Galliano Bridge Openings 

2.3 Pipeline Miles Approved Galliano Bridge Openings 

3.1 Total OCS Wells Drilled Total Port Tonnage 

3.2 Exploratory Wells Drilled Total Port Tonnage 

3.3 Pipeline Miles Approved Total Port Tonnage 

Figure 1.2. Model Specifications and Variable Relationships Estimated, Port Fourchon. 
4

1.3.b. Barge Traffic & Pipeline Miles

0

200

400

600

800

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

M.Pipelines B.trips(100)

1.3.a. OCS Wells and Truck Traffic

0

50

100

150

200

250

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Wells Total Expl. Wells Truck Trips(1000)

1.3.c. Port Tonnage (million Tons)

0

5

10

15

20

25

30

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Total Fuel/water Gen/Bulk

 Figure 1.3. Variable Trends, Port Fourchon. 
5

1.2.2. Empirical Analysis and Forecasts 

Using regression analysis, the demand relationships for truck traffic, barge traffic, and cargo 

tonnage at Port Fourchon were estimated. While the estimates derived from all nine models 

were statistically significant and consistent, the three models with the highest R-square (R2

) in 

each category are shown in Table 1.1.

Table1.1 

Regression Estimates for Truck Traffic, Inland Barge, and Cargo Tonnage, Port Fourchon 

 Independent Variable Model 

No. 

Intercept Regression 

Coefficient 

 R2 F-Value 

Truck traffic on LA HWY 1 

 Total OCS Wells 1:1 39,817 

(2.39)*

672.8 

(6.40)*

0.8723 40.98*

Inland barge traffic at Galliano Bridge 

OCS Exploratory Wells 2:2 4,142 

(25.75*)

7.78 

(4.61*)

0.7525 21.28*

Port cargo tonnage 

OCS Exploratory Wells 3:2 2.18 

(1.95**)

0.1485 

(11.98*)

0.9472 143.53*

 Statistical significance levels at 5% and 10% are denoted by * and ** respectively.

Truck Traffic South Bound on LA Hwy 1 

During the 1994-2001 period, truck traffic volume on Louisiana Highway 1 (LA Hwy 1 or 

LA HWY 1) at Port Fourchon increased from approximately 87,000 trips per (/) year (yr) to over 

211,000 trips/yr indicating an annual growth rate of 13.5 percent. According to the empirical 

analysis, the demand relationship between truck traffic and all categories of OCS wells drilled is 

positive, and is estimated to increase by 673 trips for every additional well drilled (Regression 

Model 1:1, Table 1.1). Estimated truck traffic is projected to grow at an annual rate of 6 percent 

through 2010. At this rate, truck traffic volume in 2010 is estimated at 353,333 trips, an increase 

in 2001 traffic by 67 percent. Although the current pace of 13.5 percent growth associated with 

the initial phase of development tapers off over time a sustained annual rate of 6 percent will 

lead to capacity problems unless the necessary expansions are planned ahead of time. 

Barge Traffic at Galliano Bridge 

Inland barge traffic grew at a more modest rate of 4 percent a year during the period 1993-

2001. Of the three models specified to estimate barge traffic, Regression Model 2.3, with the 

number of pipeline miles approved as the independent variable, provided statistically significant 

parameter estimates. Because of the time lag between the approval and implementation of 

pipeline projects, a two year lag variable was used in the model. For every mile of pipeline 

added, barge traffic is estimated to increase by three additional trips. Therefore, barge traffic is 

forecasted to increase from 5,717 trips/yr in 2001 to 7,129 trips/yr in 2010, an overall increase of 

25 percent for the period with an annual growth of 2-3 percent. 
6

Port Tonnage 

Cargo tonnage at the port grew from 3.9 million tons/yr to 27.2 million tons/yr between 1992 

and 2001, an increase of 24 percent a year. Regression Model 3:2 with the number of OCS 

exploratory wells drilled as the independent variable provided the ‘best-fit’ model for cargo 

tonnage with an R2 value of 0.95. The model estimates that for every exploratory well drilled, 

148,500 tons of cargo is generated at the port. The 2010 port tonnage estimate is 50.8 million 

tons. This equates to an annual growth rate of 7-8 percent with an overall doubling of the current 

tonnage volumes. 

1.3. Port of Morgan City 

Morgan City is an important onshore supply base currently serving several deepwater oil and 

gas installations. Morgan City’s supply services are distinct from Port Fourchon’s in several 

ways: 

• Shipbuilding and repair activities at Morgan City are much more significant to 

the OCS logistics system, 

• The public port plays a low-key role; OCS activities are mostly private sector 

operations, and 

• The location of Morgan City, at the intersection of several major waterways, 

is an advantage. 

1.3.1. Profiles of Major Operators 

Table 1.2 shows the number of employees and the sales volumes of major firms 

engaged in offshore services at Morgan City. The magnitude of these numbers illustrates 

the significance of offshore operations at the port. 

Table 1.2 

Major Offshore Oil and Gas Service Firms, Morgan City 

Name of Firm Number 

Employed 

Annual Sales 

($millions) 

Activity 

Bollinger Marine Fabricators 400 25-100 Shipbuilding & repair 

Cameron Corporation 268 10-25 Oil & gas field machinery 

Conrad Industries, Inc. 200 15 Boat building & repair 

Mc Dermott, Inc. 2,000 100-500 Oil & gas Field machinery 

Superior Fabricators, Inc. 110 14 Structural metal fabricated 

Swiftships Shipbuilders, LLC 245 40 Boat building & repair 

Twin Bros. Marine Corp. 240 N/A Shipbuilding & repair 

1.3.2. Demand for Port Services 

Several factors make it difficult to analyze the demand for port services at Morgan City. 

First, a database of port activities, like at Port Fourchon, is not available. Because of the 

proprietary nature of private sector operations at Morgan City, it is difficult to develop an 
7

adequate database for analysis. Second, the market share of port services at Morgan City is 

relatively low; therefore, models may not adequately reflect industry-wide changes at a macro 

level. Third, since the shipbuilding and repair services cater to a diversified set of domestic and 

foreign clients, it is more difficult to delineate the effects of the OCS oil and gas industry. 

1.3.3. Empirical Analysis and Forecasts 

Morgan City’s main access channel is the Atchafalaya River which provides the vital link for 

the delivery of offshore supply services to the GOM. Therefore, vessel traffic is hypothesized to 

represent the level of port services for Morgan City. The number of non self-propelled vessel 

trips is used as the dependent variable in the regression models estimating the demand for port 

services. The oil and gas industry variables are similar to those defined for Port Fourchon. The 

trends of the industry variables and the port activity variables are shown in Figure 1.4. 

1.4.a. Industry Variables

0

100

200

300

400

500

600

700

800

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Expl. Total Pipeliine EP

1.4.b. Port Activity Variables, Vessel Trips

0

5000

10000

15000

20000

25000

30000

35000

40000

1992 1993 1994 1995 1996 1997 1998 1999 2000

Self-prop Non SP Total

 

 Figure 1.4. Variables Trends, Morgan City. 
8

Variable Relationships between the Number of OCS Wells Drilled and Vessel Traffic 

Four regression models were specified for the Port of Morgan City. The three models using 

different categories of OCS wells (development, exploratory, and total) as the explanatory 

variable provided statistically significant parameter estimates and high F-values (Table 1.3.). 

The models with the independent variables number of OCS development wells drilled 

(Regression Model 4.1) and total number of OCS wells drilled (Regression Model 4.3) explain 

more than 80 percent of the variations in non self-propelled vessel traffic trips. Surprisingly, the 

variable number of OCS development wells drilled, which provided the “best fit” model for 

Morgan City, was dropped as a variable in the Port Fourchon analysis. The results indicated that 

for every development well and exploratory well drilled on the OCS, the number of non selfpropelled vessel trips to Morgan City increase by 40 and 13, respectively. The corresponding 

number of vessel trips for the total number of wells is 12. 

Table 1.3 

Regression Estimates for Vessel Traffic and Technical Relationships 

Between Different Variables, Morgan City 

Independent Variable1/ Model 

No. 

Intercept Regression 

Coefficient 

R2 FValue 

Number of development wells-drilled 4.1 1129.5 

(3.02)*

39.9 

(6.0)* 

0.8371 35.97

Number of exploratory wells drilled 4.2 2364.0 

(7.28)*

13.40 

(3.36)* 

0.6181 11.33

Total number of wells drilled 4.3 1796.0 

(6.21)*

12.21 

(5.64)* 

0.8195 31.77

Miles of pipeline approved (lagged by 

one year) 

4.4 2544.4 

(5.72)*

3.29 

(2.21)** 

0.4501 4.91

1/ The dependent variable for all regressions is number of non self-propelled vessel trips. 

Statistical significance levels at 5% and 10% are denoted by * and ** respectively. Numbers in 

parentheses are t-values. 

Port Activity Forecasts 

The vessel trip forecasts were developed through 2010 following procedures similar to those 

described in Chapter 3 for Port Fourchon. The forecasts from regression models were compared 

with the forecasts of vessel trips derived from linear trend extrapolation. The projections derived 

from models were lower than the trend. For example, while the trend indicated 6,900 vessel trips 

in 2010 with an annual growth rate of 5 percent, the median forecast derived from using 

exploratory variables in the model was approximately 4.5 percent. 

1.4. Port of Iberia 

The Port of Iberia is located along the Commercial Canal approximately 7.5 miles (mi) north 

of the Gulf Intracoastal Waterway (GIWW), 9 mi north of Weeks Bay on the GOM, and 4.5 mi 

southwest of the city of New Iberia. The location and configuration of the Port of Iberia are 

strongly influenced by OCS supply activities; the port specializes in platform fabrication, repair, 

and maintenance. 
9

1.4.1. Demand for Port Services 

A large number of small-scale operators provide a variety of OCS services based at the 

public port. Because of the variety of operations, an appropriate time-series database including 

the major developments is not available for analysis. However, the demand generated by OCS 

activities and its effects on the Port of Iberia are clearly evident from a qualitative analysis of the 

following developments at the port: 

• number of OCS service providers, 

• infrastructure expansion and investment, 

• demand for facilities, 

• activities of tenants, and 

• financial performance. 

Number of OCS Service Providers at the Port 

A survey conducted in 1999 indicates that 70.6 percent of the businesses in the Port of Iberia 

area are in some form connected to the offshore supply industry (Table 1.4).

Table 1.4 

Classification of Businesses (1999), Port of Iberia 

Industry Number of 

Business Units 

Percent of the 

Sample 

The offshore supply industries: 

 Fabrication 20 19.6 

 Repair Services 9 8.8 

 Other offshore services 43 42.2 

Total offshore 72 70.6 

Other Industries 30 29.4 

Grand Total 102 100 

Port Infrastructure Investment 

In the 1990’s, the Port of Iberia followed a systematic program to upgrade its facilities due to 

the demand pressures for port services. These upgrades include: 

1. Projects to provide basic port infrastructure and amenities (early 1990’s) - the 

development of a wastewater collection system, sanitary sewer collection, potable 

water system, etc., 

2. Port expansion projects (mid 1990’s) - the development of a slip in a 170-acre 

(ac) lot was undertaken in 1995, and 
10

3. Port improvement projects with public and private sector cost sharing (late 

1990’s) - improvements at the terminal such as building bulkheads, warehouses, 

etc. and sharing the costs with tenants. 

Figure 1.5 shows capital expenditures at the port under the Louisiana Port Priority Program 

during the 1990-2000 period. 

 Figure 1.5. Capital Expenditures, Cumulative Trend (1990-2000), Port of Iberia. 

Demand for Port Facilities 

An analysis of the port’s lease information indicates that 279 ac of waterfront property is 

leased to 47 tenants (Table 1.5). With 55 percent of the land leased beyond 2005, the port is 

assured of a stable revenue stream for the next 10-15 years. 

Table 1.5 

Analysis of Lease Operations, Port of Iberia 

Lease Period No. of Leases Waterfront 

Acreage 

Average Size 

(Acres) 

Percent of Total 

Leased Acreage 

2000-2005 31 123.6 4.0 44.3 

2006-2010 12 96.7 8.1 34.7 

2011-2020 4 58.6 14.7 21.0 

Total 47 278.9 5.9 100 

 Source: Port of Iberia, Master Development Plan, 2000. 

Port of Iberia, Project Investments

0

2000

4000

6000

8000

10000

90 91 92 93 94 95 96 97 98 99 00

($1000)

Investments
11

Financial Performance of the Port 

Key financial indicators for the 1992 to 2000 period indicate favorable growth. While the 

port’s operating revenues increased 205 percent, operating expenses increased by only 35 

percent leading to a 170 percent increase in net income. Total assets of the port grew by more 

than 125 percent during this period. 

1.5. Port of Galveston

The Port of Galveston is located on Galveston Bay 9.3 mi inland from the GOM. Galveston 

public port facilities are strategically located providing easy access to the GOM and the inland 

waterways network through GIWW. The Galveston Ship Channel serves as the main access 

channel to the port. It is maintained at a 40 ft depth and 1,200 ft width. Estimated sailing time 

from open sea to the public docks, located 9.3 mi on the Ship Channel, is approximately 30 

minutes. In addition, the large industrial and commercial hub around the Houston Ship Channel 

to the west, serves as a great asset in providing specialized technical services. 

1.5.1. Offshore Service Activities and Major Operators 

Four major offshore service providers operate from the Port of Galveston: 

1. Edison Chouest Offshore (ECO)/C Port Galveston, LP, at Edison Chouest 

Offshore Service Center 

2. Pier 34 Manufacturing Facility operated by Cooper-Cameron Corp-Deep Flex 

Division, 

3. Marine Repair Facility at Pier 14, operated by Smith-Hamm, Inc. and 

4. Pelican Island Marine Repair Facility operated by First Wave/Newpark 

Shipbuilding-Pelican Island, Inc. 

In April 2000, the Port of Galveston entered into a lease agreement with Edison Chouest for 

the development of an offshore multi-service terminal. The 100-ac site, located on Pelican 

Island, is an indication of the increase in demand for offshore services in the Western Planning 

Area (WPA). Edison Chouest plans to develop a multi-service facility known as C Port 

Galveston. 

The port signed a five-year lease agreement with Cooper-Cameron Corporation in March 

1999 for Pier 34. The pier’s main facility is a terminal with a water depth of 40 ft and 44,500 

square ft (ft2

) of covered space. The firm specializes in the manufacture of flexible pipes for the 

offshore oil and gas industry. 

Marine Repair Facility at Pier 14, operated by Smith-Hamm, Inc., is engaged in the repair 

and maintenance of vessels and offshore rigs. Major infrastructure at the pier includes a 1,500-ft 

dock with a minimum water depth of 24 ft, and a staging area of 35,000 ft2

. In 1999, the 

company expanded its operations by leasing six additional acres. 

First Wave/Newpark Shipbuilding-Pelican Island, Inc. operates Pelican Island Marine Repair 

Facility, a 110-ac vessel repair and maintenance facility. The company operates a network of 

five yards offering repair and maintenance services, new construction, and environmental 

services. 
12

1.5.2. Growth Trends in OCS Services 

Port-owned waterfront land increased from about 299 ac in 1965 to approximately 850 ac in 

2000, almost tripling the size of the port. The recent additions of land have been leased mostly 

by offshore service providers. As a result of the above developments, port tenants serving the 

offshore industry have increased their share of port-owned land by 23 percent (27% in 2000 v. 

4% in 1993) over the last seven years (Figure 1.6). 

1.6.a. Land Leases, 1993

4%

96%

1.6.c. Land Leases, 2000

27%

73%

OCS Leases Other Leases

1.6.b. Land Leases 1999

15%

85%

Figure 1.6. Land Leased to OCS Industries (1993, 1999, and 2000), 

Port of Galveston. 
13

The development trends of OCS activities at the Port of Galveston clearly indicate the market 

adjustments made by the service providers. Overall, the OCS service sector at the Port of 

Galveston has expanded its capacity during the last decade and is poised to serve the increasing 

demand for services in the WPA. However, the development plans identified by Edison Chouest 

and Cooper-Cameron Corporation for industry expansion are behind schedule with no substantial 

progress as originally envisaged. 

1.5.3. Long-term Industry Adjustments 

Several macroeconomic indicators were analyzed examine whether the slow development of 

OCS activities at the port are due to long-term structural changes in the industry. A trend 

analysis of state personal incomes in Texas and Louisiana indicated that the state economies 

grew at 4.5 percent/yr in Louisiana and by 7.2 percent in Texas (Table 1.6). However, during 

this period of positive economic growth for both states, the numbers employed in the oil and gas 

industry in Texas declined by 3,600persons/yr, while Louisiana registered a modest increase of 

300 persons/yr. These macroeconomic conditions may partially explain the slow development of 

offshore activities at the Port of Galveston. 

Table 1.6 

Number Employed in Oil and Gas Industry – Louisiana and Texas, 1992-2000 

Annual Growth Rate 1992-2000 Louisiana Texas 

 (percent/yr) 

Number Employed in Oil and Gas Industry 0.3 -3.6

State Personal Income 4.5 7.2

 Source: U.S. Bureau of Labor Statistics (Website: http://www.bls.gov). 

1.6. Conclusions 

The offshore service activities performed at four GOM ports are examined in this report. 

Increased demand for port services associated with the rapid expansion of OCS activities in the 

1990’s is evident from the adjustments made by the individual ports. Given that these trends are 

projected to continue, public infrastructure planning to accommodate OCS growth will be a 

priority at these ports. 
15

2. Ports and the OCS Supply Network 

2.1. Introduction 

An effective logistical support system linking offshore installations with onshore supply 

bases is vital for deepwater oil and gas exploration. The OCS supply network operates as an 

intermodal transportation system, coordinating the movement of goods and services from landbased transportation modes to offshore. In this system, ports have emerged as important supply 

bases connecting the onshore network with the waterborne offshore segment. In addition to 

cargo handling, ports also serve as industrial sites for large shipyards, equipment fabrication and 

repair, and value-added processing activities for both inputs and outputs of the industry. 

Furthermore, public port authorities effectively serve the offshore oil and gas industry in two 

other important areas. Ports play a leading role in influencing the community’s and the 

industry’s use of infrastructure at the port. The acceptance gained by public port authorities as 

non-profit agencies engaged in economic development assists in shaping community attitudes in 

favor of the oil and gas industry. As the rapid expansion of OCS activities has imposed 

pressures on limited public facilities at some ports, this issue is vital to the industry. 

Public ports, acting as a conduit for inflows of low-cost public capital, provide an element of 

subsidy to the oil and gas industry. The port infrastructure, financed from federal and state 

grants and local taxes, are leased to OCS service providers below market costs. 

2.2. Study Approach and Outline 

The main focus of this study is to 1) analyze and define the nature of port services supporting 

deepwater oil and gas exploration, and 2) estimate demand and supply adjustments of the 

industry in the 1990’s with the opening up of OCS areas for oil and gas exploration. For this 

purpose, a database on port activities was developed for four major ports in the GOM (Port 

Fourchon, Port of Morgan City, and Port of Iberia, Louisiana, and Port of Galveston, Texas), 

incorporating data on historical growth, physical facilities, capacity constraints, investment 

activities, etc. Using empirical data, supply and demand estimates were developed for several 

port activity variables. Based on the parameter estimates derived from the econometric models, 

growth forecasts were made through 2010. The information derived from these models may 

assist ports in their planning and investment decisions. 

Empirical estimates could not be developed for some ports (Port of Iberia and Port of 

Galveston) because of data constraints. In these cases, information on port operations, 

infrastructure expansion trends, and financial performance were analyzed to make qualitative 

growth assessments. To provide detailed insights on individual operations, several case studies 

of private sector investment plans and operations were also included. 

The Data - The data used throughout this report can be divided into two categories as 

offshore oil and gas industry data and data specific to each port. 

