OCS Study 

MMS 2010-007 

Coastal Marine Institute 

Assessment of Marginal Production 

in the Gulf of Mexico and Lost Production 

from Early Decommissioning 

U.S. Department of the Interior

Minerals Management Service 

Gulf of Mexico OCS Region 

Cooperative Agreement

Coastal Marine Institute 

Louisiana State University 
U.S. Department of the Interior Cooperative Agreement 

Minerals Management Service Coastal Marine Institute 

Gulf of Mexico OCS Region Louisiana State University 

OCS Study 

 MMS 2010-007 

Coastal Marine Institute 

Assessment of Marginal Production 

in the Gulf of Mexico and Lost Production 

from Early Decommissioning 

Authors 

Mark J. Kaiser 

Yunke Yu 

Allan G. Pulsipher 

April 2010 

Prepared under MMS Contract 

1435-01-04-CA-32806-39902 (M08AC12864) 

by 

Louisiana State University 

Center for Energy Studies 

Baton Rouge, Louisiana 70803 

Published by 
iii

DISCLAIMER

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

and Louisiana State University’s Center for Energy Studies. This report has been technically 

reviewed by the MMS, and it has been approved for publication. Approval does not signify that 

the contents necessarily reflect the views and policies of the 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 

This report is available only in compact disc format from the Minerals Management Service, 

Gulf of Mexico OCS Region, at a charge of $15.00, by referencing OCS Study MMS 2010-

007. The report may be downloaded from the MMS website through the Environmental Studies 

Program Information System (ESPIS). You will be able to obtain this report also from the 

National Technical Information Service in the near future. Here are the addresses. You may 

also inspect copies at selected Federal Depository Libraries. 

Minerals Management Service 

Gulf of Mexico OCS Region 

Public Information Office (MS 5034) 

1201 Elmwood Park Boulevard 

New Orleans, Louisiana 70123-2394 

Telephone requests may be placed at 

(504) 736-2519, 1-800-200-GULF, or 

Rush Orders: 1-800-553-6847 

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Email: bookstore@ntis.gov

CITATION 

Kaiser, M.J, Y. Yu, and A.G. Pulsipher. 2010. Assessment of marginal production in the Gulf 

of Mexico and lost production from early decommissioning. U.S. Dept. of the Interior, 

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

Study MMS 2010-007. 194 pp. 
v

ABSTRACT

During the 2004 and 2005 hurricane seasons in the Gulf of Mexico, Hurricanes Ivan, Katrina, 

and Rita destroyed 120 structures. When a structure is destroyed, its revenue stream is either 

lost or temporarily deferred. If the field is redeveloped, reserves will be recaptured after 

redevelopment; otherwise, reserves will be left behind in-the-ground and considered lost. We 

estimate the quantity and value of lost production from structures destroyed in the 2004 and 

2005 hurricane seasons and review operator redevelopment plans circa February 2009. A 

screening tool is developed to assess redevelopment potential and we estimate that about 70 

percent of the reserves impacted by the hurricanes and associated with destroyed structures will 

be recovered. A review of redevelopment plans indicate that gas producing assets appear to 

have more favorable economics with 11 of the 14 redevelopment plans thus far submitted for 

gas structures. 

As of June 2008, there were 3,847 structures in the Outer Continental Shelf of the Gulf of 

Mexico associated with the production of oil and gas. About 65 percent of the inventory, or 

2,514 structures, were producing with the remaining structures either serving in an auxiliary 

role or no longer in production. Structures in water depth less than 1,000 ft constitute the vast 

majority of the producing assets and contribute about 70 percent of the gas and 30 percent of 

annual oil production in the Gulf. A large portion of the shallow water assets are operating on 

the lower edge of profitability. 

We provide a historical analysis of marginal production in the Gulf and estimate the number of 

shallow water committed assets that are economic and marginal throughout a 60-year time 

horizon. Oil and gas reserves from the inventory of shallow water assets are estimated at 1,056 

MMbbl oil and 13.3 Tcf gas, and marginal production is expected to constitute 4.1 percent of 

the future oil and 5.4 percent of the total gas production. Marginal production is estimated to be 

valued at about 1 percent of the $149 billion shallow water production expected in the future. 

 
vii

TABLE OF CONTENTS

Page

LIST OF FIGURES ...................................................................................................................xiii

LIST OF TABLES.....................................................................................................................xix

EXECUTIVE SUMMARY ..........................................................................................................1

PART 1. MODELING LOST PRODUCTION AND POST-HURRICANE RECOVERY 

 IN THE GULF OF MEXICO ........................................................................................3

Chapter 1. Redevelopment Economics and Impact Assessment ..................................................3 

 1.1. Introduction ........................................................................................................3 

 1.2. Data Source ........................................................................................................4 

 1.2.1. Notice to Lessees and Operators ............................................................4 

 1.2.2. Plans for Exploration and Development.................................................5 

 1.3. Redevelopment Economics and Uncertainty......................................................6 

 1.3.1. Destroyed Structures ..............................................................................6 

 1.3.2. Cleanup Cost ..........................................................................................6 

 1.3.3. Decisionmaking Economics ...................................................................7 

 1.3.4. Revenue and Cost Uncertainty ...............................................................8 

 1.3.5. Redevelopment Strategies ......................................................................8 

 1.4. Structure and Production Classification .............................................................9 

 1.4.1. Structure Type ........................................................................................9 

 1.4.2. Production Status....................................................................................9 

 1.4.3. Production Type ...................................................................................10 

 1.5. Aggregate Assessment......................................................................................10 

 1.5.1. Energy Losses.......................................................................................10 

 1.5.2. Shut-In Production Profiles ..................................................................10 

 1.5.3. Damage Rates.......................................................................................11 

 1.5.4. Destroyed Structures ............................................................................11 

 1.5.5. Aggregate Production...........................................................................12 

 1.5.6. Structure Classification ........................................................................12

Chapter 2. Model Framework.....................................................................................................13 

 2.1. Model Framework ............................................................................................13 

 2.2. Model Production Profiles (STEP 1)................................................................13 

 2.2.1. Notation ................................................................................................13 

 2.2.2. Decline Curves .....................................................................................13 

 2.2.3. Production Classification......................................................................14 

 2.3. Forecast Future Production (STEP 2)...............................................................15 

 2.4. Forecast Future Revenue (STEP 3) ..................................................................15 
viii

TABLE OF CONTENTS 

(continued) 

Page

 2.5. Estimate Abandonment Time (STEP 4) ...........................................................16 

 2.6. Cumulative Production and Discounted Cash Flow (STEP 5).........................16 

 2.7. Aggregation ......................................................................................................17 

 2.8. Economic Limit and Estimation Techniques ...................................................17 

 2.8.1. Economic Limit ....................................................................................17 

 2.8.2. Estimation Techniques .........................................................................18

 2.9. Descriptive Statistics ........................................................................................18

Chapter 3. Model Results and Limitations .................................................................................21 

 3.1. Value of Lost Production..................................................................................21 

 3.2. Rate of Return Calculation ...............................................................................21 

 3.3. Average Redevelopment Costs.........................................................................22 

 3.4. Sensitivity Analysis..........................................................................................22 

 3.5. Limitations of the Analysis ..............................................................................22 

 3.5.1. Public Data Sources Have Limited Information Content.....................22 

 3.5.2. Inventory of Destroyed Structures May Change in the 

 Future....................................................................................................23 

 3.5.3. Decline Curves Are Subject to Significant Uncertainty.......................23 

 3.5.4. Decline Curves May Not Be a Reliable Predictor................................23 

 3.5.5. Stage of Production May Not Help to Reduce Forecast Error .............23

Chapter 4. Evaluation of Post-Hurricane Recovery of Destroyed Platforms .............................25 

 4.1. Composite Production ......................................................................................25 

 4.2. Recovered Production ......................................................................................25 

 4.3. Revenue Comparison........................................................................................26 

 4.4. Redevelopment Rates .......................................................................................27 

 4.5. Exploration and Development Plans ................................................................28 

 4.6. Redevelopment Opportunity Matrix.................................................................29 

 4.7. Redevelopment Success ...................................................................................29 

 4.8. Recovery Time .................................................................................................29 

 4.9. Remaining Reserves .........................................................................................30 

 4.10. Production at Risk ............................................................................................30 

 4.11. Redevelopment Potential..................................................................................31 

 4.12. Remaining Reserves and Discounted Revenue ................................................31 

 4.13. Redevelopment Potential Drilling Profiles.......................................................31 

 4.14. Redevelopment Potential Production Forecast.................................................32
ix

TABLE OF CONTENTS 

(continued) 

Page

PART 2. MARGINAL PRODUCTION IN THE GULF OF MEXICO.....................................33

Chapter 5. Wellbore and Structure Categorization.....................................................................33 

 5.1. Introduction ......................................................................................................33 

 5.2. Life Cycle Stages..............................................................................................34 

 5.2.1. Exploration and Delineation.................................................................34 

 5.2.2. Development.........................................................................................34 

 5.2.3. Redevelopment.....................................................................................35 

 5.2.4. Sunset Production.................................................................................35 

 5.3. Wellbore Definitions ........................................................................................36 

 5.3.1. Aggregation Unit..................................................................................36 

 5.3.2. Exploration and Development Wells....................................................36

 5.3.3. Production Status..................................................................................36 

 5.3.4. Fluid Classification...............................................................................36 

 5.3.5. Gas-Oil Ratio........................................................................................37 

 5.4. Wellbore Counting Statistics............................................................................37 

 5.4.1. Exploration and Development Wells....................................................37 

 5.4.2. Producing Wells ...................................................................................38 

 5.5. Wellbore Production Statistics .........................................................................38 

 5.5.1. Aggregate Production...........................................................................38 

 5.5.2. Oil Producers........................................................................................39 

 5.5.3. Gas Producers.......................................................................................39 

 5.6. Structure Definitions ........................................................................................40 

 5.6.1. Aggregation Unit..................................................................................40 

 5.6.2. Structure Type ......................................................................................40 

 5.6.3. Production Status..................................................................................40 

 5.6.4. Production Type ...................................................................................41 

 5.7. Structure Counting Statistics ............................................................................41 

 5.7.1. Active Structures ..................................................................................41 

 5.7.2. Producing Structures ............................................................................42 

 5.7.3. Non-producing Structures ....................................................................42 

 5.8. Structure Production Statistics .........................................................................42 

 5.8.1. Aggregate Production...........................................................................42 

 5.8.2. Oil Producers........................................................................................43 

 5.8.3. Gas Producers.......................................................................................43

Chapter 6. Shallow Water Committed Assets Production Forecast ...........................................45 

 6.1. Historical Production........................................................................................45 

 6.2. Factors that Impact Production.........................................................................45 

 6.2.1. Drilling Schedule..................................................................................45
x

TABLE OF CONTENTS 

(continued) 

Page

 6.2.2. Level of Aggregation............................................................................46 

 6.2.3. Reservoir Drive Mechanism.................................................................46 

 6.2.4. Enhanced Recovery..............................................................................46 

 6.2.5. Fluid Classification...............................................................................46 

 6.2.6. Development Plan ................................................................................47 

 6.2.7. Reservoir Pressure................................................................................47 

 6.2.8. Workover Schedule ..............................................................................48 

 6.2.9. Problem Wells ......................................................................................48 

 6.2.10. Cost Structure .......................................................................................48 

 6.2.11. Weather Events.....................................................................................48

 6.2.12. System Reconfiguration .......................................................................49 

 6.2.13. Price Effects..........................................................................................49 

 6.2.14. Regulations and Operating Policy ........................................................49 

 6.3. Production Classification..................................................................................49 

 6.4. Forecast Methodology......................................................................................50 

 6.4.1. Young Structures – History Matching..................................................50 

 6.4.2. Normal and Chaotic Structures – Regression Techniques ...................51 

 6.4.3. Latecomer Structure - Heuristics..........................................................52 

 6.5. Illustrative Examples ........................................................................................52 

 6.5.1. Young Structures – History Matching..................................................52 

 6.5.2. Normal Structure – Regression Techniques .........................................53 

 6.5.3. Chaotic Structure – Regression Techniques.........................................53 

 6.5.4. Latecomer Structure - Heuristic Method..............................................54 

 6.6. Model Results...................................................................................................54 

 6.6.1. Active Structure Forecast .....................................................................54 

 6.6.2. Production Forecast..............................................................................55 

 6.6.3. Composite Statistics .............................................................................55 

 6.6.4. Cumulative Production Models............................................................55 

 6.6.5. Present Value Models...........................................................................56

Chapter 7. Meta-Model Evaluation of Marginal Production......................................................57 

 7.1. Model Framework ............................................................................................57 

 7.1.1. General Procedure ................................................................................57 

 7.1.2. Preprocessing (STEP 0)........................................................................57 

 7.1.3. Initialization (STEP 1)..........................................................................58 

 7.1.4. Forecasting (STEP 2) ...........................................................................58 

 7.1.5. Aggregation (STEP 3) ..........................................................................60 

 7.1.6. Simulation and Regression Analysis (STEP 4)....................................61 

 7.2. Model Structure and Interpretation ..................................................................61 

 7.2.1. Model Specification..............................................................................61 

 7.2.2. Expected Signs .....................................................................................61
xi

TABLE OF CONTENTS 

(continued) 

Page

 7.2.3. Design Space ........................................................................................63 

 7.3. Model Results...................................................................................................63 

 7.3.1. Producing Structure Count ...................................................................63 

 7.3.2. Structure Count Envelopes ...................................................................64 

 7.3.3. Aggregate Production Profiles .............................................................64 

 7.3.4. Production Envelopes...........................................................................65 

 7.3.5. Production by Asset Category..............................................................65

 7.3.6. Summary Statistics ...............................................................................65 

 7.3.7. Cumulative Production Functions ........................................................65 

 7.3.8. Valuation Functions..............................................................................66

REFERENCES ...........................................................................................................................67

APPENDIX A. CHAPTER 1 TABLES AND FIGURES ..........................................................71

APPENDIX B. CHAPTER 2 TABLES......................................................................................85

APPENDIX C. CHAPTER 3 TABLES AND FIGURES ..........................................................89

APPENDIX D. CHAPTER 4 TABLES AND FIGURES ..........................................................97

APPENDIX E. CHAPTER 5 TABLES AND FIGURES.........................................................127

APPENDIX F. CHAPTER 6 TABLES AND FIGURES.........................................................161

APPENDIX G. CHAPTER 7 TABLES AND FIGURES ........................................................181 

 
xiii

LIST OF FIGURES

Page

Figure A.1. Model Rendition of Hurricane Destroyed Structure Lying Horizontally 

 on the Seafloor ....................................................................................................76 

Figure A.2. Hurricane Destroyed Platform in the East Cameron Area..................................77 

Figure A.3. Hurricane Destroyed Platform Suspected to Be Due to a Foundation 

 Failure. ................................................................................................................78 

Figure A.4. Structures Destroyed by Hurricane Ivan and Hurricane Force Wind 

 Swath...................................................................................................................79 

Figure A.5 Structures Destroyed by Hurricane Katrina and Hurricane Force Wind 

 Swath...................................................................................................................80 

Figure A.6. Structures Destroyed by Hurricane Rita and Hurricane Force Wind 

 Swath...................................................................................................................81 

Figure A.7. Shut-In Oil Production in the Gulf of Mexico....................................................82 

Figure A.8. Shut-In Gas Production in the Gulf of Mexico...................................................83 

Figure C.1. Cumulative BOE Production as a Function of Threshold Level and 

 Price Scenario .....................................................................................................94

Figure C.2. Cumulative Oil Production as a Function of Threshold Level and Price 

Scenario...............................................................................................................94 

Figure C.3. Cumulative Gas Production as a Function of Threshold Level and Price 

Scenario...............................................................................................................95 

Figure C.4. Present Value as a Function of Threshold Level Multiplier and Discount 

 Rate for Price Deck P(I)......................................................................................95 

Figure C.5. Present Value as a Function of Threshold Level Multiplier and Discount 

 Rate for Price Deck P(III)...................................................................................96 

Figure D.1 Pre- and Post-Hurricane Production from All Structures Destroyed by 

 Ivan, Katrina, and Rita......................................................................................118 

Figure D.2. Longer Term View of Production from All Structures Destroyed by 

 Ivan, Katrina, and Rita through December 2008 ..............................................118 

Figure D.3. Pre- and Post-Hurricane Production from Destroyed Structures that 

 Restarted Production.........................................................................................119 

Figure D.4. Pre- and Post-Hurricane Aggregate Monthly Gross Revenue from All 

Structures Destroyed by Ivan, Katrina, and Rita ..............................................119 

Figure D.5. Pre- and Post-Hurricane Aggregate Monthly Gross Revenue from 

 Destroyed Structures that Restarted Production through December 

 2008...................................................................................................................120 

Figure D.6. Gas Structures that Restarted Production, Leases that Have Submitted 

 DOCD Plans, Structures that Have Been Decommissioned, and Those

Structures that Have Not Restarted Production ................................................120

Figure D.7. Oil Structures that Restarted Production, Leases that Have Submitted 

 DOCD Plans, Structures that Have Been Decommissioned, and Those

 Structures that Have Not Restarted Production ................................................121 
xiv

LIST OF FIGURES 

(continued) 

Page

Figure D.8. All Structures that Restarted Production, Leases that Have Submitted 

 DOCD Plans, Structures that Have Been Decommissioned, and Those

 Structures that Have Not Restarted Production ................................................121 

Figure D.9. Redevelopment Opportunities Outlined by Regions: (I) Unlikely 

 Redevelopment, (II) Possible Redevelopment, and (III) Probable

 Redevelopment .................................................................................................122 

Figure D.10. Aggregate Annual Drilled Wellbores, Sidetrack Wells, and Plugged and 

 Abandoned Wells for the Collection of Structures that Restarted

 Production by August 2008 ..............................................................................122 

Figure D.11. Cumulative Annual Drilled Wellbores, Sidetrack Wells, and Plugged 

 and Abandoned Wells for the Collection of Structures 

 that Restarted Production..................................................................................123 

Figure D.12. Aggregate Annual Drilled Wellbores, Sidetrack Wells, and Plugged and 

 Abandoned Wells for Structures that Have Not Been Redeveloped Wells 

 by August 2008 (ex-structure 735) ...................................................................123 

Figure D.13. Cumulative Annual Drilled Wellbores, Sidetrack Wells, and Plugged and 

 Abandoned Wells for Structures that Have Not Been Redeveloped by 

 August 2008 (ex-structure 735) ........................................................................124 

Figure D.14. Forecast Gas Production for Structures that Have Restarted Production, 

 the MTLP, and Structures with a Submitted DOCD Plan ................................124 

Figure D.15. Forecast Oil Production for Structures that Have Restarted Production, 

 the MTLP, and Structures with a Submitted DOCD Plan ................................125 

Figure D.16. Forecast BOE Production for Structures that Have Restarted Production, 

 the MTLP, and Structures with a Submitted DOCD Plan ...............................125 

Figure E.1. Number of Exploration and Development Wells Drilled Annually 

in the Gulf of Mexico (1947-2007)...................................................................131 

Figure E.2. Cumulative Number of Exploration and Development Wells Drilled 

 in the Gulf of Mexico (1947-2007)...................................................................131 

Figure E.3. Number of Exploration Wells Drilled by Water Depth Category 

 (1947-2007).......................................................................................................132 

Figure E.4. Number of Development Wells Drilled by Water Depth Category 

 (1947-2007).......................................................................................................132 

Figure E.5. Stacked Area Graph of the Number of Producing Oil and Gas Wells 

 in the GOM for GOR=10,000 (1947-2006)......................................................133 

Figure E.6. Number of Producing Oil and Gas Wells in the GOM for 

 GOR=10,000 (1947-2006)................................................................................133 

Figure E.7. Number of Producing Wells in the GOM Identified as Oil Wells as a 

 Function of GOR Thresholds (1947-2006).......................................................134 

Figure E.8. Number of Producing Wells in the GOM Identified as Gas Wells as a 

Function of GOR Thresholds (1947-2006).......................................................134 
xv

LIST OF FIGURES 

(continued) 

Page

Figure E.9. Oil Well Population Ratio in the GOM as a Function of GOR Thresholds 

 (1947-2006).......................................................................................................135 

Figure E.10. Liquid Production from Oil and Gas Wells in the GOM (1947-2006).............135 

Figure E.11. Gas Production from Oil and Gas Wells in the GOM (1947-2006). ................136

Figure E.12. Cumulative Oil Production from Oil and Gas Wells in the GOM 

 (1947-2006).......................................................................................................136 

Figure E.13. Cumulative Gas Production from Oil and Gas Wells in the GOM 

 (1947-2006).......................................................................................................137 

Figure E.14. Oil Wells Categorized According to Daily Oil Production Levels 

 (1947-2006).......................................................................................................137 

Figure E.15. Stacked Area Graph of Oil Wells Categorized According to Daily Oil 

 Production Levels (1947-2006) ........................................................................138 

Figure E.16. Population Ratio of Oil Wells Categorized According to Daily Oil 

 Production Levels (1947-2006) ........................................................................138 

Figure E.17. Oil Wells Categorized According to Daily Gas Production (1947-2006) ........139 

Figure E.18. Stacked Area Graph of Oil Wells Categorized According to Daily Gas 

 Production (1947-2006)....................................................................................139 

Figure E.19. Oil Well Oil Production per Category (1947-2006). ........................................140 

Figure E.20. Oil Production Ratio per Category According to Daily Oil Production 

 (1947-2006).......................................................................................................140 

Figure E.21. Oil Well Gas Production per Category (1947-2006) ........................................141 

Figure E.22. Gas Wells Categorized According to Daily Oil Production Levels 

 (1947-2006).......................................................................................................141 

Figure E.23. Stacked Area Graph of Gas Wells Categorized According to Daily Oil 

 Production Levels (1947-2006) ........................................................................142 

Figure E.24. Gas Wells Categorized According to Daily Gas Production Levels 

 (1947-2006).......................................................................................................142 

Figure E.25. Stacked Area Graph of Gas Wells Categorized According to Daily Gas 

 Production Levels (1947-2006) ........................................................................143 

Figure E.26. Population Ratio of Gas Wells Categorized According to Daily Gas 

 Production Levels (1951-2006) ........................................................................143 

Figure E.27. Gas Well Oil Production per Category (1947-2006) ........................................144 

Figure E.28. Gas Well Gas Production per Category (1947-2006).......................................144 

Figure E.29. Gas Production Ratio per Category According to Daily Gas Production 

 (1951-2006).......................................................................................................145 

Figure E.30. Structure Installations in the Gulf of Mexico (1947-2007). .............................145 

Figure E.31. Cumulative Number of Structure Installations in the Gulf of Mexico 

 (1947-2007).......................................................................................................146 

Figure E.32. Structure Removals in the Gulf of Mexico (1973-2007)..................................146
xvi

LIST OF FIGURES 

(continued)

Page

Figure E.33. Cumulative Number of Structure Removals in the Gulf of Mexico 

 (1973-2007) ......................................................................................................147 

Figure E.34. Active Structures in the Gulf of Mexico (1947-2007)......................................147 

Figure E.35. Change in the Number of Active Structures in the Gulf of Mexico 

 (1947-2007).......................................................................................................148 

Figure E.36. Cumulative Number of Installed, Removed, and Active Structures in the 

 Gulf of Mexico (1947-2007).............................................................................148 

Figure E.37. Stacked Area Graph of Number of Producing Oil and Gas Structures 

 in the GOM (1947-2006) ..................................................................................149 

Figure E.38. Number of Producing Oil and Gas Structures in the GOM (1947-2006).........149 

Figure E.39. Number of Non-Producing Structures in the GOM (1947-2006).....................150 

Figure E.40. Population Ratio of Non-Producing Structures in the GOM (1947-2006).......150 

Figure E.41. Annual Oil Production from Oil and Gas Structures in the GOM 

 (1947-2006).......................................................................................................151 

Figure E.42. Annual Gas Production from Oil and Gas Structures in the GOM 

 (1947-2006).......................................................................................................151 

Figure E.43. Cumulative Oil Production from Oil and Gas Structures in the GOM 

 (1947-2006).......................................................................................................152 

Figure E.44. Cumulative Gas Production from Oil and Gas Structures in the GOM 

 (1947-2006).......................................................................................................152 

Figure E.45. Oil Structure Oil Production Decomposed According to Production 

 Category (1947-2006).......................................................................................153 

Figure E.46. Cumulative Oil Structure Oil Production Decomposed According to 

 Production Category (1947-2006) ....................................................................153 

Figure E.47. Oil Structure Gas Production Decomposed According to Production 

 Category (1947-2006).......................................................................................154 

Figure E.48. Oil Structures Categorized According to Daily Oil Production 

 (1947-2006).......................................................................................................154 

Figure E.49. Stacked Area Graph of Oil Structures Categorized According to Daily 

 Oil Production (1947-2006)..............................................................................155 

Figure E.50. Oil Structures Categorized According to Daily Gas Production 

 (1947-2006).......................................................................................................155 

Figure E.51. Stacked Area Graph of Oil Structures Categorized According to Daily 

 Gas Production (1947-2006).............................................................................156

Figure E.52. Gas Structure Gas Production Decomposed According to Production 

 Category (1947-2006).......................................................................................156 

Figure E.53. Cumulative Gas Structure Gas Production Decomposed According to 

 Production Category (1947-2006) ....................................................................157 

Figure E.54. Gas Structure Oil Production Decomposed According to Production 

 Category (1947-2006).......................................................................................157
xvii

LIST OF FIGURES 

(continued)

Page

Figure E.55. Gas Structures Categorized According to Daily Gas Production 

 (1947-2006).......................................................................................................158 

Figure E.56. Stacked Area Graph of Gas Structures Categorized According to Daily 

 Gas Production (1947-2006).............................................................................158 

Figure E.57. Gas Structures Categorized According to Daily Oil Production 

 (1947-2006).......................................................................................................159 

Figure E.58. Stacked Area Graph of Gas Structures Categorized According to Daily 

 Oil Production (1947-2006)..............................................................................159 

Figure F.1. Hydrocarbon Production on the OCS of the Gulf of Mexico(1991-2007) .......168 

Figure F.2. Oil Production on the OCS in the GOM (1991-2007)......................................168 

Figure F.3. Gas Production on the OCS in the GOM (1991-2007).....................................169 

Figure F.4. Average Annual Production Profiles in the Fixed Platform, 0-60 ft 

 Water Depth, Oil Production, Subcategory ......................................................169 

Figure F.5. Average Annual Production Profiles in the Caisson, 60-200 ft Water 

 Depth, Gas Production, Subcategory................................................................170 

Figure F.6. Average Annual Production Profiles in the Well Protector, 60-200 ft 

 Water Depth, Oil Production, Subcategory ......................................................170 

Figure F.7. Historical and Forecast Production of Structure 587........................................171 

Figure F.8. Annual Production Curve and Best-Fit Regression of Structure 33.................171 

Figure F.9. Historical and Projected BOE Production of Structure 33 ...............................172 

Figure F.10. Historical and Projected Oil and Gas Production of Structure 33 ....................172 

Figure F.11. Historical and Projected BOE Production of Structure 152 .............................173 

Figure F.12. Production Profile of Structure 23266 ..............................................................173 

Figure F.13. Historical Production and Best-Fit Regression Curve of Structure 23266.......174 

Figure F.14. Projected BOE Production of Structure 10042.................................................174 

Figure F.15. Forecast of Committed Shallow Water Structures in the GOM 

 (2007-2047).......................................................................................................175 

Figure F.16. Annual Oil Production from Active Structures (2007-2047) ...........................175 

Figure F.17. Annual Gas Production from Active Structures (2007-2047) ..........................176 

Figure F.18. Annual BOE Production of Active Structures (2007-2047).............................176 

Figure F.19. Annual BOE Production per Asset Category (2007-2047)...............................177 

Figure F.20. Cumulative BOE Production per Asset Category (2007-2047)........................177 

Figure F.21. Annual Gas Production per Asset Category (2007-2047) ................................178 

Figure F.22. Cumulative Gas Production per Asset Category (2007-2047) .........................178

Figure F.23. Annual Oil Production per Asset Category (2007-2047) .................................179 

Figure F.24. Cumulative Oil Production per Asset Category (2007-2047)...........................179 

Figure G.1. Number of Producing Structures Decomposed According to Marginal 

 and Economic Status (2007-2067)....................................................................189

Figure G.2. Marginal Structures as a Percentage of the Committed Asset Inventory 

 Circa 2006 (2007-2067)....................................................................................189
xviii

LIST OF FIGURES 

(continued)

Page

Figure G.3. Average Producing Structure Count and One Standard Deviation 

 Envelope (2007-2067) ......................................................................................190 

Figure G.4. Average Economic Structure Count and One Standard Deviation 

 Envelope (2007-2067) ......................................................................................190 

Figure G.5. Average Marginal Structure Count and One Standard Deviation 

 Envelope (2007-2067) ......................................................................................191 

Figure G.6. Average Annual BOE Production Profile of Producing Structures 

 Decomposed According to Economic and Marginal Categories 

 (2007-2067).......................................................................................................191 

Figure G.7. Average Cumulative BOE Production of Producing Structures 

 Decomposed According to Economic and Marginal Categories 

 (2007-2067).......................................................................................................192 

Figure G.8. BOE Production Envelopes of Producing Structures (2007-2067). .................192 

Figure G.9. BOE Production Envelopes of Economic Structures (2007-2067)...................193 

Figure G.10. BOE Production Envelopes of Marginal Structures (2007-2067) ....................193 

Figure G.11. BOE Production Contribution per Asset Category (2007-2067)......................194 

Figure G.12. Cumulative BOE Production Contribution per Asset Category 

 (2007-2067).......................................................................................................194 
xix

LIST OF TABLES 

Page

Table A.1. Structure Damage Rate and Physical Damage Estimates...................................73 

Table A.2. Structure and Rig Damage Caused by Hurricanes Ivan, Katrina, and 

 Rita......................................................................................................................73 

Table A.3. Structures Destroyed by Hurricanes Ivan, Katrina, and Rita by Age 

 Group ..................................................................................................................73 

Table A.4. Operators with Three or More Destroyed Structures in the 2004-2005 

 Hurricane Seasons...............................................................................................74 

Table A.5. Gas, Oil, and Water Production from Hurricane Destroyed Structures 

 as a Percentage of Total Gulf of Mexico Production (2000-2005).....................74 

Table A.6. Structure Count by Production Category (2000-2005).......................................75 

Table B.1. Annual Operating Cost for Gulf of Mexico Structures (2006 dollars) ...............87

Table B.2. Average Threshold Revenue for Gulf of Mexico Structures (2006 

 dollars) ................................................................................................................87 

Table B.3. Best Fit Curve Frequency and Average Model Parameters................................88 

Table B.4. Number of Structures According to Structure Type and Model 

 Specification .......................................................................................................88 

Table C.1. Estimated Lost Production and Valuation (Normal Producers) – 

Best-Fit Curves with R2 ≥ 0.75, Hurricane Destroyed Structures with 

≥ 7 Years Production ..........................................................................................91

Table C.2. Estimated Lost Production and Valuation (Young Producers) – 

 Hurricane Destroyed Structures with < 7 Years Production, Exponential 

 Decline Curves with Assumed Decline Rate......................................................91 

Table C.3. Estimated Lost Production and Valuation (Chaotic Producers) – 

 Best-Fit Curves with Initial R2 < 0.75, Half Cycle Time Horizons and 

 Exponential Decline with Historic Decline Rate................................................92 

Table C.4. Estimated Total Lost Production and Valuation – Normal, Young, 

 and Chaotic Producers (Sum of Tables C.1, C.2, C.3) .......................................92 

Table C.5. Maximum Aggregate Investment that Yields a Specific Rate of 

 Return ($ million) ...............................................................................................93 

Table C.6. Maximum Redevelopment Cost per Structure to Yield a Specific 

 Rate of Return ($ million/structure)....................................................................93 

Table D.1. Number of Producing Structures Destroyed by Hurricanes Ivan, Katrina, 

 and Rita ...............................................................................................................99 

Table D.2. Destroyed Structures that Restarted Production by August 2008.....................100 

Table D.3. Pre- and Post-Hurricane Daily Average Production Statistics for 

 Destroyed Structures that Restarted Production by August 2008.....................101

Table D.4. Pre- and Post-Hurricane Daily and Annual Revenue Statistics for 

 Destroyed Structures that Restarted Production by August 2008.....................102

Table D.5. Post/pre-Hurricane Production and Revenue Ratio Distribution for 

 Destroyed Structures that Restarted Production ...............................................103
xx

LIST OF TABLES

(continued) 

Page

Table D.6. Post/pre-Hurricane Revenue Ratios for Destroyed Structures that 

 Restarted Production.........................................................................................104 

Table D.7. Hurricane Destroyed Structures Redevelopment Rate by Pre-Hurricane 

 Production Rates ...............................................................................................105 

Table D.8. Hurricane Destroyed Structures Restart Rate by the Number of 

 Pre-Hurricane Producing Wells ........................................................................106 

Table D.9. Hurricane Destroyed Structures Restart Rate by Expected Remaining 

 Reserves ............................................................................................................107 

Table D.10. Exploration and Development Plans on Leases that Restarted 

 Production as of February 2009........................................................................108 

Table D.11. Post-Hurricane Cumulative Production, Drilling Activity Levels, and 

 Percentage of Reserves Remaining as of August 2008 ....................................109 

Table D.12. Time Offline, Duration of Production, and Last Producing Month for 

 Structures that Restarted Production.................................................................110 

Table D.13. Estimated Remaining Reserves and Discounted Gross Revenue for 

Redeveloped Structures – I. One Year Time Shift ...........................................111 

Table D.14. Estimated Remaining Reserves and Discounted Revenue for

 Redeveloped Structures – II. Two Year Time Shift .........................................112 

Table D.15. Producing Wells, Drilled Wells, and Plugged and Abandoned (P&A) 

 Wells for Redeveloped Structures ....................................................................113 

Table D.16. Structures with ≥ 250 BOEPD Pre-Hurricane Production Not 

 Redeveloped, August 2008 ...............................................................................114 

Table D.17. Pre-Hurricane Daily Revenue Distribution and Redevelopment Rates 

 for Structures that Have Not Restarted Production as of August 2008 ............115 

Table D.18. Estimated Remaining Reserves and Discounted Revenue for Top 25 

 Structures that Have Not Been Redeveloped as of February 2009 – I. 