Time-series data on industry variables - Time-series data on several industry activity 

variables for 1992-2001-period are used in the study. (1) The number of deepwater wells drilled 

in the GOM is used as a proxy for offshore industry expansion. The number of wells are further 

categorized into three as exploratory wells drilled (wells drilled for exploration), the number of 

development wells drilled (subset of exploratory wells identified for development and 
16

production), and the total number of wells (sum of exploratory and development wells). (2) The 

number of pipeline miles approved as additions to the existing offshore pipeline network is also 

used as an industry variable since it generates large cargo volumes. (3) In addition to the above, 

the number of Exploration Plans (EP) and the number of Development Operations Coordination 

Document (DOCD) filed by the industry (filing these two documents projecting deepwater 

activity levels is a statutory requirement) were also used in the empirical models for Morgan 

City. In estimating demand for port infrastructure these variables are used as exogenous 

variables hypothesizing a positive relationship between the two variables. 

Data on individual ports - In estimating the demand for infrastructure facilities at Port 

Fourchon, port tonnage, truck traffic volumes on LA Hwy 1 – the main access road to the port, 

and barge traffic on Bayou Lafourche, the main barge route to the port are used as dependent 

variables. Similarly, the data on non-self-propelled vessel traffic on the Atchafalaya River from 

Morgan City to GOM are used for the Port of Morgan City. The activity levels at the Ports of 

Iberia and Galveston are defined on a qualitative basis estimated based on the financial 

performance data and on the basis of leasing rates of port property to offshore oil and gas service 

providers. The models specified and the empirical results derived are evaluated for each port in 

Chapter 3 to Chapter 6. 

Extraneous information developed on different variables is an important source in 

interpreting the quantitative estimates derived from demand models. The information may be on 

technical relationships (e.g., exploratory wells drilled vs. the total number of wells drilled), longterm changes in structural relationships (technological developments in deepwater exploration) 

or significant public policy shifts (e.g., OCS Deepwater Royalty Act of 1995). 

Similarly, an understanding of port procedures will be useful for correct interpretation of 

model results. For example, at “conventional” ports where intermodal cargo transfer is the main 

activity, the total revenue tonnage handled or its derivatives such as tonnage per gang-hour, 

crane moves per hour, etc., are used to compare port productivity for facility planning and for 

performance evaluation. As only revenue tonnage is included, the basic objective is to maximize 

the throughput while minimizing dwell time and intermediary operations. The total tonnage at 

offshore service ports is not tied to port revenue, and there is an element of storage for inventory 

control and lot consolidation in delivering supplies. This characteristic is more in line with the 

practices at an industrial plant. Nevertheless, consistent time-series data is a good, overall 

indicator to compare port activity levels. 

The report is divided into five sections. Chapter 2 is an introduction to the supply network 

defining the major components of the system and the institutional characteristics of the public 

and private port system. Chapters 3-6 examine the nature of port services provided by the four 

ports selected for the study: Port Fourchon (Chapter 3), a major supply base for the industry 

providing a full range of services; the Port of Morgan City (Chapter 4), a location for large scale 

shipbuilding and repair services; the Port of Iberia (Chapter 5), distinct for its specialization in 

manufacturing prefabricated structures; and the Port of Galveston (Chapter 6), which operates as 

a service base for the WPA and international services 

2.3. Major Components of the System 

The major components of the offshore logistics system and the activities performed at each 

stage are illustrated in Figure 2.1. As shown in the figure, the port sector is only a part of the 

overall OCS logistics system; the inland transport and offshore sectors complete the system. The 
17 

and helicopters

Manufacturing:

Modes: Cargo Handling:

Inland barge

Storage

Transfer

Highway

Rail

Air

Shipbuilding

Inland Transport

Sector

Port Sector

Offshore Logistics System

Offshore Secto

Activities:

Equipment Fabrication

Transport of crew

and supplies 

by vessels

Figure 2.1. OCS Supply Network – Major Components. 
18

overall offshore logistics system is complex, involving concepts of efficiency and productivity, 

inventory control, pricing, supply reliability and quality, etc. The main focus of this analysis, 

though, is the transportation aspects and the process of the physical movement of goods and 

services. 

2.3.1. Inland Transport Sector 

The inland transportation system consists of highways, railroads, and waterways. Trucking 

is the predominant mode of inland transport for supplies and pipelines for delivery of crude. 

2.3.2. Offshore Sector 

The vessel fleet serving the offshore sector consists of a variety of specialized vessels 

(anchor handling tugs, cable laying vessels, supply vessels, construction vessels, dredgers, 

floating storage units, shuttle tankers, mobile drilling units, mobile production systems, remotely 

operated vessels, standby and rescue vessels, survey vessels, and tugs). The large number of 

specialized offshore vessels requires berthing areas and repair and maintenance services at the 

port. The importance of the offshore sector is enhanced because of the large scale shipbuilding 

and repair industry. 

2.3.3. Port Sector 

A wide variety of OCS supply services are performed at ports ranging from the intermodal 

transfer of cargo to the fabrication, repair, and maintenance of rigs and vessels. In addition, 

value-added activities transpire. 

Organizational Setup of the Port Sector 

The organizational set up of the port network is a combination of public and private sector 

partnerships. The public sector ports play a pivotal role in the system by planning, constructing, 

and leasing public port facilities to the private sector. Differences in pricing policies and 

operating practices by public ports and private operators have industry-wide implications. 

Public Port System 

Public port authorities are political subdivisions of the State. They are managed by a board 

of port commissioners that are either elected or appointed to serve, usually without remuneration. 

Generally, port commissioners are from the local community. The organizational set-up of most 

of the ports reflects a desire to maintain local autonomy in business and planning decisions. 

The missions and goals of public ports are to trigger economic growth and development in 

the local community by creating jobs and incomes, by attracting new industries, and by 

expanding existing industries. Predominant in their plans is the diversification of the local 

economy and community development, mainly through fuller utilization of local resources. As a 

result, the layout and facilities at most public ports resemble an industrial park as opposed to a 

traditional cargo handling port which encompasses storage, transfer, and transportation activities. 

The principal role of public ports is to function as a ‘landlord’ by providing port facilities to 

private operators in order to generate economic activity in the community. Public ports play a 

dual role in the system, both as competitors and partners with the private sector enterprises. The 

major differences between public ports and private operators are summarized in Table 2.1.
19

Table 2.1 

Major Characteristics of Public and Private Ports 

Characteristics Public Ports Private Operators 

Ownership and Management Public ownership; Managed 

by an appointed or elected 

Port Commission. 

Private ownership; The size of 

firm varies from large multinational corporations to small 

businesses. 

Mission and Goals Multi-faceted public goals; 

Economic development, job 

creation and diversification of 

the local economy. 

Business promotion motivated 

by profit. 

Financing Methods Grants from federal, state and 

local govt. agencies and selfgenerated funds. 

Private capital 

Operating Practices “Landlord Ports”; Owns and 

leases basic facilities to 

private sector tenants. 

Owns and operates, generally 

specializes in one service 

Performance Indicators Financial viability; volume of 

activities in terms of jobs 

created and economic 

development. 

Financial profitability. 

The partnership role of public port with the private sector involves the planning, 

constructing, and leasing of basic port infrastructure. By taking the initiative to invest in highrisk port expansion projects with long gestation periods, public ports limit the risk exposure of 

private firms. The tenants at public ports lease the facilities at subsidized rates and are exempt 

from paying local property taxes. Therefore, public port facilities provide an element of subsidy 

to the offshore logistics industry. 

Offshore Service Ports – Operational Characteristics 

The schematic presentation included in Figure 2.2 illustrate the typical cargo handling stages 

at a conventional port. Several significant differences at each stage are observed for an offshore 

service port: 

1. Placing trucks for unloading - At offshore service ports, terminals are leased to 

different tenants engaged in specialized services. The importance of cargo transfer 

depends on the nature of tenant’s activity, i.e., cargo transfer may be very critical 

for a supplier of barite but not to an operator of survey vessels. At conventional 

ports, all terminal operators are engaged in cargo transfer activities and 

throughput volumes is a general measure of terminal productivity. 

2. Moving to Warehouse from Trucks - –At a conventional port this will be 

associated with exports, and again, throughput is a critical component. In 
20

contrast, at offshore service ports this may be safety inventories that may be in 

storage for longer periods. 

3. Warehousing and storage - While conventional ports attempt to maximize 

throughput, the functions at an offshore terminal are akin to that of an industrial 

plant where uninterrupted input supply and inventory control are the major 

concerns. 

4. Product fabrication and consolidation in the staging area - The major logistical 

activities at offshore port service terminals are fabrication and assembly of 

equipment, storage, and consolidation of shipments. The nature of activities in 

this area will depend on offshore requirements in exploration, development, and 

production etc. At conventional ports the staging area is for loading and 

unloading of vessels. 

5. Stowage in vessel - Transporting goods (personnel and cargo) offshore by either 

air or water is an important element of the logistical system. Common cargo 

items include food and provisions, water for drinking, water for industrial use, 

drilling mud, lubricants and fluids, waste disposal, and turbines and other 

instrumentation. This stage is more or less similar to both types of ports. 

Coastal ports play a pivotal role in the OCS intermodal transportation system as service bases 

coordinating onshore and offshore segments. They provide land at the waterfront and invest in 

high-risk port projects in which the private sector may not be willing to invest. The public port 

system, with its roots in the local community, has made substantial contributions to the efficient 

and smooth functioning of the OCS logistical supply network. 

 Figure 2.2. Sequence of Intermodal Cargo Transfer at Ports. 

Step 5 Step 4 Step 3: Step 2: Step 1:

Stowage in Product fabrication and lot Warehousing Moving Placing trucks

vessel consolidation in the staging area and storage to warehouse for unloading
21

3. Port Fourchon 

Port Fourchon is as the largest supply base operating in the GOM. It provides logistical 

support to the offshore oil and gas industry in the WPA, CPA, and EPA. The major factors 

favoring the Port are its central location on the GOM and the availability of first-rate public port 

facilities which are operated by more than 70 private sector service providers. Port Fourchon is 

also the homeport for the Louisiana Offshore Oil Terminal (LOOP), a terminal equipped to 

handle 1.2 million barrels of crude oil a day and responsible for about 13 percent of the nation’s 

oil imports. . According to pending EP’s, OCS operators have designated Port Fourchon as the 

service base for 44 percent of planned deepwater projects2

 (MMS, 2002). This implies that Port 

Fourchon’s significant market share of OCS service activities will continue in the future. 

3.1. Framework for Analysis

This chapter estimates the demand for port services generated by the OCS oil and gas 

industry supply network at Port Fourchon. It includes the following sections: 

• Analysis of current port activities, historical trends, and relationships; 

• Identification of databases and definition of variables; 

• Empirical demand analysis for port services and forecasts; and 

• Implications to public port policy planning for infrastructure. 

3.2. Port Infrastructure and Operations 

3.2.1. Location and Transportation Links 

Port Fourchon is located on Bayou Lafourche in Louisiana. The main access channel from 

the Port to the GOM is Belle Pass and Bayou Lafourche. The developed area of the port is 

connected to the Gulf by the inshore channel in Belle Pass and Bayou Lafourche with a depth of 

24 feet and a bottom width of 300 feet. The distance from the port to the Gulf (mile 0.0) is 3.4 

miles and it extends another 1.3 miles maintaining -26 feet at the entrance to the Gulf. The 

channel is maintained by the U.S. Army Corp of Engineers. On the landside, the Port is linked to 

the inland waterway network through Bayou Lafourche. 

The Port is connected to the State’s main highway network through a two-mile segment on 

LA Hwy 3090 that runs from the port to LA Hwy 1, and a 40-mi segment on LA Hwy 1 to US 

Hwy 90. Excessive roadway flooding, older two-lane mechanical lift-span bridge at Leesville, 

two-lane undivided roadway are identified as the major constraints resulting in congestion, delay, 

incidents and excessive travel times on this segment of the highway. Among the major 

improvements planned are to construct a two or four-lane elevated highway structure from 

Fourchon to Golden Meadow, construct a four-lane fixed span bridge over the Gulf Intracoastal 

Waterway and Bayou Lafourche at Larose, and widen and upgrade LA Hwy 1 from Grand Isle to 

Fourchon. 

The cost of above improvements were estimated to be about $929.6 million in 19993

, and 

several methods of financing from local, state and federal sources as well as user-tolls are under 

consideration. 

 

2 Deepwater Gulf of Mexico 2002: America’s Expanding Frontier, (MMS, 2002) 3 Preliminary Implementation Plan for the OCS Intermodal Corridor, (URS Grenier Clyde, 1999). 
22

3.2.2. Port Infrastructure

In addition to OCS activities, Port Fourchon serves as an important location for outdoor 

recreation such as recreational fishing and commercial fishing and boating. Several companies 

that serve the fishing industry, repairing and maintaining yachts and boats are located at the port. 

Recreational vessel traffic on the Bayou Lafourche and Bell Pass waterways are high during 

summer and weekends. 

Port Facilities - Infrastructure at the Port consists of three major components. The basic port 

facilities, such as waterfront land, access slips, and bulkheads, are built by the public port and 

leased to private operators. Cranes, fork-loaders, storage tanks, and transit sheds necessary for 

individual operations are supplied by the private sector tenants. Service vessels which carry 

supplies and crew offshore are also private sector operations. Various degrees of vertical 

integration, though, are evident in delivering services (i.e., vessel operators controlling supplies 

and other types of functional coordination). 

The Greater Lafourche Port Commission has made significant investments to expand public 

port facilities during the last 12 years. Under the Louisiana Port Construction and Development 

Priority Program (PCDP), more than $49 million have been invested to construct a 17,000 linearft bulkhead and improve 300 ac of additional waterfront land (Figure 3.1). 

A 1999 survey, conducted by the port identified the following port facilities: 

• 283 berths, extending 34,282 linear ft in length; 

• 56 warehouses; 

• 652 storage tanks; and 

• 433 ac of leased waterfront land. 

While the berths and waterfront land are public facilities, the warehouses and storage tanks are 

built and owned by private operators. 

Demand for port facilities is strong despite a pricing policy to increase lease rental rates by 5 

percent each year by the Port. According to Port records, tenants have made commitments two 

to three years in advance for the facilities that are currently under construction. As a result of 

increased activities and higher rental rates, Port operating revenues increased by 82 percent in 

four years, from $3.38 million in 1996 to $6.16 million in 2000. 

All indications are that the port infrastructure facilities are currently in short supply. An 

aggressive investment plan to expand port facilities may be necessary to accommodate the 

anticipated growth in OCS oil and gas logistics services. The Port has acquired 1,700 acres to the 

north along the Floatation Canal for development. However, since these areas around the port 

are designated wetlands, the port has to incur additional costs for wetland mitigation. 

3.3 Data and Definition of Variables 

Time-series data available for analysis is limited; OCS oil and gas exploration activities, in 

its present form, started in the early 1990’s. The industry also went through a rapid 

transformation in the 1990’s which created structural changes in variable relationships. 

Changing government policies, developments in deepwater exploration technologies, and 

mergers among the majors contributed to these changes. Structural change problems in timeseries data tend to make the data series discontinuous and referring virtually to different 

populations. Significant changes have to be expected, though, in an industry where deepwater
23

Project Investments

0

10000

20000

30000

40000

50000

60000

90 91 92 93 94 95 96 97 98 99 00 01

($1,000)

Investment

Bulkhead Constructed

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

90 91 92 93 94 95 96 97 98 99 00 01

(Linear Feet)

Bulkhead

 Figure 3.1. Cumulative Port Investments on Bulkhead Extensions (1990-2000). 

oil production rose over 800 percent and deepwater gas production increased about 1,500 percent 

from 1992 to 2001. Similarly, by improving system efficiencies, the lag from leasing to 

production for deepwater fields has been reduced from 6.68 years in 1990 to 1.72 years in 2001. 

The data used in estimating the demand for port services at Port Fourchon is included in 

Table 3.1. While columns 1 through 4 represent OCS variables, columns 5 through 10 represent 

Port activity variables. Since the changes made in the method of categorizing the time-series 

data is not consistent over time, the data on development wells drilled (MMS, 2002; p. 50) is not 

used in the analysis. The oil and gas industry variables selected (the number of OCS wells 

drilled and the miles of planned oil and gas pipelines) are considered to be directly related to 

supply logistics and relevant to estimate the market demand for port services. 

The total tonnage handled at the port, truck traffic counts on the main port access road (LA Hwy 

1), and the barge traffic volumes on the main inland channel (Bayou Lafourche) are selected as 

variables indicating port activity-levels. While the three variables are somewhat related to each 
24

other, the analysis of traffic and growth relationships and tonnage will provide unique 

information useful for infrastructure planning decisions. Improved port access is thought to be 

particularly important for OCS service ports that are located away from large urban centers. 

Table 3.1 

Data Series on OCS- and Port-Related Variables 

Number of OCS 

Wells Drilled 

New 

Pipeline 

Trucks 

on LA 

Hwy 1 

South 

Galliano 

Bridge 

Fuel Water Bulk 

/Gen 

Total 

Year Dev. 

Well 

(1) 

Expl. 

Wells 

(2) 

Total 

(3) 

Miles 

(4) 

# Trips 

/Year 

(5) 

# of 

Openings 

(6) 

Mil. 

Tons 

(7) 

Mil. 

Tons 

(8) 

Mil. 

Tons 

(9) 

Mil. 

Tons 

(10) 

1992 27 7 34 76   **  ** ** 3.900 

1993 29 12 41 52 ** 4,188   **  4.900 

1994 37 28 65 193 87,235 4,383 **   6.800 

1995 51 34 85 139 98,550 4,492 **  ** ** 7.300 

1996 71 42 113 329 116,435 4,599 0.453 2.261 6.278 8.992 

1997 88 84 172 285 144,175 4,623 0.219 2.040 8.827 11.086 

1998 57 112 169 450 146,365 5,089 0.511 2.511 12.989 16.011 

1999 49 123 172 512 151,110 4,643 0.510 3.740 15.521 19.501 

2000 67 146 213 241 168,630 5,218 0.693 3.527 20.992 25.212 

2001 60 148 208 711 211,335 5,717 0.882 3.856 22.738 27.207 

Notes on data sources: 

1. Data in columns 1, 2, 3, and 4 are from Deepwater Gulf of Mexico 2002: America’s Expanding 

Frontier (MMS, 2002). 

2. Data in columns 5 to 10 are from the databases maintained by the Greater Lafourche Port 

Commission. 

3.3.1. Historical Trends 

An analysis of historical trends and the nature of variable relationships included in Table 3.1 

are appropriate before the empirical demand analysis. 

Truck Traffic Trends 

The trends of truck traffic with the number of OCS wells drilled and with the miles of 

pipeline approved for the period 1992 to 2001 are illustrated in Figure 3.2a. While the trend 

lines for the total number of wells drilled and truck traffic closely follow each other, the pipeline 

approvals as presented indicate wide annual variations. However, the trend lines for the 

variables indicate similar growth patterns.

Barge Traffic Trends 

The barge traffic trends are compared with the oil and gas industry variables in Figure 3.2b. 
25

3.2.a. OCS Wells and Truck Traffic

0

50

100

150

200

250

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Wells Total Expl. Wells Truck Trips(1000)

3.2.b. Barge Traffic & Pipeline Miles

0

100

200

300

400

500

600

700

800

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

M.Pipelines B.trips(100)

Figure 3.2. OCS Wells Drilled, Pipeline Miles Approved, and 

Truck, and Barge Traffic Trends. 

Port Tonnage Trends and Seasonal Variations 

As mentioned earlier, port tonnage is an important indicator useful for comparing port 

performance and for infrastructure planning. The cargo-handling trend for Port Fourchon during 

the ten-year period 1992-2001 is shown in Figure 3.3. The total tonnage database can be 

desegregated into three major cargo categories: fuel supplies, water supplies, and dry cargo 

(bulk, general, and container cargo) for the last six years. During the period 1992-2001, the 

general and bulk cargo handled increased by more than six times, and during the period 1996-

2001 the demand for water and fuel grew by 70 and 90 percent respectively. A marked increase 

in annual rates of growth in total tonnage is observed since 1997. 

Analysis of Port Tonnage for Seasonal Variations and by Cargo Type 

As port capacity requirements are directly related to peak activity periods, the seasonal 

distribution patterns of the tonnages handled at Port Fourchon were analyzed by commodity 

type. Monthly tonnage data is included in Appendix A, Table A.1.2. 

In order to make a comparative analysis between cargo types, coefficients of variation were 

computed. Coefficient of variation is a standardized measure derived by dividing the mean of 

the dataset by the standard deviation. The seasonal variability for fuel and cargo tonnage is 
26

lower than the demand variability for water and crew transport, requiring the latter two sectors to 

carry excess capacities to meet peak requirements (Table 3.2). The peak periods for bulk and 

general cargo are shown as deviations from the mean in Figure 3.4. The seasonal trends for 

other commodities more or less indicate similar patterns. 

 Port Tonnage (million Tons)

0

5

10

15

20

25

30

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Total Gen/Bulk Fuel/water

 Figure 3.3. Port Tonnage Trends. 

Table 3.2 

Monthly Variations in Cargo Handled (1996-2000 Average) 

Month General/Bulk 

Cargo (tons) 

Fuel 

(tons) 

Water 

(tons) 

Crew Change 

(# persons) 

Total 12,867,697 477,021 2,815,966 163,326

Mean 1,072,308 36,597 234,664 13,611

Range 387,406 13,690 194,132 6,954

Standard 

Deviation 

127,633 3,599 47,761 2,066

Coefficient of 

Variation 

11.9% 9.83% 20.4% 15.2%

 Source: Appendix A, Table A.1.2. 
27

Monthly Variations in Tonnage Handled 

(Jan-Dec)

-20

-10

0

10

20

30

(Percent)

 Figure 3.4. Monthly Variations for Bulk Cargo (1996-2000 Average). 

3.4. Estimating the Demand for Port Services 

3.4.1. Model Specification

The basic assumption a priory in specifying models is that changes in oil and gas exploration 

activities lead to changes in demand for port services. Since the demand for port services is 

derived from the aggregate logistics demand for the industry, this relationship is intuitively 

obvious. Two datasets, the number of OCS wells drilled and the number of oil and gas pipelines 

approvals, are used as proxy variables to represent the changes in activity levels in the oil and 

gas industry (see Table 3.1). The number of wells drilled is positively related to the cargo 

volumes generated in the logistics network in terms of industry inputs as well as to industry 

outputs of oil and gas. The increase in pipeline extensions generates substantial cargo volumes 

as an activity itself and the demand for network extension signify growth in terms of spatial 

distribution and increase output volumes. These are treated as exogenous (explanatory) variables 

generating the demand for port services. Selected port activities such as inland traffic volumes 

on access roads and channels, and port tonnage that utilize public port facilities are used as 

dependent variables responding to the demand for port services. 

A schematic of the models specified and the variable relationships are shown in (Figure 3.5). 

Based on the dataset in Table 3.1, three exogenous and three endogenous variables were 

identified for model specification. Nine single equation regression models (3x3) each with a 

unique variable relationship were specified to examine the demand for trucking, barge transport, 

and for cargo tonnage handled at the port. The choice of statistical technique was dictated by 

data limitations and other characteristics in variable relationships. Single equation regression 

models were specified to estimate the relationship between truck traffic and the number of OCS 

wells drilled. Single equation regressions with lagged explanatory variables were used to 

estimate the relationships between port activity variables and pipeline approvals because of the 

time lag between them. The lag model for estimating truck traffic in LA Hwy 1 (Model 1.3), for 

example, will use time-series data on pipeline approvals from 1992-1999 and the truck traffic 

data from 1994-2001 in the models pairing each observation of the independent variable with a 

two-year lag dependent variable. 

 
28

 

Independent Variables 

4. Total Number of OCS Wells Drilled 

5. Number of OCS Exploratory Wells Drilled 

6. Number of Pipeline Miles Approved 

↓

Dependent Variables 

4. Number of Trucks South Bound on LA Hwy 

1 

5. Number of Galliano Bridge Openings 

6. Total Tons at Port 

↓

Regression Models 

Model 

Number Independent Variable Dependent Variable 

1.1 Total OCS Wells Drilled Trucks South Bound on LA Hwy 1 

1.2 Exploratory Wells Drilled Trucks South Bound on LA HWY 1 

1.3 Pipeline Miles Approved Trucks South Bound on LA HWY 1 

2.1 Total OCS Wells Drilled Galliano Bridge Openings 

2.2 Exploratory Wells Drilled Galliano Bridge Openings 

2.3 Pipeline Miles Approved Galliano Bridge Openings 

3.1 Total OCS Wells Drilled Total Port Tonnage 

3.2 Exploratory Wells Drilled Total Port Tonnage 

3.3 Pipeline Miles Approved Total Port Tonnage 

Figure 3.5. Model Specification and Variable Relationships Estimated. 
29

3.4.2. Truck Traffic Demand 

Based on historical data from 1994 to 2001, the demand for truck traffic was estimated using 

three regressions models where the truck traffic on LA HWY 1 is the dependent variable and the 

three independent variables as shown in Figure 3.2a. A summary of all model estimates derived 

is shown in Table 3.3, and the detailed specifications of all models and the computer output are 

included as Appendix A. The numbering method for models is to identify by them by the 

number of the dependent and independent variable respectively. 

Truck Traffic Demand and Total Number of OCS Wells Drilled (Model 1:1) 

The number of wells drilled is assumed to be the causal variable driving the demand for 

logistic services and the truck traffic is a proxy for port services. The linear regression model 

specified is of the form: 

Y = a+bX, 

where Y represents truck traffic volumes on LA HWY 1 and a and b are the intercept term and 

the regression coefficient respectively. Using each independent variable mentioned above, three 

demand models were estimated. 

The regression model estimating the relationship between total OCS wells drilled and truck 

traffic (Regression Model 1.1) indicates strong, positive correlation with 85 percent of the 

variation (R2

 = 0.87) in truck traffic being explained by the model (Table 3.3). The regression 

coefficient, the intercept term, and F-values are statistically significant. According to the 

regression coefficient (slope) estimate, the technical relationship between the two variables is for 

every OCS well drilled there is a corresponding increase in truck trips by 628/yr. 

Truck Traffic Demand and the Number of OCS Exploratory Wells Drilled (Model 1.2) 

The regression results indicate that the number of exploratory wells is highly correlated with 

truck traffic volumes with a R2 value of 0.8648, and the other results are essentially comparable 

with the results derived from Regression Model 1.1. The model estimates that for every 

exploratory well drilled in the GOM, the truck traffic on LA HWY 1 will increase by an 

additional 744 trips/yr. 

Number of Pipeline Miles Approved and Truck Traffic Demand (Regression Model 1.3)

Because of the time lag involved between plan approvals and the laying of pipelines, it is 

necessary to specify the model with lagged explanatory variables. Several regression equations 

were specified with lagged data on pipeline approvals as the explanatory variable and trucking 

data as the dependent variable. After testing successive lagged models, the model with a twoyear lag (Xt-2) indicated statistically significant results. All parameter estimates were significant 

with a high R2 value of 0.85. According to model estimates for every additional mile of pipeline 

extension, the truck traffic will increase by 217 trips. 
30

Table 3.3 

Regression Estimates for Truck Traffic, Barge Traffic, and Port Tonnage 

Independent Variable Model 

Number 

Intercept Regression 

Coefficient 

R2 F-Value 

Truck Traffic South Bound on LA Hwy 1 

Total OCS Wells Drilled 1:1 39,817 

(2.39)* 

673 

(6.40)* 

0.87 40.98* 

Exploratory Wells 

Drilled 

2:1 73,757 

(6.08*) 

744 

(6.20*) 

0.86 38.39* 

Pipeline Miles Approved 

(lagged by 2-year period) 

3:1 85,327 

(7.57*) 

217 

(5.76*) 

0.85 33.20* 

Barge Traffic at Galliano Bridge 

Total OCS Wells Drilled 1:2 3,894 

(16.91*) 

6.39 

(4.16*) 

0.71 17.30* 

Exploratory Wells 

Drilled 

2:2 4,142 

(25.75*) 

7.78 

(4.61*) 

0.75 21.28* 

Pipeline Miles Approved 

(lagged by 2-year period) 

3:2 4,207 

(36.02*) 

2.51 

(6.44*) 

0.87 41.48* 

Port Tonnage 

Total OCS Wells Drilled 1:3 -1.46 

(-0.59) 

0.11 

(6.66*) 

0.85 44.39* 

Exploratory Wells 

Drilled 

2:3 2.18 

(1.95**) 

0.15 

(11.96*) 

0.95 143.53* 

Pipeline Miles Approved 

(lagged by 2-year period) 

3:3 3.64 

(2.33*) 

0.046 

(8.79*) 

0.93 77.23* 

Symbols * and ** denote statistical significance levels at 5% and 10% respectively. 

Source: Appendix A tables. 
31

3.4.3. Inland Barge Traffic Demand

Inland Barge Traffic and Total Number of OCS Wells Drilled (Regression Model 2.1) 

All parameter estimates derived from this model were statistically significant. The results 

indicated that for every OCS well drilled, bridge openings increase by about 7 openings. 

Inland Barge Traffic and OCS Exploratory Wells Drilled (Regression Model 2.2) 

The model results are more or less similar to Regression Model 2:1. The model estimates 

that 8 additional bridge openings will be necessary for each new exploratory well drilled in the 

GOM. 

Inland Barge Traffic and Miles of Pipelines Approved (Regression Model 2.3)

This model specified with the number of pipeline approvals as the explanatory variable 

shows a strong correlation with barge traffic. All parameter estimates are statistically significant 

and the regression model yields an R2

 value of 0.87. The regression equation estimates that for 

every mile extension of oil and gas pipeline three bridge openings for barges to pass will be 

necessary. 

3.4.4. Cargo Activities Demand

Demand for Cargo Handling and Total Number of OCS Wells Drilled (Regression Model 3:1) 

The model estimates indicate a strong correlation between the two variables (R2

 = 0.85). The 

slope coefficient and F-value of the regression are statistically significant. 

Demand for Cargo Handling and Number of OCS Exploratory Wells Drilled (Regression Model 

3:2) 

According to model estimates, these two variables provide the ‘best fit’ with an R2 value of 

0.95 and an F-value of 143.5. According to model estimates, for each additional OCS well 

drilled, port tonnage will increase by 114,500 tons; for each exploratory well, port tonnage will 

increase by 148,500 tons. 

Demand for Cargo Handling and Miles of Pipelines Approved (Regression Model 3.3) 

The demand relationship between these two variables was estimated using regression 

analysis with a lagged independent variable. The model estimates from the two-year lag model 

(Xt-2) were statistically significant with a R2

 value of 0.93. For every additional extension of the 

pipeline network by one mile, port tonnage increase by 45,000 tons. 

Port Cargo Tonnage Handled by Type of Cargo 

Using the tonnage data by cargo type, several models were specified to estimate the demand 

for water, fuel, and general/bulk cargo. The model specification used the tonnages of the three 

commodities as the dependent variables and the independent variables remained the same as 

described above. All models yielded statistically significant results; the computer output is 

included in Appendix A (Regression Models 4.1-4.9). 
32

3.5. Demand Forecasts 

3.5.1. Forecasting Approach 

Based on the model estimates described above, forecasts were made for trucking, inland 

barge traffic, and cargo handling trends at the port. For each activity, three alternative estimates 

were made with 2010 as the forecast horizon. The following three-step procedure was adopted 

in developing the forecasts. 

The future growth rates for the three independent variables (total number of OCS wells drilled, 

the exploratory wells drilled, and the number of pipeline approvals) were determined by trend 

extrapolation of historical data from 1992 to 2001. The trend extrapolation results for the 

variables are shown in Appendix A, Table A.1.4. The rates of annual growth for the three 

variables are shown in Table 3.4. For example, the total number wells drilled increases at an 

annual rate of 21.92 during the period;

The regression coefficient estimates derived from individual models (Table 3.3) were applied 

to the trend line estimates to derive annual rates of growth in each activity and the final forecasts 

were developed through 2010 using the actual data for 2001 as the baseline (Table 3.5). 

Table 3.4 

Technical Relationships between Variables: Estimated Annual Growth Rates 

for Truck Traffic, Barge Traffic, and Port Tonnage 

Truck Traffic 

Growth (# trips) 

Barge Traffic 

(# trips) 

Port Tonnage 

(millions) 

Independent Variables Rate of Annual 

Growth of 

Independent 

Variable 

Per 

Unit 

Annual Per 

Unit 

Annual Per 

Unit 

Annual

Total wells drilled 21.92 627.8 13,761 6.39 140 0.115 2.52 

Exploratory wells 

drilled 17.93 744.4 13,347 7.78 139 0.149 2.51 

Pipeline miles approved 57.71 216.71 12,506 2.51 145 0.0458 2.64 

3.5.2. Growth Projections 

Truck Traffic Forecasts 

The demand forecasts for trucking estimated through 2010 using the above procedure are 

shown in Table 3.5. The point estimates made for trucking by the three models are highly 

consistent, with a median forecast of 331,400 trucks in 2010 and the highest and the lowest 

forecasts falling within two percent of the median forecast. A technical evaluation of the above 

estimates using statistical comparisons for forecasting accuracy is beyond the purview of this 

report. According to the median forecast, truck traffic is expected to grow at an annual rate of 5 

percent and the overall growth for the nine-year period is about 60 percent. The three trucking 

trends are illustrated in Figure 3.6a. 
33

Table 3.5 

Truck Traffic, Barge Traffic, and Tonnage Forecasts Using Three Alternative Models 

Year Truck Traffic (1000) Barge Traffic Port Tonnage (million 

tons) 

Model 

1.1 

Model 

1.2 

Model 

1.3 

Model 

2.1 

Model 

2.2 

Model 

2.3 

Model 

3.1 

Model 

3.2 

Model 

3.3 

2001* 211.3 211.3 211.3 5,717 5,717 5,717 27.207 27.207 27.207 

2002 225.1 224.7 223.8 5,857 5,856 5,862 29.727 29.717 29.847 

2003 238.9 238.0 236.3 5,997 5,995 6,007 32.247 32.227 32.487 

2004 252.6 251.4 248.8 6,137 6,134 6,152 34.767 34.737 35.127 

2005 266.4 264.7 261.3 6,277 6,273 6,297 37.287 37.247 37.767 

2006 280.1 278.1 273.8 6,417 6,412 6,442 39.807 39.757 40.407 

2007 293.9 291.4 286.3 6,557 6,551 6,587 42.327 42.267 43.047 

2008 307.6 304.8 298.8 6,697 6,690 6,732 44.847 44.777 45.687 

2009 321.4 318.1 311.3 6,837 6,829 6,877 47.367 47.287 48.327 

2010 335.2 331.4 323.9 6,977 6,968 7,022 49.887 49.797 50.967 

*Figures for 2001 are actual numbers. 

Barge Traffic Forecasts 

The three barge traffic forecasts are very consistent with only a small variation between 

forecasts. The overall growth rate is about 22 percent for the period with 2-3 percent annual 

growth. The trends of growth for barge traffic are illustrated in Figure 3.6b. 

Port Tonnage Forecasts 

The median cargo forecast of 50 million tons in 2010 represents an overall increase of about 

100 percent or doubling of the volume. In terms of annual growth, it amounts to about 7-8 

percent. The three forecasts have a variation of less than 2 percent from the median forecast. 

The cargo forecasts are illustrated in Figure 3.6c. 

Port Tonnage Forecast by Cargo Type

The cargo tonnage was desegregated and forecasts were made for water, fuel, and 

general/bulk cargo. The model results (Models 1.4 to Model 3.6) and the forecasts are included 

in Appedix C.

3.6. Structural Analysis and Policy Implications 

Correlation Between Variables 

The correlation matrix for the ten variables included in this analysis is shown in Table 3.6. 

The industry variables are in columns 1 to 4 and the port activity variables are in columns 5 to 

10. Overall, both variables (the number of wells drilled and the miles of pipeline approvals), 
34

3.6.b. Barge Traffic Forecasts 

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

01 02 03 04 05 06 07 08 09 10

# Openings

Ex.wells Total wells Pipelines

3.6.a. Truck Traffic Forecasts 

150,000

170,000

190,000

210,000

230,000

250,000

270,000

290,000

310,000

330,000

350,000

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

# trips

Ex.wells Total wells Pipelines

3.6.c. Total Tonnage Forecasts 

10

15

20

25

30

35

40

45

50

55

01 02 03 04 05 06 07 08 09 10

tons, millions

Ex.wells Total wells Pipelines

 Figure 3.6. Truck Traffic, Barge Traffic, and Tonnage Forecasts Using Three 

 Alternative Models. 
35

Table 3.6

Correlation Matrix for Analysis Variables – Port Fourchon 

representing the rate of industry expansion, are positively correlated with the port activity 

variables, confirming the theoretical economic relationships. Note that the development wells 

data could not be used in the analysis. 

Future Forecasts 

The three trucking models, as well as the three barge models, provided statistically 

significant parameter estimates and consistent forecasts through 2010. The high correlation 

between these variables is evident from the values in Table 3.6. More or less similar results were 

derived from the models that estimated port tonnage. Therefore, these variables could be used 

for forecasting the demand for port services, infrastructure planning and investment decisions. 

It is important to note several assumptions implicit in estimating variable relationships. The 

analysis assumes the Port to be a major player in the OCS supply network, and the database 

accounts for those services. Another far-reaching assumption implicit in using historical data and 

trend extrapolation is that variable relationships and the rates of growth will continue during the 

forecast period. All industry variables such as new discoveries of oil and gas reserves, 

innovative new production systems, and the technological developments indicate a period of 

sustained growth for the industry. However, after the initial phases of deepwater oil and gas 

exploration, with maturity of the industry, it is very likely that the variable relationships for port 

services will change. According to the forecasts developed in this study, the tonnage at Port 

Fourchon will more than double by 2010 and the truck and barge traffic will increase by more 

than 50 percent. Therefore, a plan for upgrading public infrastructure such as highways, ports, 

potable water and sewerage services is a prerequisite to accommodate the high rates of industry 

growth and for regional development. 

Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 Column 9 Column 10

Column 1 1.0000

Column 2 0.5522 1.0000

Column 3 0.7333 0.9718 1.0000

Column 4 0.4331 0.7982 0.7735 1.0000

Column 5 0.3460 0.9300 0.9340 0.7983 1.0000

Column 6 0.3966 0.8675 0.8437 0.7801 0.9138 1.0000

Column 7 -0.5662 0.7101 0.5890 0.6105 0.7993 0.8829 1.0000

Column 8 -0.6895 0.8265 0.6741 0.5740 0.7461 0.5973 0.8128 1.0000

Column 9 -0.4831 0.9575 0.8998 0.4818 0.9014 0.8361 0.8631 0.8910 1.0000

Column 10 0.4482 0.9732 0.9205 0.7913 0.9326 0.9027 0.8743 0.9136 0.9985 1.0000

Notes:

Column 1 - Number of OCS development wells Column 6 - Number of Galliano bridge openings

Column 2 - Number of OCS exploratory wells Column 7 - Fuel tonnage

Column 3 - Total number of OCS wells Column 8 - Water tonnage

Column 4 - Miles of pipelines approved Column 9 - General/bulk cargo tonnage

Column 5 - Annual truck traffic on LA Hwy 1 Column 10 - Total port tonnage
37

4. Port of Morgan City 

Morgan City is an important onshore supply base currently serving several deepwater oil and 

gas installations. However, the shipbuilding and repair activities are of much more significance 

to the OCS logistics system. Most of the offshore structures served by service providers from 

Morgan City are located to the west of Port Fourchon, suggesting that proximity of Morgan City 

via the Atchafalaya River may have influenced the selection. In addition, however, business 

connections and historical relationships also play a role in the selection of service bases. 