 One Year Time Shift.........................................................................................116 

Table D.19. Estimated Remaining Reserves and Discounted Revenue for Top 25 

 Structures that Have Not Been Redeveloped as of February 2009 – II. 

 Two Year Time Shift ........................................................................................117 

Table E.1. Exploration and Development Wells Drilled in the Gulf of Mexico 

 (1947-2007).......................................................................................................129 

Table E.2. Structure Installations by Structure Type and Water Depth (1947-2007) ........129 

Table E.3. Structure Removals by Structure Type and Water Depth (1973-2007)............130 

Table F.1. Active Structures Classified by Primary Production and Structure 

 Type (2006).......................................................................................................163

Table F.2. Active Structures Classified by Class and Primary Production (2006) ............163 

Table.F 3. Number of Subcategories Based Upon Removed Structures in the GOM .......164
xxi

LIST OF TABLES

(continued) 

Page

Table F.4. History Matching Procedure for Young Structures ..........................................164 

Table F.5. Best Fit Curve Frequency and Average Model Parameters for Normal 

 and Chaotic Structures ......................................................................................165

Table F.6. Cumulative Production in Year Six for the 10 Subcategories of 

Г(CAIS, 60-200, OIL) ......................................................................................166 

Table F.7. Active Structures Applied in the Model Forecast.............................................166 

Table F.8. Model Parameters and Distribution Functions .................................................167 

Table F.9. Model Results for Cumulative Gas, Oil, BOE Production ...............................167 

Table F.10. Present Value of Gas, Oil, and BOE Production ..............................................167 

Table G.1. Classification of Shallow Water Structures in the Gulf of Mexico 

 (2006)................................................................................................................183 

Table G.2. Model Parameters and Distribution Functions .................................................183 

Table G.3. Summary Statistics for Shallow Water Committed Assets in the GOM 

 (2006)................................................................................................................184 

Table G.4. Model Results for Total (Cumulative) BOE Production (BOE).......................184 

Table G.5. Model Results for Total (Cumulative) Gas Production (Mcf)..........................184 

Table G.6. Model Results for Total (Cumulative) Oil Production (bbl) ............................185 

Table G.7. Model Results for Present Value of Total Hydrocarbon (Oil and Gas) 

 Production ($1,000) ..........................................................................................186 

Table G.8. Model Results for Present Value of Gas Production ($1,000)..........................187 

Table G.9. Model Results for Present Value of Oil Production ($1,000)...........................188 
1

EXECUTIVE SUMMARY 

The oil and gas industry in the Gulf of Mexico has the greatest weather exposure in the world 

and is vulnerable to a range of losses that include physical damage and destruction, business 

interruption, and pollution liability. Operating offshore is more complex and risky, and more 

capital intensive, than onshore environments where fixed costs are smaller and production 

profiles tend to decline at more predictable rates. The application of secondary and enhanced 

oil recovery techniques is more complex and subject to constraints not found onshore, and only 

a few offshore fields are economic to recover in secondary or tertiary mode. Marginal fields 

have different economics than large fields, require different recovery techniques, and are 

produced by smaller companies. 

During the 2004 and 2005 hurricane seasons, a number of offshore facilities, drilling rigs, and 

pipelines were destroyed and extensively damaged. In total, 120 structures were destroyed by 

Hurricanes Ivan, Katrina, and Rita. The question we first address is to estimate the amount of 

reserves likely to be recovered in the future. Recovered reserves are a useful indicator to gauge 

the impact of extreme events on offshore operations and the economic criteria employed in 

redevelopment decisionmaking. 

In the first part of this report, we examine the destroyed infrastructure from the 2004 and 2005 

hurricane seasons and the post-hurricane recovery efforts of operators. After a summary 

overview of the hurricane impacts (Chapter 1), the model framework is described (Chapter 2), 

and the value of lost production is estimated using a revenue model and scenario parameters 

assuming that all destroyed structures will be abandoned (Chapter 3). The value of lost 

production is estimated to range between $1.3 billion to $4.5 billion if no redevelopment of the 

asset occurs. Sensitivity analysis is performed and we describe the maximum redevelopment 

cost per structure that will yield a specific rate of return. 

In Chapter 4, we review pre- and post-hurricane production and revenue characteristics for the 

collection of destroyed structures that have been redeveloped circa February 2009 and compare 

these structures against structures that have not submitted redevelopment plans. A screening 

tool is presented that describes the redevelopment potential and percentage of remaining 

reserves that will likely be recaptured during recovery. We estimate that 60 percent of the 63 

MMBOE of reserves impacted by the hurricanes will be recovered by redevelopment. The 

screening tool is a generalized instrument that can be used with future hurricane events to 

assess what structures will likely be redeveloped and the amount of reserves that will be lost to 

future hurricanes.

After a structure has produced for several years, it will eventually transition to marginal status 

and operate on the lower edge of profitability. When a structure turns marginal, the conditions 

under which profit is generated tend to be more restricted, and the lease on which a marginal 

structure is producing may no longer generate a profit. We investigate the role of marginal 

production in the Gulf relative to the 2006 inventory of shallow water assets and forecast its 

expected contribution to future production. Marginal production deserves careful consideration 

from a regulatory point of view since production may not be commercial. This will put the 

lease at risk and should warrant a greater level of regulatory scrutiny. Because marginal 
2

structures are on the verge of decommissioning, they represent a useful indicator of future 

removal activity. The collection of marginal assets also provides useful insight into general 

production characteristics of the shelf. 

In the second part of this report, the number of marginal producers and the amount of marginal 

production is quantified and its expected contribution to future production is examined. Oil, 

gas, and BOE production from the shallow water committed assets in the Gulf in 2006 are 

estimated at 1,056 MMbbl oil, 13.3 Tcf gas, and 3,279 MMBOE. Marginal production is 

expected to contribute 4.1 percent of the total oil production and 5.4 percent of the total gas 

production from the collection of committed assets. The expected present value of production 

from the committed asset inventory is calculated as $149.4 billion and marginal structures are 

estimated to contribute 1.2 percent of this value. 

We begin in Chapter 5 by counting wells and structures across different categorizations, 

identifying the inventory of producing and non-producing wells and structures, and classifying 

production according to type and class. In Chapter 6, a generalized methodology is developed 

to forecast oil and gas production from shallow water assets. We categorize committed assets 

according to their age of production and the nature of their production profile and forecast 

production within each asset category. The methodology is illustrated with examples and a 

summary of results. 

In Chapter 7, we identify when a structure is expected to turn marginal using the production 

models developed in Chapter 6. A forecast of the level of marginal production from the 

inventory of shallow water assets is presented. The results of our modeling include average 

trajectories of economic and marginal structure counts over a 60-year horizon, average 

production profiles across each structure category, and expected cumulative production and 

valuation functions. 
3

PART 1. MODELING LOST PRODUCTION AND POST-HURRICANE 

RECOVERY IN THE GULF OF MEXICO 

Chapter 1. Redevelopment Economics and Impact Assessment 

In this chapter, we describe the weather risk that operators encounter and review the factors that 

are involved in redevelopment decisions. The impact of the 2004 and 2005 hurricane seasons 

on the infrastructure and production statistics in the Gulf of Mexico are summarized. 

1.1. Introduction 

Powered by heat from the sea, a hurricane acts as a gigantic heat engine transforming warm 

ocean water into powerful wind fields. Hurricanes are typically about 300-350 mile wide and 

have extreme horizontal pressure gradients that generate powerful winds. Wind speed and the 

intensity of precipitation both increase toward the center of the system (eye) and generate 

waves and current which interact with the offshore built environment increasing the stress on 

structural components, which in some cases, leads to catastrophic failure and destruction. 

Winds in excess of 74 mph usually extend 25-50 miles on each side of the storm path and 

represent the boundaries of hurricane strength winds and the zone where structures are the most 

vulnerable. In the hurricane force wind swath, old structures are especially vulnerable because 

older vintage facilities are designed to lower environmental criteria. Typically, 2-4 percent of 

all structures exposed to hurricane force winds are destroyed and 5-7 percent are damaged. The 

destruction rates of old structures are usually higher than these ranges when examined as a 

group. No general correlation exists between the eye path and distance to the destroyed 

platform because destruction is primarily based upon deck elevation and platform strength, 

which is site-specific and varies with vintage and design codes. 

Structures fail in different modes and any wells underneath the deck and substructure are 

usually bent at the mudline and require complex and expensive intervention to cleanup and 

abandon. Hurricane destroyed structures may be completely toppled (Figure A.1) or only the 

jacket structure may remain standing (Figure A.2). Structures may lean and be declared 

destroyed (Figure A.3) or be so severely damaged that it can no longer carry out its function. In 

all cases, destroyed platforms can be a hazard to navigation and need to be immediately 

identified as navigation hazards. 

Hurricane Ivan entered the GOM on September 14, 2004 as a Category1

 4 storm and passed 

through the Mississippi River delta, the area most susceptible to underwater mudslides (Figure 

 

1

 The Saffir-Simpson scale classifies hurricanes into five categories based on the highest 1-minute average wind 

speeds: Category 1 (74-95 mph), Category 2 (96-110 mph), Category 3 (111-130 mph), Category 4 (131-155 

mph), and Category 5 (156+ mph). 
4

A.4). Seven platforms were destroyed and significant damage2

 to 24 other platforms were 

reported (USDOI, MMS, 2004). One structure was toppled by a mudslide, while the other six 

failures are thought to be attributed to environmental loads (i.e., wind, wave, current) exceeding 

the capacity of the structure. Three additional platforms were later considered destroyed and 

decommissioned (Energo, 2006). 

Hurricane Katrina entered the GOM in late September 2005 as a Category 4 storm and 

destroyed 44 platforms (Figure A.5). Hurricane Rita followed in mid-October as a Category 4 

storm destroying 69 platforms (Figure A.6). Normally, most destroyed platforms occur to the 

east of the storm path, since this is the area where the winds and waves are highest. For 

Katrina, the majority of the destruction lie to the west of the eye path and has been attributed to 

the reduced fatigue life of structures, since previously, Hurricanes Ivan and Andrew (1992) also 

passed through this region (Energo, 2007). 

Property owners of damaged and destroyed infrastructure are faced with a decision: Should the 

asset be abandoned along with its potential cash flow or should the property be redeveloped? 

Decisions are made relative to other opportunities in a company’s portfolio based on a 

comparison of the cost and risk of redevelopment against the benefits of future production. 

Fields early in their lifecycle are likely to support the production rates and reserves necessary 

for redevelopment. Mature assets and small producers are the least likely to meet the economic 

thresholds, and in most cases, will be abandoned. 

1.2. Data Source 

1.2.1. Notice to Lessees and Operators 

Following every major hurricane, the Minerals Management Service (MMS) issues Notices to 

Lessees and Operators (NTLs) that require platform owners to perform above and below water 

inspections of infrastructure that were exposed to hurricane force winds. For platforms exposed 

to hurricane force winds, operators are required by the MMS in accordance with the API 

Recommended Practice 2A-WSD to conduct a Level I survey (above water visual inspection) 

before manning3

. Platform owners report the progress or results of the inspections to the MMS, 

and indicate if platforms had no damage, incurred minor or major damage, or were destroyed. 

The MMS coordinates with the operators and reports on the assessment on a periodic basis, and 

in a “final” official list, report the total number of damaged and destroyed platforms by 

category. The data source used in this analysis is the inventory of destroyed platforms reported 

 

2

 The MMS defines significant damage as exhibiting some evidence of severe structural overload which caused 

damage to the primary load bearing members. 

3

 A Level II survey (underwater visual inspection by divers or remotely operated vehicle) is required when a Level 

I survey indicates that underwater damage may have occurred. If any underwater damage is located, or if there are 

indications of wave loading on the topsides, then additional Level III inspections (close visual inspection of areas 

of known or suspected damage) is required. A Level IV survey (underwater nondestructive testing of areas of 

known or suspected damages) is based on the results of a Level III survey. 
5

by the MMS after Hurricanes Ivan (USDOI, MMS, 2004), Katrina, and Rita (USDOI, MMS, 

2006). 

After a major hurricane, the number of platforms that are declared destroyed usually increases 

in the weeks following the event, but when the official list is finally released – typically 8-12 

weeks after the event - operators have mostly finished their damage assessments and the 

inventory of destroyed structures has stabilized. The data set may still not be complete at the 

time the official list is released, however, because an owner of a damaged platform may require 

additional time to determine if it is economic to replace. If the damage was not found in the 

initial inspection, the owner may elect to remove the platform at a later date. A structure may 

also be removed if a pipeline or platform that was part of their operation scheme is no longer in 

service or removed from service at a later time. Structures not on the official list are not 

considered in this analysis although they may be significant4

. 

1.2.2. Plans for Exploration and Development 

 

All exploration, development, and production activities on the Outer Continental Shelf (OCS) 

and certain preliminary or ancillary activities (geological/geophysical)5 are conducted in accord 

with an Exploration Plan (EP), a Development and Production Plan (DPP), or a Development 

Operations Coordination Document (DOCD), approved by the MMS Regional Supervisor. 

The submission of plans for approval allows MMS to determine whether plans comply with all 

applicable Federal laws and regulations while permitting for environmental review under 

National Environmental Policy Act (NEPA) guidelines so to ensure environmental policy, and 

safety. Submission of plans for approval also allows MMS to determine whether the proposed 

activities will unreasonably interfere with other uses of the area; interferes with or endangers 

operations on other leases; or result in pollution or create hazardous conditions. 

An EP and its supporting information must be submitted for approval to the MMS before an 

operator may begin exploratory drilling on a lease. As plans evolve and change, supplemental, 

amended and revised plans are formed. A supplemental plan is a revision to an approved plan 

that proposes the addition of an activity that requires a permit. 

After the MMS receives an EP, drilling cannot begin until the lessee submits and receives the 

approval of an Application for Permit to Drill (APD) for each proposed well. An APD provides 

the MMS data that uniquely identifies a wellbore under an approved plan and allows the MMS 

to address the technical adequacy and regulatory compliance of the proposed drilling activity. If 

a well is productive, the operator may submit additional APDs to further develop the lease or 

may submit an Application for Permit to Modify (APM) to perform completion or workover 

operations. 

 

4

 For Katrina and Rita, it has been reported that an additional 150-200 platforms will be removed or have been 

removed as a result of the storms (Energo, 2007). Independent verification of this statistic was not confirmed. 

5

 See Notice to Lessees and Operators (NTL) Number 2006-G12 for details on which ancillary activities require 

submittal of a plan. 
6

If the results of exploratory or appraisal operations justify the development of one or more 

reservoirs, a company will prepare a development plan to commence the development of the 

area. DPPs and DOCDs describe the schedule of development activities, platforms, or other 

facilities, including environmental monitoring features and other relevant information. All 

platforms and pipelines, including their associated components, require the operator to submit 

an application and receive MMS approval for their installation, modification, and ultimate 

decommissioning. 

1.3. Redevelopment Economics and Uncertainty 

 

1.3.1. Destroyed Structures 

Offshore structures are designed for the environmental conditions in which they operate, and 

for day-to-day operations, platforms are extremely safe and historically have performed at an 

acceptable rate of failure. With the appearance of a tropical storm or hurricane, however, the 

risks of damage and destruction increase dramatically because structures must sustain wind 

speeds, wave forces, and potential mudslides that in extreme circumstances may equal or 

exceed their design capacity. Older platforms generally have lower strength characteristics 

(e.g., weaker joints, less robust bracing patterns, etc.) and lower topside deck height which 

make them significantly more susceptible to wave-in-deck conditions (Laurendine, 2008; 

Puskar et al., 2007; Versowski, 2006). A wave crest hitting a platform deck creates a very 

large load that will likely result in significant platform damage and in some cases collapse. A 

key ingredient in surviving hurricanes is to have a deck elevation above the largest hurricane 

waves. 

1.3.2. Cleanup Cost 

Destroyed structures must be decommissioned for removal. The nature of the work involved 

and the working environment are particularly challenging to ensure that operations are 

undertaken in a way that ensures that there is no harm to people, property, or the environment 

(Beck et al., 2008; Wisch et al., 2004). 

Structures fail in different modes and cleaning up the sites of destroyed platforms is a 

complicated and time consuming process (McCutcheon and Payne, 1986; Mailey, 2008). 

Debris over and around the wells must first be cleared and a vertical section of pipe must be 

accessed before the wells can be plugged and abandoned. This may require a section of the 

platform to be cut and removal of soil from around the wellbores. Depending on the lease area 

and water depth, there may be limited and at times zero visibility. Divers do the work with 

limited access and the tasks are often complex and require the design of new tools. To gain 

vertical access to wellbores, conductors could be cut by divers, specially-equipped remotelyoperated vehicles (ROVs), and/or explosive-severance charges. Diver cuts are more hazardous 

and expensive than mechanical or explosive cutting, and because of limited access and poor 

visibility, progress is often slow and personnel are exposed to more risk than under normal 

conditions. If the well is under pressure, it will be necessary to snub in to gain access; if the 

well is “dead” the re-entry process is only marginally simplified. In extreme cases, an operator 

may have to drill a new well to access the old well to plug. 
7

The intervention vessels required to cut, remove, or relocate downed platforms are often 

different than those used in conventional operations and their associated activities always 

require longer times to perform. Unique procedures and new technologies are commonly 

required to match the complexity of the decommissioning of a downed structure. If the 

integrity of the platform is sufficient, the platform can be lifted and transported to shore or a 

reef site (Kaiser and Kasprzak, 2008); otherwise, the toppled structure will be cut and removed 

in pieces, or dismantled in a manner that satisfies site clearance requirements. 

The risk and cost involved in decommissioning destroyed structures often range between 5-25 

times more expensive than conventional abandonment. The resources necessary to initiate 

inspections, conduct repairs, and procure materials and equipment are usually stretched thin 

during recovery efforts. Day-tripping (working during the day and traveling back to shore at the 

end of the day) is common. Time constraints associated with cleanup and increased activity 

levels (the so-called “demand surge”) put upward pressure on prices which contribute to higher 

decommissioning cost. 

1.3.3. Decisionmaking Economics 

If the value of remaining reserves at a structure is estimated to exceed the expected cleanup and 

redevelopment cost, the field will likely be redeveloped. There is little or no exploration risk, 

and it is possible that a young field can be brought back on-line at higher rates of production to 

help offset the capital expenditures. Assets capable of producing at high rates or those 

associated with significant levels of remaining reserves are more likely to achieve the economic 

criteria than assets with low production rates and/or less reserves. Structures that form a 

complex6

 or are close to other infrastructure where processing equipment or pipelines can be 

utilized will reduce redevelopment cost and may present new drilling opportunities. 

If the estimated value of future production from a destroyed asset is less than the expected 

cleanup and redevelopment cost, then the decision will likely be to postpone redevelopment or 

to decommission the asset. The MMS will typically issue an NTL to grant lease extension when 

operators cannot complete the necessary assessment work prior to lease expiration (USDOI, 

MMS, 2009a). Operators may need to apply for a Suspension of Operations (SOO) or 

Suspension of Production (SOP) to maintain lease operations. Between 1996 and 2004, the 

MMS granted a total of 553 lease suspensions, or 59 applicants on average per year. From 

2005-2008, there has been a six-fold increase in the number of lease suspensions requested by 

operators with the MMS granting 1,304 lease suspensions, or 326 applications on average per 

year. The MMS may issue suspensions for up to five years and may grant successive 

suspension periods depending on each case, but usually an SOP is for one year or less. 

Cleanup is a sunk cost, and once service vessels are on location, an operator may choose to 

decommission if the field is near the end of its life. For mature fields, reservoir pressures have 

been reduced from years of production and production rates are often low and not likely to 

support the expenditures and payback required by investors. If the operator chooses not to 

 

6

 Structures that are physically connected by a bridge (or walkway) are referred to as a complex. 
8

redevelop, it may seek a buyer for the asset contingent upon the federal government allowing 

the lease transfer. A rational operator would not spend more than the estimated value of 

remaining reserves to replace a destroyed structure or repair a damaged structure. 

1.3.4. Revenue and Cost Uncertainty 

The decision to repair, replace, or decommission damaged and destroyed infrastructure is often 

difficult because of the uncertainty involved in estimation. The return on investment that an 

owner would expect to receive depends upon future production rates and hydrocarbon prices, 

as well as the cost to cleanup and redevelop the site. Cleanup costs vary widely. Development 

cost are similar to normal operations and include the cost to fabricate/install a new platform, 

subsea assembly and/or pipeline interconnection/tieback, and the cost to re-enter or drill new 

wells. Under normal circumstances, redevelopment decisions are no different than an initial 

development decision, but in the case of destroyed or severely damaged assets, there are 

additional complications and uncertainties regarding the procedures and costs that need to be 

taken into account. Costs are weighed against the potential revenue generating capability 

expressed through the expected remaining reserves, production levels, and future prices. If 

expected benefits exceed costs, redevelopment may occur; if costs exceed benefits, deferral or 

decommissioning is likely. 

1.3.5. Redevelopment Strategies 

Redevelopment strategies available to operators are site-specific and depend on field 

configuration. To an outside observer, factors such as the geologic condition of the reservoir, 

drilling opportunities, cleanup and redevelopment cost are difficult (or impossible) to assemble. 

Fortunately, public data can be utilized to provide insight into decisionmaking. Production and 

drilling profiles, for example, and inventories of lease infrastructure can be computed with a 

high degree of accuracy. Reserves and their potential value can also be estimated. 

When a producing structure is destroyed, most wells require abandonment. Depending on the 

lease infrastructure and processing/transportation options available, the operator may seek to 

replace the structure and drill new wells. A structure may be replaced at the original site or 

elsewhere on the lease or an adjacent lease. New wells may be drilled or the original wells may 

offer recompletion or sidetrack7

 opportunities. All of these cases involve additional capital 

expenditure. If infrastructure is installed to replace destroyed structures, or if new wells are 

drilled, operators are required to submit and receive approval for activity plans. 

 

7

 A sidetrack well is a well planned and drilled from the bore of a previous well in order to achieve a geologic 

objective. Sidetracks are usually used to confirm the lateral extent and thickness of the reservoir. Savings in 

drilling cost may be achieved by using existing wellbores, but problems or unexpected conditions during re-entry 

may occur negating the anticipated savings. 
9

1.4. Structure and Production Classification 

Offshore structures can be classified in a number of ways, but the two most common 

approaches are based on the physical nature of the infrastructure and the characteristics of the 

production stream. 

1.4.1. Structure Type 

Offshore structures are designed for a particular field, and are built according to specific design 

criteria at a specific location and time. Caissons, well protectors, and fixed platforms are the 

primary configurations employed in shallow water. In the simplest configuration, a platform 

will simply protect the well(s) with minimal production handling equipment. A caisson is a 

cylindrical or tapered large diameter steel pipe enclosing a well, while a well protector employs 

a jacket structure to provide support to one or more wells. Caissons and well protectors are 

considered minimal structures, and their production is usually sent to processing facilities on 

production platforms prior to being transported to shore. Equipment on minimal structures may 

include test separators for measurement, pressure production and test headers, gas lift systems, 

sump tanks for skid drains, and fixed cranes. 

Fixed platforms resemble the jacket structure of well protectors, but are larger, more robust 

structures, that include facilities for drilling, production, and workover operations. Production 

platforms include all the equipment and facilities required to gather, separate, process, and sell 

sales quality natural gas and crude oil. Drilling platforms include the rig and all equipment to 

drill and workover wells. Platforms that combine the two functions are referred to as drilling 

and production rigs. In water depth greater than 1,500 ft, various floater technologies replace 

fixed platforms, and include spars, semisubmersibles, and tension-leg platforms. 

1.4.2. Production Status 

A structure is classified as active or idle depending on its production status. Oil production is 

expressed in barrels (bbl) and includes condensate (natural gas liquids); gas production is 

expressed in thousand cubic feet (Mcf) and includes associated gas (oil well gas, or casinghead 

gas). A barrel of oil equivalent (BOE) combines the oil and gas streams on a heat content basis 

(1 bbl = 6 Mcf). A structure is said to be active in year t if it produces any amount of oil or gas 

during the year, while a structure is said to be idle if it once produced hydrocarbons but has not 

been productive for at least one year prior to the time of observation8

. Structures which serve in 

a support role as a storage, compression, or metering facility have never produced and are 

called auxiliary structures. 

 

8

 A structure that is inactive for several years is unlikely to return to active status. According to federal regulations, 

all structures need to be removed from a lease within one year after production on the lease ceases, unless the lease 

has received an authorized suspension or is part of a unitization agreement. If an idle structure resides on a 

producing lease, the structure can remain on the lease for as long as the lease is in production. 
10

1.4.3. Production Type 

The producing gas-oil ratio (GOR) is a common means to classify reservoir fluids and field 

production and we use this measure to classify structures as primarily “oil” or “gas” producers. 

The GOR is based on observed producing characteristics and is a surface measurement, 

expressed in volume of produced gas (measured in cubic feet) per unit of produced oil 

(measured in barrels). A structure with GOR < 5,000 cf/bbl is labeled an oil structure and a 

structure with GOR > 5,000 cf/bbl corresponds to a gas structure. 

1.5. Aggregate Assessment 

1.5.1. Energy Losses 

In the final list released by MMS, 120 structures were reported destroyed from Hurricanes Ivan 

(7), Katrina (44), and Rita (69). One hundred eleven of the 120 structures produced 

hydrocarbons at some point during their lifetime, while 81 structures were producing at the 

time of the hurricane passage. A total of nine (=120-111) structures served in an auxiliary9

(non-producing) role and 30 (=111-81) structures were idle at the time of the hurricane passage. 

Idle structures are unlikely to ever return to producing status, and through February 2009, about 

half (13) of the 32 structures that have been decommissioned were idle. 

Losses incurred in a hurricane are a combination of physical damage and time element losses. 

When production operations are disrupted, either by damage on site or elsewhere, cash flow is 

impacted. Insurance claims on time element coverage are typically categorized as business 

interruption from damage to assets (e.g., platforms, pipelines, etc.), and contingent business 

interruption, associated with damage to upstream facilities such as processing plants, trunk 

lines and refineries, owned by third-parties, which prevent production from being received. 

 

Hurricane Ivan caused energy losses of $2.5-3 billion, while Katrina and Rita were responsible 

for a record $15 billion in losses (Willis Group, 2006). In Ivan, about two-thirds of the total 

losses were attributed to business interruption and contingent business interruption, while for 

Katrina and Rita, physical damage was the major cause of losses. Two-thirds of the energyrelated losses due to Katrina and Rita have been attributed to physical damage (Willis Group, 

2006). 

1.5.2. Shut-In Production Profiles 

Shut-in production statistics are reported on a daily basis by operators when hurricanes enter 

the GOM and in the weeks and months after the event. In a typical hurricane, anywhere 

between 50-100 percent of all the oil and gas that is being produced in the GOM at the time 

will be shut in 1, 2, or 3 days depending on the strength and location (path) of the storm. 

Obviously, the more central the storm path is relative to production fields, the greater the 

 

9

 Auxiliary structures do not represent lost production, at least not directly, since they are not producers. However, 

if an auxiliary structure was integral to the production at a producing platform or field, its destruction may tie-up 

production upstream, similar to what would occur if an export pipeline was disabled. 
11

amount of oil and gas will be shut in. Shut-in production is usually not “lost,” since after the 

storms pass and operators assess the integrity of their wells, pipelines, and structures, chokes 

and valves will be reopened and production resumed. After Hurricane Ivan, damage to subsea 

pipelines, production platforms, and onshore processing facilities required six weeks to restore 

80 percent of shut-in oil production and 10 weeks to restore 90 percent of shut-in gas 

production. The paths of Hurricanes Katrina and Rita crossed higher-density infrastructure 

regions and caused more damage to the natural gas systems and processing facilities (USDOE, 

2006). 

In Figures A.7 and A.8 we plot the shut-in production profiles for oil and gas for major storms 

over the past two decades. Many factors impact the shape of these curves. The MMS requires 

operators to shut down facilities and evacuate personnel with the approach of extreme weather, 

and thus the storm path, speed, strength, and operator response impact the rate at which 

production is shut in and the peak value of the curves. The duration of the storm and its impact 

on production facilities and pipeline infrastructure will determine the plateau and slope of the 

shut-in curve after peak. Many factors may complicate and delay efforts to get production back 

to pre-storm levels, including damage to onshore support facilities and staging areas, the 

availability of service vessels and helicopters, and the effects of personnel dislocation and 

property loss. If onshore gas processing plants are inoperable for any length of time, for 

example, the loss could delay a recovery of natural gas production – even if platforms and 

pipelines are unaffected – because gas needs to be processed before flowing to market. 

Production levels will return to pre-storm levels if no wells, structures, or pipelines are 

damaged or destroyed. Production associated with destroyed wells and structures that are not 

redeveloped is classified as lost. 

1.5.3. Damage Rates 

The amount of damage incurred by a hurricane would be expected to be roughly correlated 

with the strength of the storm and the number of structures in the storm path. In Table A.1, we 

tabulate exposure levels and physical damage estimates. Damage rates are stochastic and we 

observe that the number of structures destroyed are only weakly correlated with damage 

estimates; e.g., the number of structures destroyed by Katrina was about half that of Rita, but 

Katrina’s losses were nearly double. The number of offshore structures that are destroyed or 

damaged depend not only upon the path and strength of the storm, but also the physical 

characteristics of the wind and wave fields and their interaction with the offshore facilities, the 

location of the structure relative to the storm path, design characteristics, and various other 

factors. The complexity of analysis requires sophisticated meteorological, met-ocean and 

structural modeling to normalize exposed entities to wind speed, structure type, and design 

specifications (Kaiser et al., 2007a and 2007b). 

1.5.4. Destroyed Structures 

Most of the structures destroyed by Hurricanes Ivan, Katrina and Rita (Table A.2) were older 

than ten years, but some were in the prime of their production life cycle (Table A.3). Chevron, 

Apache, BP America, Forest Oil, and Energy XXI owned more than half of the destroyed 
12

structures and a majority of the destroyed wells (Table A.4). In total, over 850 wells throughout 

the Gulf were destroyed by the storms. 

1.5.5. Aggregate Production 

Gas, oil, and water production from the collection of hurricane destroyed structures as a 

percentage of total GOM production is shown in Table A.5. Hurricane destroyed structures 

represented about 1.2 percent of the total gas and 1.5 percent of the total oil production in the 

Gulf in 2005, and about 3.4 percent of the total produced water. 