According to the preferences indicated by the oil and gas industry operators in their pending 

plans filed with the MMS, Morgan City will continue to grow as a service base in the future4

. 

The shipbuilding and repair services at Morgan City are of much more strategic importance 

to the OCS logistics network than the routine supply services. The design and construction of 

larger, more economical vessels that can withstand extreme weather conditions is an integral part 

of deepwater oil and gas exploration technology. The cost-savings brought about by 

construction of vessels with higher technical capabilities and the conversion of existing vessels 

to meet the new needs are vital to the industry. 

The analysis of OCS supply activities to follow will consist of several sections. The analysis 

will first define the location and transportation links of the supply base. The next two sections 

will analyze the public port activities and the private sector operations. In the last section an 

empirical analysis of technical relationships between oil and gas industry variables and port 

activity variables will be included. These relationships will be estimated using quantitative 

techniques, and the results will be analyzed along with policy implications. 

4.1. Location and Transportation Infrastructure 

The service providers at Morgan City include the public port, the Morgan City Harbor and 

Terminal District, as well as private sector shipbuilders catering to the local, national and 

international markets. These shipyards are located mainly along the Atchafalaya River and the 

Gulf Intracoastal Waterway in the communities of Franklin, Morgan City, Patterson, Bayou 

Vista, Berwick, Amelia, and Baldwin. In general, the area including the public port and private 

offshore operators located in the above communities will be identified as the Morgan City supply 

base. 

Navigable Waterways 

The strategic location of the supply base at the intersection of busy navigable waterways has 

contributed to the development of shipbuilding and repair industries in the area. Each of the 

following waterway segments provides specific advantages to Morgan City (Table 4.1). 

1. Atchafalaya River, Morgan City to GOM - Morgan City is on the Lower 

Atchafalaya River 18 mi from the open waters of the GOM. The navigational 

channel maintained by the United States Army Corps of Engineers (COE) at a 

depth of 20 ft. and a minimum width of 400 ft provides easy access to large 

offshore structures and vessels. Currently, the COE has undertaken preliminary 

studies to examine the feasibility of deepening the channel to 35 ft. 

 

4

 The projected market shares are 44 percent for Port Fourchon, 19 percent for Venice, and 37 percent for other Gulf 

of Mexico ports including Morgan City, (MMS 2002; pp. 27-28). 
38

2. Atchafalaya River, Old River Lock to Morgan City – This segment of the 

waterway provides easy access to the Mid-West via the Upper Mississippi, 

enabling barge transportation of major supply items such as steel plates and iron 

and steel piping for the offshore oil and gas industry and the shipbuilding 

industry. 

3. Gulf Intracoastal Waterway, Morgan City-Port Allen Route – The industries in 

Morgan City area are connected to the operations on the Lower Mississippi 

including foreign commerce and the barge transportation network on the 

Mississippi. 

4. Gulf Intracoastal Waterway, Mississippi River to Sabine River – This segment of 

the waterway coupled with the Atchafalaya provides a shorter route for cargo with 

origins and destinations in Texas and western Louisiana and the Midwest. For 

example, traffic between points in southeast Texas and the Upper Mississippi 

River Valley saves approximately 342 mi per round trip by using the Atchafalaya 

River rather than the alternate link of the Intracoastal via the Harvey Locks at 

New Orleans. 

Table 4.1 

Waterways Network and Traffic (2000) 

Waterway Segment Length 

(miles) 

Depth 

(feet) 

Freight 

Traffic 

(1,000 tons) 

Vessel 

Trips 

Atchafalaya R. Morgan City to GOM 18 20 2,740 11,628

Atchafalaya R. Morgan City to Old R. Lock 123 12 13,441 12,764

GIWW- Morgan City-Port Allen Route 64 9 23,061 15,265

GIWW- Mississippi R. to Sabine R. 266 10-12 62,855 66,805

 Source: Waterborne Commerce of the United States (U.S. Army Corps of Engineers, 2001) 

Highways 

The Morgan City supply base is located on the U.S. Highway 90, which is the future corridor 

of I-49. The metropolitan cities of New Orleans, Baton Rouge and Lafayette are within a 

seventy-mile radius. Through these cities the port can access Interstates 49, 55, and 59 North 

and Interstate 10 East and West. 

4.2. The Public Port 

4.2.1. Port Organization, Location, and Facilities 

The Port of Morgan City was created by Act 530 in the State Legislature in 1952. Since 

1957, it has been active in both domestic and international trade. A nine member Board of 

Commissioners appointed by the Governor is responsible for the management. The 

commissioners serve on a voluntary basis with no remuneration. Each commissioner serves for a 

nine-year term. In the early 1990’s the Port made a decision to be an operating port and started 

developing port facilities. 
39

The Public port is on the east bank of the Atchafalaya River in a natural wide and deep 

harbor known as Berwick Bay. As discussed above, the port has benefited from its central 

location with close proximity to the GOM and several heavy traffic inland waterway segments. 

The Port of Morgan City is located 1.1 mi from U.S. Highway 90, with Lafayette 71 mi to the 

West on Highway 90, New Orleans 68 mi to the East and Baton Rouge 71 mi to the North. The 

port is served by the Burlington Northern – Santa Fe Railroad (BNSF) and provides railcarshunting services on a daily basis. 

Public Port Facilities 

The public port site has a total of 28.6 ac with 22.49 ac located inside the COE floodwall and 

6.11 ac located between the floodwall and Bayou Boeuf. The limited availability of land at the 

waterfront could constrain future port expansion plans. 

The port has been able to compete successfully for funding for infrastructure improvements 

through the PCDP. Since 1990 the port has been awarded $9.75 million for eight projects. 

These projects have provided a dock, warehousing, cargo-handling equipment, rail spur, transit 

shed, truck yard and a rail car conveyor system (Table 4.2). The wharf area at the port has 

approximately 80,000 ft2

 and is used exclusively for docking and loading/unloading cargo to and 

from vessels. With a dock length of 800 linear-ft and 20-ft draft channel, the port is geared to 

handle medium-sized cargo vessels. Other facilities at the port include a 20,000 sq. ft. 

warehouse, a large marshalling yard, and adequate rail siding facilities. Specific port cargo 

handling equipment includes: a dock side mobile crane capable of lifting a fully loaded (70,000 

lb) 40 ft container; three forklifts: one 8,000 lb and one 10,000 lb for warehouse use, and one 

15,000 lb for the yard; a 50-ton container crane with a 130-ft boom; a 35-ton cherry picker; and a 

40-ton container handler. 

Table 4.2 

Capital Investment Program (1990-2002) 

Project Year 

Funded 

Project Cost 

($) 

Project Components 

Bulkhead & Dock 1990 800,000 Construct a 500ft. wharf, fender 

piles and dolphins 

Bulkhead & Dock, Phase II 1992 2,100,000 Dock extension by 300ft. x 80ft. 

Mobile crane & cargo handling 

equipment 

1993 1,462,500 Purchase mobile crane, forklifts, and 

misc. equipment 

Transit shed & truck yard 1995 1,410,000 Construct 20,000 sq. ft. warehouse 

and paved yard 

Railroad spur & loading dock 1996 874,800 3500 linear ft. rail spur and siding, 

and 20’x200’ loading dock. 

Additional dockage 1998 1,143,000 Dock extension by 27ft x 447ft. 

Rail transfer and storage area 1999 1,957,000 A concrete container yard and hard 

surface access roads 

Total Investment 9,747,300 

Source: Port Construction and Development Priority Program, Eighth Annual Report, Louisiana 

Department of Transportation and Development, 2001. 
40

4.2.2. Port Operations and Financial Performance

As an operational port, Morgan City does not have a traditional landlord relationship with 

tenants. Once facilities that are currently under construction are completed and as cargohandling activities increase, the port hopes to attract a stevedoring company that will relieve the 

port of some of it operational responsibilities. 

The main imported items handled at the port are steel products, iron and steel pipe and tubes, 

oil and gas field machinery, and barite (Table 4.3). Raw materials required by the shipbuilding 

and repair industry and equipment fabrication needs remain as the major component in port’s 

tonnage. In addition, the port derives revenue by offering berthing facilities for vessels 

providing services to the off shore oil industry.

Table 4.3 

Oil and Gas Industry Related Cargo (1996-2000 Average) 

Cargo Category 1996-2000 Average 

(tons) 

1996-2000 Average 

(%) 

Oil and Gas Related 

 Barite 1,750 3.3 

 Iron, steel sheets & pipes 1,879 3.5 

 Oil and gas field machinery 9,688 18.1 

 Fuel oils 25,48 4.8 

 Total (oil and gas related) 15,865 29.6 

Other Cargo 37,772 70.4 

Total 53,637 100 

Financing of Public Ports 

The summary financial indicators included in Table 4.4 emphasize several features typical to 

a public port. It is interesting to note that while 12 percent of the port revenue is from a selfimposed property tax on the local community, another 81 percent are federal and state grants. 

Port operating revenues contribute only 5 percent to total revenue, emphasizing the local 

community support to public ports for job creation and economic development. 

4.3. Private Sector Operators 

As mentioned earlier, the private sector businesses dominate the shipbuilding and repair 

industries in the Morgan City area. Characteristically, these industries are large, multi-plant 

operations specializing in building vessels for different sectors such as the cruise industry, 

military vessels for the navy, recreation vessels and yachts, vessels designed for research 

purposes, etc. The supply and repair of offshore vessels and other drilling equipment has 

continued to be a significant part of the industry since the 1940’s. However, with the recent 

developments in deepwater oil and gas exploration activities, the need for larger and faster 

vessels has provided a new impetus to the industry. 
41

Table 4.4 

Analysis of Revenue Sources (2000) 

Budget Item 2000 

 ($) (%) 

Property Taxes 520,188 11.9 

Federal & State Govt. Grants 3,528,987 80.8 

Port Operating Revenue 227,470 5.2 

Total 4,366,366 100 

Total assets 17,959,543 100 

Source: Annual Financial Statements, Port of Morgan City. 

4.3.1. Profiles of Major Operators 

The major businesses engaged in offshore related services with more than 100 employees are 

listed in Table 4.5. Most of the firms are multi-plant operations, and the number of employees 

and annual sales shown are only for the plants located in Morgan City. For example, 

McDermott, Inc. is a conglomerate employing 11,400 employees in more than a dozen countries 

with $3.4 billion in annual revenue in 2001. Similarly, Bollinger Shipyards consist of 14 plants 

located in Louisiana and Texas. 

Table 4.5 

Major Offshore Oil and Gas Service Firms 

Name of Firm Number 

Employed 

Annual Sales 

(million $) 

Activity 

Bollinger Marine Fabricators 400 25-100 Shipbuilding & repair 

Cameron Corporation 268 10-25 Oil & gas field machinery 

Conrad Industries, Inc. 200 15 Boat building & repair 

Gulf Craft, Inc. 130 5-10 Boat building & repair 

McDermott, Inc. 2,000 100-500 Oil & gas field machinery 

SMI Cos. 120 5-10 Metal products-fabricated 

Superior Fabricators, Inc. 110 14 Structural metal fabricated 

Swiftships Shipbuilders, LLC 245 40 Boat building & repair 

Twin Bros. Marine Corp. 240 N/A Shipbuilding & repair 
42

The company profiles included in Table 4.6 illustrate the typical shipyard configuration 

operated by the private sector. Typically, shipyards are multi-plant firms catering to national and 

international markets. The description of facilities indicates the highly capital intensive nature of 

the industry. The products and services emphasize that the shipyards cater to various industrial 

sectors such as the cruise industry, U.S. government agencies and the military, the offshore oil 

and gas industry and inland barge industry, etc. The diversified market provides a hedge against 

downturns in any individual sector. 

In addition to the large-scale industries described above, the offshore supply network consists 

of many smaller firms that provide specialized services and raw materials to the shipyards. 

Table 4.6 

Infrastructure Facilities at Selected Private Sector Shipyards 

Conrad Industries, Inc. Bollinger Marine 

Fabricators McDermott International 

Plant Locations 

Operates 2 plants in LA and 1in 

Texas 

Operates 14 shipyards, 12 in LA 

and two in Texas 

International conglomerate; 

Multi-plant locations in Asia, 

Africa, North and South America 

Products and Services 

Construction and repair of marine 

vessels and oil and gas 

equipment. 

Construction and repair of marine 

vessels and oil and gas 

equipment. 

Fabrication of offshore platforms, 

marine vessels and installing 

offshore pipelines 

Facilities at Morgan City 

5 dry docks with lifting capacity 

900-3,000 tons; 

Over 110,000 sq. ft. of indoor 

fabrication space; 

Over 2,000 feet of bulkhead area; 

Two dredged basins for vessel 

repair 

3 dry docks with lifting capacity 

1,600 to 8,100 tons; 

More than 60,000 sq. ft of 

covered space including 

workshops and offices; 

2,000ft.of wet dock area; 

17,000 sq. ft construction slab. 

. 

2 deck assembly buildings, each 

400’x 800’ with 8 bays and three 

20-ton overhead cranes in each 

bay; 

Jacket erection area with 46 

crawler cranes ranging in 

capacity from 40 to 350 tons; 

Pipe mills – 5 buildings 

Recent Projects

Pusher tug for U.S. Army; 

Double hull tank barge for U.S. 

Navy; 

Towboat for Corp of Engineers; 

FPSO living quarters for 60 

persons; 

A warehouse barge. 

Barge derrick for U.S. Army; 

Patrol crafts for U.S. Coast 

Guard; 

Offshore supply vessels; 

Lift boats; 

Passenger boats and dredges. 

Drilling & prod. Spar for 

Chevron; 

Sub-sea development system for 

Conger; 

Pipeline systems for BP 

Exploration; 

Drilling and prod. Platform for 

Marathon Oil 

 Source: Based on marketing information provided by individual firms. 
43

4.4. Data and Definition of Variables 

The approach followed in estimating the demand for port services at Port Fourchon is 

inappropriate for the present analysis for several reasons: 

1. The Database – A database maintained by the public port was available for 

analysis at Port Fourchon. At Morgan City, as the services are provided by the 

private sector, a public database on port services is not available. Because of the 

proprietary nature of private sector operations, it is difficult to develop an 

adequate database for analysis. 

2. Low Market Share – As the market share of port services at Morgan City is 

relatively low, it is likely that the models may not adequately represent industrywide changes at a macro level. 

3. The Nature of Services – The shipbuilding and repair services at Morgan City 

cater to a diversified set of clients and foreign markets. It is much more difficult 

to delineate the effects of the OCS oil and gas industry. 

4.4.1 Industry Variables and Port Activity Levels 

The set of OCS oil and gas industry variables (columns 1-6) and the volumes of vessel traffic 

on the Atchafalaya River representing the port activity levels (columns 7-9) were selected as 

variables for the demand analysis (Table 4.7). While the number of wells drilled act as a proxy 

for industry expansion and as a quantitative measure for logistical service requirements, the 

number of pipeline miles approved provides an estimate of one major item of freight generated 

by the industry. The EP’s and Development Operations Coordination Documents (DOCD) are 

indications of progress made by the industry in terms of individual operations. In modeling the 

demand for port services, these six variables are treated as exogenous variables. 

Port Activity Variables 

Unlike at Port Fourchon where port operations are centered at the public port, the activities at 

Morgan City are by private operators. Therefore, the database on vessel trips on the Atchafalaya 

River from Morgan City to GOM was examined as an option for the selection of port activity 

variables. As described earlier, the Atchafalaya River from Morgan City to the GOM is the main 

access channel providing the vital link for the delivery of offshore supply services. The database 

on non self-propelled vessel movements on this navigable waterway was selected to represent 

the port activity levels at Morgan City. As illustrated in Figure 4.1, self-propelled vessels 

account for 81 percent of the total vessel trips and are mainly recreational and commercial 

fishing vessels with no connection to OCS activities. 

4.4.2. Historical Trends

The historical trends of the industry variables and the port activity variables are shown in 

Figure 4.2. The trends of OCS wells drilled and miles of pipeline approvals were discussed in an 

earlier section. The EP data, as expected, closely follow the number of exploratory wells. In the 

case of total vessel trips, the data points for 1997 and 1999 will remain as large outliers from the 

trend line. However, these wide variations did not affect the non self-propelled vessels category.
44

Table 4.7 

Data and Analysis Variables 

Dev. Expl. Total Pipeline EP DOCD Self-prop Non SP Total 

Wells Wells Wells miles Vessel Vessel Vessel 

Trips Trips Trips 

 (1) (2) (3) (4) (5) (6) (7) (8) (9) 

1992 27 7 34 76 25 3 18,398 2,112 20,510 

1993 29 12 41 52 25 4 21,540 2,225 23,765 

1994 37 28 65 193 37 4 23,421 2,515 25,936 

1995 51 34 85 139 38 8 25,302 2,805 28,107 

1996 71 42 113 329 64 10 28,367 3,643 32,010 

1997 88 84 172 285 105 11 30,168 4,371 34,539 

1998 57 112 169 450 125 16 22,983 4,095 27,078 

1999 49 123 172 512 168 14 15,479 3,127 18,606 

2000 67 146 213 241 157 27 18,753 4,266 23,019 

2001 60 148 208 711 150 37 -- -- --- 

 Notes on data sources: 

1. Columns 1 to 6 are from Deepwater Gulf of Mexico 2002: America’s Expanding Frontier 

(MMS, 2002). 

2. Columns 7 to 9 are from Waterborne Commerce of the United States (U.S. Army Corps 

of Engineers, 2000). 
45

4.1.a. Atchafalaya to Gulf of Mexico

19%

81%

Non self-propelled Self-propelled

4.1.b. Louisiana Waterways

45%

55%

Non self-propelled Self-propelled

 Figure 4.1. Self-Propelled and Non Self-Propelled Vessel Trips on the 

 Atchafalaya River from Morgan City to the Gulf of Mexico 

 and on Other Louisiana Waterways. 
46

4.2.a. Industry Variables

0

200

400

600

800

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Expl. Total Pipeline EP

4.2.b. Port Activity Variables, Vessel Trips

0

5000

10000

15000

20000

25000

30000

35000

40000

1992 1993 1994 1995 1996 1997 1998 1999 2000

Self-prop Non Self-prop Total

 Figure 4.2. Variable Trends. 
47

4.5. Estimating the Demand for Port Services 

Six regression models were specified using each of the six industry variables as the 

independent variable and the number of non self-propelled vessels as the dependent variable. The 

model specifications and the complete computer output are included in Appendix B. A summary 

of model estimates is shown in Table 4.8. 

Table 4.8 

Regression Estimates for Vessel Traffic and Technical Relationships Between Variables 

Independent Variable* Model 

No. 

Intercept Regression 

Coefficient 

R2 FValue 

Number of development wells-drilled 4.1 1129.5 

(3.02) 

39.9 

(6.0) 

0.8371 35.97

Number of exploratory wells drilled 4.2 2364.0 

(7.28) 

13.40 

(3.36) 

0.6181 11.33

Total number of wells drilled 4.3 1796.0 

(6.21) 

12.21 

(5.64) 

0.8195 31.77

Miles of pipeline approved (lagged by 

one year) 

4.4 2544.4 

(5.72) 

3.29 

(2.21)** 

0.4501 4.91

Number of EPs filed 4.5 2303.0 

(5.87) 

11.33 

(2.85) 

0.5375 8.13

Number of DOCDs filed 4.6 2248.5 

(6.44) 

92.0 

(3.41) 

0.6244 11.63

Notes: 1 * The dependent variable for all regressions is the number of non self-propelled vessel trips. 

2. Numbers in parentheses are t-values, and all t-values and F-values are significant at the 5% 

level 

3. ** Significant at the 10% level. 

Variable Relationships Between OCS Wells Drilled and Vessel Traffic 

The three models provided statistically significant and consistent estimates. The models with 

the total number and the number of development wells as the explanatory variable indicated very 

high R-square values. 

The models were capable in explaining more than 80 percent of the variations in non selfpropelled vessel traffic trips on the Atchafalaya River. Surprisingly, the development wells 

category that was dropped as a variable in the Port Fourchon analysis provided the “best fit” 

model in this case. The interpretation of the regression results could be expressed as that for 

every development well and exploratory well drilled in the OCS, the number of non selfpropelled vessel trips will increase by 40 and 13 vessel trips respectively. The corresponding 

number for the total number of wells is 12 trips. 

Pipeline Approvals and Vessel Traffic 

The model where the miles of pipelines was the explanatory variable yielded statistically 

more significant results when the data lagged by one year was used in the model. This is in line 

with the observed phenomena where there is a gap between plan approvals and implementation. 
48

4.6. Model Forecasts 

The vessel trip forecasts were developed through 2010 for the Atchafalaya River from 

Morgan City to the GOM following similar procedures described earlier in this report. The six 

alternative forecasts made using the results of regression models and the forecasts of vessel trips 

derived from linear trend extrapolation are shown in Table 4.9. 

While four of the forecasts deviate less than 10 percent of the extrapolated trend, two model 

forecasts are substantially lower than the trend. According to the trend extrapolation, the growth 

rate in vessel traffic will be about 5 percent a year; however, it is about 3 percent according to 

lower forecasts. 

4.7. Structural Analysis and Policy Implications 

Correlation Analysis 

The correlation matrix in Table 4.10 provides a summary of the quantitative relationships for 

all variables included in this section. While columns 1 to 6 of the matrix are industry variables, 

columns 7 to 9 are port activity variables. 

The relevant relationships between the dependent variable used in the regression analysis and 

other variables are indicated in column 8. High and positive correlation coefficients are 

observed between the number of non self-propelled vessels and the industry variables. The 

positive correlations confirm an a priory economic relationship that oil and gas industry 

expansion leads to higher port activity levels, leading to higher traffic levels. In contrast, the 

category of self-propelled vessels (column 7) representing mostly recreation vessels and 

commercial fishing vessels are negatively correlated with most of the industry variables.

In this section, we have examined the nature of OCS logistics services provided by the 

Morgan City supply base and the organizational structure in terms of public and private sector 

operations. The public port, which started as an operating port in the mid 1990’s, remains as a 

potential service base that could expand operations in the future. The private sector operations 

that specialize in shipbuilding and repair services will continue to cater to a diversified market 

and have the capacity to accommodate the increasing demands of the expanding OCS oil and gas 

industry. Although the traffic volumes on the Atchafalaya River from Morgan City to the GOM 

will continue to grow, it is not likely to be a constraint for the expansion of port services. 
49

Table 4.9 

Model Forecasts of Vessel Traffic 

Model Number 

4.1 4.2 4.3 4.4 4.5 4.6 

Independent Variable 

Year Dev. 

Wells 

Explor. 

Wells 

Total 

Wells 

Pipeline 

Miles 

EP DOCD 

Trend 

Extrapol. 

(number of non self-propelled vessel trips) 

2000 4,266 4,266 4,266 4,266 4,266 4,266 4,266 

2001 4,425 4,506 4,534 4,456 4,472 4,568 4,533 

2002 4,584 4,746 4,801 4,646 4,679 4,870 4,801 

2003 4,743 4,987 5,069 4,836 4,885 5,173 5,068 

2004 4,902 5,227 5,336 5,025 5,092 5,475 5,336 

2005 5,062 5,467 5,604 5,215 5,298 5,777 5,603 

2006 5,221 5,707 5,872 5,405 5,504 6,079 5,871 

2007 5,380 5,948 6,139 5,595 5,711 6,381 6,138 

2008 5,539 6,188 6,407 5,785 5,917 6,684 6,406 

2009 5,698 6,428 6,674 5,975 6,124 6,986 6,673 

2010 5,857 6,668 6,942 6,165 6,330 7,288 6,941 

Var. trend 3.99 17.93 21.92 57.71 18.22 3.28 N/A

Reg. 

Coeff. 

39.90 13.40 12.21 3.29 11.33 92.00 N/A

Annual 

Growth 

159.12 240.23 267.58 189.86 206.41 302.21 267.47 

Variation from Trend 

 -1,084 -272 1 -776 -611 347 0 
50

Table 4.10 

Correlation Matrix for Analysis Variables – Morgan City 

Col. 1 Col. 2 Col. 3 Col. 4 Col. 5 Col. 6 Col. 7 Col. 8 Col. 9

Column 1 1.0000

Column 2 0.5675 1.0000

Column 3 0.7585 0.9670 1.0000

Column 4 0.4932 0.7422 0.7400 1.0000

Column 5 0.5408 0.9811 0.9438 0.8058 1.0000

Column 6 0.5745 0.9250 0.9098 0.5271 0.8614 1.0000

Column 7 0.5946 -0.2571 -0.0195 -0.0730 -0.3066 -0.2043 1.0000

Column 8 0.9149 0.7862 0.9052 0.6155 0.7331 0.7902 0.3582 1.0000

Column 9 0.7072 -0.1034 0.1369 0.0378 -0.1583 -0.0539 0.9871 0.5029 1.0000

Column 1 - Number of development wells drilled

Column 2 - Number of exploratory wells drilled

Column 3 - Total number of wells drilled

Column 4 - Miles of pipeline approvals

Column 5 - Number of exploration plans filed

Column 6 - Number of DOCD's filed

Column 7 - Number of self-propelled vessel trips

Column 8 - Number of none self-propelled vessel trips

Column 9 - Number of total vessel trips
51

5. Port of Iberia 

The Port of Iberia is located in southcentral Louisiana along the Commercial Canal, 

approximately 7.5 mi north of the Gulf Intracoastal Waterway (GIWW), 9 mi north of Weeks 

Bay on the GOM, and 4.5 mi southwest of the city of New Iberia. The location and 

configuration of the Port of Iberia, a public port that specializes mainly in platform fabrication, 

repair, and maintenance, are strongly influenced by OCS supply activities. Maintaining direct 

and easy access routes to the GOM, improvements to the network of channels, slips, and land at 

the waterfront, and market promotion are high priorities for the Port. 

The purpose of this analysis is to assess the Port of Iberia’s role as a supply base to the OCS 

oil and gas industry and to examine the nature of supply adjustments made by the Port during the 

1990’s in response to the expansion of OCS activities. Since a comprehensive database is not 

available for the Port, the evaluation of adjustments is qualitative rather than quantitative. 

Quantitative analysis is performed, though, whenever data is available, i.e., for capital 

investment and port financial performance. A qualitative assessment of this nature is thought to 

be quite instructive and useful for public port infrastructure planning. 

5.1. Port Location and Transportation Links

Access Channels 

The access to the GOM is vital to the Port for delivery of large prefabricated structures and 

other offshore products. Several access channel options available to Port tenants and the major 

constraints of each are listed in Table 5.1. 

1. Commercial Canal/GIWW (East)/Atchafalaya Route. Constraint: the 73 ft airdraft at the Highway 317 Bridge. 

2. Commercial Canal/GIWW/Acadiana Navigation Channel Route. Constraint: the 

nine-foot depth of the Acadiana Navigation Channel. Because of environmental 

concerns (salt water intrusion and erosion), there are no plans to deepen this 

channel at present. 

3. Commercial Canal/GIWW (West)/Vermilion River Cutoff. Constraint: the depth 

(8 ft) and width (80 ft) of the Vermillion River Cutoff. Feasibility studies 

conducted by the Port have identified this route, with the necessary modifications, 

as the best alternative for accessing the GOM. The project is currently awaiting 

Congressional approval for funding. 

4. Commercial Canal/GIWW (West)/Freshwater Bayou Canal Route. Constraint: 

the longer distances and therefore time involved in using a bypass channel. 
52

Table 5.1 

Access Channels and Constraints 

Channel Location and Characteristics Constraints 

Commercial Canal Port access channel 

8 mi long 

Connects to GIWW, south 

Actual Depth: 12 ft 

Actual Width: 25 ft 

Gulf Intracoastal Waterway 

(GIWW) 

8 mi south of port 

140 mi west of Mississippi 

River 

100 mi east of Calcasieu Ship 

Channel 

Actual Depth: 12 ft 

Actual Width: 125 ft 

Authorized Depth: 16 ft 

Authorized Width: 50 ft 

Atchafalaya River 30 mi east on GIWW Actual Depth: 20 ft 

Actual Width: 200 ft 

Air draft: 73 ft at Hwy 317 

bridge 

Acadiana Navigation 

Channel 

Extension of Commercial 

Canal to the south across 

Vermilion Bay 

Actual Depth: 9 ft 

Actual Width: 200 ft 

Vermilion River Cutoff Northwest corner of Vermilion 

Bay 

Authorized Depth: 8 ft 

Authorized Width: 80 ft 

Freshwater Bayou Canal 25 mi southwest on GIWW Authorized Depth: 12 ft 

Authorized Width: 125 ft 

Must pass through a lock: 

12 ft deep x 84 ft wide 

Source: Master Development Plan (Port of Iberia, 2000). 

Highway Access 

Two access roads running North-South connect the Port to Highway 90. Highway 90 is a 

four-lane highway, which is earmarked for improvements as a southern extension of Interstate 49 

below Interstate 10. Average daily traffic counts (AADT) at two locations on Highway 90 

indicate a volume to capacity (V/C) ratio of 70 percent, which is considered a good level of 

service (LOS) by transportation planners (Table 5.2). In addition, the Port is served by more 

than half a dozen Louisiana highways, which are fairly well maintained. According to the 

Louisiana Department of Transportation and Development, the current highway facilities are 

adequate and do not impose any constraints to Port operations. 
53

Table 5.2 

AADT Counts on Highway 90 

Location 

Number 

of Lanes 

Volume (V)/ 

Capacity (C) 

V/C 

Ratio 

Level of Service 

(LOS)* 

Hwy 90 

North of Hwy 14 Four-lane 22,880/32,000 0.72 C 

Hwy 90 

near Hwy 329 junction Four-lane 21,810/32,000 0.68 C 

* The level of service is graded from A to F (where F is very congested). 

Rail Access 

Rail services to the port are provided by the BNSF, Union Pacific (UP), and the Louisiana 

Delta Railroad Company. BNSF and UP are mainline railroads providing an easterly route to 

New Orleans, a westerly route to Lake Charles and Houston, and northerly route to Opelousas. 

The Louisiana Delta Railroad Company, a short-line railroad company provides services 

between Vermillion and Iberia Parishes, and also operate spurs which service Avery Island and 

Weeks Island. 

5.2. Port Infrastructure 

5.2.1. Port Layout and Land Use 

Businesses at the public sector of the Port of Iberia and several private sector businesses are 

engaged primarily in offshore metal fabrication activities. These activities are concentrated 

along Commercial Canal and Rodere Canal (Figure 5.1). The Port area which encompasses 

about 3,848 ac could be divided into four functional zones on the basis of ownership and major 

activities (Figure 5.2): 

1. Mixed Land Use (Zone 1) - This area, approximately 1,475 ac located north of 

Port Road, is currently not accessible by water transportation. The land use is 

mixed with commercial, industrial, and residential uses. On a functional basis 

this area can be identified as the “service sector” of the Port, as most of its 

activities are oriented toward servicing Port needs. These range from technical 

and professional services to hotels and restaurants. 

2. Private Sector (Zone 2) - This area, located to the west of Commercial Canal 

along Rodere Canal, is an industrial zone with a concentration of private sector 

operators. Most of the metal fabrication industries are located at nine slips on 

Rodere Canal, which provides waterway access to the GOM via Commercial 

Canal. Rodere Canal extends 6,400 ft in length, is 14 ft deep, and has bottom and 

top widths of 140 ft and 200 ft respectively. The southern section of this zone 

extends east of Commercial Canal, dividing the public Port property. 
54

3. Public Port (Zone 3) - This area defines the public Port section. Public Port 

properties are located in two areas east of Commercial Canal, covering a total of 

590 ac. In 1995, a 170 ac was added to the southern section. A detailed analysis 

of Port facilities is described below. 

4. Future Expansion (Zone 4) - This area, 410 ac east of the public Port, is identified 

for future expansion. 

 Figure 5.1. Port Layout and Plan Use. 
55

N Commercial Canal

 Private Public 

Sector Port Area

Operators

Rodere Canal Public port

tenants

Future

Expansion

 Figure 5.2. Functional Zones. 

5.2.2. Public Port Organization and Operations 

The Port of Iberia was created in 1938 by Act 128 of the Louisiana State Legislature and Act 

486 in 1978. The Port’s jurisdiction covers most of Iberia Parish and the communities of 

Jeanerette and Loreauville. The overall responsibility for the management of the public Port is 

entrusted to a seven-member Port Commission. The Commissioners, appointed by the parish 

government and the municipalities of Jeanerette and Loreauville, serve for a six-year term. An 

executive director is responsible for the management of Port operations. The general mission of 

the Port Commission is to cooperate with public and private organizations in promoting 

economic development, and creating employment opportunities by diversifying the local 

economy. 

As a landlord port, the major activity of the public Port is to plan port facilities and lease 

them to the private sector tenants. An analysis of the lease information indicates that the Port has 

leased 279 ac of waterfront property to 47 tenants (Table 5.3). With 55 percent of the land 

leased beyond 2005, the Port is assured of a stable revenue stream for the next 10 to 15 years. A 

positive relationship also exists between the length of the lease term and the number of acres 

leased – leases extending beyond 2010 are about four times larger (with respect to the number of 

acres leased) than short-term leases. 
56

Table 5.3 

Analysis of Lease Operations 

Lease Period 

Number of 

Leases 

Waterfront 

Acreage 

Average Size 

(acres) 

Percent of Total 

Leased Acreage 

2000 - 2005 31 123.6 4.0 44 

2006 - 2010 12 96.7 8.1 35 

2011 - 2020 4 58.6 14.7 21 

Total 47 278.9 5.9 100 

Source: Master Development Plan (Port of Iberia, 2000). 

Lease Rates 

The lease rates charged by the Port depend on the location and the improvements made to the 

area in terms of land stabilization, buildings, access to bulkheads, etc. The main factors that 

determine lease rates are: 

1. Waterfront Location. Lease rates for waterfront locations are about five times 

more than non-waterfront lands for similar sized areas. For example, less than 

one-acre waterfront sites are leased for approximately $6,500/ac/yr compared to 

non-waterfront lease rates of $1,300.

2. Lease Site Size. Lease rates are on a sliding scale with rates decreasing for larger 

lots. For example, 1999 lease rates per acre for waterfront sites less than one acre 

averaged $ 6,500 while sites larger than 20 ac averaged $1,800/ac.

3. Cost of Site Improvements. The current policy of the Port is to recover 6 percent 

of site improvement costs as annual rent.

5.2.3. Tenant Activities 

The results of a survey5

 conducted in the Port area (including public Port and private sector 

firms around Commercial Canal and Rodere Canal) indicate that 71 percent of the businesses at 

the Port are in some form connected to the offshore supply industry (Table 5.4). Fabrication and 

repair services comprise the largest single activity with 29 percent while other offshore services 

make up 42 percent. However, this information is of limited value, as it includes a wide 

spectrum of industries from those engaged exclusively in offshore supply logistics (e.g., offshore 

supply boats) to those industries with very limited dependence (e.g., local retailers). 

Nevertheless it indicates that the local economic outlook is closely dependent on the offshore oil 

and gas industry. 

 

5 Master Development Plan (Port of Iberia, 2000).
57

Table 5.4 

Classification of Businesses (1999) 

Industry Number of Business Units Percent of the Sample 

Offshore Supply Industries 

 Fabrication 20 20 

 Repair Services 9 9 

 Other offshore services 43 42 

Total Offshore 72 71 

Other Industries 30 29 

Grand Total 102 100 

Fabrication Activities 

The layout and major components of a typical fabrication yard is shown in Figure 5.3. It 

consists of three major components: 

1. Dock and Channel Slip. The dock and slip area are used to assemble large 

structures as well as for loading and unloading.

2. Fabrication Buildings. The typical building configuration consists of several 

fabrication bays, equipped with overhead cranes, serving as work areas, material 

preparation areas, and equipment maintenance and storage areas.

3. Yard Storage and Staging Area. The yard staging area with concrete surface is 

usually used for cargo handling and as areas for equipment fabrication. The rest 

of the yard used for storage of raw materials is typically earthen surface stabilized 

with limestone. 

5.2.4. Profile of a Port Tenant 

Since data on private sector operations are scarce, a profile of a typical Port tenant was 

developed in order to gain some insights. The major characteristics of a typical business, such as 

the leasing terms for public facilities, site improvements made by the operator, the products and 

services provided, the total payroll, etc., are provided in Table 5.5. Similarly, Table 5.6 was 

developed to show the typical procedures adopted when expanding Port facilities with public and 

private sector participation. 
58

Machine shop,

office, warehouse, etc. Yard storage and staging area

 (yard cranes, forklifters, etc.)

Dock cranes The Dock Dock cranes

 Pre-fabricated structure Slip

 Figure 5.3. Layout of a Typical Prefabrication Terminal. 
59

Table 5.5

Profile of a Tenant 

Company 

The ABC Company (ABC) is a tenant at the Port of Iberia. It has been engaged in metal 

fabrication since 1995. For the past five years ABC has manufactured process systems and 

equipment, including cold boxes, thermal vacuum control systems, and custom-engineered 

cryogenic and vacuum systems. Major customers include Beltech, Air Liquide, Praxair, 

Messar, Lockheed-Martin, Philips Petroleum, NASA, and other government-private sector 

joint ventures. 

Annual Tonnage - The ABC Company assembles 25 units per year. Each unit averages 

255,000 pounds. Average annual tonnage is estimated at 3,200 tons. 

Employment – The ABC Company employs approximately 100 people and 20 contract 

welders, with an annual payroll of about $2.5 million. 

Lease Agreement 

Primary term and rental - The initial lease is for a ten-year period (1995-2005) at an annual 

rent of $140,400, with an option to renew for three more 10-year periods by mutual consent. 

Location and access - The 20-ac site, leased from the Port, has 1,300 linear ft of water 

frontage with a 100-ft bulkhead. The site is well connected to the regional highway system, 

and the raw material supply by trucks is satisfactory. 

Buildings and other improvements - In addition to the slip and the 100-ft bulkhead, the 

present improvements at the site consist of (1) a stabilized fabrication and lay-down yard, (2) 

an open, concrete slab (100'x200') yard used for fabrication work, (3) a 55,000 ft2 fabrication 

building, and (4) a smaller fabrication building (15,000 ft2 capacity). The 55,000 ft2

fabrication building consists of three 50'x225' fabrication bays: one bay for small 

fabrication; one for pipe spooling and material preparation; and the third for equipment 

storage and warehouse space. The 15,000 ft2 building consists of one fabrication bay of 

35'x150' and two 32'x150' material preparation bays. 

Future Plans

The ABC Company plans to expand activities at the site by adding another fabrication 

building. 
60

Table 5.6

Fabrication Building: A New Project 

Project Description 

The ABC Company plans to construct a 27,500 ft2 fabrication building in order to meet the 

increasing demand for fabricated materials. The new building will provide two 75'x150' 

fabrication bays and one 50'x100' warehouse bay. Each bay will be equipped with electrical 

and mechanical welding stations and two 20 ton double girder overhead bridge cranes. 

Tenant’s Equipment 

The ABC Company is committed to supplying welding machines and equipment, plasma 

torches, and fitting equipment, estimated at $250,000. 

Project Cost and Modes of Financing 

The estimated project cost is $1.65 million. The Port of Iberia Port Commission applied to 

the Louisiana Port Construction and Development Priority Program (PCDP) for funding for 

the project. The PCPD will fund $1.25 million of the project with the Port providing the 

remaining $400,000. 