1.5.6. Structure Classification 

In Table A.6, structures are classified according to their primary output and level of production, 

in terms of barrels of oil per day (BOPD) for oil producers, thousand cubic feet per day 

(MCFPD) for gas producers, and in total barrels of oil equivalent per day (BOEPD) for all 

structures. 

A marginal producer would likely be producing less than 50 BOPD oil or 300 MCFPD gas, 

depending upon structure type, water cut, oil and gas price, operating expense, and other 

factors, but it may vary at somewhat higher or lower levels. Production greater than 200 BOPD 

oil or 1,200 MCFPD gas will be commercial under most circumstances. 
13

Chapter 2. Model Framework 

In this chapter, we develop a model framework to forecast the production and revenue streams 

associated with the collection of destroyed assets. The general framework of analysis is 

outlined along with the assumptions employed in modeling. 

2.1. Model Framework 

To estimate the amount and value of production that a structure would have generated if it was 

not destroyed, a five-step procedure is applied: 

Step 1. Model the structure’s historic oil and gas production data. 

Step 2. Forecast future production based on model curves assuming stable 

reservoir and investment conditions. 

Step 3. Forecast future revenue based on a given hydrocarbon price deck. 

Step 4. Terminate production when revenue from the structure falls below its 

estimated cost of operation. 

Step 5. Output cumulative production and present value of the revenue stream. 

2.2. Model Production Profiles (STEP 1) 

2.2.1. Notation 

Structure s is the basic unit of analysis. Define q (s) i

t as the amount of hydrocarbon type i (i 

=oil, gas, BOE) produced by structure s in year t. Oil production is expressed in barrels (bbl) 

and includes condensate (natural gas liquids); gas production is expressed in thousand cubic 

feet (Mcf) and includes associated gas (oil well gas, or casinghead gas). The production stream 

for an asset is described by its oil, gas, and BOE vectors, denoted as: ( ) ( , ,Lo

2

o

1 q s q q o = ), 

( ) ( , ,Lg

2

g

1

g q s = q q ) and q

BOE(s)= (q1BOE, q2BOE, L), where the ith element of each vector 

denotes the ith year of production. 

2.2.2. Decline Curves 

Production levels exhibit a wide variety of shapes due to factors and events that are 

unobservable, unpredictable, or both, related to reservoir characteristics, aggregation levels, 

investment strategies, weather events, technical intervention, and various other conditions. 

Multiple production peaks after plateau are common. Pre-plateau peaks may also occur if 

development occurred in stages or unforeseen events arose during development. The purpose of 

decline curves is to characterize production outside the influence of exogenous factors. 

Three types of decline curves are commonly used in reservoir engineering to describe the 

production of a well or group of wells after plateau: exponential decline, hyperbolic decline, 

and harmonic decline: 

dt

t q s q e− = 0 ( )
14

Ct

q q s t + = 1 ( ) 0

n n

n

C t q t

q q s

(1 ) ( ) 1/

0

0

+ =

where qt(s) denotes the production rate of structure s in year t, qo represents the initial (or peak) 

production rate, and d, C, n are parameters determined from historical data. 

 

The exponential model is probably the most frequently used method to model production 

profiles because of its ease of application and ability to capture basic reservoir dynamics. 

Hyperbolic decline models the production drop as a fractional power of the production rate and 

is usually applied during the later stages of the life cycle of a well. Harmonic decline is often 

used to model gravity drainage or water drive mechanisms. For some fields, the production rate 

may not be adequately modeled using any of these function types. 

 

2.2.3. Production Classification 

For each structure, we fit each fluid stream (oil, gas) to each of the three model forms 

(exponential, harmonic, hyperbolic) using regression techniques and select the best-fit curve 

using the maximum R2

-value. The input to the procedure is the structure’s historic production 

of oil and gas, and the output is the model parameters for the best-fit decline curve for each 

hydrocarbon stream. If the model fit for qt

i

(s) has an R2-value that exceeds 0.75 the model is 

considered an acceptable fit and a reasonable predictor of future production. We refer to 

structures that satisfy this criterion as “Normal” producers. 

A small number of structures have production profiles that do not yield an acceptable best-fit 

curve. If R2 < 0.75 for the oil or gas stream, the model fit is deemed unacceptable and 

simplified techniques are applied to generate the forecast curve. In this case, we repeat the 

curve fitting procedure from the second-half of the production profile. In other words, if a 

structure is T years old at the time of observation, then we model the second-half of the 

production history using data beginning in year T/2. If the reduced time horizon model does not 

satisfy R2

 > 0.75, then we assume an exponential model based on the structure’s historic 

decline rate. Structure profiles with initial R2 < 0.75 are referred to as “Chaotic” producers. 

Structures that are early in their life cycle present a special problem, since production has 

probably not peaked and remains largely unknown. Forecasting lost production from early 

producers, say within 7 years of first production, are subject to a large amount of uncertainty. 

For this subset of producers, we make a conservative estimate that production has peaked over 

the time horizon observed and declines following the exponential model according to a 

specified decline rate that is held fixed across time. Structures that are within 7 years of first 

production are classified as “Young” producers. 

 
15

“Idle” structures refer to structures that were not producing at the time of their destruction. Idle 

structures are unlikely to re-start production or to be re-developed at a later time. We consider 

any structure inactive prior to 2003 incapable of future production. 

“Uneconomic” structures are producing structures with revenue streams in 2006 that have 

already fallen below their estimated economic threshold. When the revenue stream generated 

by production falls below a structure’s economic threshold, the operator will stop producing. 

 

2.3. Forecast Future Production (STEP 2) 

The model curves determined in Step 1 are used to forecast future oil and gas production for 

the three classes of assets identified: 

• Normal producers: structures that yield best-fit oil and gas production 

profiles with R2 ≥ 0.75. 

• Chaotic producers: structures that have initial best-fit production profiles 

with R2

 < 0.75. 

• Young producers: structures with less than 7 years production history. 

 

Structures that do not exhibit a reasonable model fit or are early in their life cycle are subject to 

a greater amount of forecasting uncertainty. These structures are considered separately. For all 

three asset classes, the production curves q

i

(s) determined in Step 1 are used as the forecast 

model. Time is initialized to the year 2006 (t = 1), and for the model form and decline curve 

parameters determined, we step ahead year-by-year in the production forecast, yielding q

i

(s) = 

(q1

i

, q2

i

, ...). 

The forecast is performed under the assumption of “stable reservoir and investment 

conditions.” This is a strong assumption. A structure that was producing prior to the appearance 

of a hurricane is assumed to produce according to its historic rates after the event. We assume 

that the modeled production will not be altered in the future due to reservoir/production 

problems or additional investment (to enhance production, recover additional reserves, etc.). 

We control for the impact of the stability assumption on our model results by performing 

sensitivity analysis. 

 

2.4. Forecast Future Revenue (STEP 3) 

 

Revenue is estimated by multiplying the oil and gas production forecast by the average market 

hub prices in the year received. The hydrocarbon quality (API gravity, sulfur content, etc.) and 

transportation expense to deliver production to market is not considered. Company oil and gas 

sales are primarily made in the spot market or pursuant to contracts based on spot market 

prices. In an attempt to reduce price risk, a company may enter into hedging transactions with 

respect to a portion of future production. The impact of hedging or other price risk management 

strategies that the owner may have employed are not considered. 
16

Revenue in year t for structure s is computed as follows: 

rt(s) = qt

o

Pt

o

+ qt

g

 Pt

g 

where Pt

o

 and Pt

g

 represent the average oil and gas price in year t, respectively. We assume a 

price deck that is constant throughout the life cycle of the structure: Pt

o

 = Po and Pt

g

 =Pg. 

The revenue forecast vector starts in the year 2006 and is denoted as: ) ( ) ( , , , r s = r

1 r2 r3 L . Five 

commodity price scenarios are employed: P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = 

$60/bbl, Pg = $6/Mcf}; P(III) = {Po = $80/bbl, Pg = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg

 = 

$10/Mcf}; and P(V) = {Po = $120/bbl, Pg = $12/Mcf}. For each scenario, the oil and gas price 

is assumed constant over the life cycle of the structure. 

2.5. Estimate Abandonment Time (STEP 4) 

 

When the production revenue generated by the asset falls below its current costs, the asset is 

considered uneconomic and production at the structure will cease. The time at which a structure 

is no longer commercial is determined by comparing the revenue in year t, rt(s), to the 

economic limit of the structure, τa(s), yielding Ta(s): 

T (s) min{t |r (s) (s)} a t a = <τ

The value of the revenue threshold τa(s) is derived from empirical relations using historical data

and is correlated with structure characteristics such as development type (caisson, well 

protector, fixed platform), primary production (oil, gas), and site characteristics (water depth). 

The values of the economic limit represent category averages based on statistical analysis of 

over 1,500 structures removed in the GOM over the past two decades. Ta(s) determines the time 

- for a given production forecast, price deck, and revenue threshold - that a structure will no 

longer be commercial (economic). At t = Ta(s), a rational operator will stop producing, which 

will terminate the cash flow vector: ( ) ( , , , ) 1 2 T (s) a r s = r r L r . 

2.6. Cumulative Production and Discounted Cash Flow (STEP 5) 

The cumulative production Q(s) and discounted cash flow V(s) associated with each structure is 

computed from 2006 (t = 1) through the time of abandonment (t = Ta(s)) as shown: 

∑=

= =

( )

1

( ) ( )

T s

t

t

a

Q Q s q s

∑= + = =

( )

1 (1 ) ( )

T s

t

t

t a

D

r V V s

The choice of D has a significant impact on the value of lost production and the redevelopment 

decisions of operators. Each company uses its own rate to guide decisions, which may be the 
17

cost of capital, the borrowed cost of money plus the cost of dividends, the return from the least 

profitable investment, etc. For our purposes, since we are evaluating the aggregate value of lost 

production, a common discount rate is applied. 

2.7. Aggregation 

The final step is to aggregate the production profiles and discounted cash flow across all 

structures in the sample set. The model output for structure s is the forecast production profile, 

q

i

(s), cumulative production, Qi(s), and discounted cash flow, V(s). If the set of hurricane 

destroyed structures is denoted Γ, aggregating across this collection yields: 

Γ = ∑s

i i q ( ) q (s)

Γ = ∑s

i i Q ( ) Q (s)

Γ = ∑sV ( ) V (s)

The cumulative oil and gas production, Qo(Γ) and Qg(Γ), and the value of production, V(Γ), 

represent the primary model output. 

 

2.8. Economic Limit and Estimation Techniques 

2.8.1. Economic Limit 

When marginal costs exceed marginal revenues and the net cash flow for a structure is 

negative, the operator is unlikely to continue production. Operations may be shut down 

temporarily or permanently, depending upon the producing status of the lease, whether oil or 

gas is being produced, etc. The economic limit is defined as the time when the direct operating 

cost of the structure is equal to the income under production (Harrel and Cronquist, 2007). 

The economic limit criteria is reasonable given profit-maximizing decision makers. In practice, 

an operator may shut-in wells before the economic limit is reached if the return on the 

investment does not satisfy a given threshold or the operator decides for strategic reasons to 

exit the region. An operator may also produce for a period of time after the economic limit is 

reached if they intend to perform additional drilling on the property or believe prices will 

increase to return the operations to profitability. Because many structures in the GOM are 

operated in units either on a field- or lease-basis, the cash flow position of an individual 

structure is often reviewed in terms of its incremental impact to the overhead position of the 

production unit. An operator may continue to produce at marginal levels at a loss simply to 

delay the cost of abandonment. The decision criteria an operator employs for a specific asset is 

ultimately unobservable to analysts outside the company, but this does not negate the use of the 

economic limit as a proxy for these criteria. 
18

2.8.2. Estimation Techniques 

The economic limit of a structure can be estimated based on its operating cost or by using 

historical data to assess the revenue position of structures at the time they stopped producing. 

Both approaches have advantages and disadvantages. With expert opinion, estimates can be 

performed quickly and updated relatively easily. The main advantage of historic data is that we 

are measuring actual outcomes that incorporate a broad set of random events. Ultimately, the 

two approaches are roughly similar in their level of uncertainty. 

 

Expert Opinion 

The EIA provides oil and gas lease equipment and operating costs on an annual basis for 

domestic oil and gas production operations (USDOE, EIA, 2007). EIA personnel track 

equipment, labor, and maintenance cost, and categorize operating costs on a location and 

production basis. For the GOM, operating costs are estimated for 12- and 18-well slot platforms 

with dual-completions assumed to be 50, 100, and 125 miles from shore (corresponding to 

water depths of 100, 300, and 600 feet, respectively). Maximum crude oil production is 

assumed to total 11,000 BOPD and maximum associated gas production is assumed to be 40 

MMCFPD. Meals, maintenance, helicopter and boat transportation, communication, insurance, 

and administration are included in expenses; water disposal costs are not included. Table B.1 

provides operating cost estimates for offshore wells displayed by platform size and water depth. 

On a per-well basis, operating costs range from $621,000/well to $802,000/well. 

Historical Data 

In the threshold level approach, the revenue of structures at the time of their abandonment is 

quantified relative to a set of attributes. Structures are grouped according to type (caisson, well 

protector, fixed platform), primary production (oil, gas), and site characteristics (water depth). 

Inflation-adjusted averages are computed across each categorization based on structure 

removals in the GOM over the past two decades (Kaiser, 2008a). We associate the economic 

limit of a producing structure with its category average (Table B.2). Near abandonment, most 

structures will be producing from a small set of wells. When normalized on a per well basis, 

there is general agreement between the expert opinion values in Table B.1 and the historic data 

presented in Table B.2. 

2.9. Descriptive Statistics 

 

Three decline models were fit to each structure’s oil and gas production profile and the best-fit 

model parameters are shown in Table B.3 in terms of structure type, model function, and 

frequency of occurrence. The average value of the model coefficients, average model fit, and 

coefficient of variation are also depicted. All producing structures were modeled, including idle 

and uneconomic producers. The exponential decline was the most frequently applied model 

specification. 

The number of model curves classified as idle, uneconomic, normal, young, and chaotic are 

shown in Table B.4. Idle and uneconomic structures form the largest subset of the collection. 
19

Nearly half the destroyed structures were no longer producing or were producing at levels 

below their economic limit in 2006. Of the remaining structures, 39 of the 67 producers yielded 

reasonable model fits; 19 producers were classified as young producers; and 9 did not yield an 

acceptable best-fit curve. 
21

Chapter 3. Model Results and Limitations

In this chapter we estimate the value of lost production assuming that all destroyed structures 

will be abandoned and that no redevelopment will occur. In Chapter 4, we will review the 

redevelopment status of destroyed structures. The value of lost production is estimated to range 

between $1.3 billion to $4.5 billion depending upon the scenario assumptions employed. For a 

future average oil and gas price of $100/bbl and $10/Mcf, the total lost production is estimated 

to be $3.7 billion. We perform sensitivity analysis, describe the maximum redevelopment cost 

per structure that will yield a specific rate of return, and discuss the limitations of modeling. 

3.1. Value of Lost Production 

For each destroyed structure, we forecast future production and abandonment according to the 

model specification described in Chapter 2. Production is valued at a constant oil and gas price 

across the life cycle of each asset under five scenarios. We break out the production forecast 

and valuation for structures that yielded an acceptable initial model fit – normal producers 

(Table C.1); structures with less than 7 years production history – young producers (Table C.2); 

and structures that required additional processing to yield an acceptable decline model – 

chaotic producers (Table C.3). Model results for all three categories are subject to uncertainty, 

but the later two asset classes – and especially young producers – are considerably more 

uncertain than normal producers. The aggregate forecast and valuation is summarized in Table 

C.4. 

For the normal producer class, the amount of lost production is reasonably sensitive to the price 

deck (Table C.1), while for the early and chaotic producers, the variation in production output 

is less sensitive (Tables C.2 and C.3). The likely explanation for this is due to the nature of the 

models employed in Table C.1 (which includes exponential, harmonic, and hyperbolic curves), 

relative to the assumed (exponential) decline forms employed in Tables C.2 and C.3. Most of 

the value of future production is contained with the early producers, both by virtue of their 

higher production rates and longer anticipated production cycles. It is interesting to note that 

across all producing structures, the amount of lost production is only slightly sensitive to the 

price deck, while the valuation estimates are highly sensitive. This is primarily due to the 

mature nature of the producing properties – a high price deck may delay the economic limit, 

but does not play a significant role in contributing to additional quantities of production 

because of the high fixed cost associated with offshore operations. In Table C.2, as decline 

rates increase, production drops more quickly, decreasing the reserves estimates. 

 

3.2. Rate of Return Calculation 

The aggregate present value of each structure’s cash flow stream for each price deck is shown 

in Table C.5 under variable discount rates, extending the valuation estimates provided in Tables 

C.1-C.4. The values represent the maximum capital investment that owners would be able to 

spend to provide a specified return. For a given price deck, as the rate of return increases, the 

allowable capital expenditures will necessarily decrease. As the price deck increases, the 

revenue from production will increase, and with it the total expenditures that can be spent to 

achieve a given return. Thus, as we proceed down a given column, the maximum allowed 
22

investments increase, and as we proceed across a given row, the maximum allowable 

investment decreases. The redevelopment cost per structure that yields a specific rate of return 

is shown in Table C.6. 

 

3.3. Average Redevelopment Costs 

Average redevelopment costs provide insight into the cost equation facing operators. Consider 

an operator with price deck P(III) = {Po = $80/bbl, Pg = $8/Mcf} and a desired internal rate of 

return (IRR) of 15 percent. An “average” GOM operator could spend between $11.4 to 24.3 

million to achieve a 15 percent return, while an operator with a young producer could spend as 

much as $93.1 million on redevelopment and clean-up. An operator that required a 25 percent 

return would have a more constrained capital budget, ranging between $8.2-18.3 million (for 

normal/chaotic producers) to $66.5 million (for young producers). Structures early in their 

production cycle, by virtue of their reserves potential and expected number of years of 

remaining production, can spend significantly more capital for redevelopment. The results in 

Table C.6 represent average cost but can be specialized to individual assets. 

3.4. Sensitivity Analysis 

There are many factors in production and valuation estimation that are not directly amenable to 

analysis. Commodity price level was considered explicitly by using price deck scenarios, and 

for early producers, we illustrated the impact of changes in the assumed decline rate (Table 

C.2). Additional parameters that impact the cumulative production and valuation estimate is the 

threshold used to determine when production will no longer be commercial and the discount 

factor used in the cash flow analysis. We vary the economic limit and the discount rate across 

all structures to determine the degree to which changes in these factors impact the model 

output. 

 

The change in cumulative oil, gas, and BOE production across five price scenarios as a 

function of changes in the threshold level are depicted in Figure C.1 and Figure C.2. In these 

figures, the economic limit τa(s) is multiplied by the factor k, k ≥ 0, and as the value of k

increases, k·τa will increase, causing the economic limit to occur at an earlier time, reducing 

cumulative production and valuation estimates. The greatest change in cumulative production 

occurs at low price decks. 

The sensitivity of the present value to changes in the discount rate is shown in Figure C.3 for 

the price deck P(I) and in Figure C.4 for the price deck P(III). As k and D increase, present 

value decreases. Similar figures can be broken out for each price deck and producer class 

category. 

3.5. Limitations of the Analysis 

3.5.1. Public Data Sources Have Limited Information Content 

Production data is extracted from public domain sources, and so it is not possible to fully 

identify those factors which make each property unique. We are thus limited in our ability to 
23

understand why structures produce in a particular way without detailed, site-specific 

information. Our ability to infer production trends from curve fitting exercises is similarly 

limited, and hence our results are only indicative of general trends, and should only be 

interpreted in this manner. 

 

3.5.2. Inventory of Destroyed Structures May Change in the Future 

We only considered those structures that were destroyed in the 2004 and 2005 hurricane 

seasons. Several dozen structures were severely damaged, and some of these may not return to 

producing status. Conversely, early producers and those structures with a sufficient amount of 

remaining reserves may be redeveloped in the future, which would subsequently reduce the 

quantity and value of “lost” production reported. We assumed that idle structures will not 

return to producing status, and this is believed to be a reasonably good assumption. The impact 

of damaged or destroyed infrastructure that served as an active conduit, link, or hub for other 

producing structures was not assessed. 

3.5.3. Decline Curves Are Subject to Significant Uncertainty 

Decline curve analysis is an empirical technique that relates production data with one or more 

attributes, such as time, cumulative production, reservoir pressure, etc. Empirical equations fit 

data to assumed model forms, and do not include most of the factors that affect past, present, or 

future performance. Extrapolating the results of an empirically-derived equation to the future 

assumes that all the factors affecting performance in the past have exactly the same cumulative 

effect in the future. This is a strong, and certainly, questionable assumption. The use of decline 

curves necessitates assumptions regarding operating policy, field investment, mechanical 

problems, marketing issues, and the occurrence of exogenous events. The collective set of all 

these conditions are assumed constant for all future time and are referred to as “stable reservoir 

and investment conditions.” Changes to any of the above-named factors have the potential to 

dramatically change both the production rate and reserves, which will impact the forecast 

results. 

3.5.4. Decline Curves May Not Be a Reliable Predictor 

The production rate of a well, group of wells, structure, lease, field, or other aggregation unit 

can be fit to any functional form or curve type. The function may fit the observed data so well 

that the user may consider it to be an accurate and reliable predictor of the future. Such a 

conclusion would, of course, be a serious mistake, since many other factors that we cannot 

control or directly account for will impact production levels. The ability to forecast is severely 

restricted by conditions that are both unobservable and unpredictable. 

 

3.5.5. Stage of Production May Not Help to Reduce Forecast Error 

The stage of production of an asset is often used as a rough indication of the amount of 

uncertainty that can be expected in forecast models, but such indicators are often ambiguous 

and should be used with caution. Early in the life of a field, little is known about the extent, 

quality, and drive mechanisms of the reservoir, and at this time, reserves estimates and 
24

production forecasting are the most uncertain. As a field is developed and production 

performance accumulates, the range of error often decreases, assuming no change in investment 

strategy. For mature assets, forecasting is considered less uncertain because a smaller number 

of factors influence production and dwindling remaining reserves are likely to be irreversible. 

 

“Less uncertain” is not certainty, however, and there is still a large degree of unpredictability 

that can occur near the end of the life cycle of production. Offshore production has different 

economic characteristics than onshore production, where fixed costs are smaller and production 

profiles tend to decline at smoother rates. In offshore operations, production levels tend to be 

chaotic throughout the life of the field, and smoothly declining profiles near the end of 

production are not common, exacerbating the difficulty associated with forecasting 

abandonment timing. 
25

Chapter 4. Evaluation of Post-Hurricane Recovery of Destroyed Platforms 

In this chapter we examine the post-hurricane recovery efforts of structures destroyed in the 

2004-2005 hurricane seasons and infer operational information on redevelopment decisionmaking. We review the production and revenue characteristics of structures that restarted 

production through redevelopment and summarize the plans that have been reported through 

February 2009. Our objectives are twofold: (1) to compare the pre- and post-hurricane 

production and revenue characteristics of structures that have been redeveloped with those 

structures that have not yet been redeveloped; and (2) to estimate the redevelopment rates of 

destroyed oil and gas platforms. An evaluation technique is presented to assess the 

redevelopment potential of destroyed structures to help predict the percent of reserves likely to 

be recaptured in future hurricane events. 

 

4.1. Composite Production 

Most destroyed structures were fixed platforms, with gas producers slightly exceeding the 

number of oil producers (Table D.1). One deepwater floating structure, Chevron’s mini 

tension-leg platform (MTLP), was also destroyed. At the time of the analysis (January - 

February 2009), production profiles were only available through August 2008, but by midMarch, production data through December 2008 was reported10. We include as much of the 

recent data as possible, but the reader should be cautioned that this data may be subject to 

reporting error and other integrity issues. Twenty-one of the 81 producing structures restarted 

production via redevelopment, roughly evenly split between oil and gas producers (12 gas, 9 

oil), but by August 2008, only ten of these structures (8 gas, 2 oil) were still producing. By 

December 2008, only two of the original 21 structures were still producing (1 gas, 1 oil).

Composite oil and gas production profiles pre- and post-hurricane for all structures destroyed 

by Ivan, Katrina, and Rita are shown in Figure D.1. Time is initialized at 1 with the occurrence 

of each hurricane and is reported through December 2008 on a monthly basis. The contribution 

of Chevron’s deepwater MTLP Typhoon field is broken out separately since these reserves are 

expected to be recovered after new11 infrastructure is installed and commissioned in 2009-

2010. A longer-term view of production and recovery efforts to date is shown in Figure D.2. 

4.2. Recovered Production 

A list of the destroyed structures that restarted production as of August 2008 is presented in 

Table D.2. In Table D.3, average pre- and post-hurricane daily production is reported for oil 

and gas in terms of barrels of oil per day (BOPD) and thousand cubic feet per day (MCFPD). A 

 

10 There is usually a 3-6 month time delay in production reporting. 

11 The Typhoon field has new owners and a new name. Energy Resource Technology, a wholly owned subsidiary 

of Helix Energy Solutions, acquired a 100% working interest in the Typhoon field (GC 236, 237) from Chevron 

(50%) and BHP Billiton (50%), the Boris field (GC 282), the Little Burn field (GC 238), and farm-in rights on five 

nearby blocks for an undisclosed amount. The new field will be called Phoenix and developed using a floating 

production system featuring a dynamic positioning system and a disconnectable transfer system. The cost of 

redevelopment is estimated at $140 million. 
26

composite stream is reported on a barrel of oil equivalent (BOE) basis. Pre-hurricane 

production levels were computed 1-year prior to the appearance of each hurricane and 

normalized on a daily basis, while post-hurricane production was averaged over producing 

months through August 2008. A post/pre daily production ratio is also depicted. The production 

profiles were generated by aggregating well production associated with each structure, and 

because not all wells have a structure identifier, some profiles might include well production 

belonging to other structures, which could bias the results. 

Stuctures 1479 and 21599 were not producing at the time of the hurricanes. Structure 1479 

began operating in August 2005 but did not produce any hydrocarbons prior to being destroyed. 

Structure 21599 was idle when Rita passed through and last produced in 2001. Structure 1479 

has subsequently been decommissioned. Post-hurricane production totals in Table D.3 do not 

include the production from these two structures. 

In Figure D.3, the pre- and post-hurricane production profiles are compared for those structures 

that restarted production through December 2008 through new wells and structures. The 

aggregate daily pre-hurricane production was 8,460 BOEPD and post-hurricane production was 

9,433 BOEPD. In total, post-hurricane oil production was about 75 percent pre-hurricane 

levels, while gas production exceeded pre-hurricane levels. 

Gas structures appear more successful in redevelopment operations. As of August 2008, eight 

of the 12 gas structures and only two of the ten oil structures were still producing. We do not 

know if any of the structures that stopped production will resume at a later date. Curiously, 

structure 1207 which had the largest recovery (7.31 post/pre production ratio), stopped 

producing in June 2008. Until a lease expires and a structure is decommissioned, we do not 

know if the cessation of production is permanent or temporary. Three gas structures increased 

their post-hurricane production above pre-storm levels (798, 1529, 32033). Oil structure 20981 

also achieved higher post-production levels. 

4.3. Revenue Comparison 

In Table D.4, the average pre- and post-hurricane daily and annual revenues are presented. 

Revenue levels are estimated based on monthly average oil and gas prices reported by the 

Energy Information Administration (EIA) and is CPI-adjusted through August 2008. We do not 

adjust prices for quality differences in gravity and sulfur content, or apply a location 

differential for net-back prices. These may be important factors for specific platforms, but can 

reasonably be ignored in first-order estimates. Because of increasing commodity prices in the 

months following the hurricane events, the post-hurricane revenue streams are nearly identical 

to pre-hurricane levels despite a decline in overall production. Significant differences in preand post-hurricane daily revenue exist on an individual structure basis. 

In Figure D.4, the aggregate monthly revenue streams for all destroyed structures are depicted. 

Collectively, destroyed structures were producing hydrocarbons at an average monthly revenue 

of $60 million (including the MTLP, $104 million) one year before the hurricanes, and 

thereafter, average monthly revenues dropped to about $14 million. For the collection of 

structures that restarted production, post-hurricane daily revenues exceeded pre-hurricane 
27

levels at $360,462/d and $491,015/d (Table D.4). Pre- and post-hurricane monthly revenue are 

approximately $11 million and $15 million. See Figure D.5. 

In Table D.5, the post/pre-hurricane production and revenue ratio distribution is depicted for 

structures that restarted production. We observe that gas structures produced at almost twice 

pre-hurricane levels, while oil structures produced at about 20 percent pre-hurricane levels. The 

majority of structures had smaller post-hurricane production and revenue levels. The average 

post/pre-hurricane revenue ratios for gas and oil structures are 2.2 and 0.22, respectively. 

The post/pre-hurricane revenue ratios for structures categorized according to pre-hurricane 

production rates is shown in Table D.6. There is no apparent pattern or trend within the 

production groups. Oil structures that restarted production appear less successful than gas 

restarts, perhaps indicating more complex reservoir characteristics and/or difficult producing 

conditions. We would not expect significant differences in success rates to exist between oil 

and gas producers in full redevelopment. 

4.4. Redevelopment Rates 

The decision to redevelop is based on many factors, including expected production rates and 

remaining reserves, probability of success, cleanup and redevelopment cost, and expected 

future prices. We use pre-hurricane production as a proxy for post-hurricane production 

potential under the assumption that new reserves are not being targeted. Pre-hurricane 

production rates are known with a high degree of certainty. Remaining reserves can be 

estimated with a reasonable degree of certainty, while probability of success and cleanup and 

redevelopment cost are unknown and are not considered. 

Pre-hurricane production rates are used as a proxy of post-hurricane rates that would be 

expected after redevelopment. In this sense, pre-hurricane rates provide a rough indication of 

minimum thresholds that are likely required to be considered for redevelopment. Daily 

production levels for structures that restarted production ranged from 79 – 1,004 BOEPD for 

gas structures and 71 – 4,904 BOEPD for oil structures (Table D.3). Our working assumption is 

that structures with greater pre-hurricane production rates are more likely to be redeveloped. 

This tendency is true although a more complex picture emerges. 

In Table D.7, redevelopment rates are computed for structures according to pre-hurricane 

production levels and production type. Rates are based on production statistics through August 

2008. Gas structures with pre-hurricane production levels less than 600 MCFEPD restarted at a 

3 percent rate, increasing to 11 percent for production levels less than 1,500 MCFEPD. Above 

1,500 MCFEPD, restart rates vary between 20-40 percent. Oil structures with pre-hurricane 

production levels less than 100 BOEPD restarted 14 percent of the time and elsewhere varied 

widely. Overall restart rates for destroyed oil and gas structures are roughly similar, with about 

one-in-four structures restarting production. On an aggregate BOE basis, structures producing 

less than 100 BOEPD have a 7 percent restart rate, while above 100 BOEPD, there is about a 

one-in-four chance of restarting production. 
28

In Tables D.8 and D.9, the restart rates of destroyed structures according to the number of prehurricane producing wells and expected remaining reserves are depicted. Structures without 

any producing wells (i.e. idle structures) are highly unlikely to be redeveloped as shown in 

Table D.8. As the number of producing wells increase, the likelihood the structure will resume 

production also increases. We expect that structures with greater remaining reserves will be 

redeveloped at a greater rate, and this is generally supported by the empirical data. Table D.9 

results are subject to a higher degree of uncertainty than the statistics presented in Tables D.7 

and D.8 because pre-hurricane production rates and the number of producing wells are known 

quantities, while remaining reserves are estimated quantities. 

4.5. Exploration and Development Plans 

Operators that submitted EPs and DOCDs on leases that contained destroyed structures and 

restarted production is shown in Table D.10. We list the number of plans submitted, plan date 

and type, and activity description from August 2005 to February 2009. Hurricane damage is not 

always explicitly mentioned in the plans, indicating that the development may not be related to 

the destroyed structure. If plans are submitted on a lease and hurricane destruction is not 

mentioned explicitly, it is possible that the plans are not in support of redevelopment. 

Conversely, if no plans are submitted and the post-hurricane production profiles are positive, it 

is possible that model error is present. 

Any activity in which new infrastructure is installed or new wells are drilled require that the 

operator submit an EP or DOCD. Plans for redevelopment at five locations were submitted by 

operators where hurricane destruction was mentioned explicitly; four plans were submitted on 

leases that contained destroyed infrastructure without explicit reference to hurricane 

destruction. If a well was re-entered for a workover or sidetrack operation, only an Application 

for Permit to Drill (APD) would be required, and we have not compiled these statistics. 