Port Revenue from the Project 

The ABC Company is committed to paying the Port an additional $98,000 in rent/yr for the 

additional improvements.

Other Project Benefits 

Tonnage - The ABC Company estimates that total output will increase by 50 percent. The 

new facility will increase output by 1,600 tons enlarging total output to 4,800 tons. 

Employment and payroll - The project is estimated to generate 52 jobs with an annual payroll 

of $1.2 million. 

5.3. Historical Trends 

5.3.1. Port Capital Investments 

In the 1990’s the Port of Iberia embarked on a systematic program to improve and expand 

Port facilities with state funds, federal grants, and self generated revenues. The PCDP program 

funded most of the development projects. The historical cumulative trend of these investments is 

illustrated in Figure 5.4. Projects undertaken during the 1992-2000 period can be classified into 

three functional categories and roughly corresponds with three time periods: 

1. Projects to provide basic port infrastructure and amenities in the early 1990’s. 

The development of a wastewater collection system, sanitary sewer collection, 

and a drinkable water system were undertaken during this period providing the 
61

basic amenities at the Port. In addition, the public dock area was developed, 

expanding the basic infrastructure available for public use. By making these 

investments in the early 1990’s, the Port laid the foundation for growth. 

2. Port expansion projects in the mid 1990’s. A major expansion of the Port was 

undertaken in 1995 by purchasing additional land and by developing a new 170-

ac slip. This project provided the Port with opportunities to expand its customer 

base. 

3. Port expansion projects in the late 1990’s. During this period, the Port made 

terminal improvements such as building bulkheads, warehouses, etc., sharing the 

costs with tenants. All tenants who participated in these projects were engaged in 

offshore supply activities, indicating the demand pressures for Port services. 

 Figure 5.4. Capital Expenditures, Cumulative Trend (1990-2000). 

5.3.2. Port Financial Performance 

Table 5.7 shows the Port’s financial performance during the 1990’s from annual financial 

reports. 

Growth Trends in Total Assets and Operating Revenues 

During the 1992-2000 period, total assets at the Port grew by 125 percent, while operating 

revenues grew by 205 percent (Figure 5.5a). This indicates better returns on assets, which in 

turn, points to the increased demand for facilities. 

Port of Iberia, Project Investments

0

2000

4000

6000

8000

10000

90 91 92 93 94 95 96 97 98 99 00

($1000)

Investments
62

Table 5.7 

Financial Performance Trends, Selected Years 

1992 

($) 

1994 

($) 

1996 

($) 

1998 

($) 

2000 

($) 

Change 

1992 - 2000 

(%) 

Operating 

Revenue 

455,429 744,445 1,021,856 1,085,665 1,388,130 205 

Operating 

Expenses 

411,105 604,965 438,612 578,043 554,976 35 

Depreciation 161,496 356,701 358,109 690,593 813,940 404 

Non-operating 

Income 

128,577 61,684 119,227 125,007 187,628 46 

Net Income 11,405 -155,537 344,362 -57,964 206,842 1,714 

Total Assets 14,931,158 17,491,571 28,599,228 30,356,119 33,610,795 125 

Source: Annual Financial Reports, Port of Iberia. 
63

5.5 a. Growth in Op. Revenue & Expenses

0

50

100

150

200

250

(percent Growth)

Op.rev. 63 124 138 205

OP. exp. 47 7 41 35

92-94 92-96 92-98 92-00

5.5.b. Growth in Assets & Op. Revenue

0

50

100

150

200

250

(Percent Growth)

Op. rev. 63 124 138 205

T. assets 17 92 103 125

92-94 92-96 92-98 92-00

5.5.c. Growth in Depreciation

0

50

100

150

200

250

300

350

400

450

(Percent Growth)

Op. rev 63 124 138 205

T. assets 17 92 103 125

Depr. 121 122 328 404

92-94 92-96 92-98 92-00

5.5.d. Growth in Retained Earnings

0

50

100

150

200

250

(Percent Growth)

Op. rev 63 124 138 205

T. assets 17 92 103 125

Ret. Earn 44 65 181 235

92-94 92-96 92-98 92-00

Figure 5.5. Financial Performance Trends (1992-2000).

The growth rate for operating revenues and expenses were 205 percent and 35 percent 

respectively (Figure 5.5b). This is typical for a landlord port with expenses that are substantial in 

the initial stages (i.e., salaries, insurance, marketing, and promotion) and then more or less 

constant thereafter. 

Growth Trends in Depreciation 

Depreciation grew by 404 percent during the 1992-2000 period, a rate faster than most other 

indexes (Figure 5.5c). The reason for this growth is the aggressive capital investment program 

initiated by the Port. Since depreciation is a noncash accounting expense, is available to the Port 

for reinvestment or to meet any other Port expenses. 
64

Growth in Retained Earnings 

With steep increases in depreciation and increases in net income, the retained earnings of the 

Port increased by 245 percent during the analysis period (Figure 5.5d). 

Sources and Uses of Funds 

Major sources of operating revenues and expenses for the Port are shown in Figure 5.6. 

Eighty-seven percent of the operating revenues are derived from leasing Port facilities. Each 

year the Port tries to recover 6 percent of its capital costs (for site improvements) from its 

leaseholders. According to the terms of the lease agreement, routine maintenance of leased 

facilities is the responsibility of tenants. The revenues from contract and dockage fees are 

primarily from public dock operations performed by private labor contractors. 

5.6.a. Operating Revenue

87%

7% 4% 2%

Leases Ton.Fees Dockage Other

5.6.b. Operating Expenses

60%

8%

21%

11%

Depr. Subcontract Payroll Other

 Figure 5.6. Financial Indicators, Sources, and Uses of Funds (2000). 
65

5.3.3. Port Employment 

Results from a survey on Port employment data are shown in Table 5.8. The survey, 

conducted in 1999, was completed for the Port’s Master Plan Study. The results are a 

compilation of a mail survey and personal interviews. According to survey estimates, 3,538 

persons were employed in Port-related activities in 1999 generating an annual payroll of $118 

million by the public Port and the private sector Port tenants around the Commercial Canal area. 

Although the vast majority of these workers were engaged in the offshore oil and gas service 

sector, it is difficult to desegregate them because of the interrelated nature of activities. 

Table 5.8 

Employment by Job Categories 

Job Category Occupations Included 

Number 

Employed 

Administrative/Professional Managers, engineers, foremen, supervisors 606 

Technicians Electronic and engineering technicians 164 

Sales/Clerical/Support Services Shipping, dispatchers, clerical, security, 

maintenance workers, etc 

337 

Skilled Labor Electricians, welders, divers, fitters, etc 1,069 

Transportation and Equipment 

Pperators 

Crane/truck/heavy equipment operators 232 

Mariners Boat captains, mates, and seamen 380 

Laborers/Helpers Painters, riggers, warehousemen, shop hand 750 

Total 3,538 

Source: Port of Iberia, Master Development Plan, 2000 

5.4. Conclusions 

Constraints imposed by the existing access channel from the port to the GOM are a major 

limitation in expanding OCS services from the port. Currently, the port is sponsoring a project to 

develop an access channel 20 feet in depth and 125 feet wide with the U.S. Army Corps of 

Engineers. The route selected consists of the Commercial Canal, a section on the GIWW to the 

west and then to gain access to the GOM through Freshwater Bayou. The total distance of this 

option is 51 miles including the distance from the mouth of the Freshwater Bayou to the 20-foot 

contour of the GOM6

. 

 

6

 Benefit-Cost Analysis for Acadiana Gulf of Mexico Access Channel, Coastal Engineering and Environmental 

Consultants, Inc., July 2001 
66

The location of the port with its connections to highways and rail, the availability of trained 

and skilled labor, the proximity to GOM, and healthy financial position of the port lay down a 

strong foundation for future development. The development of port infrastructure which started 

in the late 1990’s continues expanding the capabilities of the Port. Recently the Port expanded 

its capacity by adding new waterfront land and extending the network of channels and slips. The 

port’s marketing activities and financial performance are good indicators of the offshore 

industry’s demand for port services since more than 60 percent of the Port’s activities are oil and 

gas industry-related. With 55 percent of Port lands under long-term lease (beyond 2005), the 

Port is assured of a stable source of revenue over the next decade. Although operating revenues 

tripled over the 1992-2000 period and operating expenses grew at a much slower rate, net 

income at the Port was inconsistent. This was due to the substantial increase in depreciation of 

added assets. 
67

6. Port of Galveston 

The Port of Galveston is located on Galveston Bay 9.3 mi inland from the GOM. The public 

Port, as presently constituted, was created in 1940 by City Charter, and remains a political 

subdivision of the City of Galveston. The Port is managed by a 7-member board consisting of 

one City Council representative and six members appointed by the City Council. Two members 

are appointed each year resulting in staggered terms while all appointments are for three years. 

The stated mission of the Port is to manage its assets and resources so as to create optimum 

economic benefit to the local community. The analysis in this chapter examines the trends of 

growth in OCS activities at the port during the 1990’s which coincides with the period of 

expansion in OCS oil and gas activities. 

6.1. Port Location and Transportation Links

Channel Access 

Public port facilities are strategically located, providing easy access to the GOM and the 

inland waterways network. The Galveston Ship Channel serves as the main access channel to 

the port. It is maintained at a minimum depth of 40 ft and a minimum width of 1,200 ft. Sailing 

time from open sea to the public docks, located 9.3 mi on the Ship Channel, is estimated at 30 

minutes. The Port’s location on the GIWW which connects with the Mississippi River system 

provides access to barge transportation. 

A classification of vessel traffic on the Galveston Ship Channel analyzed by types of vessels, 

by domestic or foreign, and by draft is shown in Table 6.1. Ninety-three percent of the vessel 

fleet using the channel is by vessels with less than 18-foot draft and mainly for domestic 

services. The tanker traffic accounted for 14 percent of the traffic volumes. 

Table 6.1

Analysis of Vessel Traffic on Galveston Ship Channel, 2001 

Vessel Draft Passenger/Dry 

Cargo 

Tanker Tow or Tug Total 

Foreign 

18 ft and less 846 4 1 851 

> 18 feet 329 52 0 381 

Total-Foreign 1,175 56 1 1,232 

Domestic 

18 ft and less 11,884 2,272 4,273 18,429 

> 18 feet 2 568 2 572 

Total-Domestic 11,886 2,840 4,275 19,001 

Total 13,061 2,896 4,276 20,233 

Highways 

Highway 45 is the main access to the Port. It connects to Interstate 10 and other major roads 

in Houston which is 49 mi from Galveston. 
68

Railroads 

The Galveston Railroad, L.C. (GVSR), a short-line railroad company, operates rail services 

at the Port. The company operates 43.3 mi of tract and with connections to BNSF and UP. The 

rail infrastructure is owned by the City of Galveston and has been leased to the present operator 

(GVSR) since 1987. 

6.2. Port Infrastructure 

The cargo throughput from all terminals at the Port of Galveston exceeded 4.2 million tons in 

2001 with 76 percent of the total consisting of bulk cargos and the rest as containers and general 

cargo (Table 6.2). The Port with 300 acres of waterfront land on Galveston Island and 549 acres 

on Pelican Island included 10 mid-stream berths and 20 alongside berths with more than one 

million square feet of warehouse space and on-dock rail services. Terminals at the Port can be 

broadly classified on a functional basis into four major categories: container and break-bulk 

cargo, bulk cargo, industrial, and cruise ship (Table 6.3). 

Table 6.2 

Port Tonnage (2001) 

Bulk Cargo Container and Other 

Cargo Type Tonnage Cargo Type Tonnage 

Grain 2,365,904 Container 732,572 

Sugar 372,670 RO/RO 97,834 

Cement 193,607 General 21,439 

Liquid-bulk 297,715 Bananas/Fruit 188,993 

Total 3,229,896 Total 1,040,838 

Total (%) 76 Total (%) 24 

Source: Port of Galveston 

 

6.2.1. Container and Break-bulk Cargo Terminals 

Four terminals are included in this category: one container terminal, two roll-on/roll-off 

(RO/RO) terminals, and a terminal handling fresh fruit. The container terminal, which is 

managed by the Port of Houston, consists of a two berth dock 1,350 ft in length with a 40 ft 

water depth. Several mutually beneficial economic factors form the background for this 

collaborative arrangement between two independent public port authorities. The terminal at 

Galveston was a convenient outpost for the Port of Houston to divert traffic from the congested 

Houston Ship Channel. Further, the Port of Houston intended to use its business contacts and 

marketing information to attract more shippers and shipping lines to the new terminal managed 
69

Table 6.3 

Classification of Cargo Terminals 

Terminal Operator Type of Activity 

Container and Break-bulk Cargo Terminals 

Pier 10 Port of Houston Container 

Pier 16/18 Del Monte Fresh Produce Bananas and other fresh fruit 

Pier 34 “K” Line RO/RO – vehicle handling 

Pier 37 Wallenius Wilhelmsen Lines RO/RO – vehicle handling 

Bulk Cargo Terminals 

Pier 30/32 ADM/Farmland Industries Inc. Grain elevator 

Pier 35/36 Imperial Sugar Company Sugar 

Pier 28 Cement 

Industrial Terminals 

Pier 14 Smith-Hamm, Inc. Vessel repair and fabrication 

Pier 34 Cooper Cameron Corp., Deep Flex 

Division 

Manufacture flexible pipes 

Pelican Island Newpark Shipbuilding-Pelican Island, 

Inc. 

Vessel repair and fabrication 

Pelican Island Edison Chouest Offshore, 

C Port Galveston LP 

Offshore multi-service (planned) 

Cruise Ship and Other Services 

Pier 19-22 Port of Galveston Tourism 

Pier 25 Carnival Cruise Lines 

Royal Caribbean International 

Cruise ships 

Pelican Island Galveston Terminals Bunker fuel for vessels 

Pier 19 Port of Galveston Commercial fishing 
70

by them. For the Port of Galveston, it was an opportunity to lease an underutilized terminal and 

collaborate with a port partner with larger assets in terms of financial resources and management 

know-how. In 2001, the terminal handled 732,572 tons of cargo, an increase of approximately 4 

percent over 2000 tonnage. The Port of Houston is presently attempting to attract a new operator 

at the terminal since the current operator ceased operations in June 2002. In the meantime, the 

Port of Houston continues to pay their lease payments to the Port of Galveston. 

The two RO/RO terminals mainly handle farm vehicles and construction equipment (Table 

6.2 and Figure 6.1). Cargo transfer at RO/RO terminals is by driving in or driving out cargo 

using trailers in and out of the vessel. In the case of farm vehicles, the vehicles are driven out of 

the vessel over a ramp for unloading. Other cargo, such as construction equipment may be in 

containers already loaded on to trailers or stacked without trailers. In the latter case a tractor 

trailer will move into the ships hold, load the containers on board by fork-loaders and driven out. 

The two terminals also handle other break-bulk cargos: forest products (lumber, linerboard, 

plywood, newsprint, waste paper, pulp, and paper) and cotton bales. These are handled by 

conventional methods either using ship’s gear or using shore cranes. The cargo delivery could 

either be direct delivery, in which case cargo is transferred direct to rail, barge, or trucks for 

inland transportation or will be stored in port warehouses for delivery later to consignees. 

The fresh fruit terminal is managed by Del Monte Inc. and imports bananas from Guatemala and 

exports paper and plantation supplies. Major facilities at the terminal include a two-berth dock 

(1,200 ft in length with a 34 ft water depth) and 65,000 ft2

 of refrigerated warehouse space.

6.2.2. Bulk Cargo Terminals 

The bulk cargo terminals consist of a grain export elevator operated by Archer Daniels 

Midland/Farmland Industries, a sugar terminal, and a bulk cement terminal that began operating 

in December 1998. The cement silo complex located at Pier 28 is designed to ship about 2,800 

tons/day of imported cement by truck and rail out of the port. Rail service to the bulk terminals 

is provided by GVSR, and handles about 50,000 carloads/yr. 

6.2.3. Industrial Terminals 

Four industrial terminals are engaged in offshore activities. A detailed analysis of these 

terminals is presented below in Section 6.3. 

6.2.4. Cruise Ship Terminals 

The cruise ship industry is the fastest growing activity at the Port. In September 2000, 

renovations to the Texas Cruise Ship Terminal on Galveston Island were completed at a cost of 

$10.6 million. This is the greatest one time investment in improvements to a single facility in the 

Port’s 175-year history. Terminal facilities, located at Piers 23 through 26, consist of a 49,600 

ft2

 embarkation area, a 60,800 ft2 disembarkation area, and a 137,800 ft2 cruise terminal area. 

Royal Caribbean International Lines and Carnival Cruise Lines operate this terminal. The 

enlarged terminal combining piers 23-26 is referred to as Pier 25. 
71

6.1.a. Cargo Handled at Bulk Terminals

Grain

73%

Sugar

12%

Cement

6%

Liquid-bulk

9%

6.1.b. Cargo Handled at Other Terminals

RO/RO 

9%

General 

2%

Bananas

18%

Containers

71%

 Figure 6.1. Tonnage by Major Categories (2001). 

6.3. Offshore Supply Activities and Major Operators 

6.3.1. Smith-Hamm, Inc. 

At Pier 14’s Marine Repair Facility, Smith-Hamm, Inc. is engaged in repair and maintenance 

of vessels and offshore rigs. Infrastructure facilities include a 1,500-ft dock, with a minimum 

water depth of 24 ft, and a 35,000 ft2 staging area. In 1999, the company expanded its operations 

at the Port by leasing an additional six acres of waterfront land. Smith-Hamm typically employs 

100-125 people, depending on project requirements, and maintains a 3.5-ac offshore repair 

facility on the Houston Ship Channel. 
72

6.3.2. Cooper Cameron Corp-Deep Flex Division 

In March 1999 the Port signed a five-year lease agreement with Cooper Cameron Corp-Deep 

Flex Division for Pier 34’s Manufacturing Facility. The terminal, with a water depth of 40 ft and 

44,500 ft2

 of covered space, is the main facility supporting Deep Flex operation. The firm 

specializes in the manufacture of flexible pipes for the offshore oil and gas industry and is 

expected to construct a $20 million portable conveyor system that connects the manufacturing 

facility to the loading vessel. Deep Flex estimates two vessel calls a month and has identified 

offshore drilling sites in the GOM, South America, West Africa, and Eastern Canada as potential 

markets for their product. Table 6.4 describes Deep Flex’s planned operations at the Port. 

6.3.3. First Wave/Newpark Shipbuilding-Pelican Island, Inc. 

First Wave/Newpark Shipbuilding-Pelican Island, Inc. operates a 110-ac vessel repair and 

maintenance facility at the Pelican Island Marine Repair Facility. The company operates a 

network of five yards offering repair and maintenance services, environmental services, and new 

construction. Table 6.5 describes Newpark’s operations at the Port. 

Table 6.4 

Cooper Cameron Corp-Deep Flex Division Planned Development 

Development Stage/Facilities Description 

Lease Agreement Signed March 1999 for a 5-yr term 

Port Facilities 44,500 ft2 covered terminal at Pier 34 

Planned Construction Construction of a portable conveyor system 

$20 million estimated investment 

Manufacturing Schedule Year 1 - 10.5 km of flexible pipe 

Year 2 - 50 km 

Year 3 - 150 km/yr thereafter 

Shipping Year 1 - 2 ship/month by specialized vessels laying pipes 

Employment Year 1 - 25 employees 

Year 3 - 150 employees 

6.3.4. Edison Chouest Offshore/C Port Galveston, LP 

In April 2000, the Port entered into a lease agreement with Edison Chouest Offshore, C Port 

Galveston, LP (Chouest) for the development of an offshore multi-service terminal. The 100-ac 

site, located on port land on Pelican Island, is an indication of the increase in demand for 

offshore services in the WPA. Chouest plans to develop a multi-service facility known as C Port 

Galveston Full Service Center. Upon completion, the facility will create a centralized hub for 

goods and services required for deepwater offshore operations in the WPA. C Port Galveston 
73

will transport offshore fuel, water, cement, and liquid mud in bulk form, and various machinery 

and equipment mostly carried as deck cargo. Table 6.6 describes Chouest’s operations at the 

Port. 