In Figures D.6-D.8, we plot the expected remaining reserves and pre-hurricane production for 

all destroyed structures by production type according to those structures that have restarted 

production (through August 2008), structures that have submitted DOCD plans (through 

February 2009), structures that have not restarted production (through August 2008) and 

structures that have been decommissioned (through February 2009). In Figure D.6, the point at 

the far upper right is the deepwater Phoenix (formerly Typhoon) development. 

Structures with no pre-hurricane production reside on the vertical axis and 13 of the 30 idle 

structures on the y-axis have been decommissioned. Structures on the horizontal axis also 

deserve comment since it does not seem logical that structures with positive pre-hurricane 

production can have zero expected remaining reserves. This is the result of modeling across a 

structure’s entire life-cycle as opposed to curve fitting an exponential decline, say, from the 

structure’s last producing year12. Structures along the x-axis are often uneconomic but may 

provide opportunities for redevelopment. 

 

12 If an exponential curve is fit to the last production year of a structure, then reserves would be positive and the 

coordinate would move upward off the x-axis. The forecast models were based on best-fit life cycle curves 

referenced to peak or truncated profiles over the structure’s production history. 
29

4.6. Redevelopment Opportunity Matrix 

We delineate three regions in Figure D.8 and label them as “Unlikely Redevelopment”, 

“Possible Redevelopment” and “Probable Redevelopment” based on the data presented (Figure 

D.9). 

Structures in the “Unlikely Redevelopment” quadrant with production rates less than 100-200 

BOEPD are unlikely to be redeveloped because they will suffer from low cash flows and low 

valuations. Redevelopment in this region are estimated at 20 percent and considered unlikely. 

Structures in the “Possible Redevelopment” and “Probable Redevelopment” regions have a 

greater likelihood to be redeveloped. In the Possible Redevelopment quadrant, where prehurricane production rates range from 200 - 1,000 BOEPD and expected remaining reserves 

generally range from 10,000 - 3 million BOE, there is a 40 percent chance of redevelopment. In 

the Probable Redevelopment quadrant where production exceeds 1,000 BOEPD, 

redevelopment rates are estimated at 80 percent. Structures with high pre-hurricane production 

and reserves are good candidates for re-investment because the reserves estimates are 

sufficiently strong and the long-term value of production is expected to exceed expenditures. 

4.7. Redevelopment Success 

Profitability measures are difficult to compute without accurate cost data, but some basic 

inferences may be useful to attempt. Readers are cautioned that conclusions may change as 

better information becomes available. 

In Table D.11, post-hurricane cumulative production, drilling activity, and percentage of 

remaining reserves is depicted for each structure that restarted production. The percentage of 

remaining reserves that have been captured provides an indicator of progress to date. None of 

the structures listed have been decommissioned, and an asterisk denotes if the structure was 

still producing in August 2008. Post-hurricane cumulative production to August 2008 is 

depicted. A cross denotes a structure producing in December 2008. Structures that are still 

producing are expected to capture additional reserves. The reason percent values are in some 

instances greater than 100 percent is provided by clues given in the last two columns of the 

table. The production forecast models and reserves estimates are based upon the assumption 

that no additional capital investment in drilling activity is made beyond the original field plan, 

so operators who drill additional wells are more likely to recover reserves beyond the modelestimated values. 

4.8. Recovery Time 

The time in which a destroyed structure resumes production depends on factors such as the 

complexity of the cleanup operations, access to service vessels, and the strategic interests of the 

owner group. In Table D.12, the time after which destroyed structures resumed production, the 

duration of post-hurricane production, and the status of production in August 2008 is depicted. 

Structures that did not file a DOCD plan were offline an average of 9.6 months for gas 

structures and 12.0 months for oil structures compared to 15.3 months (gas) and 11.2 months 

(oil) for structures that filed plans. Twelve of the 20 structures that restarted production were 
30

offline less than 1 year; 4 structures were offline greater than 2 years. Several of the structures 

producing in August 2008 did not file a lease DOCD plan, which indicates that the production 

data may be erroneous. If a structure stopped producing before August 2008 but has a plan date 

falling after this time, it will likely resume production in the future. 

4.9. Remaining Reserves 

Estimated remaining reserves and discounted gross revenue under constant future price 

scenarios and a discount rate of 10 percent is computed for each structure. Remaining reserves 

were estimated using production models specific to each structure, and for each production 

model, revenue streams were discounted using a 10 percent discount rate assuming first 

revenue would occur either one year (Table D.13) or two years (Table D.14) after initial 

investment. 

Reserves are presented as a range based upon future prices assumed to vary from $60/bbl to 

$140/bbl. Estimates of remaining reserves show varying degrees of sensitivity to changes in 

price depending upon the age of the asset and nature of the production curve. In aggregate, total 

reserves were not sensitive to price variation demonstrating the lack of feedback mechanisms13

in the forecast model. This is not considered a serious drawback, but reflects the limitations of 

the model. For two assets (structures 20981 and 21599), initial revenue fell below the 

structure’s economic limit, and so future production is considered uneconomic. The fact that 

20981 was producing in August 2008 is also problematic, although it is possible that new 

reserves were targeted. For mature assets low on the production curve, reserves exhibit a 

smaller variation to price than younger assets, which is consistent with expectations. 

Discounted revenues increase significantly with changes in future prices and also with the 

timing of the revenue stream. Cash flow received sooner will have a greater present value for 

constant future prices. Estimates of remaining reserves and discounted gross revenue range 

from 7.9 MMBOE and $209 million ($60/bbl) to 8.5 MMBOE and $514 million ($140/bbl). 

See Table D.13. Delaying initial investment by two years will yield smaller discounted 

revenues, ranging from $190 million ($60/bbl) to $468 million ($140/bbl). Refer to Table D.14. 

4.10. Production at Risk 

The number of producing wells is a simple indicator of production risk. Mature structures low 

on the production curve often produce from one or two wells and are especially vulnerable to 

disruptions, since if a well stops producing it may not be economic to rework and/or re-enter, 

causing a sudden disruption in cash flow. Structures in the early/mid-life cycle of production 

usually produce from 5-10 wells and undergo frequent workovers and repair to maintain 

production. 

In Table D.15, the pre- and post-hurricane number of producing wells is depicted for each 

redeveloped structure. The number of producing wells post-hurricane is often small, indicating 

 

13 Price enters the production forecast through the economic limit at the end of the life of the structure and not 

through additional capital investment. 
31

risky production. In several cases, the number of pre- and post-hurricane wells is identical, 

indicating minimal well damage or congruent redevelopment strategies. 

A graphical presentation of the total number of wells drilled and the number of wells plugged 

and abandoned (P&A) for those structures that restarted production is presented on an annual 

basis (Figure D.10) and in cumulative form (Figure D.11). Since all wells will eventually need 

to be P&A’d, the difference between the cumulative number of wells drilled and those P&A’d 

for these structures provides a rough indication of future expenditures. 

 

4.11. Redevelopment Potential 

Most destroyed structures have not been redeveloped and are unlikely to be redeveloped unless 

they fall within the middle or right quadrants of Figure D.9. In Table D.16, a list of structures 

with at least 250 BOEPD are shown along with pre-hurricane daily production and revenue 

levels and if an EP or DOCD plan has been submitted on the area block where the structure is 

located. The total pre-hurricane production from all 61 structures is 30.9 MBOEPD and 

structures with at least 250 BOEPD comprise 90 percent of the total daily production. 

Structures on leases with DOCD plans indicate where production will resume in the future if 

DOCD plans are executed successfully. A total of 14 redevelopment plans have been submitted 

as of February 2009. 

The pre-hurricane daily revenue distribution for structures that have not been redeveloped as of 

August 2008 is depicted in Table D.17. Structures with less than $10,000 daily revenue are 

unlikely to be redeveloped. In the $10,000/d - $50,000/d range, there is a greater chance of 

redevelopment, and structures with more than $50,000/d are likely to be redeveloped. DOCD 

plan submissions broken out according to pre-hurricane daily revenue provides reasonable 

confirmation of this statement. Gas structures appear to present better economics and 

redevelopment potential than oil structures. 

4.12. Remaining Reserves and Discounted Revenue 

Estimated remaining reserves and associated gross revenue is computed for each structure 

assuming five price scenarios, a 10 percent discount rate, and a one-year (Table D.18) or twoyear (Table D.19) investment timing. Reserves are decomposed according to structures that 

have been decommissioned and those leases that have filed an EP or DOCD. About 35 

MMBOE out of 48 MMBOE (= 56 - 7.6 MMBOE) recoverable reserves are accounted for in 

redevelopment plans, nearly 75 percent of the total, which we expect to be recovered. 

Discounted gross revenue estimates range from $988 million ($60/bbl) to $2.32 billion 

($140/bbl). See Table D.18. For a two year investment plan, the aggregate discounted revenue 

ranges from $899 million to $2.11 billion (Table D.19). 

4.13. Redevelopment Potential Drilling Profiles 

The number of producing wells pre-hurricane along with the cumulative number of drilled 

wells and plugged and abandoned wells is presented graphically in Figures D.12 and D.13. A 

large uptick occurred in the number of P&A wells in 2005-2007, but a large inventory still 
32

remains. Structures that restart production will attempt to use available wells when 

redeveloping a field, either as producers or possible injectors, but technical complications will 

limit the extent of the practice. 

4.14. Redevelopment Potential Production Forecast 

Gas, oil, and BOE production forecasts for structures that have restarted production, the MTLP, 

and structures with a submitted DOCD plan are depicted in Figures D.14-D.16. Profiles were 

computed on an individual basis and then aggregated. The MTLP and structures with submitted 

DOCD plans are assumed to begin production in 2010. 
33

PART 2. MARGINAL PRODUCTION IN THE GULF OF MEXICO 

Chapter 5. Wellbore and Structure Categorization 

The purpose of this chapter is to categorize production in the GOM to gain insight into the 

nature and extent marginal production has contributed to total production. We take a historical 

view and consider both wells and structures. We begin with an overview of the life cycle stages 

of production followed by basic definitions. Well inventory and production is considered first, 

followed by structure inventory and production. 

5.1. Introduction 

Experts may disagree on when world oil production will peak, but there is general agreement 

that in the future marginal fields will contribute a greater percentage of world supply. Marginal 

production in the United States is already an important source of onshore supply. One of every 

five barrels of crude oil produced in the lower 48 states and about 8 percent of natural gas is 

produced from a marginal or stripper well (IOGCC, 1999; IOGCC, 2005), defined as a well 

whose production rate falls below 15 barrels of oil per day (BOPD) or 60 thousand cubic feet 

of gas per day (MCFPD). There are nearly 500,000 marginal wells and 230,000 stripper wells 

in the United States (IOGCC, 2005). 

Simple definitions of production rates do not adequately capture the characteristics of marginal 

producers, but is often the standard approach in state and federal regulations. The best way to 

define a marginal well is with respect to the economics of its operation, but the economics of 

production is proprietary and is generally unobservable. When the operating cost of a well, 

structure, or field begins to approach the revenue from production, the unit 

(well/structure/field) can be considered to be marginal. Operating cost can vary considerably 

across operators, depending on size, complexity and age of operations, scale economies, 

accounting units employed, and other factors. 

 

Marginal fields have different economics than large fields, require different recovery 

techniques, and are produced by smaller companies – proprietorships, partnerships, and limited 

liability companies – rather than the corporate structure of independents and majors. Marginal 

wells operate on the lower edge of profitability and the conditions under which profit is 

generated tend to be more restricted than “normal” commercial operations. 

When an onshore field is shut in, wells are plugged and abandoned, the surface infrastructure – 

the pumps, piping, storage vessels, and other processing equipment – is removed, and the site is 

returned to its greenfield condition. After infrastructure and production equipment is removed, 

any hydrocarbons left behind in the ground are usually considered “lost” because prices would 

have to remain high for a sustained period of time to bring the field back into production. In a 

high price environment, operators have a strong incentive to maintain marginal wells in 

production, and if the economics make sense, perhaps even return to abandoned and orphaned 

wells to re-enter and re-develop. The value of all producing properties will eventually approach 

zero and turn negative because of decommissioning obligations. 

 
34

Operating in the Outer Continental Shelf14 (OCS) is more complex and risky, and more capital 

intensive, than onshore environments. Mature assets tend to produce from a small number of 

wells, and if a problem arises, it may not be economic to perform a workover (NRC, 1996; 

USDOE, NETL, 2001). In offshore operations, production levels also tend to be chaotic 

throughout the life of the field, and smoothly declining profiles near the end of production are 

not common, exacerbating the difficulty associated with forecasting abandonment timing. 

Production near the end of the life of an asset is at significantly greater risk than in the early 

years of production. 

 

5.2. Life Cycle Stages 

All producing properties pass through the same life cycle stages from discovery to depletion, 

but each stage is uniquely characterized in terms of its length, risk, cost, recovery, and value 

(Haag, 2005). Production characteristics and profitability change during the life cycle of every 

structure. The capital intensive expenditures associated with drilling wells, fabricating and 

installing infrastructure and topsides equipment, and producing during the early years of a 

structure’s life cycle are gradually replaced by a decreasing revenue stream, high operating 

costs, fewer upside opportunities, and eventually, production that is worth less than the cost to 

operate and maintain the structure. 

 

5.2.1. Exploration and Delineation 

After a lease is acquired and a discovery made, the field will be delineated and the company 

will assign probable values to the expected reserves, costs, and economic measures, and place 

the property in a priority list of development plans. Investments are selected in descending 

order of rank by top management during the capital budgeting process until either the total 

available funds are exhausted or the minimum acceptable yard stick value reached. 

 

5.2.2. Development 

Projects that reach the development stage are subject to a number of complex tradeoffs. 

Development schemes vary widely across the world, depending upon the size, shape, depth, 

heterogeneity, and productivity of the reservoir; the time of development and proximity to 

infrastructure; logistical considerations in moving the production to market; economic 

considerations and technical constraints; strategic decisions such as an interest in establishing a 

production hub for the area; and the lead time required to acquire or design and construct 

structures, rigs, facilities, pipelines, and other downstream facilities. 

 

If a reservoir is small or isolated, it will normally be completed with a “minimal” structure – a 

caisson, well protector, or subsea completion – with flow lines tied back to shore or an 

accompanying fixed platform. Fixed platforms can support both drilling and production 

operations, and tend to be large, self-contained structures built to robust design standards. 

 

14 The OCS of each coastal state generally begins three nautical miles from shore for all but two states – Texas and 

west Florida – which are three marine leagues (nine nautical miles), and extends at least 200 miles through the 

Exclusive Economic Zone. 
35

After a structure has produced for several years, the drive mechanisms and cost structure of the 

field are better understood. Properties usually remain highly profitable and continue to have 

upside potential. As fields pass into the later stages of profitability, production declines, and the 

operating cost begins to rise. The value of the structure will still exceed abandonment cost and 

have positive value, but usually only limited or risky drilling upside remains. The number of 

inactive wells of a structure during mid-life will typically outnumber producing wells. 

 

5.2.3. Redevelopment 

 

A field may be revitalized during its mid-life period. Production and performance data may 

indicate the need for additional wells to increase or accelerate recovery, or new seismic data 

may be obtained to exploit undrilled areas of the reservoir. The infrastructure to support new 

production is in place, but most often, the reserves target per well is not as large as the original 

development. An economic comparison of the expected incremental production versus cost is 

used in decisionmaking. 

 

The natural energy of the reservoir is usually exhausted near the end of the mid-life period, and 

secondary recovery techniques that use injectants to re-pressurize the reservoir and to displace 

oil to producer wells may be considered. Water flooding is the main injectant in secondary 

recovery and gas re-injection for pressure maintenance is also employed. Enhanced oil 

recovery (EOR) refers to reservoir processes that recover oil not produced by secondary 

processes. The primary economic driver for secondary and tertiary recovery is project 

profitability. In some cases, development of a reliable production stream, reserves additions, or 

employment related to project longevity might also be considerations. 

 

A number of offshore fields in the GOM are under secondary recovery, primarily water 

flooding and gas re-injection for pressure maintenance. There are no EOR projects in the GOM, 

and only a few offshore EOR projects worldwide (Bondor et al., 2005; Brashaer et al., 1982). 

The application of EOR methods is more complex in the offshore environment and subject to a 

number of constraints that challenge the economics. Space and weight restrictions, subsurface 

constraints, high capital costs and technical risk, and the need for high reliability impose 

constraints not present in onshore environments which significantly restrict its application. 

 

5.2.4. Sunset Production 

 

Fields that have reached the advanced stages of depletion are referred to as “sunset”, 

“marginal”, “brownfield”, or “mature” properties. Structures that produce from sunset 

properties are nearing abandonment and the value of production is approaching the cost of 

decommissioning. Owners must decide whether an asset should be divested and offered to the 

market or produced to depletion. Owners that decide to sell need to maintain sufficient residual 

value that qualified buyers would be interested in acquiring the property. Some companies 

prefer not to perform decommissioning activities, especially offshore, where costs are 

significantly higher and more uncertain than onshore. Marginal structures usually produce from 

one or two wells and carry a large risk if one of the wells goes off production. Workovers may 

not be economical in mature wells. Fields that are marginal are often sold as part of a large 

package that includes better fields to attract a buyer. 
36

5.3. Wellbore Definitions 

5.3.1. Aggregation Unit 

The wellbore is the most fundamental unit in petroleum studies since all hydrocarbons are 

extracted from one or more formation horizons15 in a well. Typically, a well is produced from 

one horizon and is then recompleted from another (higher) formation at a later period. It is 

possible to produce from more than one formation at the same time as long as the production 

streams are not commingled. 

5.3.2. Exploration and Development Wells 

Exploratory (wildcat) wells are drilled in an area with no known hydrocarbon reserves, while 

delineation and development wells are used to delineate a known deposit and then produce it. A 

successful development well will produce hydrocarbons, while “success” for an exploratory 

well may not actually result in production. Onshore, discovery wells are usually turned into 

producers, while offshore, successful exploration wells may be plugged and abandoned because 

the location is not optimal for field development. Successful exploratory wells may be 

protected with a caisson or well protector, and as delineation wells are drilled, additional 

infrastructure such as fixed platforms, subsea tiebacks, and flowlines will be installed. Today, 

many development wells are deviated or drilled horizontally to enhance production rates and 

reduce pressure drawdown in the wellbore region. 

5.3.3. Production Status 

At any point in time, a well may be producing or inactive. An inactive well is classified as shutin, temporarily abandoned, or idle. Shut-in and temporarily abandoned wells are transitory16

states and may be brought back on-line at a later time. A well that is shut-in or temporarily 

abandoned for longer than one or two years is referred to as idle or non-producing. A well may 

transition between producing and non-producing status several times during its life cycle 

because of workover operations, technical problems, hurricane damage, etc. Idle wells may 

come back into production at a later time, but the probability of returning to producing status 

generally decreases with the time of inactivity. 

 

5.3.4. Fluid Classification 

Wellbore production contains various liquid and gas products, with oil, natural gas, condensate, 

and water the primary components. Hydrocarbon reservoirs contain complex mixtures of liquid 

and gaseous compounds, specific to the site and manner in which the deposits were laid down 

and transformed over time. Hydrocarbons also change as they are released from a high-pressure 

high-temperature environment to ambient conditions and are processed at the surface. 

 

15 An individual sealed reservoir is referred to as a block, and one or more blocks having comparable depth, origin, 

and characteristics is referred to as a horizon. Multi-block horizons are generally created by faulting. 

16 MMS regulations govern the manner in which well production is suspended and the frequency of inspection. 
37

Producing wells contain a mixture of oil and gas, and often, a significant amount of water, 

especially as a well ages. Oil wells produce gas and gas wells produce condensate, and we will 

distinguish between the two output streams. Gas production associated with “oil” wells is 

typically referred to as associated gas, while liquid production associated with “gas” wells is 

called condensate or natural gas liquids (NGL’s). 

5.3.5. Gas-Oil Ratio 

The producing gas-oil ratio (GOR) is the standard way to classify wells as either “oil” or “gas” 

producers. The GOR of a well is defined as the ratio of gas output (expressed in cubic feet) to 

oil output (expressed in barrels) computed on either an annual or cumulative basis. The solution 

gas-oil ratio describes the reservoir conditions of the fluid, and frequently, a value of 5,000 or 

less indicates a black oil with minimal gas production, while a GOR value between 5,000 to 

10,000 indicates a volatile oil with gas production. A solution gas-oil ratio of 50,000 or more 

indicates a gas reservoir. 

The producing gas-oil ratio is not equivalent to the solution gas-oil ratio since it is measured at 

the surface and after processing, but since public data only report produced hydrocarbon 

streams, we necessarily apply the producing GOR in our assessment. We choose to compute 

the producing GOR on a cumulative basis since cumulative metrics take into account the entire 

history of the well (through the time of observation), and is more representative17 than a oneyear snapshot. We apply a threshold value of 10,000 to distinguish between oil and gas wells: 

“oil” wells having a cumulative GOR < 10,000 and “gas” wells having a cumulative GOR ≥

10,000. Sensitivity analysis on this value will be performed. 

5.4. Wellbore Counting Statistics 

5.4.1. Exploration and Development Wells 

The number of exploration and development wells drilled in the GOM is shown in Figure E.1. 

Drilling activity dropped off significantly in 2007 due in large part to the intense recovery 

efforts of the 2005 hurricane season. The last time drilling activity in the GOM fell below 600 

wells drilled was in 1992, the year of Hurricane Andrew. The ten-year (1995-2005) average 

number of wells drilled in the GOM is 1,094; while in 2006 and 2007, a total of 780 and 600 

wells were drilled. 

From 1947-2007, 47,270 wells have been drilled in the GOM: 16,707 exploratory wells and 

30,563 development wells (Figure E.2). The number of exploratory and development wells 

drilled by water depth is depicted in Figures E.3 and E.4. Since the mid-1990s, deepwater 

exploratory wells have played an increasingly important contribution to the total number of 

wells drilled. The total number of exploration and development wells by water depth category 

is shown in Table E.1. 

 

17 GORs change over time with changes that occur in the reservoir, reservoir fluids, and production techniques. 

Trends in GOR are useful to distinguish the drive mechanism of the reservoir and can also be beneficial in 

forecasting. 
38

5.4.2. Producing Wells 

The number of producing wells in the GOM changes over time, increasing when a successful 

exploration or development well goes online, or when a shut-in well returns to producing 

status, and decreasing when a well is shut-in, temporarily abandoned, or permanently 

abandoned. The total number of producing wells in the GOM has never exceeded 8,000, and in 

2006, 5,546 wells were producing (Figure E.5). 

In Figure E.5, the producing well count is disaggregated in terms of oil and gas producers using 

a GOR threshold GOR = 10,000. Prior to 1980, the number of oil wells dominated gas wells, 

but in recent years, the well types have converged (Figure E.6). The 2006 well count realized a 

significant reduction from 2004 (6,825) and 2005 (6,490) levels. At the end of 2006, there were 

2,807 oil wells and 2,739 gas wells. 

Oil and gas well count will vary with the level of the GOR threshold, and so we examine the 

manner in which well count varies as a function of GOR. The default threshold we apply is 

GOR = 10,000, and for any value of GOR < 10,000, the number of wells identified as “oil” will 

decrease as the number of “gas” wells increase. Conversely, for a GOR > 10,000, the number 

of oil wells will increase with a comparable reduction in the number of wells identified as gas. 

The greater the difference between the threshold values selected, the greater the difference in 

the well counts across category. 

In Figures E.7 and E.8, the number of producing oil and gas wells for three GOR levels 

(5,000; 10,000; and 15,000) are depicted. Changing the GOR threshold from 10,000 to 5,000 

decreases the average annual number of oil wells by 6.8 percent, and in aggregate across the 

entire time horizon, by 8.6 percent. The gas well count increases on average by 11.0 percent, 

and in aggregate, by 9.7 percent. The percentage values are not equivalent because the number 

of oil and gas wells vary each year, and thus, the percentage contribution. The percentage ratio 

of oil wells as a function of GOR is shown in Figure E.9. 

5.5. Wellbore Production Statistics 

5.5.1. Aggregate Production 

Oil wells produce gas and gas wells produce oil, and as one would suspect, gas production from 

“oil” wells and liquid production from “gas” wells do not represent a significant percent of 

category production. On an individual well basis, however, residual production can be 

significant, depending on the level of the primary output stream; e.g., if the level of oil 

production is sufficiently high (and thus with it, associated gas) gas production will also be 

high. Liquid (oil and condensate) production from gas wells are a smaller percentage of the 

total production levels (Figure E.10) than gas production from oil wells (Figure E.11). 

Cumulative liquid and gas production from oil and gas wells is depicted in Figures E.12 and 

E.13. 

 
39

5.5.2. Oil Producers 

Oil wells are categorized by production level in terms of daily output, as producing less than 15 

barrels oil per day (BOPD), between 15-200 BOPD, and greater than 200 BOPD. Oil well gas 

production is categorized18 in terms of daily output as producing less than 90 thousand cubic 

feet per day (MCFPD), between 90-1,208 MCFPD, and greater than 1,208 MCFPD. 

 

Oil wells are classified in terms of daily output for each year the wells are active and we also 

count and categorize gas output. Oil well oil production by category (number of each oil well 

division categorized according to daily oil production) is shown in Figures E.14 and E.15. 

About 500 oil wells currently populate the < 15 BOPD category, another 1,600 or so wells fall 

within the 15-200 BOPD category, and around 600 wells reside within the > 200 BOPD class. 

If a marginal oil well is considered as producing less than 15 BOPD, then as a percentage of the 

total number of producing wells, we see that the number of marginal wells has been relatively 

constant over the past 3 decades, comprising roughly 10 percent of the total number of oil wells 

in any given year (Figure E.16). The number of oil wells categorized according to daily gas 

production is shown in Figures E.17 and E.18. 

 

Oil well oil production is shown in Figure E.19, and in Figure E.20, the relative contributions 

of each category are depicted. Oil well oil production is primarily due to large producers. 

Marginal producers contribute a relatively insignificant amount of liquid production. Medium 

wells contribute larger quantities of liquid and gas production, but relative to the larger 

producers, the values are relatively small on an annual basis. Oil well gas production is 

depicted in Figure E.21. 

 

5.5.3. Gas Producers 

Gas producers are classified according to marginal, medium, and large producer groups similar 

to oil producing wells. Gas wells categorized according to daily oil production is shown in 

Figures E.22 and E.23; gas wells categorized according to daily gas production is shown in 

Figures E.24 and E.25. In 2006, there were 531 wells with a daily gas production less than 90 

MCFPD; 1,179 wells with daily production between 90 MCFPD to 1,208 MCFPD; and 1,029 

wells producing greater than 1,208 MCFPD. Our focus is on gas well gas production. The 

population ratio of marginal gas producers is similar to marginal oil producers, but the trend 

toward greater marginal production and smaller large producers is clear as current gas fields 

deplete and new fields remain undiscovered (Figure E.26). 

 

Gas well condensate production is shown in Figure E.27. Gas well gas production is shown in 

Figure E.28. Although large producers constitute less than half of the total number of gas wells, 

they contribute more than 95 percent of gas well gas production. Between 1947 and 2006, gas 

well oil production contributed approximately 11 percent of cumulative oil production in the 

GOM. 

 

 

18 The oil and gas categories are equivalent under the standard heat-conversion ratio: 6 MCF = 1 BOE. 
40

The relative contribution of gas well gas production according to daily production levels is 

shown in Figure E.29. Similar to oil producers, marginal gas producers contribute an 

insignificant amount of total gas production, and even if the 90-1,208 MCFPD producer 

category is included, we see that the levels are reasonably constant around 10 percent. The 

most significant portion of gas in the GOM has always come from large gas producers. 

5.6. Structure Definitions 

5.6.1. Aggregation Unit 

Wellbores access formations and are tied into structures via flowlines and pipelines for 

processing. Each well is associated with a unique structure, and the composite wellbore 

production streams yield the production profile of a structure. 

 

Structures that are in close physical proximity and connected by a walkway, bridge, or similar 

infrastructure is referred to as a complex. The MMS assigns each site where platforms are 

installed a complex identification number, and within a complex of structures, individual 

structures are identified by a structure number. All structures in the OCS are uniquely identified 

by a complex identification number and structure number. 

Leases, fields, and basins represent higher levels of aggregation. A field is an organizational 

unit that groups together production from similar blocks, horizons, or prospects, while a lease is 

an artificial (man-made) geographic construct. Lease and field units are not considered further. 

5.6.2. Structure Type 

Offshore structures are designed for a particular field, and are built according to a specific 

design criteria at a specific location and time. Shallow water structures, defined as development 

in water depths less than 1,000 ft, primarily employ caissons, well protectors, and fixed 

platforms. 

5.6.3. Production Status 

A structure is said to be active in the year of observation if it produces hydrocarbons during the 

year, while a structure is said to be idle if it once produced hydrocarbons but has not been 

productive for at least one year prior to the year of observation. 

An auxiliary structure is a structure that has never produced hydrocarbons but serves in an 

auxiliary and supporting role, say as a quarters facility, flare tower, or storage platform. 

Auxiliary structures may exist on a producing or non-producing lease, and may or may not 

serve a useful economic function. Because auxiliary structures are not directly associated with a 

production stream, it is not easy to identify the structure as active or inactive. 

Structure classification depends on the time of observation and structures may transition 

between active and idle status one or more times during their lifetime. A structure that is 
41

inactive for several years, however, is unlikely to return to active status.19 Idle structures may 

or may not serve a useful economic function, and because we do not break-out the historic 

records of auxiliary structures over time, we prefer use of the category descriptor “nonproducers” when referring to structures that are not in production rather than “idle” structures. 

5.6.4. Production Type 

Analogous to the wellbore classification adopted previously, a structure with cumulative GOR 

< 10,000 cf/bbl is defined as an oil structure, while if cumulative GOR > 10,000 cf/bbl, the 

structure is identified as a gas structure. 

5.7. Structure Counting Statistics 

5.7.1. Active Structures 

The number of structures installed in the GOM by structure type is depicted in Figure E.30. The 

“other structures” category shown in Figure E.30 refers to deepwater structures, such as spars 

and tension leg platforms, and although they only represent a few dozen structures (Table E.2), 

they are currently responsible for about 72 percent of the total oil production in the GOM. Over 

the past decade, the number of structures installed per year has range between 73 and 161 (with 

average 119, standard derivation 27). To date, nearly 7,000 structures have been installed, with 

about one-third of the installations being caissons (Figure E.31). 

When lease production ceases, all oil and gas infrastructure on the lease will be removed. The 

first offshore structures in the GOM were removed in the early 1970s, and by 1990, the number 

of structure removals in a typical year began to exceed 100 (Figure E.32). Over the past decade, 

the number of structures removed has ranged from 76 to 194 (with average 136, standard 

deviation 36). In total, nearly 3,000 structures have been removed in the GOM, almost half of 

which are caissons (Figure E.33). In Table E.3, the number of removals by structure type and 

water depth is depicted. About half of the installed unmanned fixed platforms have been 

removed, compared to only 10 percent of the manned installations. 

The number of active (existing) structures in the GOM is shown in Figure E.34. There are 

currently 3,838 active structures: 2,324 fixed platforms, 380 well protectors, 1,091 caissons, 

and 43 other structures. The number of removals began to equal or exceed the number of 

installations in the early 1990s (Figure E.35), and so during this time, the inventory of active 

structures quit growing and began to stabilize. The average number of structure removals now 

slightly exceeds the number of installations, which we anticipate will continue in the future, as 

fewer, larger structures in the deepwater are installed, and a larger number of smaller structures 

supporting marginal fields, are abandoned. The cumulative number of installed, removed, and 

active structures is shown in Figure E.36. 

 

19 According to federal regulations, all structures need to be removed from a lease within one year after production 

stops. However, if idle structures reside on a producing lease, the structures can remain on the lease for as long as 

the lease is in production. 
42

5.7.2. Producing Structures 

The number of structures producing hydrocarbons in the GOM each year is shown in Figures 

E.37 and E.38. The number of producing structures is dynamic, similar to a “pool”, where new 

(producing) installations or idle structures that re-enter production add to the inventory, and 

decommissioned producing structures deplete the inventory. A producing structure may also 

stop production for a period of time, perhaps due to hurricane damage or reservoir problems, 

temporarily reducing the producing structure count, only to re-enter the inventory at a later 

time. 

 

Producing structures are classified according to their primary production using the gas-oil ratio 

threshold GOR = 10,000 (Figure E.37). Gas structures began to outnumber oil structures in 

1978, and currently represent about 65 percent of the total inventory of producing structures in 

the GOM (Figure E.38). The sharp decline in the number of producing structures in 2006 is due 

to the impact of the 2005 hurricane season: producing structures declined from 2,328 in 2005 to 

2,017 in 2006. At the end of 2006, there were 813 oil structures and 1,204 gas structures in the 

GOM. 

 

5.7.3. Non-producing Structures 

The number of non-producing (idle) structures in the GOM is computed as the difference 

between the number of active structures in a given year and the number of producing structures. 

The count of non-producers includes auxiliary structures, and as mentioned previously, at an 

aggregate level it is not possible to distinguish between those structures that serve a useful 

function and those structures that do not. The number of non-producing structures in the GOM 

on a historical basis is recreated in aggregate (Figure E.39) and as a percentage20 of the total 

number of active structures (Figure F.40). Over the past several decades, the percentage of the 

total infrastructure in the GOM that is non-producing has remained relatively constant. 

5.8. Structure Production Statistics 

5.8.1. Aggregate Production 

Annual oil (and condensate) and gas (including associated gas) production from GOM 

structures is shown in Figures E.41 and E.42. Oil structures produce the majority of oil 

production with relatively small amounts of condensate contributed by gas structures. Oil 

structures produce a significant amount of associated gas, currently about a third of total gas 

production. Gas production from “oil” wells and condensate production from “gas” wells will 

correlate with primary output stream. Cumulative oil and gas production from oil and gas 

structures is shown in Figures E.43 and E.44. 

 

20 The percentage values before 1960 appear quite high, and may be due to reporting problems and/or other data 

integrity issues, or may simply be reflective of the immature state of the industry at the time. 
43

5.8.2. Oil Producers 

The contribution to total oil production from low (marginal), medium, and high producer 

groups is shown in Figure E.45. Marginal producers contribute less than 0.1 percent total 

production on both an annual and cumulative basis (Figure E.46). Gas production from oil 

structures is shown in Figure E.47. 

The number of oil structures that produce less than 15 BPD, between 15-200 BPD, and more 

than 200 BPD as shown in Figures E.48 and E.49. The number of oil structures categorized as 

marginal producers has remained relatively stable for the past 25 years, similar to the number 

of structures in the medium and high producer category. Gas production from oil structures is 

depicted in Figures E.50 and E.51. 

5.8.3. Gas Producers 

The contribution to total gas production from the low (marginal), medium, and high producer 

groups is shown in Figures E.52 and E.53. Liquid production from gas structures is shown in 

Figure E.54. 

The number of gas structures categorized according to daily gas production is shown in Figures 

E.55 and E.56. High producer groups constitute the majority of active gas structures and 

contribute more than 95 percent of total annual production and cumulative production. While 

marginal producers account for about 4.6 percent of total active structures, their gas production 

is less than 0.1 percent on both an annual and cumulative basis. 

 

Oil production from gas structures is shown in Figures E.57 and E.58. Marginal producers 

contribute a significant amount of liquid production, due to the changing nature of the gas 

reservoir near the end of their life. 
45

Chapter 6. Shallow Water Committed Assets Production Forecast 

The purpose of this chapter is to forecast oil and gas production from shallow water committed 

assets in the GOM. Shallow water is defined as water depth less than 1,000 ft and committed 

assets refer to the collection of all existing structures circa December 2006. We present a 

general overview of the factors that impact production and describe the units of our analysis. 

The basic model framework is introduced, followed by a description of the forecast 

methodology with worked examples. Model results are summarized. 

6.1. Historical Production 

About 25 percent of the United States domestic oil and gas supply comes from the OCS, and in 

2007, OCS lands averaged daily production of about 1.3 million barrels (MMbbl) of oil and 7.6 

billion cubic feet (Bcf) of natural gas. More than 96 percent of offshore production takes place 

in the GOM, and currently accounts for more than 25 percent of domestic oil production and 14 

percent of domestic natural gas. Historical trends in oil and gas production on a BOE basis is 

shown in Figure F.1. 

Oil production in the GOM rose rapidly in the 1960’s, peaked in 1971, and has undergone 

cycles of increase and decline. From 1991 through 2001, oil production increased, leveling off 

through 2003, and then declined in 2004-2005, due in large part to hurricane activity. Since 

1997, shallow water production has steadily declined, while deepwater production does not yet 

appear to have peaked (Figure F.2). Gas production in the Gulf has fallen steadily from 2001. 

Shallow water gas production has dropped beginning from 1996, with deepwater production 

unable to prevent an overall decline in total production levels (Figure F.3). 

6.2. Factors that Impact Production 

Oil and gas fields are developed in accord with the drive mechanisms of the reservoir, fluid 

characteristics, the investment decisions of operators, geologic constraints, the technology 

available at the time of development, infrastructure and market requirements, and many other 

factors. Production is the direct result of development and operational decisions, as well as 

events driven by factors which cannot be predicted – such as the price of oil and gas, and 

regulatory requirements – and events that interrupt production – such as extreme weather, 

equipment failure and problem wells. Additional factors such as the level of data aggregation 

will also impact the measurement of production volatility. A combination of design factors and 

exogenous conditions determine the production profiles that are observed in practice. 

6.2.1. Drilling Schedule 

The production rate of a structure will fluctuate as the number of producing wells change. 

During the development period, as the number of wells increase, the production rate of the 

structure will increase. As wells mature and the formation is depleted, structure production will 

decline. Not all wells will reach their economic limit at the same time, however, and as wells 

are shut-in or temporarily abandoned, the decline rate will accelerate. Well production begins 

and ends at different periods of time, and so depending on the drilling schedule, production 
46

profiles will exhibit various shapes. Near the end of the life of a structure, there may only be 

one or two wells producing, as opposed to a dozen or more wells at the start of development. 

Problems with wells at the end of the field life will have a more significant impact on 

production than earlier in the life cycle of the field. 

6.2.2. Level of Aggregation 

There are many choices when selecting the level of aggregation, grouped broadly across fluid 

type, spatial categories, and time dimension. The level of aggregation and time dimension 

selected will impact the appearance and statistical characteristics of production profiles. A well 

produces from one or more formation zones and each well is associated with a unique structure. 

A field will require one or more structures for development, which may be contained within 

one lease or overlap two or more leases. A field is a geologic structure while a lease is an 

artificial (man-made) geographic construct. Production is reported on a monthly basis and may 

be aggregated at any higher time dimension (semiannual, annual, etc.). 

6.2.3. Reservoir Drive Mechanism 

There are several sources of energy available to move reservoir fluids to the wellbore, and the 

type of drive mechanism and the geometry (depth, areal extent, shape) of the reservoir will 

affect decisions on the location and number of wells and the manner in which a field is 

developed. The primary drive mechanisms that provide the energy for oil production include: 

solution gas drive, water drive, and gas-cap drive. For gas production, gas expansion and water 

drives are common. Reservoirs are usually subject to more than one drive mechanism over the 

life of the asset and can be used to explain the general shape of production profiles, the 

producing gas-oil ratio, and extent of water cut. 

6.2.4. Enhanced Recovery 

A producing reservoir is a depleting resource that will exhibit declining production at some 

point during its life cycle. After or during primary recovery, secondary recovery techniques 

such as waterflooding may be initiated. Other enhanced recovery techniques such as CO2

flooding, chemical injection, heat treatment, etc. may also be implemented if the economics are 

favorable. The primary economic driver for secondary and tertiary recovery is project 

profitability. A number of offshore fields in the GOM are under secondary recovery, primarily 

water flooding and gas re-injection for pressure maintenance, but there are no enhanced oil 

recovery projects in the GOM. 

6.2.5. Fluid Classification 

Each reservoir contains a unique blend of hydrocarbon compounds and exists under conditions 

specific to the site and nature of deposition, and so no two reservoirs are developed or behave 

the same when produced. Produced water is often a major output stream. Processing facilities 

separate the various phases and treat each stream before transportation to shore. The basic 

system collects production from each well or zone through an individual flowline. The 

flowlines are manifolded together and production from the combined well streams goes to the 
47

bulk separator. Liquid hydrocarbons are collected and sent to an oil treater, where it is 

sometimes necessary to heat the oil to facilitate the removal of latent gas and water. Produced 

water is treated to remove the latent oil and gas and is then injected back into the reservoir or 

deposited into the ocean. Declines in productivity generally coincide with changes in reservoir 

pressure which affects the physical chemistry of reservoir fluids and the cost of treatment. 

6.2.6. Development Plan 

A development plan will normally include the structure type, equipment capacity, and the 

number, location, and timing of development wells. Engineers design the production rate to 

maximize field profitability within the constraints of the optimal production rate – the 

maximum rate at which a well or field can be produced – without wasting reservoir energy or 

leaving oil in the reservoir. The maximum efficient production rate is usually designed to 

range between 3 – 8 percent of the recoverable reserves. To obtain a high ratio, the operator 

will need to have a large number of producing wells and adequate production equipment to 

handle the volumes of oil and gas produced. A low ratio provides an indication that an operator 

has chosen to drill less wells and produce longer. Fewer wells require smaller production, 

processing, and transportation facilities; less operating personnel; reduced financing cost, and 

presumably, lower operating expenditures. Fields generally deplete faster than operating costs 

decline, so as production falls, the cost per barrel will typically increase unless the asset is 

divested or farmed-out to a lower cost operator. 

Production is generally considered to follow three phases: ramp-up, plateau, and decline. In 

practice, there is no one general model that can be used to describe production. Following the 

installation, hookup, and certification of the platform, development drilling is carried out and 

production started after a few wells are completed. The plateau period represents the maximum 

rate of production the facilities were designed to handle, pipeline capacity, or contractual 

constraints. The duration of the plateau is based upon the productivity of the reservoir and the 

economies of the project. After peak production, fields will decline due to the geology and 

pressure loss at a rate determined by the reservoir drive, investment, and economic conditions. 

6.2.7. Reservoir Pressure 

In order to be produced, reservoir fluids have to flow through the pore space of the rock, into 

the wellbore, and up through tubing to the surface facilities. After a well is drilled, a pressure 

sink is created at the wellbore, which allows oil and gas to flow because of the pressure 

differential. As the reservoir pressure depletes, the friction across the formation and through the 

tubing drops the pressure further, and the production rate declines. Changes in reservoir 

pressure affect the physical chemistry of reservoir fluids, and at some point in time, artificial 

lift methods will be required to continue production. How long a well flows before artificial lift 

is required depends on initial pressure and maintenance programs, water cut, fluid viscosity, 

and many other factors. Gas fields flow until the reservoir pressure approaches separator 

pressure conditions. 
48

6.2.8. Workover Schedule 

 

Several times during the life of a producing well, the well will be shut in and remedial work 

performed to maintain, restore, or improve production. This is called a workover. A workover 

may involve solving mechanical problems (such as collapsed casing, casing holes, collapsed 

tubing), cleaning out the well (from scale, waxes, and sand), stimulation, or replacing downhole 

equipment (such as leaking tubing, malfunctioning gas-lift valves, or leaking packers). A well 

can be recompleted to plug and abandon a zone on the bottom of a well and completed in a 

higher zone, to drill deeper, or to sidetract in a lateral direction. Workover activity will take 

production streams off line temporarily, and when the well re-starts production, the flow rates 

and decline parameters may be subject to a step change. 

6.2.9. Problem Wells 

A well may go off production due to mechanical reasons (e.g., equipment failure if pumping), 

wellbore damage (e.g., from unconsolidated sands), extraneous water production (e.g., due to a 

casing leak or bad cement job), or other issues such as flow assurance. One of the primary 

reasons to maintain a periodic workover schedule is to reduce and/or minimize the occurrence 

of problem wells and subsequent production interruption. 

6.2.10. Cost Structure 

Onshore, decline curves are often characterized by relatively smooth decreasing functions, 

while offshore, the additional uncertainty and risk of the operating environment contributes to a 

more volatile production profile. The cost of operating and maintaining offshore infrastructure 

is more expensive and uncertain than onshore, which will also negatively impact an operator’s 

ability to sustain commercial production late in its life. Structures are abandoned as high 

operating costs set an economic limit that typically range from 3 – 7 times higher than for 

comparable onshore operations (Brashaer et al., 1982). 

6.2.11. Weather Events 

There are many exogenous events that contribute to production volatility and weather is a 

primary factor. Offshore production occurs in an uncertain and hostile environment, where 

weather, supply vessel delays, and other events may temporarily disrupt or significantly impair 

production. The occurrence of extreme weather forces operators to shut down facilities and 

evacuate personnel. Hurricanes will suspend production for at least several days, and 

sometimes, weeks or months at a time, and the magnitude of the disruption relative to the time 

scale of aggregation will determine the impact observed. In physical terms, shutting-in a well 

will usually not cause a loss of the hydrocarbon resource, but in financial terms, the impact of 

deferred production can have a significant economic effect. Operators attempt to recover 

deferred production by increasing production “at the margins,” but because operators usually 

produce at the maximum design rate allowed by the reservoir dynamics or equipment capacity, 

the ability to increase production is often limited without additional capital investment. 
49

6.2.12. System Reconfiguration 

Reconfiguration, restaging, and optimization of surface facilities and subsea architecture are 

commonly applied to maximize production and increase recovery when bottlenecks arise or 

production levels reach threshold levels. Production will be offline during some or all of a 

redevelopment period. 

6.2.13. Price Effects 

Operators control the production rate of oil and gas and generally produce at capacity to 

maximize return on investment, but differences may arise in how oil and gas is produced. Oil is 

a global commodity while gas is often produced to satisfy local demand. Changes in the local 

demand and supply balance of gas will impact prices, which will impact production decisions 

to varying degree. Associated gas is produced in conjunction with crude production, and since 

crude is almost always produced at capacity, the quantity of associated gas is a byproduct of oil 

production and outside the operator’s control. Non-associated gas is expected to be more 

sensitive to price fluctuations to maximize profitability; i.e., gas production from nonassociated reservoirs may be reduced in the summer season in anticipation of higher gas prices 

during the winter season. This sort of operational flexibility is generally not present with 

associated gas production. 

6.2.14. Regulations and Operating Policy 

The occurrence of extreme weather in the GOM requires operators to decide what facilities to 

shut-down and when. Decisions are operator, facility, and event specific, guided by the level of 

risk tolerance of the operator and knowledge regarding the expected storm path. MMS 

regulations require operators to evacuate all personnel before the latest safe departure time and 

shutdown all production activity affected. During the early years of GOM production, gas was 

allocated, and so output was constrained by government regulation rather than market forces, 

but today, this is no longer an issue. 

6.3. Production Classification 

Offshore structures come in many different types and sizes and can be characterized in a 

number of ways, similar to well characterization. Structures are classified into four 

subcategories denoted as: (I) Young, (II) Normal, (III) Chaotic, and (IV) Latecomer. A fifth 

subcategory is used to identify structures with missing identification: (V) Unknown. Recall that 

young structures are defined to be any structure with less than 7 years production. Normal 

structures have production profiles that are best-fit by decline curves with R2 ≥ 0.75, while 

chaotic structures have best-fit decline curves with R2 < 0.75. Latecomers have a production 

history 7 years or more, and a peak occurring within the past 7 years. Unknown structures have 

missing identifiers on structure type, water depth, or similar attribute that prevent their 

classification. The number of active structures classified by primary production and structure 

type are shown in Table F.1. 
50

6.4. Forecast Methodology 

The methodology used to forecast production across each structure class is now described. For 

young structures, a production forecast is achieved through a history match, using the statistical 

characteristics of structures that have been previously removed as the matching set. Normal and 

chaotic structures have produced to a condition of pseudo steady-state flow which allows curve 

fitting with standard regression techniques. Latecomers exhibit unusual profiles, usually late 

peaks, that do not permit standard curve fitting techniques to be employed. For latecomer 

structures, various heuristic techniques are applied to generate forecast curves. In the next 

section, examples with step-by-step calculations are used to illustrate the manner in which 

forecasting is achieved. 

6.4.1. Young Structures – History Matching 

Structures with a short production history pose difficulties in forecasting because the structure 

is unlikely to have achieved its peak production and the limited sample population cannot 

support regression analysis. What constitutes a “young” (or new) structure is, of course, 

somewhat subjective, and we select 7 years as the threshold21 to denote young structures. All 

structures with less than 7 years production are classified within the young class category. 

To forecast the future production of a young structure, we match the cumulative production of 

the structure with “similar” structures that have been previously removed in the GOM. 

Similarity is defined according to structure type, water depth, and primary production. The 

production history of an average structure removed within each categorization that most closely 

resembles the cumulative production of the structure at the time of observation is used as the 

forecast curve. The details of how this is accomplished follows. 

Young structures are classified according to structure type (ST), water depth (WD) and primary 

production (OIL/GAS). Three structure types (caisson, well protector, fixed platform), three 

water depth categories (<60ft, 60-200ft, >200ft), and two production groups (oil, gas) are 

employed for a total of 3*3*2 = 18 categories, denoted by Гijk, i, j = 1, 2, 3; k = 1, 2, or 

alternatively, Г (ST, WD, OIL/GAS). Within each category Гijk, a number of subcategories ijk γ

are created based upon the size of the sample set. 

From 1973-2006, a total of 1,867 gas structures and 477 oil structures were removed in the 

GOM. These structures were categorized according to structure type, water depth, and primary 

production, and then depending on the number of structures N within the category Гijk, average 

production profiles q ( ijk γ ,t) for each subcategory ijk γ was computed. The number of profiles 

computed (i.e., the number of subcategories) increases with the number of elements N in the 

sample. If N ≤ 25, 3 average production profiles are computed. For 25 < N < 50, 5 average 

profiles were computed, and for N ≥ 50, 10 average profiles were used. Hence, there are either 

 

21 We recognize that our age cut off is arbitrary, but the selection is robust in the sense that neither the size of our 

sample set nor the results of our modeling differ dramatically with small changes in the cut-off point. 
51

3, 5, or 10 average profiles q ( ijk γ ,t) within each main category Гijk. The distribution of 

subcategories that result is shown in Table F.3. 

Average production profiles are computed for each category and used as reference 

(comparison) profiles. We illustrate 3 of 18 categories that were employed in Figures F.4 – F.6. 

In Figure F.4, the five average BOE production profiles in the fixed platform, 0 – 60 ft water 

depth, oil production, subcategory is depicted. In Figure F.5, the average BOE profiles for the 

caisson, 60 - 200 ft, gas production, subcategories are depicted. In Figure F.6, the average BOE 

profiles for the well protector, 60-200 ft water depth, oil production, subcategories are shown. 

Profiles may not be smooth or yield strictly decreasing trends because they represent sample 

averages. Trends are reasonably consistent, however, with production increasing, on average, 

according to structure type and water depth category. 

The cumulative production of structure s of age T, Q(s,T), is compared with the cumulative 

production from each subcategory profile at the same age T, Q ( ijk γ ,T) = ∑=

T

t

ijk q t

1

(γ , ) , and the 

profile with the smallest absolute difference is selected as the best match: 

 

Q *( ijk γ ,T) = 

γ

min Q(s,T) Q( ,T) ijk − γ . 

The annual production curve corresponding to Q *( ijk γ ,T) is q *( ijk γ ,t) and is used as the 

structure match. Q(s,T) will either be greater or less than the category cumulative production, 

Q *( ijk γ ,T), and so we adjust the profile using the multiplier α , 

α = . ( , )

( , )

Q T

Q s T

ijk γ

Note that if Q(s,T ) < Q( ,T) ijk γ , α <1, and if Q(s,T ) > Q( ,T) ijk γ , α > 1. The final step is the 

identification of the structure production with the category average: 

q(s,t) = α q *( ijk γ ,t), t > T. 

A summary of the history matching procedure for young structures is presented in Table F.4. 

6.4.2. Normal and Chaotic Structures – Regression Techniques 

 

Decline curve analysis is a common method used for analyzing reserves in areas with 

established performance trends and was previously described in Chapter 2. The decline curve 

method extrapolates an established trend into the future, assuming that the wells have been 

produced to a steady-state flow and that whatever conditions that influenced the behavior of the 

well in the past will continue to influence it in the same way in the future. A summary of the 

best-fit curve parameters for normal and chaotic structures are shown in Table F.5. For each 
52

structure class and production type, the best fit curves are depicted by frequency along with the 

average coefficients for the model parameters and average R2-values. 

6.4.3. Latecomer Structure - Heuristics 

The production curves of some structures may yield multiple peaks during their lifetime, often 

due to changes in capital investments or production problems. Multiple production peaks after 

plateau are common. Pre-plateau peaks may also occur if development occurred in stages or 

unforeseen events arose during development. There are several ways to handle these profiles, 

and we choose to use heuristic techniques to generate the forecast. The most common heuristic 

method adopted was to truncate the production history and fit a decline curve from the most 

recent production peak of the structure. If an adequate number of observations to perform 

regression is not available, an assumed exponential model form and decline parameter was 

adopted. 

6.5. Illustrative Examples 

6.5.1. Young Structures – History Matching 

Structure 587 is a caisson in 63 ft water depth with a GOR = 590,000. First production began in 

2000, and by 2006, cumulative production was 2.08 MMBOE. 

From the removed structure category Г(CAIS, 60-200, GAS), we compare the cumulative BOE 

production of structure 587 with the cumulative production from each of the 10 subcategories 

in year six (Table F.6). The cumulative production of structure 587 is closest to subcategory 10, 

which is selected as the reference category for the structure (Figure F.5). The ratio of the 

structure’s cumulative production to subcategory 10 cumulative production is α =2.08/2.36 = 

0.88. 

The forecast production of structure 587 in the seventh year is computed from the average BOE 

production of subcategory 10 in the seventh year multiplied by the adjustment factor α: 

 q

BOE(587,7) = 0.88 × 169,353 = 149,312 BOE. 

The production stream is then decomposed into its oil and gas components assuming a constant 

GOR = 590,000: 

 

 qo

(587,7) = 149,312 BOE ×

) 6,000cf

bbl

bbl

590,000cf (1

1

+ ×

=1,503 bbl 

 qg(587,7) = (149,312 BOE – 1,503 bbl) × 6 Mcf/BOE = 886,853 MMcf 

This process is repeated each year using the subcategory 10 profile as reference forecast and 

assuming a constant GOR throughout the life cycle of the structure. The forecasted production 

profile of structure 587 is shown in Figure F.7. 
53

If oil and gas maintain an average price of $80 per barrel and $8 per Mcf over the production 

lifetime of the structure, 587 is forecast to cease production in the year 2014 when the 

structure’s revenue ($621,847) is equal to its economic limit. 

6.5.2. Normal Structure – Regression Techniques 

Structure 33 is a typical normal structure. First oil began in 1997 and production peaked a year 

later. The best fit regression was determined to be an exponential model with R2 = 0.99 (Figure 

F.8): 

 

 q

BOE (33,t) = qBOE (33,0) × e-0.4821t

. 

The peak year is set as time 0. In 2007, the BOE production is forecast to be: 

 q

BOE (33,9) =1,156,791 BOE × e -9×0.4821 = 15,090 BOE, 

which yields the expected future production profile shown in Figure F.9. The GOR is used to 

decompose the BOE production stream into oil and gas production: 

 

 qo

(33,t) = q

BOE (33,t) ×

6000

1

1

GOR

+

 qg

(33,t) = q

BOE (33,t) – qo

(33,t) 

The cumulative GOR of structure 33 is 1,190. In 2007, the expected annual oil and gas 

production is 12,592 bbl and the expected annual gas production is 14,987 Mcf: 

 qo (33,9) = 15,090 BOE ×

6,000

1,190 1

1

+

 = 12,592 bbl 

 qg (33,9) = (15,090 BOE –12,592 BOE) × 6 Mcf/BOE= 14,987 Mcf 

Production is expected to stop when revenue falls below the operating threshold. Assuming oil 

and gas prices average $120/bbl and $12/Mcf over the forecast horizon, production will cease 

in 2011 when the structure revenue ($245,776) equals its economic limit. Historical and 

projected oil and gas production is shown in Figure F.10. 

6.5.3. Chaotic Structure – Regression Techniques 

Structure 152 is a caisson in 18 ft water depth and a gas producer with a GOR = 231,642. 

Structure 152 has a 9-year production history, and because the best-fit curve is an exponential 

model with R2

 = 0.69, we classify the structure as a chaotic producer and apply regression 

modeling. The exponential curve has the form, 
54

 q

BOE (152,t) = 368,601× e -0.2794 t

, 

and in 2007, the BOE production is q

BOE (152,9) = 368,601e (-0.2794 × 9) =29,803 BOE, yielding 

an oil and gas production stream: 

 qo (152,9) = q

BOE (152,9) ×

6,000

231,543 1

1

+

 = 753 bbl 

 qg (152,9) = (29,803 BOE– 753 BOE) × 6 Mcf/BOE = 174.3 MMcf 

For $120/bbl oil and $12/Mcf gas, the expected revenue in 2007 is computed to be $2,181,960. 

Under this price scenario, the structure is expected to stop producing in 2012 at its economic 

limit of $539,520 (Figure F.11). 

6.5.4. Latecomer Structure - Heuristic Method 

Structure 23266 is a fixed platform in 219 ft water depth that is primarily a gas producer (GOR 

= 12,533). Multiple production peaks require care in modeling, and ultimately, forecasting from 

such structures remains subject to significant uncertainty. We truncate the first half of the 

production profile in Figure F.12 and determine the peak year of the second half (Figure F.13). 

Since there are 8 observations in the truncated history, the sample population is sufficient for 

regression analysis. The best-fit decline curve is a harmonic function with n = 1.876 and c = 

0.00074. 

Structure 10042 illustrates another variation of latecomer structures (Figure F.14). In this case, 

since there are only a few years of empirical data from peak production, we assume that 

production declines following an exponential curve at rate d: 

 q

BOE (10042,t) = qBOE (10042,0) × e-dt 

In 2006, structure 10042 has 255,053 BOE production. For d = 0.1, the expected BOE 

production of structure 10042 in 2007 is: 

 q

BOE (10042,1) = 255,053 BOE × e(-0.1 × 1) = 230,782 BOE 

The GOR of the structure is 125,967, yielding the oil and gas production streams qo

(10042,1) = 

10,493 and qg(10042,1) = 1.32 Bcf. At $120/bbl oil and $12/Mcf gas, the revenue in 2007 is 

computed to be $17.1 million. Structure 10042 is expected to stop producing in 2041. 

6.6. Model Results 

6.6.1. Active Structure Forecast 

The average number of committed shallow water structures is shown in Figure F.15 across a 

40-year time horizon. In 2006, 380 of the 2364 shallow water producing structures fall below 

their economic threshold and were removed from analysis, reducing the inventory of 
55

committed assets as shown in Table F.7. Producing structures start out economic, but as 

production declines, operating expenditures increase and commercial structures will transition 

into marginal status, and eventually, stop production at their economic limit. The trajectory of 

active structures represents the average of multiple simulations that varied oil and gas prices, 

economic limits, and discount rates according to the distribution functions shown in Table F.8. 

A one standard deviation envelope is used to bound the average trajectory, and assuming 

normality conditions on the model parameters, the trajectory of the active structure count is 

expected to stay within the envelope about two-thirds of the time. 

6.6.2. Production Forecast 

The oil, gas, and BOE production forecast for committed shallow water structures are 

illustrated in Figures F.16 – F.18. Production profiles exhibit the same decreasing trend as the 

average count trajectory. One and two standard deviation envelopes bound the results. 

In Figures F.19 and F.20, the annual and cumulative BOE production profile per structure class 

is depicted. In Figure F.20, we observe that young and normal structures are responsible for 

nearly two-thirds of cumulative production from the committed asset inventory. Latecomer 

structures are also a significant producing class. In Figures F.21 and F.22, the annual and 

cumulative gas production for each asset class is depicted; and in Figures F.23 and F.24, the 

annual and cumulative oil production is depicted. 

6.6.3. Composite Statistics 

The expected amount of hydrocarbon production from committed assets in the GOM is 

estimated to be 1,056 MMbbl oil and 13.3 Tcf gas assuming the range of the design space 

given in Table F.8. The present value of hydrocarbon production from this asset class is 

estimated to be $149.4 billion. 

6.6.4. Cumulative Production Models 

Cumulative oil, gas and BOE production in the GOM is given by regression models depicted in 

Table F.9 and summarized as follows: 

 Qo (d, Po

, Pg, a) = -2.1E9d + 5.5E7Po + 5.6E8Pg + 3.5E7a

 Qg(d, Po, Pg, a) = -2.1E10d + 6.4E7Po + 7.0E8Pg + 2.9E7a 

 QBOE(d, Po

, Pg, a) = -5.6E9d + 1.6E7Po + 1.7E8Pg + 8.3E7a, 

where d represents the decline rate of latecomer structures that do not have a sufficient time 

horizon for analysis, Po

 is the expected oil price ($/bbl), Pg is the expected gas price ($/Mcf), 

and a is the multiplier of the economic threshold. Most of the coefficients of the regression 

model are of the expected sign and statistically significant. 

Application of the regression functions provide a quick way to infer cumulative production for 

any value of (d, Po

, Pg, a) selected within the design space. For example, for (d, Po, Pg, a) = 
56

(0.10, 140, 10, 1), the total BOE production from the committed asset set is estimated to be 

QBOE(0.10, 140, 10, 1) = -5.6E8 + 2.24E9 + 1.7E9 + 8.3E7 = 3.3 billion BOE. 

6.6.5. Present Value Models 

The present value functionals of the oil, gas and BOE production is given by regression models 

depicted in Table F.10 and summarized as follows: 

 PVo

(d, Po, Pg, a, D) = -9.3E7d + 7.0E5Po + 1.3E6Pg + 8.3E5a – 1.5E8D

 PVg

(d, Po, Pg, a, D) = -9.3E7d + 1.2E5Po + 8.7E6Pg – 4.5E6a – 1.6E8D

 PVBOE(d, Po, Pg, a, D) = -1.9E8d + 8.1E5Po + 10.0E6Pg – 3.66E6a – 3.1E8D 

The present value functionals employ the same model variables as the cumulative production, 

but also require the discount rate D to discount the future cash flows. Again, most of the 

coefficients of the regression model are of the expected sign and statistically significant, and 

can be used to infer present values for any input variables within the design space. Present 

value functions provide a quick and simple way to estimate the production value of the 

committed assets for given model parameters; e.g., PVBOE (0.1, 100, 10, 1, 0.15) = $112 billion. 
57

Chapter 7. Meta-Model Evaluation of Marginal Production 

The purpose of this chapter is to forecast the level of marginal production from the existing 

inventory of shallow water assets in the GOM. The model framework is outlined and the model 

structure described. The results of our modeling include the trajectories of structure counts over 

a 60-year horizon, average production profiles, and expected cumulative production and 

valuation functions. 

7.1. Model Framework 

7.1.1. General Procedure 

A meta model methodology is described to quantify the quantity and value of marginal and 

economic production. The approach is as follows. 

Step 1. Sample the input parameters d, Po

, Pg, m, a, D from their respective 

distribution functions. 

Step 2. (a) Forecast future oil and gas production, qo(s,t) and qg(s,t), and 

revenue, r(s,t), based on the model specifications described in Step 1. 

(b) Determine the time when each committed asset turns marginal and 

uneconomic based on the marginal threshold, τm(s), and economic limit, 

τa(s), respectively. Denote the time a structure turns marginal and 

uneconomic as Tm(s) and Ta(s). 

(c) Decompose each structures production profile into “economic” and 

“marginal” components. The economic component of production (s) is 

defined for t ≤ Tm(s), while the marginal component (s) is defined for 

Tm(s) < t ≤ Ta(s). 

(d) Compute the cumulative oil and gas production for each structure 

according to its economic and marginal status, Q (s) i

e and Q (s), im and the 

associated discounted cash flows, Ve(s) and Vm(s). 

Step 3. Aggregate total oil and gas production for all structures in the shallow 

water Gulf of Mexico, Qo

(Γ) and Qg(Γ), and compute the total value of 

production, V(Γ). 

Step 4. Repeat Step’s 1-3, and regress the model output {Qo

(Γ), Qg(Γ), V(Γ)} 

against the input variables (d, Po

, Pg, m, a, D) to construct functional 

relations describing cumulative production and value. 