The planned developments Cooper Cameron Corp and by Edison Chouest Offshore is behind 

schedule, and their business plans seem to be on hold. 

Table 6.5 

Newpark Shipbuilding, Pelican Island, Inc., Profile of a Marine Repair Facility 

Major Characteristics Description 

Location 110-ac facility at Pelican Island, Port of Galveston 

Operates 4 other yards: 

2 on the Houston Ship Channel 

2 in the Galveston area 

Facilities Multi-plant firm 

5,000-ton dry dock, water depths up to 40 ft 

Covered slip served by 500-ton crane capacity 

280,000 ft2

 of covered space for various activities 

Services - Repairs Repairs, conversions, and modifications to inland and ocean 

barges 

Top-side and in-water repairs to vessels 

OSV stretch jobs 

Converting offshore rigs 

Double-skinning of barges 

Services - New Construction Complementary capabilities at different yards make them mutually 

supporting in new construction 

Services - Fabrication Fabrication of offshore equipment 

Construction of oil platforms 

Services - Environmental Barge cleaning 

Wastewater treatment from vessels and rigs 

Gas-free services 

Marine chemist services 
74

Table 6.6 

Edison Chouest Offshore Service Center, Major Stages of Planned Development 

Development Stage/Facilities Description 

Lease Conditions Signed in April 2000 for a primary term of 10 yr 

Port revenue: 

Year 1 - $100,000 

Year 2 - $170,000 

Year 3 - $325,000/yr thereafter 

Facility Development 

(3 Phases) 

Phase One: Engineering, site work, marketing, and promotion 

Phase Two: Construction 

Phase Three: Plant operation 

Facilities and Cost 2,100 linear ft of water frontage and land area of 100 ac 

$89 million investment 

Products and Services One-stop service center for goods and services required in 

offshore deepwater drilling operations 

Projected Employment 250-300 jobs will be created in operational phase 

6.4. Development Trends 

The infrastructure facilities at Port of Galveston have steadily increased during the last three 

decades. The port-owned waterfront land, for example, increased from about 299 ac in 1965 to 

850 ac in 2000, almost tripling the size of the Port (Figure 6.2). The fastest growing port sectors 

in the 1990’s were the cruise ship industry and OCS service activities. The development trends 

of OCS activities at the Port clearly indicate the adjustments made by the offshore service 

providers. Out of the four port tenants presently engaged in OCS activities, three moved to the 

port in the 1990’s and the other tenant expanded activities during this time period. A summary 

of major developments: 

• The operator at the Marine Repair Facility in Pier 14, Smith-Hamm, Inc., 

expanded operations by leasing an additional six acres of port land in 1998, 

• The Manufacturing Facility at Pier 34, operated by Cooper Cameron Corp-Deep 

Flex Division, leased port land and started operations in 1999, 

• The Pelican Island Marine Repair Facility operated by Newpark ShipbuildingPelican Island Inc., leased a 110-ac facility in 1997, and 

• Edison Chouest began construction of C Port Galveston in 2000. 

As a result of the above developments, port tenants serving the offshore industry increased their 

share of leased port-owned land to 27 percent in 2000 from 4 percent in 1993 (Figure 6.3). 
75

 Figure 6.2. Port Owned Waterfront Land. 

6.4.1. Structural Changes in the Industry 

Although the industry-wide expansion in offshore activities was emphasized in this report, 

the regional differentials in expansion patterns were not evaluated. With most of the offshore 

expansion projects on hold in the Port of Galveston, a brief analysis of macroeconomic variables 

was undertaken to examine regional trends. 

6.4.2. Analysis of Industry Trends in Louisiana and Texas 

To start with, the numbers employed in the oil and gas industry and the state personal income 

from 1992 to 2000 for Texas and Louisiana were selected for a trend analysis. The data 

observations and the analysis results are shown in Table 6.7. The data indicate that the oil and 

gas sector in Texas is about five times larger (288,003/55917 = 5.15) than that of Louisiana in 

terms of the number employed in 1992. In contrast, in 2000 it is (216,260/55,086=3.93) only 

about four-times larger. However, this result has two major weaknesses in determining longterm changes in the industry. First, as they are point estimates, a peak or a valley in data in one 

year can skew the results. Second, for a comparative analysis to be valid, the economic 

conditions in both regions have to be stable during the period. 

Port of Galveston - Expansion Trend

0

100

200

300

400

500

600

700

800

900

1965 1969 1970 1974 1993 1999 2002

Year

# Acres 
76

6.3.a. Land Leases, 1993

4%

96%

6.3.c. Land Leases, 2000

27%

73%

OCS Leases Other Leases

6.3.b. Land Leases 1999

15%

85%

 Figure 6.3. Land Leased to OCS Industries (1993, 1999, and 2000). 
77

Table 6.7 

Analysis of Long-Term Trends in the Oil and Gas Industry for 

Louisiana and Texas, 1992-2000 

Year State Personal Income 

(Million $) 

Employment in Oil and Gas 

Industry (1,000 jobs) 

 Texas Louisiana Texas Louisiana 

Data 

1992 337,934 72,466 288,003 55,917 

1993 356,784 75,911 278,841 54,970 

1994 377,583 80,871 272,372 56,469 

1995 402,097 84,573 245,029 54,824 

1996 428,726 87,879 226,052 56,210 

1997 468,950 92,286 240,872 61,458 

1998 511,964 97,458 238,944 64,473 

1999 539,527 99,052 219,844 54,573 

2000 586,587 103,630 216,260 55,086 

Trend Analysis Results 

Trend1992-2000 7,200 4,500 -3,600 300 

Forecast 2010 -- -- 122,530 61,339 

 Source: U.S. Bureau of Labor Statistics (Website: http//www.bls.gov.). 

Trend Analysis 

A trend analysis, that estimates the trend-line minimizing squared deviations for all 

observations are shown under trend analysis in Table 6.7. State personal income in Texas 

increased by $7.2 million a year during the period compared to $4.5 million in Louisiana. From 

a qualitative analysis since both states experienced steady growth, the patterns of growth are 

comparable. In terms of numbers employed in the oil and gas industry, Texas on the average lost 

3,600 jobs/yr compared to 300 jobs/yr gain in Louisiana. Based on this analysis, there is 

evidence to indicate that structural changes are taking place in the oil and gas industry – moving 

activities to Louisiana. A rigorous analysis is beyond the purview of this report. Assuming these 

trends to continue, the numbers employed in Texas in 2010 will be about twice that of Louisiana. 

6.4.3. Port of Galveston and Industry Trends 

Another added reason for the slow progress in offshore oil and gas projects at the Port of 

Galveston may be the timing of the investments. In order to examine this hypothesis the same 

data described earlier in Table 6.7 were arranged as three year moving averages and the 

percentage change for the periods were calculated (Table 6.8). Results indicate that both Texas 

and Louisiana experienced severe downturns in the industry during the 1997-2000-period. In 

fact, when the effects of both states are combined it is the most severe downturn in a decade. 
78

Table 6.8 

Analysis of Long-Term Trends in the Oil and Gas Industry for 

Louisiana and Texas, Three Year Moving Averages, 1992-2000 

Year State Personal Income 

(Million $) 

Employment in Oil and Gas 

Industry (1,000 jobs) 

 Texas Louisiana Texas Louisiana 

1992 337,934 72,466 288,003 55,917 

1993 356,784 75,911 278,841 54,970 

1994 377,583 80,871 272,372 56,469 

1995 402,097 84,573 245,029 54,824 

1996 428,726 87,879 226,052 56,210 

1997 468,950 92,286 240,872 61,458 

1998 511,964 97,458 238,944 64,473 

1999 539,527 99,052 219,844 54,573 

2000 586,587 103,630 216,260 55,086 

Percentage Change – 3-Year Moving Average 

1992-1994=100 

1993-1995 5.98 5.28 -1.60 -0.65 

1994-1996 6.33 4.96 -6.63 0.75 

1995-1997 7.56 4.51 -4.24 2.98 

1996-1998 8.45 4.87 -0.85 5.59 

1997-1999 7.86 4.02 -0.88 -0.90 

1998-2000 7.74 3.93 -3.52 -3.53 

Average 7.32 4.59 -2.95 0.71 

 Source: U.S. Bureau of Labor Statistics (Website: http//www.bls.gov.). 

6.5. Conclusions 

The Port of Galveston backed by a much larger industrial base in the Houston area is 

strategically located to play an important role as a service base for the offshore oil and gas 

industry. The technological and scientific challenges faced by the industry as it moves to ultradeep-sea exploration will require more contributions from the Galveston-Houston industrial 

base. The Port of Galveston is located as an outpost with proximity to many areas that can 

deliver these services. 

 Further, the port with its 40 ft access channel and corresponding infrastructure, is 

strategically located to serve the expanding OCS-deepwater logistical needs. Overall, the OCS 

service sector at the Port has expanded its capacity during the last decade and is poised to serve 

the increasing demand for services in the WPA as well as international markets. 
79

REFERENCES 

Baud, R.D, R. Peterson, G. E. Richardson, L. S. French, J. Regg, T. Montgomery, T. S. 

Williams, C. Doyle and M. Dorner. 2002. Deepwater Gulf of Mexico 2002: America’s 

Expanding Frontier. Minerals Management Service, Gulf of Mexico OCS Region, OCS 

Report, 2002-021. New Orleans, LA. 133 p. 

Benefit-Cost Analysis for Acadiana Gulf of Mexico Access Channel (AGMAC). 2001. A Report 

prepared by Coastal Engineering and Environmental Consultants, Inc. for the Port of Iberia, 

New Iberia, Louisiana. 

Louisiana Department of Transportation and Development. 2001. Port Construction and 

Development Priority Program, Eighth Annual Report. 

Port Fourchon Feasibility Study, August 1994. Environmental Impact Statement, Main Report, 

U.S. Army Corps of Engineers, New Orleans District. 

Port of Iberia. 2000. Master Development Plan. New Iberia, Louisiana. 

URS and Greiner-Clyde. 1999. Preliminary Implementation Plan for the OCS Intermodal 

Support Corridor. Report prepared for the U.S. Army Corps of Engineers, New Orleans 

District. 

U. S. Army Corps of Engineers, Port Fourchon, Feasibility Study. 1994. Main Report, 

Environmental Impact Statement. 

U. S. Army Corps of Engineers. 2001. Waterborne Commerce of the United States, Part 2- 

Waterways and Harbors, Gulf Coast, Mississippi River System and Antilles. (Website: 

http://ntl.bts.gov/lib/23000/23500/23560/wcusmvgc01.pdf ). 

U. S. Bureau of Labor Statistics (Website: http://www.bls.gov). 
81

Appendix A: Data and Regression Model Output - Port Fourchon 

 

Appendix A: Table A.1.1 The Data Used in Regression Models - Port Fourchon 

 

Year 

OCS 

Activities 

Miles of 

Pipe Southbound 

Galliano 

Br. 

Fuel - 

Tons 

Water - 

Tons 

Dry 

Cargo 

Cargo 

Total 

Dev. 

Wells Expl. Wells 

OCS 

total 

Lines 

Appd. 

TrucksLA1 Openings Millions Millions 

Tons 

Miin. 

Tons 

Miln 

 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) 

1992 27 7 34 76 3.900 

1993 29 12 41 52 4,188 4.900 

1994 37 28 65 193 87,235 4,383 6.800 

1995 51 34 85 139 98,550 4,492 7.300 

1996 71 42 113 329 116,435 4,599 0.453 2.261 6.278 8.992 

1997 88 84 172 285 144,175 4,623 0.219 2.040 8.827 11.086 

1998 57 112 169 450 146,365 5,089 0.511 2.511 12.989 16.011 

1999 49 123 172 512 151,110 4,643 0.510 3.740 15.521 19.771 

2000 67 146 213 241 168,630 5,218 0.693 3.527 20.992 25.212 

2001 60 148 208 711 211,335 5,717 0.883 3.856 22.468 27.207 

Truck Traffic Relationships 

 

Regression Model 1:1 

 Independent Variable: Column (3) Total Number of OCS Wells Drilled 1994-2001 

 Dependent Variable: Column (5) Southbound Truck Traffic on La 1 1994-2001 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.933966808 

R Square 0.872293999 

Adjusted R 

Square 0.851009666 

Standard Error 15402.06323 

Observations 8 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 9722112312 9722112312 40.982914 0.000684646 

Residual 6 1423341310 237223552 

Total 7 11145453622 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 39816.66793 16640.36812 2.39277567 0.0538222 -900.875811 80534.21167 -900.875811 80534.21167 

X Variable 1 672.7666304 105.0903956 6.40178987 0.0006846 415.6195078 929.9137529 415.6195078 929.9137529 
82

Appendix A: Data and Regression Model Output - Port Fourchon (Contd.) 

 

Regression Model 1. 2: 

Independent Variable: Column (2) Number of OCS Exploratory Wells Drilled 1994-2001 

 Dependent Variable: Column (5) Southbound Truck Traffic on La 1 1994-2001 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.929959671 

R Square 0.864824989 

Adjusted R 

Square 0.842295821 

Standard Error 15846.06584 

Observations 8 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 9638866807 9638866807 38.386902 0.000814492 

Residual 6 1506586815 251097802 

Total 7 11145453622 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 73757.39041 12139.17948 6.07597824 0.0009028 44053.86655 103460.9143 44053.86655 103460.9143 

X Variable 1 744.4572897 120.1567722 6.19571645 0.0008145 450.4440447 1038.470535 450.4440447 1038.470535 

 

 

Regression Model 1. 3: 

 Independent Variable (lag): Column (4) Miles of Pipelines Approved 1992-1997 

 Dependent Variable: Column (5) Southbound Truck Traffic on La 1 1996-2001 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.920290751 

R Square 0.846935067 

Adjusted R 

Square 0.821424245 

Standard Error 16862.07833 

Observations 8 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 9439475509 9439475509 33.19905 0.001191612 

Residual 6 1705978113 284329686 

Total 7 11145453622 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 85326.79279 11276.72534 7.56662863 0.0002768 57733.61974 112919.9658 57733.61974 112919.9658 

X Variable 1 216.7095568 37.61103064 5.7618617 0.0011916 124.6786129 308.7405007 124.6786129 308.7405007 

 
83

Appendix A: Data and Regression Model Output - Port Fourchon (Contd.) 

 

Barge Traffic Relationships 

Regression Model 2. 1: 

 Independent Variable: Column (3) Total Number of OCS Wells Drilled 1993-2001 

 Dependent Variable: Column (6) Galliano Bridge Openings 1993-2001 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.843739647 

R Square 0.711896591 

Adjusted R 

Square 0.670738961 

Standard Error 274.5902388 

Observations 9 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 1304177.628 1304177.63 17.296832 0.004247346 

Residual 7 527798.5945 75399.7992 

Total 8 1831976.222 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 3893.852402 230.2299111 16.9128867 6.188E-07 3349.44556 4438.259244 3349.44556 4438.259244 

X Variable 1 6.38717963 1.535768841 4.15894597 0.0042473 2.755665982 10.01869328 2.755665982 10.01869328 

 

 

Regression Model 2. 2: 

 Independent Variable: Column (2) Number of OCS Exploratory Wells Drilled 1997-2001 

 Dependent Variable: Column (6) Galliano Bridge Openings 1997-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.867471379 

R Square 0.752506593 

Adjusted R 

Square 0.717150392 

Standard Error 254.5028871 

Observations 9 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 1378574.185 1378574.19 21.283582 0.00244509 

Residual 7 453402.0368 64771.7195 

Total 8 1831976.222 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 4141.88145 160.867583 25.7471479 3.408E-08 3761.490334 4522.272566 3761.490334 4522.272566 

X Variable 1 7.784728328 1.687411885 4.61341324 0.0024451 3.794636117 11.77482054 3.794636117 11.77482054 
84

Appendix A: Data and Regression Model Output - Port Fourchon (Contd.) 

 

Regression Model 2. 3: 

 

 Independent Variable (Lag) Column (4) Miles of Pipelines Approved 1993-1997 

 Dependent Variable: Column (6) Galliano Bridge Openings 1997-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.934685194 

R Square 0.873636413 

Adjusted R 

Square 0.852575815 

Standard Error 174.6124618 

Observations 8 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 1264766.929 1264766.93 41.482033 0.000662909 

Residual 6 182937.071 30489.5118 

Total 7 1447704 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 4207.093692 116.7742632 36.0275764 3.05E-08 3921.357155 4492.83023 3921.357155 4492.83023 

X Variable 1 2.508472721 0.389474804 6.44065469 0.0006629 1.555461511 3.461483932 1.555461511 3.461483932 

Cargo Tonnage Relationships 

 

Regression Model 3.1: 

 Independent Variable: Column (3) Total Number of OCS Wells Drilled 1992-2001 

 Dependent Variable: Column (10) Total Port Tonnage 1992-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.920496089 

R Square 0.84731305 

Adjusted R 

Square 0.828227181 

Standard Error 3.508133912 

Observations 10 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 546.3667825 546.366783 44.394785 0.000158666 

Residual 8 98.45602838 12.3070035 

Total 9 644.8228109 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept -1.45615164 2.452572769 

-

0.59372413 0.5690997 -7.11179825 4.199494959 -7.11179825 4.199494959 

X Variable 1 0.114575878 0.017195991 6.6629412 0.0001587 0.074921825 0.15422993 0.074921825 0.15422993 
85

Appendix A: Data and Regression Model Output - Port Fourchon (Contd.) 

Regression Model 3.2: 

 Independent Variable Column (2) Number of OCS Exploratory Wells Drilled 1992-2001 

 Dependent Variable: Column (10) Total Port Tonnage 1992-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.973244081 

R Square 0.947204041 

Adjusted R 

Square 0.940604546 

Standard Error 2.062887509 

Observations 10 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 610.7787719 610.778772 143.52675 2.17093E-06 

Residual 8 34.04403899 4.25550487 

Total 9 644.8228109 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 2.184254665 1.121810437 1.94708 0.0873855 -0.40264652 4.771155845 -0.40264652 4.771155845 

X Variable 1 0.148554964 0.012399973 11.9802649 2.171E-06 0.119960556 0.177149372 0.119960556 0.177149372 

 

Regression Model 3.3: 

 Independent Variable Column (2) Miles of Pipelines Approved 1992-1999 

 Dependent Variable: Column (10) Total Port Tonnage 1994-2001 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.963279116 

R Square 0.927906656 

Adjusted R 

Square 0.915891099 

Standard Error 2.336426392 

Observations 8 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 421.5650302 421.56503 77.225436 0.000120404 

Residual 6 32.75332971 5.45888828 

Total 7 454.3183599 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 3.642054841 1.562514311 2.33089375 0.0585691 -0.18128274 7.465392422 -0.18128274 7.465392422 

X Variable 1 0.045796936 0.005211422 8.78780043 0.0001204 0.033045036 0.058548835 0.033045036 0.058548835 
86

Appendix A: Data and Regression Model Output - Port Fourchon (Contd.) 