7.1.2. Preprocessing (STEP 0) 

Each producing structure in the Gulf of Mexico is classified into one of five categories based 

upon the age of the structure, the nature of its production profile, and the completeness of 

information available. The classes Young, Normal, Chaotic, Latecomer, and Unknown were 

defined previously in Chapters 2 and 6. The committed shallow water structures are classified 
58

according to class and primary production as follows: 525 young structures, 1,280 normal 

structures, 90 chaotic structures, 427 latecomers, and 42 unknown structures (Table G.1). 

7.1.3. Initialization (STEP 1) 

The user selects the model variables and quantifies the manner in which they vary. The input 

set is user-defined and varies with the objectives of the problem and the model formulation. 

The variables that we employ include: the price of oil and gas (Po

, Pg), the marginal and 

abandonment threshold multipliers (m, a), and the discount rate (D). A decline parameter is 

associated with those latecomer structures that do not have a sufficient production history to 

perform regression analysis. In this case, we assume an exponential model with decline rate d. 

The input parameters of the model are denoted by the vector (d, Po, Pg, m, a, D). 

Each system parameter is governed by a distribution function i = 1,..., 6, that is assumed 

invariant22 across time. The specification of each function is determined by empirical analysis 

or user preference. For example, if the historic price of oil is determined to follow a 

Lognormal distribution according to the parameters μ and σ

2

, Po ~ LN(μ,σ

2

), the user may 

model future prices according to this specification or may prefer to assume another distribution 

type, such as the Uniform distribution U(a,b) with endpoints (a,b). 

 

The distribution functions of the model variables that we select in this analysis are shown in 

Table G.2. We refer to the set of all input variables and their distribution functions as the 

design space. 

 

7.1.4. Forecasting (STEP 2) 

(a). The model curves determined in preprocessing are used to forecast future oil and gas 

production under the assumption that production will not be altered in the future from 

reservoir/production problems or additional investment. The assumption of “stable reservoir 

and investment conditions” is required to eliminate additional sources of uncertainty that we 

are not prepared to model. 

The production forecast for each structure for each hydrocarbon stream i (i = oil, gas, BOE) are 

initialized in the year 2006 (t = 1): 

 

q

i

(s) = (q

i

(s, 1), q

i

(s, 2), ... ). 

Revenue is estimated by multiplying the oil and gas production forecast by the average market 

hub pricesin the year received. The hydrocarbon quality (API gravity, sulfur content, etc.) and 

transportation expense (netback cost) to deliver production to market is not considered. 

Revenue in year t for structure s is computed as 

 

22 It is possible to allow the system parameters to vary with time, but the additional complexity involved with this 

modification requires a significant investment in processing capability and modeling structure. It is for this reason 

that we do not allow input variables to vary across time within a given simulation run. 
59

r(s, t) = qo(s, t) Po(t) + qg(s, t) Pg(t), 

where Po

(t) = Po and Pg(t) = Pg represent the oil and gas price in the year t which is assumed 

constant throughout the life cycle of the structure. The revenue forecast vector is denoted as: 

r(s) = (r(s, 1), r(s, 2), ...). 

(b). The time at which a structure becomes marginal or economic is determined by comparing 

its revenue in year t, r(s, t), to a marginal threshold, specific to the structure, τm(s): 

T (s) min{t |r(s,t) m (s)} m m = < ⋅τ , 

where m is a user-defined multiplier that is used to capture the sensitivity of the model output 

to variation in parameter uncertainty. 

 

The time at which a structure is no longer profitable is determined by comparing the revenue in 

year t, r(s, t), to the economic limit of the structure, τa(s): 

 

T (s) min{t |r(s,t) a (s)} a a = < ⋅τ , 

where a is user-defined multiplier that plays a role similar to m, but in this case, tests the model 

results against the sensitivity of the economic limit. 

 

The values of τa(s) are determined by historic data as described in (Kaiser, 2008a) and applied 

previously in Chapter 6, while τm(s) is set as a multiple of τa(s). Tm(s) denotes the time when 

structure production transitions from economic to marginal status. Ta(s) denotes the time when 

production at the structure is no longer profitable and cash flow terminates: 

r(s) = (r(s,1), r(s,2), ...., r(s,Ta(s)). 

For convenience, we assume that once a structure reaches its economic limit it will be removed 

from the GOM. According to federal regulations, structures only need to be removed from a 

lease once lease production stops. A structure that reaches its economic limit can thus be “held” 

by lease production, and this can be built into the model (e.g., Kaiser, 2008b), but we have not 

pursued this development. 

(c). At some point in time during the life of every structure, an asset will transition from 

economic to marginal status and continue to produce marginally until it becomes unprofitable. 

The production profile of each structure is decomposed into economic and marginal 

components: 

( ) ( ( ,1), , ( , 1), ( , ), , ( , )), m m a

i q s = q s L q s T − q s T L q s T
60

where the “economic” production components are defined by q(s,t), t = 1, ...., Tm-1, and the 

“marginal” components are defined for t = Tm, ..., Ta. At any point in time, a structure is either 

“economic” or “marginal.” 

The revenue stream is similarly segmented into economic and marginal components 

corresponding to the economic and marginal components of production: 

r(s) (r(s,1), ,r(s,T 1),r(s,T ), ,r(s,T ) (r (s),r (s)), = L m − m L a = e m

where, ) ( ) = ( ( ,1), , ( , −1),0,...,0 e Tm r s r s L r s and )). ( ) (0,...,0, ( , ),..., ( , m m Ta r s = r s T r s 

(d). The cumulative production Q(s) and discounted cash flow V(s) associated with structure s

is decomposed into its economic and marginal components for oil, gas, and BOE output 

streams, beginning from 2006 (t = 1) through the time the structure reaches marginal status (t 

< Tm(s)), and thereafter, until the structure is no longer economic (Tm(s) ≤ t < Ta(s)): 

( ) ( ),

1

1

Q s q s m

t

T

t

i i

e ∑

−

=

= Q (s) q (s) a

m

t

T

t T

i i

m ∑=

= , Q (s) Q (s) Q (s) i

m

i

e

i

T = + . 

The discounted present value of the economic and marginal production streams are computed 

similarly: 

∑

−

= + =

1

1 (1 )

( ) ( )

Tm

t

t

t

e D

r s V s , ∑= + = a

m

T

t T

t

t

m D

r s V s

(1 )

( ) ( ) , ) V (s) V (s) V (s T = e + m . 

The value of D denotes an industry-wide discount rate. 

 

7.1.5. Aggregation (STEP 3) 

The model output for structure s is the forecast production profiles, (s) and (s); production 

status vectors, σe(s) and σm(s); cumulative production, (s), (s), (s); and discounted cash 

flows, Ve(s), Vm(s), and VT(s). The collection of all shallow water structures in the GOM is 

denoted as Г and the aggregation is presented as: 

( ) (s), sσ e Γ = ∑σ e ( ) (s) s

σ m Γ = ∑σ m . 

q ( ) q (s), s

i

e

i

e Γ = ∑ q ( ) q (s) s

i

m

i

m Γ = ∑ . 

Q ( ) Q (s), s

i

e

i

e Γ = ∑ Q ( ) Q (s), s

i

m

i

m Γ = ∑ (Γ) = (Γ) + (Γ) i

m

i

e

i QT Q Q . 
61

(Γ) = ∑ ( ), s

e e V V s (Γ) = ∑ ( ), sm m V V s VT (Γ) = (Γ) + (Γ) Ve Vm . 

7.1.6. Simulation and Regression Analysis (STEP 4) 

The input parameters for each loop of the simulation include (d, Po, Pg, m, a, D), and the output 

includes { (Γ), (Γ), (Γ), (Γ), (Γ), (Γ), (Γ)} e m T

g

T

o σ e σ m QT Q V V V . The model curves used to forecast 

production is fixed, with the exception of structures in the latecomer class, where a subset of 

profiles are modeled with an assumed decline parameter. The values of (d, Po, Pg, m, a, D) are 

sampled from distribution functions for each loop in the cycle, the output metrics are computed, 

and after a sufficient number of iterations have been performed, the model outputs are 

regressed against the input parameters. 

 

7.2. Model Structure and Interpretation 

7.2.1. Model Specification 

A linear model is specified that relates the output measures to the input parameters, as follows: 

 

∑=

= +

6

1

0

i

iXi f α α , 

where f is selected from the set { ,

i Qe , i Qm ,

i QT Ve , Vm , VT} and (X1, X2, X3, X4, X5, X6) = (d,

Po

, Pg, m, a, D). A linear model is specified for simplicity and ease in interpretation, and if the 

model fits are unacceptable, it is straightforward to apply a general nonlinear specification. The 

model coefficients αi, i = 0, ..., 6 are unique to the selection of f and will vary with the size and 

shape of the design space of the input parameters. 

 

7.2.2. Expected Signs 

The signs of the model coefficients are expected to follow certain values, which can be 

motivated through economic theory and the mechanics of the model structure. A check on the 

signs of the model coefficients provides a first indication of the veracity of the model results. 

 

The coefficient α0 represents the fixed term (intercept) of the functional and its sign is 

indeterminate. The fixed term coefficient may be excluded from the formulation, depending 

upon user preference and model specification. 

 

The coefficient α1 is associated with d, which defines the rate of decline of production for a 

subset of latecomer structures. The magnitude of the coefficient α1 relative to the other model 

coefficients depends upon the proportion of total production controlled by d. If d increases, 

holding all other model parameters fixed, structure production will decline faster and reach its 

economic limit sooner, and so the quantity of latecomer reserves and its value will decline. We 
62

would thus expect α1 < 0 for Qe

i

, Qm

i

, and QT

i

and Vm, Ve, and VT since increasing d will lead to 

declining cumulative production and value. 

 

The coefficients α2 and α3 are associated with the price of oil and gas, respectively. As Po

 and 

Pg increase, revenue streams for all assets will increase, delaying the onset of the economic 

limit. This will allow the production of additional reserves, and at an elevated price level, lead 

to a greater valuation. Thus, increases (decreases) in Po

 and Pg will lead to increases (decreases) 

of α2 and α3, and so we would expect α2, α3 >0 across all the functional outputs Qj

i

and Vj

i

 (i = 

oil, gas; j = m, e, T). We expect differences to exist in the relative magnitude of oil and gas 

price for a particular asset (depending, say, if it is primarily an oil or gas producer) and on the 

stage of its lifecycle; e.g., if it is economic or marginal. Because the value of economic 

production is expected to be at least one or two orders-of-magnitude larger than a structure that 

is a marginal producer, oil and gas prices are expected to play a more significant role for 

economic production. 

The coefficient α4 is associated with the multiplier m, and the coefficient α5 is associated with 

the multiplier a. These multipliers are used to vary the marginal and economic thresholds τm

and τa. The impact of the multipliers will vary depending upon the functional under 

consideration. 

The value of m ranges over a positive interval bounded below by a and above by twice the 

upper limit of the economic threshold interval. As m increases, m·τm(s) will increase, and thus, 

production will become marginal at an earlier time, decreasing the amount of economic 

production (Qe) and its value (Ve). Since marginal production occurs at an earlier time and at a 

higher rate, the amount of production that is classified as marginal (Qm) will subsequently 

increase along with its value (Vm). The value of the coefficient α4 is thus expected to be 

negative for the functionals Qe and Ve, and positive for Qm and Vm. For the composite 

production and valuation functionals QT and VT, coefficient α4 does not enter into the model 

formulation because there is no need to segment the production and revenue streams. 

 

The variable a ranges over a positive interval, and as a increases, a·τa(s) will increase, forcing 

production out of profitability at an earlier time. This will not have any impact on Qe and Ve, 

but will reduce marginal production (Qm) and its value (Vm). Thus, the coefficient α5 will not 

enter into the economic production model but is expected to be negative for the functionals Qm

and Vm. By linearity, QT and VT will also be negative. Coefficient α5 will not enter into the Qe

and Ve functional since the amount and value of economic production is not influenced by what 

happens at the end of the life of the structure. 

 

The coefficient α6 is associated with the discount rate D used to compute present value, and 

thus, will only influence the valuation estimates Vm, Ve, and VT. The behavior of discount rate

with present value is obvious: as D increases, the value of future cash flow declines, and so, we 

expect the sign of coefficient α6 to be negative for all three valuation functionals. Further, since 

changes in discount rate have a greater impact on early cash flows, we would expect that the 

magnitude of α6 would be greater for Ve than Vm since it is defined earlier in the life of cycle of 

the asset. Coefficient α6 is not included in the model specification for cumulative production 

since it is only a component of the valuation estimate. 
63

7.2.3. Design Space 

The model input parameters and assumed distribution functions are shown in Table G.2. The 

vector (d, Po

, Pg, m, a, D) represents our design (input) parameters and the collection of the 

variable intervals denote the design space: 

 

∑ = {(d, Po

, Pg, m, a, D) | 0.05 ≤ d ≤ 0.30, 80 ≤ Po ≤ 160, 8 ≤ Pg ≤ 16, a ≤ m≤ 6, 

 0.5 ≤ a ≤ 0.3, 0.08 ≤ D ≤ 0.14}. 

The Uniform distribution has well-defined endpoints, and for the Normal distribution, we 

truncate the endpoints at two standard deviations. 

 

Model output includes a count of the number of economic and marginal structures over time; 

cumulative economic, marginal, and total production; and the valuation of each production 

stream and class. Cumulative production and present value are numeric quantities, while the 

count and annual production profile are vectors. Numeric quantities are easier to configure and 

compute, while vector quantities require somewhat more advanced modeling techniques to 

handle. 

The influence of the design space on the model results is subtle but important. The design space 

represents the input variables of the model, and as such, all model results are related to the size 

and shape of ∑. If the distribution type or parameter values changes, the coefficients of the 

regression model will also change. Fortunately, small perturbations in ∑ along one or more 

directions - either in distribution type or parameter value - do not change the output 

significantly. Changes in the dimensionality of the design space, however, which would occur 

by adding or deleting variables, will have a more significant impact since the structural aspects 

of the model are no longer compatible. Model comparisons should be performed carefully 

across different dimensional design spaces. 

7.3. Model Results 

7.3.1. Producing Structure Count 

The number of shallow water committed structures that are expected to produce over a 60-year 

horizon is depicted in Figure G.1 according to their marginal and economic status. The 

trajectories represent the result of several hundred simulations, and so the paths denote the 

average trajectory computed from all of the simulations runs. New installations that will occur 

in the future and deepwater structures are not considered; hence, our structure count and 

production forecast is tied to the inventory of shallow water structures circa 2006. 

 

The total number of structures decline over time as production at individual assets decrease and 

transition from economic to marginal status, and eventually, to abandonment. As structures 

transition from economic to marginal status, and then to abandonment, the number of structures 

classified as economic and marginal will change. 

 
64

All structures transition from economic to marginal status, and are removed from service at 

their economic limit, regardless of the production status of the lease on which they reside. The 

number of economic structures decrease over time, since once a structure leaves the economic 

category, it will not return. Economic structures transition to a marginal classification, and 

operate as marginal producers until their revenue falls below their economic limit. The size of 

the marginal subcategory can therefore increase or decrease over time, depending upon the 

relative difference between the number of structures entering the class (from economic 

production) and structures departing the class (to abandonment). 

 

The economic and marginal structure categories are dynamic and change over time. In Figure 

G.1, we note that the absolute size of the marginal class is relatively constant over the first 20 

years of the forecast, but on a percent basis, as the number of economic structures decline, the 

inventory of marginal structures will represent an increasing share of the committed asset 

inventory (Figure G.2). 

 

7.3.2. Structure Count Envelopes 

The number of committed assets for a given (d, Po

, Pg, m, a) is denoted σ(d, Po, Pg, m, a), while 

the counting function for economic and marginal structures is denoted σe(d, Po, Pg, m, a) and 

σm(d, Po, Pg, m, a). Counting functions represent a simple enumeration of the number of 

economic and marginal structures over a 60-year horizon. 

In Figures G.3-G.5, the average number of economic, marginal, and total structures are 

depicted with a one standard deviation envelope. It is useful to think of the envelope as 

bounding the path trajectories that arise from selecting points (d, Po, Pg, m, a) in the design 

space. Each point (d, Po

, Pg, m, a) is associated with one path trajectory, and as we sample 

points within ∑, the trajectories will change. The average path is computed from the collection 

of all the sample paths in the simulation. Under Normality assumptions on the input variables, 

the path trajectories would be expected to be bound within the envelope about two-thirds of the 

time. 

 

In Figures G.3 and G.4, the structure counts are strictly decreasing functions, while the 

marginal structure count in Figure G.5 increases and plateaus for several years before 

declining. Because the number of economic structures initially dominates the total structure 

count, the behavior of the composite trajectory (Figure G.3) will mostly follow the economic 

count path (Figure G.4). The impact of the marginal trajectory plays a more important role later 

in the time horizon when the number of economic structures declines, but at this time, the shape 

of the two trajectories are similar. 

7.3.3. Aggregate Production Profiles 

The average annual BOE production from economic and marginal structures is shown in Figure 

G.6. The production profile parallels the general shape of the structure count and illustrates the 

relative contribution provided by economic and marginal assets for each year of the forecast. 

Marginal assets provide a mere fraction of the production from economic structures, although 
65

over time its relative contribution increases (Figure G.7). BOE production from marginal 

structures contributes less than 5 percent total production. 

7.3.4. Production Envelopes 

Average BOE production envelopes for economic and marginal structures are shown in Figures 

G.8-G.10. In Figure G.8, the average BOE production profile for all producing structures is 

bound by a two standard deviation interval. Near the beginning and end of the production 

forecast for the economic class, the envelope is tight, due in part to the relative insensitivity of 

the total production to parameter variation at these points in time (Figure G.9). As structures 

age and profiles become more diverse, the impact of changes in input variables becomes more 

pronounced. The production envelope of marginal structures maintains a wide interval at the 

start of the horizon, but shows a similar convergence near the end of production (Figure G.10). 

 

7.3.5. Production by Asset Category 

In Figure G.11, BOE production is decomposed according to the five structure subcategories. 

The cumulative production profiles in Figure G.12 depict the relative contribution of each asset 

class. Observe the large contribution played by young and normal producers. Young and 

normal assets contribute nearly two-thirds to cumulative production; with latecomer structures, 

the relative contribution exceeds 80 percent of the total production. 

7.3.6. Summary Statistics 

Composite statistics for oil, gas, and BOE production from all shallow water committed assets 

in the GOM in 2006 are summarized in Table G.3. Production quantity and value are 

decomposed in terms of economic, marginal, and the composite class. The expected amount of 

hydrocarbon production is estimated at 1,056.4 MMbbl oil and 13.3 Tcf gas, or 3,279 

MMBOE. The expected present value of hydrocarbon production is calculated as $149.4 

billion. Marginal production is expected to contribute 4.1 percent of the total oil production, 5.4 

percent total gas production, and 1.2 percent of the total present value over the productive life 

of the committed asset inventory. 

 

7.3.7. Cumulative Production Functions 

The cumulative economic, marginal, and total BOE production functions in the GOM are 

expressed in terms of the model input variables and given by (Table G.4): 

 Qe (d, Po

, Pg, m) = -5.3E9d + 1.5E7Po + 1.7E8Pg + 2.9E7m

 Qm (d, Po, Pg, m, a) = -1.8E8d + 4.2E5Po + 1.1E6Pg + 7.7E7m – 9.1E7a

 QT (d, Po, Pg, a)= -5.6E9d + 1.6E7Po + 1.7E8Pg + 8.3E7a 

The coefficients of the regression models are of the expected sign and statistically significant 

for most of the variables, and the model fits are relatively high. For any input parameters 

selected within the design space, the output for cumulative BOE production will vary in accord 
66

with the regression models shown. In Tables G.5 and G.6, regression results for the individual 

gas and oil production streams are depicted with somewhat better model fits. 

Cumulative production functionals are useful to estimate the total BOE production for any 

given input vector and to investigate parameter sensitivity. For example, for the collection of 

marginal assets and (d, Po

, Pg, m, α) = (0.10, 120, 10, 4, 1), cumulative production is computed 

as Qm (0.10, 120, 10, 4, 1) = -1.8E7 + 5.04E7 + 1.1E7 + 3.08E8 – 9.1E7 = 2.60E8 BOE = 260 

million BOE. Similarly, Qe (0.10, 120, 10, 4) = 3.09 billion BOE, and QT (0.10, 120, 10, 1) = 

3.14 billion BOE. Cumulative oil and gas production estimates are applied similarly using the 

results in Tables G.5 and G.6. 

7.3.8. Valuation Functions 

The present value of future oil and gas production is obtained by valuing the individual oil and 

gas production streams at assumed future prices, discount rates, and economic and marginal 

thresholds. The model results for total BOE, gas, and oil production for the economic, 

marginal, and combined asset classes are shown in Tables G.7-G.9 and summarized for the 

total hydrocarbon production stream (without a fixed term coefficient) as follows (in $1,000): 

PVe (d, Po, Pg, m, D) = -1.9E8d + 8.1E5Po + 9.6E6Pg – 2.6E5m – 3.2E8D

PVm (d, Po

, Pg, m, α, D) = 4.4E5d + 2.2E3Po + 7.9E4Pg + 1.3E6m – 1.8E6a – 1.0E7D

PVT (d, Po, Pg, α, D) = -1.9E8d + 8.1E5Po + 10.0E6Pg – 3.66E6a – 3.1E8D 

The use of a fixed-term coefficient is optional and we present model results with and without 

this term. The coefficients of the regression models are of the expected sign and statistically 

significant for most of the variables, and the model fits are again relatively high. 

 

The most important components of marginal production are the values of m, a, D; the decline 

parameter and hydrocarbon price are less significant. This is not surprising considering the 

nature of the producing assets. The decline parameter only contributes to the portion of total 

production due to latecomer structures. For economic assets, the abandonment threshold does 

not play a role in determining value, and thus a term for a is not included in the model. The 

present value of economic production at a 10 percent decline rate, $100/bbl oil, $10/Mcf gas, 

and a 15 percent discount rate is computed to be PVe (0.1, 100, 10, 4, 0.15) = $147 billion. The 

present value of marginal producing assets is computed to be PVm (0.1, 100, 10, 4, 1, 0.15) = 

$3.0 billion. 
67

REFERENCES 

Beck, R.D., J.P. Davis, R. Lynch, T. Philips, M. Taylor, G. Openshaw, M. Buhrke, W. 

Tomaszkiewicz, R. Simpson, and R. Butcher. 2008. Imaging downed platforms. OTC 

19650. Presented at the 2008 Offshore Technology Conference. Houston, TX, 5-8 May. 

Bondor, P.L., J.R. Hite, and S.M. Avasthi. 2005. Planning EOR projects in offshore oil fields. 

Presented at the SPE Latin America and Caribbean Petroleum Engineering Conference, 

Rio de Janeiro, Brazil, June 20 – 23, 2005. SPE #94637. 

Brashaer, J.P., F. Morra, M.R. Haas, and S. Payne. 1982. Enhanced oil recovery from offshore 

Gulf of Mexico reservoirs. Presented at the 1982 SPE/DOE Third Joint Symposium on 

Enhanced Oil Recovery, Tulsa, OK, April 4 – 7, 1982. SPE/DOE #10698. 

Energo. 2006. Assessment of fixed offshore platform performance in Hurricanes Andrew, Lili 

and Ivan. Report to MMS by Energo Engineering, Inc. TAR No 549. 

Energo. 2007. Assessment of fixed offshore platform performance in Hurricanes Katrina and 

Rita. Report to MMS by Energo Engineering, Inc. TAR No 578. 

Haag, J. 2005. The acquisition and divestiture of petroleum property. Penn Well, Tulsa, OK. 

Harrel, R. and C. Cronquist. 2007. “Estimation of primary reserves of crude oil, natural gas, 

and condensate.” Ch. 16, 1480-1570, in Reservoir Engineering and Petrophysics, Vol 

V(B), Ed. E. Holstein, SPE, Richardson, TX. 

Interstate Oil and Gas Compact Commission (IOGCC). 1999. Marginal oil and gas: Fuel for 

economic growth. Internet website: http://iogcc.publishpath.com/. 

Interstate Oil and Gas Compact Commission (IOGCC). 2005. Marginal oil and natural gas: 

American energy for the American dream. Internet website: 

http://iogcc.publishpath.com/. 

Kaiser, M.J. 2008a. “An empirical assessment of the economic limit of offshore structures in 

the Gulf of Mexico – Descriptive statistics.” Energy Sources, B: Economics, Planning, 

and Policy. 3(2): 314-322. 

Kaiser, M.J. 2008b. “Modeling regulatory policies associated with offshore structure removal 

requirements in the Gulf of Mexico.” Energy. 33: 1038-1054. 

Kaiser, M.J. and R. Kasprzak. 2008. The impact of the 2005 hurricane season on the Louisiana 

Artificial Reef Program. Marine Policy, 32: 956-967. 
68

Kaiser, M.J., A.G. Pulsipher, A. Singhal, T. Foster, and R. Vojjala. 2007a. “Catastrophic 

event modeling – I. How coverage has evolved for offshore storm risks.” Oil and Gas 

Journal. 105(48): 39-47, December 3. 

Kaiser, M.J., A.G. Pulsipher, A. Singhal, T. Foster, and R. Vojjala. 2007b. “Catastrophic 

event modeling – II. Industry exposure and value at risk.” Oil and Gas Journal.

105(49): 39-47, December 10. 

Laurendine, T.T. 2008. Gulf of Mexico offshore platforms-risk engineering. OTC 19576, 2008 

Offshore Technology Conference. Houston, TX, 5-8 May. 

Mailey, J.F. 2008. Technology and innovations contribute to safety and efficiency in storm 

disaster recovery. SPE 111563. Presented at the 2008 SPE International Conference on 

Health, Safety, and Environment. Nice, France, 15-17 April. 

McCutcheon, J.B. and M.L. Payne. 1986. Successful salvage and tie-back operations for a 

hurricane-damaged satellite well in the Gulf of Mexico. SPE 15450. Presented at the 

61th Annual Technical Conference and Exhibition. New Orleans, LA, 5-8 October. 

National Research Council (NRC). 1996. Maintaining oil production from marginal fields: A 

review of the department reservoir class program. National Academy Press, 

Washington, D.C. 

Puskar, F.J., S.M. Verret, and C. Roberts. 2007. Fixed platform performance during recent 

hurricanes: comparison to design standards. OTC 18989. Presented at the 2007 

Offshore Technology Conference. Houston, TX, April 30-May 3. 

Twachtman Snyder and Byrd, Inc. 2008. Twachtman Snyder and Byrd, Inc.: Total 

decommissioning solutions. Internet website: http://www.tsboffshore.com/. 

U.S. Department of Energy. 2006. Impact of the 2005 Hurricanes on the Natural Gas Industry 

in the Gulf of Mexico Region, Washington, D.C. 

 

U.S. Department of Energy. Energy Information Administration (USDOE, EIA). 2007. Oil 

and gas lease equipment and operating costs 1988 through 2006. Internet website: 

http://www.eia.doe.gov/oil_gas/natural_gas/data_publications/cost_indices/c_i.html. 

U.S. Department of Energy. National Energy Technology Laboratory (USDOE, NETL). 2001. 

An evaluation of marginal production in the Gulf of Mexico. National Petroleum 

Technology Office, National Energy Technology Laboratory, U.S. Department of 

Energy, DOE/BC-01/5/SP. 

U.S. Department of the Interior. Minerals Management Service (USDOI, MMS). 2004. MMS 

updates damage assessment from Hurricane Ivan. Release: #3164. October 8. Available 

at: www.mms.gov/ooc/press/2004/press1008a.htm. 
69

U.S. Department of the Interior. Minerals Management Service (USDOI, MMS). 2006. MMS 

updates Hurricanes Katrina and Rita damage. Release: #3486. May 1. Available at: 

www.mms.gov/ooc/press/2006/press0501.htm. 

U.S. Department of the Interior. Minerals Management Service (USDOI, MMS). 2007. 

Minerals Management Service. Gulf of Mexico Region. Production Information. 

Internet website: http://www.gomr.mms.gov/homepg/pd/index.html. 

U.S. Department of the Interior. Minerals Management Service (USDOI, MMS). 2008. 

Minerals Management Service. Gulf of Mexico Region. Production Information. 

Internet website: http://www.gomr.mms.gov/homepg/pd/index.html. 

U.S. Department of the Interior. Minerals Management Service (USDOI, MMS). 2009a. 

Lease Term Extensions Pursuant to 30 CFR 250.180(e) Due to Hurricane Damage. NTL 

No. 2008-G24. Internet website: http://www.ocsbbs.com/ntls/08-G24.pdf. 

 

U.S. Department of the Interior. Minerals Management Service (USDOI, MMS). 2009b. 

Minerals Management Service. Gulf of Mexico Region. Production Information. 

Internet website: http://www.gomr.mms.gov/homepg/pd/index.html. 

Versowski, P., G. Rodenbusch, P. O’Connor, and M. Prins. 2006. Hurricane impact reviewed 

through API. Offshore Technology Conference, OTC 18417. Houston, TX. 

Willis Group. 2006. Willis energy market review. Internet website: www.willis.com. 

Wisch, D.W., F.J. Puskar, T.T. Laurendine, P. O’Connor, P.E. Versowsky, and J. Bucknell. 

2004. An update on API RP 2A Section 17 for the assessment of existing platforms, 

OTC 19454. Presented at the 2004 Offshore Technology Conference. Houston, TX, 2-5 

May. 
71

APPENDIX A. 

CHAPTER 1 TABLES AND FIGURES
73

Table A.1.

 

Structure Damage Rate and Physical Damage Estimates 

Hurricane Year Structures in 

Storm Path

Structures Destroyed and 

with Major Damage

Damage Ratea

(%)

Physical Damage 

($ billion)

Andrew 1992 700 87 12% 0.9

Lili 2002 800 10 1% 0.4

Ivan 2004 150 31 21% 1.5

Katrina 2005 2,068 66 3% 6.4

Rita 2005 793 101 13% 3.7

Source: USDOI, MMS, 2006. 

Footnote: (a) Damage rate expressed as percent exposed, computed as the number of structures destroyed and with 

major damage divided by the number of structures in a 50-mile envelope centered on the storm path. 

 

Table A.2. 

Structure and Rig Damage Caused by Hurricanes Ivan, Katrina, and Rita 

Ivan Katrina Rita

Platforms destroyed 7 46 69

Platforms extensively damaged 24 20 32

Rigs adrift 5 6 13

Rigs destroyed 1 4 4

Rigs extensively damaged 4 9 10

Source: USDOI, MMS, 2006. 

Table A.3. 

 

Structures Destroyed by Hurricanes Ivan, Katrina, and Rita by Age Group 

Age Group (yrs) Number

< 10 24

11-20 9

21-30 17

31-40 49

> 40 23

Total 122

 Source: USDOI, MMS, 2006. 
74

Table A.4. 

 

Operators with Three or More Destroyed Structures in the 2004-2005 Hurricane Seasons 

Operator Structures Destroyed Total Wells Active Wells (2005)

Chevron 15 179 38

Apache 11 131 39

BP America 11 109 24

Forest Oil 11 53 11

Energy XXI 9 17 6

Stone Energy 7 37 11

Energy Resources Technology 5 29 10

Newfield Exploration Company 5 21 10

Anglo-Suisse Offshore Partners 4 72 13

Noble 4 101 18

Mariner Energy 3 4 1

Maritech 3 28 2

 Source: USDOI, MMS, 2006. 

Table A.5. 

Gas, Oil, and Water Production from Hurricane Destroyed Structures as a Percentage of 

Total Gulf of Mexico Production (2000-2005) 

Fluid Type 2000 2001 2002 2003 2004 2005

Gas 1.7 1.9 2.0 2.3 2.1 1.2

Oil 2.2 3.0 3.7 2.9 2.7 1.5

BOEa 1.7 2.3 2.7 2.6 2.4 1.3

Water 3.9 3.7 4.2 4.3 4.3 3.4

 Source: USDOI, MMS, 2006. 

 Footnote: (a) BOE = barrels of oil equivalent, computed on a heat equivalent basis, where 6,040 cf of gas 

provides 1 barrel of oil equivalent. The BOE stream is the combined oil and gas production 

output. 
75

Table A.6. 

Structure Count by Production Category (2000-2005) 

 Production (BOPD)b

Structure Typea Year <100 100-500 500-1,000 > 1,000 Total

Oil 2000 8 18 7 5 38

2001 8 18 6 7 39

2002 9 15 8 6 38

2003 6 17 7 5 35

2004 7 16 9 3 35

2005 13 15 1 3 32

 Production (MCFPD)

Structure Type Year <600 600-3,000 3,000-6,000 > 6,000 Total

Gas 2000 12 19 9 8 48

2001 13 14 9 11 47

2002 14 17 7 7 45

2003 15 18 7 7 47

2004 18 17 6 9 50

2005 14 21 9 2 46

 Production (BOEPD)

Structure Type Year <100 100-500 500-1,000 > 1,000 Total

ALL 2000 14 37 17 18 86

2001 26 18 14 28 86

2002 12 34 21 16 83

2003 14 28 23 17 82

2004 18 35 15 17 85

2005 21 35 16 6 78

 Source: USDOI, MMS, 2006. 

 Footnote: (a) Structures are classified as oil or gas producers according to their cumulative gas-oil ratio 

(GOR) measured in cf/bbl. Structures with GOR ≤ 5,000 are classified as primarily oil 

producers; structures with GOR > 5,000 are primarily gas producers.

 (b) BOPD = barrels of oil per day; MCFPD = thousand cubic feet per day; BOEPD = barrels of 

oil equivalent per day. 

 
76

 

 Figure A.1. Model Rendition of Hurricane Destroyed Structure Lying Horizontally 

 on the Seafloor. 

Source: Twachtman Synder and Byrd, Inc., 2008.
77

Figure A.2. Hurricane Destroyed Platform in the East Cameron Area. 

Source: USDOI, MMS, 2006. 
78

Figure A.3. Hurricane Destroyed Platform Suspected to Be Due to a Foundation Failure. 

Source: USDOI, MMS, 2006. 
79

Figure A.4. Structures Destroyed by Hurricane Ivan and Hurricane Force Wind Swath. 
80

 Figure A.5. Structures Destroyed by Hurricane Katrina and Hurricane Force Wind 

Swath. 
81

Figure A.6. Structures Destroyed by Hurricane Rita and Hurricane Force Wind Swath. 

 
82

 Figure A.7. Shut-In Oil Production in the Gulf of Mexico. 

Source: USDOI, MMS, 2006. 
83

 Figure A.8. Shut-In Gas Production in the Gulf of Mexico. 

Source: USDOI, MMS, 2006. 
85

APPENDIX B. 

CHAPTER 2 TABLES
87

Table B.1. 

Annual Operating Cost for Gulf of Mexico Structures (2006 dollars) 

Water Depth

(ft)

12-Slot Platform

($ million)

18-Slot Platform

 ($ million)

Average

 ($ million)

 100 9.34 11.18 10.26

300 9.62 11.52 10.57

600 12.15 12.15

Source: USDOE, EIA, 2007. 

Table B.2. 

Average Threshold Revenue for Gulf of Mexico Structures (2006 dollars) 

Water Depth 

(ft)

Primary 

Production 

Caisson

($1,000)

Well Protector 

($1,000)

Fixed Platform

($1,000)

< 100 Oil 162 152 451

Gas 525 446 491

101-200 Oil 345 398 715

Gas 589 692 588

> 200 Oil 520

Gas 935

Source: Kaiser, 2008a. 
88

Table B.3. 

Best Fit Curve Frequency and Average Model Parameters 

 Frequency Coefficients Curve Fit

Structure Type Model Type (%) a, C n R2 CV

Gas Exponential 62% 0.891 0.89 0.09

Harmonic 18% 7.1E-07 0.79 0.41

Hyperbolic 20% 0.049 3.6E5 0.90 0.11

Oil Exponential 40% 0.875 0.88 0.15

Harmonic 20% 1.7E-06 0.76 0.38

Hyperbolic 40% 0.068 798 0.89 0.13

Table B.4. 

Number of Structures According to Structure Type and Model Specification 

Structure Type Idle Uneconomic Normal Young Chaotic Total

Oil 7 10 17 4 6 44

Gas 15 11 22 15 3 66

All 22 21 39 19 9 110
89

APPENDIX C. 

CHAPTER 3 TABLES AND FIGURES

 
91

Table C.1.

Estimated Lost Production and Valuation (Normal Producers) – Best-Fit Curves with 

R2 ≥ 0.75, Hurricane Destroyed Structures with ≥ 7 Years Production 

 

Lost Production Present Valueb

Price Decka Oil (MMbbl) Gas (Bcf) BOE (MMbbl) $ Million 

I

a 19.4 31.8 24.7 231

II 21.1 37.9 27.5 393

III 22.2 41.7 29.1 561

IV 22.9 44.0 30.2 732

V 23.4 45.6 31.0 905

Footnote: (a) P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = $60/bbl, Pg = $6/Mcf}; P(III) = {Po = 

$80/bbl, Pg

 = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg = $10/Mcf}; and P(V) = {Po = 

$120/bbl, Pg

 = $12/Mcf} 

 (b) Discount rate = 10% 

 

Table C.2. 

Estimated Lost Production and Valuation (Young Producers) – Hurricane Destroyed 

Structures with < 7 Years Production, Exponential Decline Curves 

with Assumed Decline Rate 

 

Decline Rate a Lost Production Present Valueb

(%) Price Decka Oil (MMbbl) Gas (Bcf) BOE (MMbbl) $ Million 

a = 0.05 I 78.4 279.8 141.7 1,493

II 79.1 290.4 144.1 2,288

III 79.4 396.5 145.5 3,086

IV 79.6 400.0 146.3 3,885

V 79.8 402.5 146.9 4,684

a = 0.1 I 38.1 184.2 68.8 1,061

II 38.5 189.4 70.0 1,634

III 38.6 192.5 70.7 2,209

IV 38.7 194.1 71.1 2,796

V 38.8 195.4 71.4 3,363

a = 0.15 I 24.7 118.7 44.5 811

II 24.9 122.5 45.4 1,252

III 25.1 124.6 45.8 1,696

IV 25.1 125.6 46.1 2,141

V 25.2 126.5 46.3 2,587

Footnote: (a) P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = $60/bbl, Pg = $6/Mcf}; P(III) = {Po = 

$80/bbl, Pg

 = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg = $10/Mcf}; and P(V) = {Po = 

$120/bbl, Pg

 = $12/Mcf} 

 (b) Discount rate = 10% 
92

Table C.3. 

Estimated Lost Production and Valuation (Chaotic Producers) – Best-Fit Curves 

with Initial R2 < 0.75, Half Cycle Time Horizons and Exponential Decline 

with Historic Decline Rate 

 Cumulative Lost Production Present Valueb

Price Decka Oil (MMbbl) Gas (Bcf) BOE (MMbbl) $ Million 

I 2.4 21.6 6.0 50 

II 2.7 23.2 6.5 85 

III 2.8 24.1 6.8 121

IV 2.8 24.4 6.9 157

V 2.9 24.7 7.0 193

Footnote: (a) P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = $60/bbl, Pg = $6/Mcf}; P(III) = {Po = 

$80/bbl, Pg

 = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg = $10/Mcf}; and P(V) = {Po = 

$120/bbl, Pg = $12/Mcf} 

 (b) Discount rate = 10% 

Table C.4. 

Estimated Total Lost Production and Valuation – Normal, Young, and Chaotic Producers 

(Sum of Tables C.1, C.2, C.3) 

Lost Productionb Present Valuec

Price Decka Oil (MMbbl) Gas (Bcf) BOE (MMbbl) $ Million 

I 59.9 230.5 99.5 1,342

II 62.3 250.5 104 2,012

III 63.6 258.3 106.6 2,891

IV 64.4 262.5 108.2 3,684

V 65.1 265.7 109.4 4,460

Footnote: (a) P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = $60/bbl, Pg = $6/Mcf}; P(III) = {Po = 

$80/bbl, Pg

 = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg = $10/Mcf}; and P(V) = {Po = 

$120/bbl, Pg

 = $12/Mcf} 

 (b) For young producers, we assume the model output for a = 0.1 

 (c) Discount rate = 10% 
93

Table C.5. 

Maximum Aggregate Investment that Yields a Specific Rate of Return ($ million) 

Production Type Price Decka IRR =10% IRR = 15% IRR = 20% IRR = 25%

Normal I 231 185 155 133

II 393 313 261 225

III 561 446 372 320

IV 732 581 484 416

V 905 717 598 513

Chaotic I 50 98 84 74

II 85 158 136 119

III 121 218 188 164

IV 157 280 240 210

V 193 341 292 255

Young I 1,342 853 712 611

II 2,012 1,310 1,093 937

III 2,891 1,769 1,474 1,263

IV 3,684 2,228 1,856 1,590

V 4,460 2,688 2,238 1,917

Footnote: (a) P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = $60/bbl, Pg = $6/Mcf}; P(III) = {Po = 

$80/bbl, Pg

 = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg = $10/Mcf}; and P(V) = {Po = 

$120/bbl, Pg = $12/Mcf} 

Table C.6. 

Maximum Redevelopment Cost per Structure to Yield a Specific Rate of Return 

($ million/structure) 

 

Production Type Price Decka IRR = 10% IRR = 15% IRR = 20% IRR = 25%

Normal I 7.4 6.2 5.2 4.4

II 10.6 8.9 7.5 6.4

III 13.8 11.4 9.5 8.2

IV 17.5 14.5 12.1 10.4

V 21.3 17.9 14.9 12.8

Chaotic I 12.4 10.8 9.4 8.2

II 20.3 17.5 15.1 13.2

III 28.4 24.3 20.8 18.3

IV 36.5 31.1 26.6 23.3

V 44.7 37.9 32.4 28.3

Young I 60.0 50.2 41.9 36.0

II 92.6 77.1 64.3 55.1

III 112.5 93.1 77.6 66.5

IV 140.5 117.3 97.7 83.7

V 171.3 141.5 117.8 100.9

Footnote: (a) P(I) = {Po = $40/bbl, Pg = $4/Mcf}; P(II) = {Po = $60/bbl, Pg = $6/Mcf}; P(III) = {Po = 

$80/bbl, Pg

 = $8/Mcf}; P(IV) = {Po = $100/bbl, Pg = $10/Mcf}; and P(V) = {Po = 

$120/bbl, Pg

 = $12/Mcf} 
94

Figure C.1. Cumulative BOE Production as a Function of Threshold Level and Price 

Scenario. 

Figure C.2. Cumulative Oil Production as a Function of Threshold Level and Price 

Scenario. 
95

Figure C.3. Cumulative Gas Production as a Function of Threshold Level and Price 

Scenario. 

 Figure C.4. Present Value as a Function of Threshold Level Multiplier and Discount 

 Rate for Price Deck P(I).
96

Figure C.5. Present Value as a Function of Threshold Level Multiplier and Discount Rate 

 for Price Deck P(III). 

 
97

APPENDIX D. 

CHAPTER 4 TABLES AND FIGURES
99

Table D.1.

 

Number of Producing Structures Destroyed 

by Hurricanes Ivan, Katrina, and Rita 

Structure Type Oil Gas

Caisson 4 12

Well Protector 6 7

Fixed Platform 32 49

Mini Tension Leg Platform 1 0

Total 43 68

Source: USDOI, MMS, 2006. 

 
100

Table D.2.

Destroyed Structures that Restarted Production by August 2008

Complex Operator Area Block Hurricane Production 

Type 

Structure 

Type 

397 Chevron U.S.A. Inc. WC 172 Rita Gas CAIS 

798 Energy Partners, Ltd. EC 161 Rita Gas CAIS 

1207 Dominion Exploration & Production, Inc. MP 270 Katrina Gas FIXED 

1479 Taylor Energy Company SS 218 Rita Gas FIXED 

1525 East Cameron Partners, LP EC 71 Rita Gas CAIS 

1529 Chevron U.S.A. Inc. SS 181 Rita Gas CAIS 

20677 Merit Energy Company EC 254 Rita Gas FIXED 

22438 BP Exploration & Production Inc. WC 110 Rita Gas CAIS 

22929 Energy Partners, Ltd. EC 160 Rita Gas FIXED 

32008 Gulf of Mexico Oil & Gas Properties LLC SS 148 Rita Gas FIXED 

32033 Chevron U.S.A. Inc. SM 90 Rita Gas FIXED 

80022 Newfield Exploration Company SS 69 Rita Gas CAIS 

20040 BP America Production Company GI 47 Katrina Oil FIXED 

20042 BP America Production Company GI 40 Katrina Oil FIXED 

20223 Anglo-Suisse Offshore Partners, LLC WD 117 Katrina Oil FIXED 

20224 Anglo-Suisse Offshore Partners, LLC WD 117 Katrina Oil FIXED 

20225 Anglo-Suisse Offshore Partners, LLC WD 117 Katrina Oil FIXED 

20981 Marlin Energy Offshore, LLC ST 21 Katrina Oil WP 

21599 Forest Oil Corporation SM 11 Rita Oil WP 

21802 Anglo-Suisse Offshore Partners, LLC WD 117 Katrina Oil FIXED 

23831 Newfield Exploration Company MP 138 Katrina Oil FIXED 

 Source: USDOI, MMS, 2009b. 
101

Table D.3. 

 

Pre- and Post-Hurricane Daily Average Production Statistics for Destroyed Structures 

that Restarted Production by August 2008 

Pre-Hurricane Daily Productiona Post-Hurricane Daily Productionb 

Complex Oil 

(BPD) 

Gas 

(MCFPD) 

BOE 

(BOEPD) 

Oil 

(BPD) 

Gas 

(MCFPD) 

BOE 

(BOEPD) 

Post/Pre BOE

 Production 

Ratio 

397 3.2 2,196.8 369.4 3.0 1,946.0 327.3 0.89 

798 4.9 2,922.6 492.0 - 4,036.8 672.8 1.37 

1207 62.4 2,364.1 456.5 445.6 17,357.8 3,338.6 7.31 

1479c - - - 143.7 13,185.0 2,341.2 N/A 

1525d 34.4 4,689.3 816.0 13.1 2,202.5 380.2 0.47 

1529d 249.4 4,526.3 1,003.8 578.8 13,612.7 2,847.5 2.84 

20677 7.8 3,421.8 578.1 3.7 275.9 49.7 0.09 

22438 2.3 3,360.5 562.4 252.2 40.1 258.9 0.46 

22929 8.0 981.1 171.5 - 72.1 12.0 0.07 

32008 7.0 1,736.9 296.5 2.3 739.8 125.6 0.42 

32033 437.0 1,763.2 730.9 434.5 3,389.5 999.4 1.37 

80022 53.7 149.7 78.7 43.6 143.7 67.6 0.86 

20040 964.3 2,628.2 1,402.3 0.2 - 0.2 0.00 

20042 45.0 156.4 71.1 3.1 - 3.1 0.04 

20223 432.9 615.9 535.5 143.3 - 143.3 0.27 

20224 104.8 212.4 140.2 6.2 - 6.2 0.04 

20225 103.1 1,153.3 295.3 20.1 - 20.1 0.07 

20981 131.4 99.4 148.0 127.5 175.6 156.8 1.06 

21599e - - - 0.0 19.8 3.3 N/A 

21802 177.9 209.2 212.8 22.6 - 22.6 0.11 

23831 55.6 261.9 99.2 1.2 - 1.2 0.01 

Totalf 2,885.3 33,449.1 8,460.2 2,101.0 43,992.6 9,433.1 1.10 

 Source: USDOI, MMS, 2009b. 

a. Computed 1-year prior to each hurricane event and normalized on a daily basis. 

b. Computed over the duration of post-hurricane production for producing months through August 

2008. 

c. Structure 1479 began operations in August 2005 but did not produce before being destroyed. 

d. Structures 1525 and 1529 started producing 8 and 9 months before Hurricane Rita. Pre-hurricane 

daily production is averaged during this period. 

e. Structure 21599 last produced in 2001 and was idle at the time Rita destroyed it. Production 

restarted in June 2006, and in August 2008, one of 6 wells were producing. 

 f. Post-hurricane production from 1479 and 21599 is not included in the aggregate production total. 
102

Table D.4. 

Pre- and Post-Hurricane Daily and Annual Revenue Statistics for Destroyed Structures 

that Restarted Production by August 2008 

 Pre-Hurricanea Post-Hurricaneb 

Complex Production 

Type 

Daily 

Revenue 

($) 

Annual 

Revenue 

($1,000) 

Daily 

Revenue 

($) 

Annual 

Revenue 

($1,000) 

Post/Pre Daily 

Revenue Ratio 

397 Gas 14,568 5,317 14,312 5,224 0.98 

798 Gas 18,951 6,917 33,517 12,234 1.77 

1207 Gas 17,835 6,510 155,815 56,872 8.74 

1479c Gas - - 106,693 38,943 N/A 

1525d Gas 22,771 8,311 16,330 5,961 0.72 

1529d Gas 33,598 12,263 145,791 53,214 4.34 

20677 Gas 22,300 8,140 2,090 763 0.09 

22438 Gas 22,413 8,181 26,641 9,724 1.19 

22929 Gas 6,947 2,536 707 258 0.10 

32008 Gas 12,059 4,401 6,029 2,201 0.50 

32033 Gas 36,251 13,232 59,573 21,744 1.64 

80022 Gas 3,995 1,458 4,588 1,675 1.15 

20040 Oil 71,478 26,089 11 4 0.00 

20042 Oil 3,505 1,279 298 109 0.08 

20223 Oil 29,187 10,653 9,706 3,543 0.33 

20224 Oil 7,275 2,655 421 154 0.06 

20225 Oil 13,460 4,913 1,361 497 0.10 

20981 Oil 7,901 2,884 12,216 4,459 1.55 

21599e Oil - - 142 52 N/A 

21802 Oil 11,417 4,167 1,528 558 0.13 

23831 Oil 4,553 1,662 79 29 0.02 

Totalf 360,462 131,569 491,015 179,221 1.36 

a. Computed 1-year prior to each hurricane event based on monthly average oil and gas prices 

adjusted using CPI. 

b. Computed over the duration of post-hurricane production for producing months through 

August 2008 and based on monthly average oil and gas prices adjusted using CPI. 

c. Structure 1479 began operations in August 2005 but did not produce before being destroyed. 

d. Structures 1525 and 1529 started producing 8 and 9 months before Hurricane Rita. Prehurricane daily production is averaged during this period. 

e. Structure 21599 last produced in 2001 and was idle at the time Rita destroyed it. Production 

restarted in June 2006, and in August 2008, one of 6 wells were producing. 

f. Post-hurricane production from 1479 and 21599 is not included in the aggregate production 

total. 
103

Table D.5.

Post/pre-Hurricane Production and Revenue Ratio Distribution 

for Destroyed Structures that Restarted Production 

Production Revenue Ratio 

Gas Oil All Gas Oil All

0-0.5 5 7 13 3 7 11

0.5-1.0 2 0 2 2 0 2

1.0-1.5 2 1 3 2 0 2

1.5-2.0 0 0 0 2 1 3

2-4 1 0 1 0 0 0

4-6 0 0 0 1 0 1

6-8 1 0 1 0 0 0

8-10 0 0 0 1 0 1

All 11 8 20 11 8 20

Average (SD)a 1.63(2.09) 0.21(0.33) 0.79(1.66) 2.20(2.54) 0.20(0.49) 1.00(2.05)

a. SD = Standard deviation 
104

Table D.6. 

Post/Pre-Hurricane Revenue Ratios for Destroyed Structures that Restarted Productio

Gas Structures Oil Structures All 

Pre-Hurricane 

Production 

(BOEPD) 

Pre-Hurricane 

Aggregate 

Daily Revenue 

(US Dollar) 

Post-Hurricane

Aggregate 

Daily Revenue

(US Dollar) 

Ratio 

Pre-Hurricane 

Aggregate 

Daily Revenue

(US Dollar) 

Post-Hurricane 

Aggregate 

 Daily Revenue 

(US Dollar) 

Ratio 

Pre-Hurricane

Aggregate 

Daily Revenue

(US Dollar) 

<100 3,995 4,588 1.15 8,058 377 0.05 12,053 

100 - 250 6,947 707 0.10 26,593 14,165 0.53 33,540 250 - 500 63,413 209,673 3.31 13,460 1,361 0.10 76,873 

500 – 1,000 103,735 104,634 1.01 29,187 9,706 0.33 132,922 

1,000 - 2,500 33,598 145,791 4.34 71,478 11 0.00 105,076 2,500 - 5,000 0 0 - 0 0 - 0 

5,000 - 10,000 0 0 - 0 0 - 0 

>10,000 0 0 - 0 0 - 0 

All 211,688 465,393 2.20 148,776 25,620 0.17 360,464 
105

Table D.7.

Hurricane Destroyed Structures Redevelopment Rate by Pre-Hurricane Production Rates

Gas Structures 

Pre-Hurricane 

Production 

(MCFEPD) 

Restarted Not Restarted Restart Ratea

 (%) 

<600 1 28 3 

600 – 1,500 1 8 11 

1,500 – 3,000 4 6 40 

3,000 – 6,000 4 9 31 

6,000 - 15,000 1 4 20 

15,000 - 30,000 0 1 0 

30,000 - 60,000 0 0 - 

>60,000 0 0 - 

All 11 56 16 

Oil Structures 

Pre-Hurricane 

Production 

(BOEPD) 

Restarted Not Restarted Restart Ratea

 (%) 

<100 2 12 14 

100 - 250 3 7 30 

250 - 500 1 6 14 

500 – 1,000 1 6 14 

1,000 - 2,500 0 2 0 

2,500 - 5,000 1 0 100 

5,000 - 10,000 0 0 - 

>10,000 0 1b 0 

All 8 34 19 

All Structures 

Pre-Hurricane 

Production 

(BOEPD) 

Restarted Not Restarted Restart Ratea

 (%) 

<100 3 40 7 

100 - 250 4 15 21 

250 - 500 5 12 29 

500 – 1,000 5 15 25 

1,000 - 2,500 1 6 14 

2,500 - 5,000 1 1 50 

5,000 - 10,000 0 0 - 

>10,000 0 1b 0 

All 19 90 17 

a. Restart rates are based on production statistics through August 2008. 

b. The Typhoon field announced a plan to restart production in 2009-2010. 
106

Table D.8.

Hurricane Destroyed Structures Restart Rate by the Number 

of Pre-Hurricane Producing Wells 

Gas Structures 

Pre-Hurricane 

Producing Wells Restarted Not Restarted Restart Ratea

 (%) 

0 0 23 0 

1 3 13 19 

2 4 8 33 

3-4 4 9 31 

>4 0 3 0 

All 11 56 16 

Oil Structures 

Pre-Hurricane 

Producing Wells Restarted Not Restarted Restart Ratea

 (%) 

0 0 10 0 

1 2 6 25 

2 2 7 22 

3-4 1 2 33 

>4 3 9 25 

All 8 34 19 

All Structures 

Pre-Hurricane 

Producing Wells Restarted Not Restarted Restart Ratea

 (%) 

0 0 33 0 

1 5 19 21 

2 6 15 29 

3-4 5 11 31 

>4 3 12 20 

All 19 90 17 

a. Restart rates are based on production statistics through August 

2008. 
107

Table D.9. 

Hurricane Destroyed Structures Restart Rate by Expected Remaining Reserves 

Gas Structures 

Remaining Reservesa

(MBOE) Restarted Not Restarted Restart Rateb

 (%) 

<100 4 27 13 

100-250 2 5 29 

250-500 1 7 13 

500-1,000 2 9 18 

1,000-2,500 2 4 33 

2,500-5,000 0 3 0 

5,000-20,000 0 1 0 

All 11 56 16 

Oil Structures 

Remaining Reservesa

(MBOE) Restarted Not Restarted Restart Rateb (%) 

<100 6 17 26 

100-250 0 6 0 

250-500 1 2 33 

500-1,000 0 4 0 

1,000-2,500 0 2 0 

2,500-5,000 1 1 50 

5,000-20,000 0 2 0 

All 8 34 19 

All Structures 

Remaining Reservesa

(MBOE) Restarted Not Restarted Restart Rateb

 (%)

<100 10 44 19 

100-250 2 11 15 

250-500 2 9 18 

500-1,000 2 13 13 

1,000-2,500 2 6 25 

2,500-5,000 1 4 20 

5,000-20,000 0 3 0 

All 19 90 17 

a. Remaining reserves are estimated on a structure basis as depicted 

in Table D.13 (restarted) and Table D.18 (not restarted). 

b. Restart rates are based on production statistics through August 

2008. 
108

Table D.10. 

Exploration and Development Plans on Leases that Restarted 

Production as of February 2009 

Block Complex Number of Plans 

8/05-2/09 Plan Date Plan Typea

 Description 

WC 712 397 0 

EC 161 798 0 

MP 270 1207 0 

SS 218 1525 0 

EC 71 1529 1 3/14/07 DOCD 

SS 181 20677 0 

EC 254 22438 1 8/13/07 DOCD 

WC 110 22929 2 9/11/06 DOCD 

5/11/07 DOCD 

EC 160 32008 0 

SS 148 32033 0 

SM 90 80022 0 

SS 69 20040 0 

8/21/06 EP Drill six wells (five wells on GI 47, 

One on GI 40) and install well 

protector 

GI 47 20042 2 

10/24/06 DOCD 

GI 40b 20223 2 

WD 117 20224 1 12/16/05 DOCD Drill six wells and install a 4-pile 

platform 

WD 118 20225 0 

WD 119 20981 0 

1/23/06 EP 

2/7/06 DOCD 

2/16/06 DOCD 

3/2/06 DOCD 

3/22/06 DOCD 

7/27/06 DOCD Drill one well and install caisson 

12/19/06 DOCD 

ST 21 21599 8 

10/23/06 DOCD 

SM 11 21802 1 7/14/08 DOCD 

MP 138 23831 1 6/15/06 DOCD Drill four wells and install fixed 

platform to replace two destroyed 

 platforms 

Source: USDOI, MMS, 2009b. 

a. EP = Exploration Plan, DOCD = Development Operations Coordination Document. 

b. Development plans for GI 47 and GI 40 are combined. 
109

Table D.11.

Post-Hurricane Cumulative Production, Drilling Activity Levels, 

and Percentage of Reserves Remaining as of August 2008 

Complexa

Daily 

Revenue 

($) 

Post-Hurricane 

Cumulative 

Production 

(BOE) 

Post-Hurricane 

Cumulative 

Production 

(MMCFE) 

Percentage 

of 

Remaining 

Reservesb

($60/bbl) 

Percentage 

of 

Remaining 

Reservesb

($140/bbl) 

PostHurricane 

Development 

Wells 

PostHurricane

Sidetrackc

 

Wells 

397* 14,312 284,739.8 1,708.4 24% 23% 0 0 

798* 33,517 161,473.8 968.8 66% 64% 0 0 

1207 155,815 2,904,544.3 17,427.3 307% 298% 1 0 

1525† 16,330 273,718.5 1,642.3 450% 306% 0 0 

1529* 145,791 2,904,487.2 17,426.9 6514% 5610% 2 0 

20677 2,090 11,930.0 71.6 8% 7% 0 0 

22438 26,641 23,301.8 139.8 2% 2% 0 0 

22929 707 360.5 2.2 2% 1% 0 0 

32008* 6,029 128,134.8 768.8 22% 20% 0 0 

32033* 59,573 809,550.0 4,857.3 470% 427% 4 3 

80022† 4,588 70,969.5 425.8 542% 130% 0 0 

20040 11 32.0 0% 0% 0 0 

20042 298 93.0 0% 0% 0 0 

20223 9,706 8,599.0 N/A 81% 3 2 

20224 421 373.0 1% 0% 0 0 

20225 1,361 1,206.0 2% 1% 0 0 

20981‡ 12,216 122,291.7 N/Ad N/Ad 0 0 

21599 142 1,981 N/Ad N/Ad 0 0 

21802 1,528 1,354.0 4% 2% 0 0 

23831 79 111.0 0% 0% 0 0 

Total 491,157 7,709,251 45,439 43% 42% 10 5 

a. Asterisk (*) denotes structure was producing August 2008. Cross (†) denotes structure producing 

in December 2008. Double cross (‡) denotes structure has been decommissioned. 

b. Post-hurricane cumulative production divided by estimated remaining reserves computed in 

Table D.13. 

c. A sidetrack well is a well planned and drilled from the bore of a previous well in order to achieve 

a geologic objective. Sidetracks do not represent a new well. 

d. Structures 20981 and 21599 were evaluated as uneconomic and by default will have no 

remaining reserves (zero denominator term). 
110

Table D.12.

Time Offline, Duration of Production, and Last Producing Month 

for Structures that Restarted Production 

Complex Hurricane Production 

Type 

Time offline

(mo) 

Duration of 

Production 

(mo) 

Last 

Producing 

Month 

DOCD Plan 

on Lease 

Last Plan 

Date 

397 Rita Gas 6 29 2008 Aug. No 

798 Rita Gas 27 8 2008 Aug. No 

1207 Katrina Gas 4 29 2008 June No 

1479 Rita Gas 8 27 2008 Aug. No 

1525 Rita Gas 11 24 2008 Aug. Yes 3/14/07 

1529 Rita Gas 1 34 2008 Aug. No 

20677 Rita Gas 7 8 2006 Dec. Yes 8/13/07 

22438 Rita Gas 28 3 2008 Apr. Yes 5/11/07 

22929 Rita Gas 31 1 2008 May No 

32008 Rita Gas 1 34 2008 Aug. No 

32033 Rita Gas 8 27 2008 Aug. No 

80022 Rita Gas 0 35 2008 Aug. No 

20040 Katrina Oil 9 7 2007 Jan. No 

20042 Katrina Oil 27 1 2008 Jan. Yes 10/24/06 

20223 Katrina Oil 4 2 2006 Mar. Yes 10/24/06 

20224 Katrina Oil 4 2 2006 Mar. Yes 12/16/05 

20225 Katrina Oil 4 2 2006 Mar. No 

20981 Katrina Oil 9 26 2008 Aug. No 

21599 Rita Oil 11 20 2008 Apr. Yes 10/23/06 

21802 Katrina Oil 4 2 2006 Mar. Yes 7/14/08 

23831 Katrina Oil 17 3 2007 May Yes 6/15/06 

Source: USDOI, MMS, 2008. 
111

Table D.13.

Estimated Remaining Reserves and Discounted Gross Revenue for 

Redeveloped Structuresa

 – I. One Year Time Shift 

Discounted Revenue at 10%c

Complex ($1,000) Remaining Reservesb

(MBOE) $60/bbl $80/bbl $100/bbl $120/bbl $140/bbl 

397 1,191 – 1,233 29,951 40,339 50,424 60,627 70,731

798 245 - 254 6,686 8,915 11,430 13,716 16,002

1207 945 - 975 26,159 34,879 43,979 53,116 61,968

1525 61 - 89 1,996 3,667 4,584 5,501 6,418

1529 45 - 52 1,645 2,193 2,741 3,740 4,363

20040 2,843 – 2,887 77,361 103,177 129,005 154,823 180,634

20042 39 - 83 1,694 2,876 4,310 5,364 6,592

20223 0 - 11 0 723 904 1,085 1,265

20224 36 - 75 1,649 3,006 4,389 5,531 6,697

20225 80 - 92 3,504 5,039 6,299 7,559 9,153

20677 144 - 165 4,450 6,322 7,903 9,844 11,484

20981d 0 - 0 0 0 0 0 0

21599d 0 - 0 0 0 0 0 0

21802 33 - 87 1,579 3,366 5,152 6,565 8,005

22438 1,201 – 1,290 23,487 31,508 39,482 47,457 55,429

22929 21 - 39 711 1,430 1,788 2,145 2,933

23831 227 - 305 8,174 11,697 15,027 18,362 21,682

32008 579 - 643 13,517 18,202 22,959 27,652 32,304

32033 172 - 190 5,848 7,798 10,151 12,489 14,570

80022 13 - 55 515 1,204 2,763 3,316 4,167

Subtotale 5,569 - 6,009 148,768 204,023 258,238 311,851 365,842

Subtotalf 2,306 – 2,516 60,158 82,318 105,052 127,041 148,555

Total 7,875 – 8,525 208,926 286,341 363,290 438,892 514,397

a. Structure 1479 is excluded from analysis. 

b. Remaining reserves are presented as a range corresponding to oil prices from $60/bbl - $140/bbl. 

c. Computed based on the assumption that first revenue occurred one year after destruction. 

d. Structure was evaluated as uneconomic. 

e. Computed based on structures not producing as of August 2008. 

f. Computed based on structures producing as of August 2008. 