 

Appendix A: Table A.1..2 Cargo Handles at Port Fourchon, 1996-2000 Monthly Average (1000 tons) 

Month Gen/bulk Fuel Water Crew Change 

 # people 

January 902.5 39.2 168 11.3 

February 935.5 27.3 176.2 18.3 

March 1088.6 38.5 239.2 11.3 

April 1012.9 31.6 223.4 11.5 

May 915.1 36 215.5 11.5 

June 1030.1 35.9 212.4 11.8 

July 1043.7 36.8 240.4 15 

August 1063.4 37.6 224.4 13.7 

September 1232.6 41 362.1 15 

october 1289.9 39 225.8 15 

November 1281.3 37 252.4 14.4 

December 1072.3 39.2 276.2 14.4 

 12867.9 439.1 2816 163.2 

 

Regression Models by Cargo Type 

Model 1.4 Independent variable: Total OCS wells drilled 

 Dependent variable: Tonnage water 

water/total wells 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.674078762 

R Square 0.454382178 

Adjusted R 

Square 0.317977722 

Standard Error 0.667271916 

Observations 6 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 1.483195593 1.48319559 3.3311388 0.142026544 

Residual 4 1.781007241 0.44525181 

Total 5 3.264202833 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% 

Lower 

95.0% Upper 95.0% 

Intercept 0.338799492 1.477474455 0.22930988 0.829876 -3.76333572 4.440934707 

-

3.76333572 4.440934707 

X Variable 1 0.015188351 0.008321742 1.82514077 0.1420265 -0.00791656 0.038293258 

-

0.00791656 0.038293258 
87

Appendix A: Data and Regression Model Output - Port Fourchon (Contd.) 

 

Model 2:4 Independent variable: Exploratory wells drilled 

 Dependent variable: Tonnage water 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.826547799 

R Square 0.683181264 

Adjusted R 

Square 0.60397658 

Standard Error 0.508468439 

Observations 6 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 2.230042219 2.23004222 8.6255159 0.042519286 

Residual 4 1.034160615 0.25854015 

Total 5 3.264202833 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 1.189857166 0.646862886 1.83942717 0.1396912 -0.60612585 2.98584018 -0.60612585 2.98584018 

X Variable 1 0.016482224 0.005612073 2.93692287 0.0425193 0.000900581 0.032063868 0.000900581 0.032063868 

 

Model 3:4 Independent variable: Pipeline miles approved (Lag) 1994-1999 

 Dependent variable: Tonnage water 1996-2001 

 

SUMMARY OUTPUT 

Regression Statistics 

Multiple R 0.806987756 

R Square 0.651229238 

Adjusted R 

Square 0.564036547 

Standard Error 0.533492856 

Observations 6 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 2.125744323 2.12574432 7.4688513 0.052285377 

Residual 4 1.138458511 0.28461463 

Total 5 3.264202833 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 1.551031737 0.569517444 2.72341393 0.0528005 -0.03020546 3.132268931 -0.03020546 3.132268931 

X Variable 1 0.004522437 0.0016548 2.73291992 0.0522854 -7.2035E-05 0.009116909 -7.2035E-05 0.009116909 
88

Appendix A: Data and Regression Model Output for Port Fourchon (Contd.) 

 

Model 1.5 Independent variable: Total OCS wells drilled 1996-2001 

 Dependent variable: Tonnage fuel 1996-2001 

 

SUMMARY OUTPUT 

Regression Statistics 

Multiple R 0.5890095 

R Square 0.346932191 

Adjusted R 

Square 0.183665239 

Standard Error 0.203348053 

Observations 6 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 0.087867111 0.08786711 2.1249382 0.218658927 

Residual 4 0.165401722 0.04135043 

Total 5 0.253268833 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept -0.10025621 0.450253556 

-

0.22266613 0.8347032 -1.35036309 1.149850656 -1.35036309 1.149850656 

X Variable 1 0.003696788 0.002536013 1.45771679 0.2186589 -0.00334433 0.010737903 -0.00334433 0.010737903 

 

Model 2.5 Independent variable: Exploratory wells drilled 1996-2001 

 Dependent variable: Tonnage fuel 1996-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.710145739 

R Square 0.504306971 

Adjusted R 

Square 0.380383714 

Standard Error 0.177160658 

Observations 6 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 0.127725238 0.12772524 4.0695103 0.113847114 

Residual 4 0.125543595 0.0313859 

Total 5 0.253268833 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 0.114219784 0.225380074 0.50678741 0.6389641 -0.51153692 0.739976484 -0.51153692 0.739976484 

X Variable 1 0.003944552 0.001955359 2.01730273 0.1138471 -0.00148441 0.009373511 -0.00148441 0.009373511 
89

Appendix A: Data and Regression Model Output for Port Fourchon (Contd.) 

Model 3.5 Independent variable: Pipeline miles approved (Lag) 1994-1999 

 Dependent variable: Tonnage fuel 1996-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.959919163 

R Square 0.9214448 

Adjusted R 

Square 0.901806 

Standard Error 0.070525853 

Observations 6 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 0.233373249 0.23337325 46.919608 0.002377516 

Residual 4 0.019895584 0.0049739 

Total 5 0.253268833 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 0.068325925 0.075288175 0.90752531 0.4154587 -0.14070799 0.277359844 -0.14070799 0.277359844 

X Variable 1 0.001498451 0.000218759 6.8497889 0.0023775 0.000891078 0.002105824 0.000891078 0.002105824 

 

 

Model 1.6 Independent variable: Total OCS wells drilled 1996-2001 

 Dependent variable: 

General/bulk cargo 

tonnage 1996-2001 

 

SUMMARY OUTPUT 

Regression Statistics 

Multiple R 0.899840082 

R Square 0.809712174 

Adjusted R 

Square 0.762140217 

Standard Error 3.151246889 

Observations 6 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 169.0224977 169.022498 17.020788 0.014545611 

Residual 4 39.72142782 9.93035696 

Total 5 208.7439255 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept -13.7805058 6.97749548 

-

1.97499315 0.1194844 -33.1531791 5.592167504 -33.1531791 5.592167504 

X Variable 1 0.162137569 0.039300116 4.12562574 0.0145456 0.053022729 0.271252409 0.053022729 0.271252409 
90

Appendix A: Data and Regression Model Output for Port Fourchon (Contd.) 

Model 2.6 Independent variable: Exploratory wells drilled 1996-2001 

 Dependent variable: 

General/bulk cargo 

tonnage 1996-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.957509873 

R Square 0.916825158 

Adjusted R 

Square 0.896031447 

Standard Error 2.083401252 

Observations 6 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 191.3816824 191.381682 44.091465 0.00266976 

Residual 4 17.36224311 4.34056078 

Total 5 208.7439255 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept -2.15611496 2.650459385 

-

0.81348727 0.461588 -9.51498519 5.202755271 -9.51498519 5.202755271 

X Variable 1 0.152689603 0.022994936 6.64014041 0.0026698 0.088845293 0.216533912 0.088845293 0.216533912 

 

Model 3.6 Independent variable: Pipeline miles approved (Lag) 1994-1999 

 Dependent variable: Tonnage Gen/bulk cargo 1996-2001 

 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.943695959 

R Square 0.890562063 

Adjusted R 

Square 0.863202579 

Standard Error 2.389796253 

Observations 6 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 185.899421 185.899421 32.550397 0.004665972 

Residual 4 22.84450453 5.71112613 

Total 5 208.7439255 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 

Intercept 1.063712265 2.551169406 0.41695086 0.6981189 -6.01948421 8.146908745 -6.01948421 8.146908745 

X Variable 1 0.042291785 0.007412725 5.70529549 0.004666 0.021710719 0.062872851 0.021710719 0.062872851 
91

Appendix A: Data and Regression Model Output for Port Fourchon (Contd.) 

 

Appendix A: Table A.1.3. Port Fourchon, Correlation Matrix for Various Variables 

 

Column 

1 

Column 

2 

Column 

3 

Column 

4 

Column 

5 

Column 

6 

Column 

7 

Column 

8 

Column 

9 

Column 

10 

Column 1 1.0000 

Column 2 0.5522 1.0000 

Column 3 0.7333 0.9718 1.0000 

Column 4 0.4331 0.7982 0.7735 1.0000 

Column 5 0.3460 0.9300 0.9340 0.7983 1.0000 

Column 6 0.3966 0.8675 0.8437 0.7801 0.9138 1.0000 

Column 7 -0.5662 0.7101 0.5890 0.6105 0.7993 0.8829 1.0000 

Column 8 -0.6895 0.8265 0.6741 0.5740 0.7461 0.5973 0.8128 1.0000 

Column 9 -0.4831 0.9575 0.8998 0.4818 0.9014 0.8361 0.8631 0.8910 1.0000 

Column 10 0.4482 0.9732 0.9205 0.7913 0.9326 0.9027 0.8743 0.9136 0.9985 1.0000 

Notes: 

Column 1 Number of OCS Development wells Column 6 Number of Galliano bridge openings 

Column 2 Number of OCS Exploratory wells Column 7 Fuel tonnage 

Column 3 Total Number of OCS wells Column 8 Water tonnage 

Column 4 Miles of Pipelines Approved Column 9 General/bulk cargo tonnage 

Column 5 Annual truck traffic on LA 1 

Column 

10 Total port tonnage 
92

 A: Table A.1.4. Trend Extrapolation Estimates Through 2010 : Port Fourchon 

FORECASTING OF PORT ACTIVITIES 

Year OCS Activities Miles of Southbound 

Galliano 

Bridge Fuel Water Dry Cargo Total 

 Dev. Wells Expl. Wells 

OCS 

total Pipelines 

Trucks 

 LA Hwy 1 Openings 

Million 

Tons 

Million 

Tons 

Million 

Tons 

Million 

Tons 

 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) 

1992 27 7 34 76 3.900 

1993 29 12 41 52 4188 4.900 

1994 37 28 65 193 87235 4383 6.800 

1995 51 34 85 139 98550 4492 7.300 

1996 71 42 113 329 116435 4599 0.453 2.261 6.278 8.992 

1997 88 84 172 285 144175 4623 0.219 2.04 8.827 11.086 

1998 57 112 169 450 146365 5089 0.511 2.511 12.989 16.011 

1999 49 123 172 512 151110 4643 0.51 3.74 15.521 19.771 

2000 67 146 213 241 168630 5218 0.693 3.527 20.992 25.212 

2001 60 148 208 711 211335 5717 0.883 3.856 22.468 27.207 

2002 64 166 230 769 227113 5874 0.985 4.246 25.896 29.904 

2003 68 184 252 826 242890 6031 1.087 4.637 29.324 32.601 

2004 72 202 274 884 258668 6188 1.189 5.027 32.752 35.298 

2005 76 220 296 942 274445 6345 1.291 5.418 36.180 37.996 

2006 80 238 318 1000 290223 6501 1.393 5.808 39.608 40.693 

2007 84 256 339 1057 306000 6658 1.495 6.199 43.035 43.390 

2008 88 273 361 1115 321778 6815 1.597 6.589 46.463 46.087 

2009 92 291 383 1173 337555 6972 1.699 6.979 49.891 48.784 

2010 96 309 405 1230 353333 7129 1.801 7.370 53.319 51.481 
93

Appendix A: Data and Regression Model Output for Port Fourchon (Contd.) 

Appendix A: Table A.1.5. Cargo Forecasts Through 2010 for Water, Fuel, and Dry Cargo- Port Fourchon 

 

Year Water Water Water Fuel Fuel Fuel Dry Cargo Dry Cargo 

Dry 

Cargo 

Total wells Exp. wells Pipeline s Total wells Ex.wells Pipelines Total wells Exp. wells Pipelines 

Model 4.1 Model 4.2 Model 4.3 Model 4.4 Model 4.5 Model 4.6 Model 4.7 Model 4.8 Model 4.9 

2001 3.856 3.856 3.856 0.883 0.883 0.883 22.468 22.468 22.468 

2002 4.189 4.152 4.117 0.964 0.954 0.969 26.021 25.205 24.909 

2003 4.522 4.448 4.3509 1.045 1.024 1.056 29.575 27.943 27.670 

2004 4.855 4.743 4.5848 1.126 1.095 1.142 33.128 30.680 30.431 

2005 5.188 5.039 4.8187 1.207 1.166 1.229 36.681 33.417 33.192 

2006 5.520 5.335 5.0526 1.288 1.236 1.315 40.235 36.155 35.953 

2007 5.853 5.631 5.2865 1.369 1.307 1.402 43.788 38.892 38.714 

2008 6.186 5.927 5.5204 1.450 1.377 1.488 47.341 41.629 41.475 

2009 6.519 6.222 5.7543 1.531 1.448 1.575 50.895 44.367 44.236 

2010 6.852 6.518 5.9882 1.612 1.519 1.661 54.448 47.104 46.997 
95

 

 Appendix B: Data and Regression Model Output - Port of Morgan City 

 

Appendix B: Table 1 The Data and Variables Used In the Analysis 

 Dev. Expl. Total Pipeliine EP DOCD Self-prop Non SP Total 

 Wells Wells Wells miles Vessel Vessel Vessel 

 Trips Trips trips 

 

1992 27 7 34 76 25 3 18398 2112 20510 

1993 29 12 41 52 25 4 21540 2225 23765 

1994 37 28 65 193 37 4 23421 2515 25936 

1995 51 34 85 139 38 8 25302 2805 28107 

1996 71 42 113 329 64 10 28367 3643 32010 

1997 88 84 172 285 105 11 30168 4371 34539 

1998 57 112 169 450 125 16 22983 4095 27078 

1999 49 123 172 512 168 14 15479 3127 18606 

2000 67 146 213 241 157 27 18753 4266 23019 

2001 60 148 208 711 150 37 -- -- --- 

 

Appendix B: Table 2 Correlation Matrix Indicating Variable Relationships for Morgan City 

 Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 Column 9 

Column 1 1 

Column 2 0.5675412 1 

Column 3 0.758536 0.9670177 1 

Column 4 0.4932071 0.7422342 0.7400146 1 

Column 5 0.5407655 0.9810721 0.943754 0.8058073 1 

Column 6 0.5744607 0.9250053 0.9098042 0.5271029 0.8614299 1 

Column 7 0.5946418 -0.2571051 

-

0.0195263 

-

0.0730038 -0.3066105 

-

0.2043403 1 

Column 8 0.9149284 0.786163 0.9052451 0.6154918 0.7331255 0.7901586 0.3582037 1 

Column 9 0.7071948 -0.1033986 0.136943 0.0378146 -0.1583129 -0.053865 0.9871359 0.5028699 1 

 

Column (1) Number of Development wells drilled 

Column 2 Number of Exploratory Wells drilled 

Column 3 Total Number of wells drilled 

Column 4 Miles of Pipeline Approvals 

Column 5 Number of Exploration Plans Filed 

Column 6 Number of DOCDs Filed 

Column 7 Number of Self-Propelled Vessel trips 

Column 8 Number of None Self-Propelled Vessel trips 

Column 9 Number of Total Vessel trips 

 

 
96

 Appendix B: Data and Regression Model Output - Port of Morgan City 

 (Continued) 

Regression Model 4:1 

 Dependent Variable: Column (8): Number of non self-propelled vessel trips 1992-2000 

 Independent Variable: 

Column 

(1) Number of Development wells drilled 1992-2000 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.9149284 

R Square 0.837094 

Adjusted R 

Square 0.8138217 

Standard Error 381.54916 

Observations 9 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 5236440.5 5236440.5 35.969564 0.0005436 

Residual 7 1019058.3 145579.76 

Total 8 6255498.9 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% 

Upper 

95% 

Lower 

95.0% Upper 95.0% 

Intercept 1129.5222 374.15591 3.0188542 0.0194177 244.78465 2014.2597 244.78465 2014.2597 

X Variable 1 39.901892 6.6531284 5.9974631 0.0005436 24.169754 55.634029 24.169754 55.634029 

 

Regression Model 4:2 

 Dependent Variable: Column (8): Number of non self-propelled vessel trips 1992-2000 

 Independent Variable: 

Column 

(2) Number of Exploratory Wells drilled 1992-2000 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.786163 

R Square 0.6180523 

Adjusted R 

Square 0.5634883 

Standard Error 584.2301 

Observations 9 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 3866225.2 3866225.2 11.327115 0.0119925 

Residual 7 2389273.6 341324.81 

Total 8 6255498.9 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% 

Upper 

95% 

Lower 

95.0% Upper 95.0% 

Intercept 2364.3071 324.97251 7.2754065 0.0001662 1595.8698 3132.7444 1595.8698 3132.7444 

X Variable 1 13.401762 3.9820092 3.3655779 0.0119925 3.9858134 22.817711 3.9858134 22.817711 

 
97

 Appendix B: Data and Regression Model Output - Port of Morgan City 

 (Continued) 

 

Regression Model 4:3 

 Dependent Variable: Column (8): Number of non self-propelled vessel trips 1992-2000 

 Independent Variable: 

Column 

(3) Total Number of wells drilled 1992-2000 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.9052451 

R Square 0.8194688 

Adjusted R 

Square 0.7936786 

Standard Error 401.6596 

Observations 9 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 5126185.9 5126185.9 31.774451 0.0007851 

Residual 7 1129313 161330.43 

Total 8 6255498.9 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% 

Upper 

95% 

Lower 

95.0% Upper 95.0% 

Intercept 1795.9972 289.03078 6.2138614 0.0004393 1112.5485 2479.4459 1112.5485 2479.4459 

X Variable 1 12.213369 2.1666884 5.6368831 0.0007851 7.089969 17.33677 7.089969 17.33677 

 

Regression Model 4:4 

 Dependent Variable: Column (8): Number of non self-propelled vessel trips 1993-2000 

Independent Variable: (Lag) 

Column 

(4) Miles of Pipeline Approvals 1992-1999 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.6708839 

R Square 0.4500852 

Adjusted R 

Square 0.3584327 

Standard Error 664.95377 

Observations 8 

 

ANOVA 

 df SS MS F 

Significance 

F 

Regression 1 2171367.8 2171367.8 4.9107802 0.0685718 

Residual 6 2652981.1 442163.51 

Total 7 4824348.9 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% 

Upper 

95% 

Lower 

95.0% 

Upper 

95.0% 

Intercept 2544.3891 444.69613 5.7216354 0.0012357 1456.2561 3632.5221 1456.2561 3632.5221 

X Variable 1 3.2867815 1.4831859 2.216028 0.0685718 -0.3424463 6.9160092 

-

0.3424463 6.9160092 
98

 Appendix B: Data and Regression Model Output - Port of Morgan City 

 (Continued) 

Regression Model 4:5 

 Dependent Variable: Column (8): Number of non self-propelled vessel trips 1992-2000 

 Independent Variable: 

Column 

(5) Number of Exploration Plans Filed 1992-2000 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.7331255 

R Square 0.537473 

Adjusted R 

Square 0.4713977 

Standard Error 642.91047 

Observations 9 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 3362161.8 3362161.8 8.1342518 0.0246157 

Residual 7 2893337.1 413333.87 

Total 8 6255498.9 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% 

Upper 

95% 

Lower 

95.0% Upper 95.0% 

Intercept 2303.0358 392.20781 5.8719784 0.0006167 1375.6124 3230.4592 1375.6124 3230.4592 

X Variable 1 11.3329 3.9735828 2.852061 0.0246157 1.9368769 20.728924 1.9368769 20.728924 

 

Regression Model 4:6 

 Dependent Variable: Column (8): Number of non self-propelled vessel trips 1992-2000 

 Independent Variable: 

Column 

(6) Number of DOCDs Filed 1992-2000 

SUMMARY OUTPUT 

 

Regression Statistics 

Multiple R 0.7901586 

R Square 0.6243507 

Adjusted R 

Square 0.5706865 

Standard Error 579.39302 

Observations 9 

 

ANOVA 

 df SS MS F Significance F 

Regression 1 3905625 3905625 11.634401 0.0112737 

Residual 7 2349873.9 335696.28 

Total 8 6255498.9 

 

 Coefficients 

Standard 

Error t Stat P-value Lower 95% 

Upper 

95% 

Lower 

95.0% Upper 95.0% 

Intercept 2248.4579 348.97687 6.4429997 0.0003526 1423.2593 3073.6565 1423.2593 3073.6565 

X Variable 1 91.988445 26.968778 3.4109237 0.0112737 28.217464 155.75943 28.217464 155.75943 
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