 
112

Table D.14.

Estimated Remaining Reserves and Discounted Revenue for 

Redeveloped Structuresa

 – II. Two Year Time Shift 

Discounted Revenue at 10%c

Complex ($1,000) Remaining Reservesb

(MBOE) $60/bbl $80/bbl $100/bbl $120/bbl $140/bbl 

397 1,191 - 1,233 27,229 36,672 45,840 55,115 64,301

798 245 - 254 6,078 8,104 10,391 12,469 14,547

1207 945 - 975 23,781 31,708 39,981 48,287 56,335

1525 61 - 89 1,815 3,334 4,167 5,001 5,834

1529 45 - 52 1,495 1,993 2,492 3,400 3,967

20040 2,843 - 2,887 70,328 93,797 117,278 140,748 164,213

20042 39 - 83 1,540 2,614 3,918 4,876 5,993

20223 0 - 11 0 657 822 986 1,150

20224 36 - 75 1,499 2,733 3,990 5,028 6,089

20225 80 - 92 3,185 4,581 5,726 6,871 8,321

20677 144 - 165 4,046 5,747 7,184 8,949 10,440

20981d 0 - 0 0 0 0 0 0

21599d 0 - 0 0 0 0 0 0

21802 33 - 87 1,435 3,060 4,684 5,968 7,277

22438 1,201 - 1,290 21,352 28,643 35,892 43,143 50,390

22929 21 - 39 646 1,300 1,625 1,950 2,666

23831 227 - 305 7,431 10,634 13,661 16,692 19,711

32008 579 - 643 12,288 16,547 20,872 25,138 29,367

32033 172 - 190 5,317 7,089 9,229 11,353 13,246

80022 13 - 55 468 1,095 2,512 3,015 3,788

Subtotale 5,569 – 6,009 135,243 185,474 234,761 283,498 332,585

Subtotalf 2,306 – 2,516 54,690 74,834 95,503 115,491 135,050

Total 7,875 – 8,525 189,933 260,308 330,264 398,989 467,635

a. Structure 1479 is excluded from analysis. 

b. Remaining reserves are presented as a range corresponding to oil prices from $60/bbl - $140/bbl. 

c. Computed based on the assumption that first revenue occurred two years after destruction. 

d. Structure was evaluated as uneconomic. 

e. Computed for structures not producing as of August 2008. 

f. Computed for structures producing as of August 2008. 
113

Table D.15. 

Producing Wells, Drilled Wells, and Plugged and Abandoned (P&A) 

Wells for Redeveloped Structures 

Number of Producing Wells 

Complex Production 

Type Pre-Hurricane Post-Hurricane 

Cumulative 

Number of 

Drilled Wells 

Cumulative 

Number of 

P&A Wells 

397 Gas 2 2 3 0 

798 Gas 3 0a 4 1 

1207 Gas 3 3 4 0 

1479 Gas 0 3 4 1 

1525 Gas 1 1 3 2 

1529 Gas 3 3 3 0 

20677 Gas 3 1 17 13 

22438 Gas 1 0 1 0 

22929 Gas 2 0 3 0 

32008 Gas 2 1 2 0 

32033 Gas 2 2 8 0 

80022 Gas 1 1 1 0 

20040 Oil 8 1 24 3 

20042 Oil 1 0 16 3 

20223 Oil 6 6 21 6 

20224 Oil 2 2 14 4 

20225 Oil 3 2 23 8 

20981 Oil 1 1 2 0 

21599 Oil 0 1 6 0 

21802 Oil 2 2 32 10 

23831 Oil 5 1 12 0 

Total 54 33 203 51 

Source: USDOI, MMS, 2008. 

a. Producing structures with no post-hurricane producing wells may be due to clerical error, late 

reporting, or a failure to update records. An incorrect well assignment may also lead to erroneous 

results. 
114

Table D.16.

Structures with ≥ 250 BOEPD Pre-Hurricane Production Not Redeveloped, August 2008 

Pre-Hurricane Daily Production

Complex Production 

Type Area Block Hurricane Structure Type Plan Filed Oil 

(BPD) 

Gas 

(MCFPD) 

BOE 

(BOEPD) 

Pre-Hurricane 

Daily Revenue

(US Dollar) 

20901 Gas SM11 Rita WP Yes 197 333 252 13,258 

21602 Gas SM49 Rita FIXED No 8 1,496 257 10,291 

23257 Gas MP98 Ivan FIXED No 1 1,842 307 10,672 

20606 Gas ST135 Katrina FIXED No 41 1,770 336 13,627 

20123 Gas WC176 Rita WP Yes 198 1,424 435 20,498 

669 Gas WD137 Katrina FIXED No 44 2,470 456 18,662 

20958 Gas ST161 Rita FIXED No 2 3,028 506 19,922 

20940 Gas EC272 Rita FIXED Yes 151 2,352 543 23,936 

20025 Gas WD70 Katrina FIXED No 437 838 577 29,797 

20527 Gas VR255 Rita FIXED No 337 1,711 622 30,886 

21573 Gas EI276 Rita FIXED Yes 554 888 702 37,221 

20524 Gas VR217 Rita FIXED Yes 48 4,125 735 31,687 

20708 Gas SM108 Rita FIXED Yes 2 4,998 835 34,053 

20959 Gas ST161 Katrina FIXED No 6 5,217 876 34,918 

20031 Gas GI32 Katrina FIXED Yes 746 1,090 928 48,674 

21581 Gas EI333 Rita FIXED No 46 6,165 1,073 43,359 

20655 Gas SM76 Rita FIXED Yes 14 8,205 1,381 54,500 

96 Gas MP312 Katrina FIXED Yes 838 6,584 1,935 90,419 

21994 Gas ST51 Rita FIXED Yes 443 12,055 2,452 109,041 

80011 Gas SS193 Rita FIXED Yes 211 19,068 3,389 135,460 

20618 Oil ST151 Katrina FIXED No 209 334 264 13,941 

20045 Oil GI40 Katrina FIXED No 314 197 346 18,904 

20228 Oil WD103 Katrina FIXED No 338 307 389 20,999 

20450 Oil MP293 Ivan FIXED No 384 237 423 16,957 

21571 Oil EI276 Rita FIXED Yes 366 367 427 22,951 

20982 Oil ST21 Katrina WP No 439 232 478 26,043 

20229 Oil WD103 Katrina FIXED No 489 511 575 30,747 

20446 Oil MP305 Ivan FIXED No 488 1,057 664 27,563 

21582 Oil EI338 Rita FIXED Yes 582 1,133 770 39,615 

20449 Oil MP306 Ivan FIXED No 740 674 852 35,512 

21763 Oil EC322 Rita FIXED No 701 1,068 879 46,378 

20612 Oil ST151 Katrina FIXED No 791 1,194 990 52,723 

20615 Oil ST151 Katrina FIXED No 1,835 2,192 2,200 117,085 

735 Oil GC237 Rita MTLP Yes 21,492 34,763 27,285 1,413,483 

Subtotal 11,999 95,161 27,859 1,280,299 

Total 13,479 104,724 30,933 1,427,205 
115

Table D.17.

Pre-Hurricane Daily Revenue Distribution and Redevelopment Rates for Structures 

that Have Not Restarted Production as of August 2008 

Structures DOCD Plans Submitted Redevelopment Rates Pre-Hurricane a

Daily Revenue 

($1,000/d) Gas Oil All Gas Oil All Gas (%) Oil (%) All (%) 

<10 35 16 51 0 0 0 0 0 0 

10-25 9 8 17 3 1 4 33 13 24 

25-50 8 6 14 4 1 5 50 17 36 

50-100 2 1 3 2 0 2 100 0 67 

100-200 2 1 3 2 0 2 100 0 67 

>200 0 1 1 0 1 1 N/A 100 100 

All 56 33 89 11 3 14 20 9 16 

 a. Computed as the ratio of DOCD plans submitted to the total number of structures in 

 each category. 
116

Table D.18.

Estimated Remaining Reserves and Discounted Revenue for Top 25 Structures that 

Have Not Been Redeveloped as of February 2009 – I. One Year Time Shift 

Discounted Revenue at 10%a

Complex ($1,000) Remaining Reserves 

(MBOE) 

$60/bbl $80/bbl $100/bbl $120/bbl $140/bbl 

735 17,073 - 17,073 570,013 760,017 950,021 1,140,026 1,330,030

21994 4,908 - 4,952 122,202 163,064 203,882 244,704 285,529

20615 4,313 - 4,393 117,153 156,279 195,386 234,494 273,600

80011 5,162 - 5,232 112,023 149,404 186,782 224,146 261,516

20606 2,897 - 2,965 68,955 92,019 115,064 138,109 161,141

20524 3,166 - 3,248 61,351 81,887 102,402 122,918 143,419

669 1,684 - 1,708 44,886 59,848 74,810 90,093 105,384

20655 2,212 - 2,299 42,293 56,520 70,715 84,911 99,086

20450 1,624 - 1,691 40,812 54,477 68,127 81,769 95,410

96 1,256 - 1,293 35,050 47,249 59,061 70,874 82,686

20045 1,389 - 1,458 31,524 42,085 52,634 63,181 73,722

20982 943 - 958 26,104 34,819 43,531 52,243 60,953

20447 817 - 873 24,526 32,856 41,180 49,471 57,740

20123 926 - 980 23,983 32,109 40,203 48,298 56,390

21763 601 - 620 23,213 31,131 39,071 46,886 54,853

20723 918 - 996 22,787 30,617 38,391 46,166 53,937

20026 496 - 579 15,089 20,570 25,946 31,328 36,704

20025 513 - 578 14,303 19,399 24,417 29,437 34,403

20612 290 - 305 12,893 17,191 21,920 26,303 31,051

23257 387 - 432 9,723 13,337 16,824 20,327 23,838

21573 244 - 263 9,253 12,728 15,910 19,438 22,678

20449 250 - 295 9,073 12,574 15,948 19,238 22,538

20527 245 - 261 8,993 11,991 15,353 18,699 21,815

12 274 - 297 7,405 9,873 12,737 15,285 18,142

20708 229 - 275 6,361 9,151 11,692 14,030 16,625

Subtotalb 2,179 - 2,504 62,561 86,261 110,545 134,258 157,745

Subtotalc 35,321 - 35,799 988,853 1,321,080 1,652,393 1,984,366 2,315,901

Totald 54,080 - 56,025 1,506,105 2,023,937 2,541,878 3,058,498 3,574,357

a. Computed based on the assumption that first revenue occurred one year after initial redevelopment 

 investment. 

b. Computed based on structures that have been decommissioned by February 2009. 

c. Computed based on structures/leases that filed an EP or DOCD by February 2009. 

d. For all 61 structures that have not restarted production. 
117

Table D.19.

Estimated Remaining Reserves and Discounted Revenue for Top 25 Structures that 

Have Not Been Redeveloped as of February 2009 – II. Two Year Time Shift 

Discounted Revenue at 10%a

Complex ($1,000) Remaining Reserves 

(MBOE) 

$60/bbl $80/bbl $100/bbl $120/bbl $140/bbl 

         

735 17,073 - 17,073 518,193 690,925 863,656 1,036,387 1,209,118

21994 4,908 - 4,952 111,093 148,240 185,347 222,458 259,571

20615 4,313 - 4,393 106,503 142,071 177,624 213,176 248,728

80011 5,162 - 5,232 101,839 135,821 169,802 203,769 237,742

20606 2,897 - 2,965 62,686 83,653 104,603 125,553 146,492

20524 3,166 - 3,248 55,774 74,443 93,093 111,743 130,381

669 1,684 - 1,708 40,806 54,408 68,010 81,903 95,804

20655 2,212 - 2,299 38,448 51,382 64,286 77,192 90,078

20450 1,624 - 1,691 37,102 49,525 61,934 74,335 86,737

96 1,256 - 1,293 31,864 42,954 53,692 64,431 75,169

20045 1,389 - 1,458 28,659 38,260 47,849 57,438 67,020

20982 943 - 958 23,731 31,654 39,574 47,494 55,412

20447 817 - 873 22,296 29,869 37,437 44,974 52,491

20123 926 - 980 21,802 29,190 36,548 43,907 51,264

21763 601 - 620 21,103 28,301 35,519 42,623 49,867

20723 918 - 996 20,716 27,834 34,901 41,969 49,034

20026 496 - 579 13,717 18,700 23,588 28,480 33,367

20025 513 - 578 13,003 17,636 22,197 26,761 31,275

20612 290 - 305 11,721 15,628 19,927 23,912 28,229

23257 387 - 432 8,840 12,125 15,294 18,479 21,671

21573 244 - 263 8,412 11,571 14,464 17,671 20,617

20449 250 - 295 8,248 11,431 14,498 17,489 20,489

20527 245 - 261 8,176 10,901 13,958 16,999 19,832

12 274 - 297 6,732 8,976 11,579 13,895 16,493

20708 229 - 275 5,783 8,319 10,629 12,755 15,113

Subtotalb 2,179 - 2,504 56,873 78,419 100,496 122,053 143,405

Subtotalc 35,321 - 35,799 898,957 1,200,982 1,502,175 1,803,969 2,105,365

Totald 54,080 - 56,025 1,369,186 1,839,943 2,310,798 2,780,453 3,249,415

a. Computed based on the assumption that first revenue occurred one year after initial redevelopment 

 investment. 

b. Computed based on structures that have been decommissioned by February 2009. 

c. Computed based on structures/leases that filed an EP or DOCD by February 2009. 

d. For all 61 structures that have not restarted production. 
118

 

 Figure D.1 Pre- and Post-Hurricane Production from All Structures Destroyed by Ivan, 

Katrina, and Rita. (Time unit is month and is set at 1 for the first month 

after each hurricane event and ends in December 2008.) 

 

 Figure D.2. Longer Term View of Production from All Structures Destroyed by Ivan, 

Katrina, and Rita through December 2008. 

Source: USDOI, MMS, 2009b. 

Source: USDOI, MMS, 2009b. 
119

Figure D.3. Pre- and Post-Hurricane Production from Destroyed Structures that 

Restarted Production. (Time unit is month and is set at 1 for the first month 

after each hurricane event through December 2008.) 

Figure D.4. Pre- and Post-Hurricane Aggregate Monthly Gross Revenue from All 

Structures Destroyed by Ivan, Katrina, and Rita. (Time unit is month and 

is set at 1 for the first month after each hurricane through December 2008.) 

Source: USDOI, MMS, 2009b. 

Source: USDOI, MMS, 2009b. 
120

Figure D.5. Pre- and Post-Hurricane Aggregate Monthly Gross Revenue from 

Destroyed Structures that Restarted Production through December 2008. 

(Time unit is month and is set at 1 for the first month after each hurricane 

event.) 

Figure D.6. Gas Structures that Restarted Production, Leases that Have Submitted 

DOCD Plans, Structures that Have Been Decommissioned, and Those 

Structures that Have Not Restarted Production. 

Source: USDOI, MMS, 2009b. 
121

 Figure D.7. Oil Structures that Restarted Production, Leases that Have Submitted 

 DOCD Plans, Structures that Have Been Decommissioned, and Those 

 Structures that Have Not Restarted Production. 

 Figure D.8. All Structures that Restarted Production, Leases that Have Submitted 

 DOCD Plans, Structures that Have Been Decommissioned, and Those 

 Structures that Have Not Restarted Production. 
122

Figure D.9. Redevelopment Opportunities Outlined by Regions: (I) Unlikely 

Redevelopment, (II) Possible Redevelopment, and (III) Probable 

Redevelopment. 

Figure D.10. Aggregate Annual Drilled Wellbores, Sidetrack Wells, and Plugged and 

Abandoned Wells for the Collection of Structures that Restarted 

Production by August 2008. 

Unlikely 

Redevelopment 

Probable 

Redevelopment 

Possible 

Redevelopment 

Source: USDOI, MMS, 2009b. 
123

Figure D.11. Cumulative Annual Drilled Wellbores, Sidetrack Wells, and 

Plugged and Abandoned Wells for the Collection of Structures that 

Restarted Production. 

Figure D.12. Aggregate Annual Drilled Wellbores, Sidetrack Wells, and Plugged and 

Abandoned Wells for Structures that Have Not Been Redeveloped Wells by 

August 2008 (ex-structure 735). 

Source: USDOI, MMS, 2009b. 

Source: USDOI, MMS, 2009b. 
124

Figure D.13. Cumulative Annual Drilled Wellbores, Sidetrack Wells, and 

Plugged and Abandoned Wells for Structures that Have Not Been 

Redeveloped by August 2008 (ex-structure 735). 

 Figure D.14. Forecast Gas Production for Structures that Have Restarted Production, 

 the MTLP, and Structures with a Submitted DOCD Plan.

Source: USDOI, MMS, 2009b. 
125

 Figure D.15. Forecast Oil Production for Structures that Have Restarted Production, 

 the MTLP, and Structures with a Submitted DOCD Plan. 

 Figure D.16. Forecast BOE Production for Structures that Have Restarted 

Production, the MTLP, and Structures with a Submitted DOCD Plan. 
127

APPENDIX E. 

CHAPTER 5 TABLES AND FIGURES
129

Table E.1.

Exploration and Development Wells Drilled in the Gulf of Mexico (1947-2007)

Water Depth (ft) Exploration Wells Development Wells 

0-60 4,257 8,651 

61-200 6,337 12,229 

201-600 3,894 7,836 

601-1,000 414 487 

> 1,000 2,005 1,360 

Total 16,907 30,563 

Source: USDOI, MMS, 2008. 

Table E.2. 

 Structure Installations by Structure Type and Water Depth (1947-2007) 

 Water Depth 

Structure Typea 0-60 ft 61-200 ft 201-600 ft 601-1,000 ft > 1,000 ft Total 

CAIS 1,970 488 4 0 0 2,462 

FP/Manned 384 501 301 18 6 1,210 

/Unmanned 860 1,135 301 3 0 2,299 

 /Total 1,244 1,366 602 21 6 3,509 

CT 0 0 0 1 2 3 

MOPU 2 2 0 0 0 4 

SEMI 0 0 0 0 6 6 

SPAR 0 0 0 0 14 14 

SSMNF 0 1 0 0 0 1 

SSTMP 0 1 1 0 1 3 

TLP 0 0 0 0 10 10 

WP 450 310 39 0 0 799 

 TOTAL 3,666 2,438 646 22 39 6,811 

Source: USDOI, MMS, 2008. 

Footnote: (a) CAIS = caisson, FP = fixed platform, CT = compliant tower, MOPU = mobile offshore production 

unit, SEMI= semisubmersible, SPAR = deep draft floating caisson, TLP = tension leg platform, WP = 

well protector. 
130

Table E.3. 

 

Structure Removals by Structure Type and Water Depth (1973-2007) 

 Water Depth 

Structure Typea 0-60 ft 61-200 ft 201-600 ft 601-1,000 ft > 1,000 ft Total 

CAIS 1,084 283 2 0 0 1,369

FP/Manned 39 68 30 1 0 138

/Unmanned 393 523 127 0 0 1,043

 /Total 432 591 157 1 0 1,181

CT 0 0 0 0 0 0

MOPU 0 2 0 0 0 2

SEMI 0 0 0 0 1 1

SPAR 0 0 0 0 14 14

SSMNF 0 0 0 0 0 0

SSTMP 0 2 0 0 1 3

TLP 0 0 0 0 0 0

WP 211 187 21 0 0 419

 TOTAL 1,727 1,065 180 1 16 2,989

Source: USDOI, MMS, 2008. 

Footnote: (a) CAIS = caisson, FP = fixed platform, CT = compliant tower, MOPU = mobile offshore production 

unit, SEMI= semisubmersible, SPAR = deep draft floating caisson, TLP = tension leg platform, WP = 

well protector.
131

 Figure E.1. Number of Exploration and Development Wells Drilled Annually in the Gulf 

of Mexico (1947-2007). 

 Figure E.2. Cumulative Number of Exploration and Development Wells Drilled in the 

Gulf of Mexico (1947-2007). 

Source: USDOI, MMS, 2008. 

Source: USDOI, MMS, 2008. 
132

 Figure E.3. Number of Exploration Wells Drilled by Water Depth Category (1947-2007). 

 

Figure E.4. Number of Development Wells Drilled by Water Depth Category (1947-

2007). 

Source: USDOI, MMS, 2008. 

Source: USDOI, MMS, 2008. 
133

Figure E.5. Stacked Area Graph of the Number of Producing Oil and Gas Wells in the 

 GOM for GOR=10,000 (1947-2006). 

 Figure E.6. Number of Producing Oil and Gas Wells in the GOM for GOR=10,000 

(1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
134

 Figure E.7. Number of Producing Wells in the GOM Identified as Oil Wells as a 

Function of GOR Thresholds (1947-2006). 

 Figure E.8. Number of Producing Wells in the GOM Identified as Gas Wells as a 

Function of GOR Thresholds (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
135

 Figure E.9. Oil Well Population Ratio in the GOM as a Function of GOR Thresholds 

 (1947-2006). 

 

 Figure E.10. Liquid Production from Oil and Gas Wells in the GOM (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
136

 Figure E.11. Gas Production from Oil and Gas Wells in the GOM (1947-2006). 

Figure E.12. Cumulative Oil Production from Oil and Gas Wells in the GOM (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
137

Figure E.13. Cumulative Gas Production from Oil and Gas Wells in the GOM (1947-

2006). 

Figure E.14. Oil Wells Categorized According to Daily Oil Production Levels (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
138

Figure E.15. Stacked Area Graph of Oil Wells Categorized According to Daily Oil 

Production Levels (1947-2006). 

Figure E.16. Population Ratio of Oil Wells Categorized According to Daily Oil 

Production Levels (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
139

 Figure E.17. Oil Wells Categorized According to Daily Gas Production (1947-2006). 

Figure E.18. Stacked Area Graph of Oil Wells Categorized According to Daily Gas 

Production (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
140

 Figure E.19. Oil Well Oil Production per Category (1947-2006). 

 Figure E.20. Oil Production Ratio per Category According to Daily Oil Production 

 (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
141

 Figure E.21. Oil Well Gas Production per Category (1947-2006). 

Figure E.22. Gas Wells Categorized According to Daily Oil Production Levels (1947-

2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
142

 Figure E.23. Stacked Area Graph of Gas Wells Categorized According to Daily Oil 

Production Levels (1947-2006).

 Figure E.24. Gas Wells Categorized According to Daily Gas Production Levels (1947-

2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
143

Figure E.25. Stacked Area Graph of Gas Wells Categorized According to Daily Gas 

Production Levels (1947-2006). 

Figure E.26. Population Ratio of Gas Wells Categorized According to Daily Gas 

Production Levels (1951-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
144

 Figure E.27. Gas Well Oil Production per Category (1947-2006). 

 Figure E.28. Gas Well Gas Production per Category (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
145

 Figure E.29. Gas Production Ratio per Category According to Daily Gas Production 

 (1951-2006). 

 Figure E.30. Structure Installations in the Gulf of Mexico (1947-2007). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2008. 
146

 Figure E.31. Cumulative Number of Structure Installations in the Gulf of Mexico 

 (1947-2007). 

 Figure E.32. Structure Removals in the Gulf of Mexico (1973-2007). 

Source: USDOI, MMS, 2008. 

Source: USDOI, MMS, 2008. 
147

 Figure E.33. Cumulative Number of Structure Removals in the Gulf of Mexico 

 (1973-2007).

 Figure E.34. Active Structures in the Gulf of Mexico (1947-2007). 

Source: USDOI, MMS, 2008. 

Source: USDOI, MMS, 2008. 
148

 Figure E.35. Change in the Number of Active Structures in the Gulf of Mexico 

 (1947-2007). 

 Figure E.36. Cumulative Number of Installed, Removed, and Active Structures 

 in the Gulf of Mexico (1947-2007). 

Source: USDOI, MMS, 2008. 

Source: USDOI, MMS, 2008. 
149

 Figure E.37. Stacked Area Graph of Number of Producing Oil and Gas Structures in the 

GOM (1947-2006). 

 Figure E.38. Number of Producing Oil and Gas Structures in the GOM (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
150

 Figure E.39. Number of Non-Producing Structures in the GOM (1947-2006). 

 Figure E.40. Population Ratio of Non-Producing Structures in the GOM (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
151

Figure E.41. Annual Oil Production from Oil and Gas Structures in the GOM (1947-

2006). 

Figure E.42. Annual Gas Production from Oil and Gas Structures in the GOM (1947-

2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
152

 Figure E.43. Cumulative Oil Production from Oil and Gas Structures in the GOM (1947-

2006). 

Figure E.44. Cumulative Gas Production from Oil and Gas Structures in the GOM 

(1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
153

Figure E.45. Oil Structure Oil Production Decomposed According to Production 

Category (1947-2006). 

Figure E.46. Cumulative Oil Structure Oil Production Decomposed According to 

Production Category (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
154

 Figure E.47. Oil Structure Gas Production Decomposed According to Production 

Category (1947-2006). 

Figure E.48. Oil Structures Categorized According to Daily Oil Production (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
155

 Figure E.49. Stacked Area Graph of Oil Structures Categorized According to Daily Oil 

 Production (1947-2006). 

 Figure E.50. Oil Structures Categorized According to Daily Gas Production (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
156

 Figure E.51. Stacked Area Graph of Oil Structures Categorized According to Daily Gas 

 Production (1947-2006). 

 Figure E.52. Gas Structure Gas Production Decomposed According to Production 

Category (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
157

 Figure E.53. Cumulative Gas Structure Gas Production Decomposed According to 

Production Category (1947-2006). 

Figure E.54. Gas Structure Oil Production Decomposed According to Production 

Category (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
158

Figure E.55. Gas Structures Categorized According to Daily Gas Production (1947-2006). 

 Figure E.56. Stacked Area Graph of Gas Structures Categorized According to Daily 

Gas Production (1947-2006).

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
159

Figure E.57. Gas Structures Categorized According to Daily Oil Production (1947-2006). 

 Figure E.58. Stacked Area Graph of Gas Structures Categorized According to Daily Oil 

 Production (1947-2006). 

Source: USDOI, MMS, 2007. 

Source: USDOI, MMS, 2007. 
161

APPENDIX F. 

CHAPTER 6 TABLES AND FIGURES
163

Table F.1. 

 

Active Structures Classified by Primary Production and Structure Type (2006) 

Primary 

Production Caisson Fixed 

Platform 

Well 

Protector Unknown Total 

Gas 458 1,093 157 27 1,735 

Oil 126 416 72 15 629 

All 584 1,509 229 42 2,364 

 Source: USDOI, MMS, 2007. 

Table F.2. 

 

Active Structures Classified by Class and Primary Production (2006) 

Structure Class Primary Production Total 

 Gas Oil 

Young 462 63 525 

Normal 854 426 1,280 

Chaotic 64 26 90 

Latecomer 378 49 427 

Unknown 27 15 42 

Total 1,735 629 2,364 
164

Table.F 3. 

 

Number of Subcategories Based Upon Removed Structures in the GOM 

 

Primary 

Production

Water 

Depth 

(ft) 

Caisson Well 

Protector 

Fixed 

Platform 

Gas < 60 10 10 10 

 60 - 200 10 10 10 

 > 200 - 3 10 

Oil < 60 10 10 5 

 60 - 200 3 5 10 

 > 200 - 3 3 

Table F.4. 

 

History Matching Procedure for Young Structures 

Step 1. For s∈Г at time T, compute Q(s,T) = ∑=

T

t

q s t

1

( , )

Step 2. Compare Q(s,T) with Q (Г, T) and select Q *(Г, T) = 

γ

min Q(s,T) Q( ,T) ijk − γ

Step 3. Label the annual production profile corresponding to Q *

 (Г, T) as q * (Г, t). 

Step 4. Calculate α = . ( , )

( , )

Q T

Q s T

ijk γ

Step 5. Identify s with the production profile q(s,t)= α q *

 (Г, t), t >T

 
165

Table F.5. 

Best Fit Curve Frequency and Average Model Parameters 

for Normal and Chaotic Structures 

Normal Class Frequency Coefficients Curve Fit 

Primary Production Model Type (%) a, C n R2

Gas Exponential 46% 0.415 0.91 

 Harmonic 3% 1.8E-05 0.89 

 Hyperbolic 51% 0.063 14,331.8 0.91 

Oil Exponential 36% 0.294 0.90 

 Harmonic 4% 1.0E-05 0.90 

 Hyperbolic 59% 0.023 1,176.9 0.90 

Chaotic Class Frequency Coefficients Curve Fit 

Primary Production Model Type (%) a, C n R2

Gas Exponential 22% 0.506 0.54 

 Harmonic 63% 1.9E-05 0.58 

 Hyperbolic 16% 1.18E-04 1.603 0.56 

Oil Exponential 23% 0.12 0.59 

 Harmonic 50% 1.0E-05 0.46 

 Hyperbolic 27% 1.19E-03 2.315 0.64 
166

Table F.6. 

 

Cumulative Production in Year Six for the 

10 Subcategories of Г(CAIS, 60-200, OIL) 

Subcategory Cumulative Production (BOE) 

1 45,495 

2 147,727 

3 348,192 

4 491,615 

5 615,902 

6 791,521 

7 960,707 

8 1,101,116 

9 1,555,745 

10 2,355,294 

Table F.7. 

 

Active Structures Applied in the Model Forecast 

Structure Class Gas Oil Total 

Uneconomic 321 59 380 

Normal 662 380 1,042 

Young 394 60 454 

Chaotic 53 23 76 

Latecomer 279 93 372 

Unknown 26 14 40 

Total 1,735 629 2,364 
167

Table F.8. 

 

Model Parameters and Distribution Functions 

Parameter Notation (Unit) Distributiona 

Decline rate d (%) U(5, 30) 

Oil price Po ($/bbl) N(120, 20) 

Gas price Pg ($/Mcf) N(12, 2) 

Economic limit multiplier a U(0.5, 3) 

Discount rate D (%) U(8, 14) 

Footnote: (a) U(a, b) denotes the Uniform distribution with endpoint (a, b). N(μ, σ2) represents the Normal 

distribution with mean μ and variance σ2. 

Table F.9. 

Model Results for Cumulative Gas, Oil, BOE Production 

Qi = α1d + α2Po + α3 Pg + α4 a 

Coefficient Gas Oil BOE 

α1 -2.1E10(-7.7) -2.1E9(-9.0) -5.6E9(-8.2)

α2 6.4E7(6.8) 5.5E6(6.8) 1.6E7(6.8)

α3 7.0E8(7.5) 5.6E7(6.9) 1.7E8(7.3)

a4 2.9E8(1.1) 3.5E7(1.6) 8.3E7(1.3)

R2 0.97 0.97 0.82

Table F.10. 

Present Value of Gas, Oil, and BOE Production 

PV= α0 + α1d + α2Po

 + α3 Pg + α4a + α5D 

 Gas Oil BOE 

 Coefficient α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 0

α0 5.1E7(19.0) 4.5E7(15.6) 9.64E7 (19.4) 

α1 -9.3E7(13.5) -8.9E7(28.3) -9.3E7(-14.5) -9.0E7(-26.3) -1.86E8 (-14.3) -1.79E8 (-30.6) 

α2 1.2E5(4.7) -1.7E4(-1.3) 7.0E5(30.2) 5.8E5(40.1) 8.12E5 (17.4) 5.61E5 (22.7) 

α3 8.7E6(36.1) 7.3E6(55.2) 1.3E6(5.6) 2.3E4(0.2) 1.00E7 (22.0) 7.36E6 (29.8) 

α4 -4.5E6(-6.9) -6.0E6(19.6) 8.3E5(1.4) -5.5E5(-1.6) -3.67E6 (-3.0) -6.59E6 (-11.5) 

α5 -1.6E8(-6.9) -3.0E8(23.4) -1.5E8(-7.1) -2.7E8(-19.9) -3.08E8 (-7.2) -5.70E8 (-24.2) 

R2 0.98 0.99 0.99 0.97 0.99 0.98 
168

 Figure F.1. Hydrocarbon Production on the OCS of the Gulf of Mexico (1991-2007). 

 Figure F.2. Oil Production on the OCS in the GOM (1991-2007). 

Source: USDOI, MMS, 2008. 

Source: USDOI, MMS, 2008. 
169

 Figure F.3. Gas Production on the OCS in the GOM (1991-2007). 

 Figure F.4. Average Annual Production Profiles in the Fixed Platform, 0-60 ft Water 

Depth, Oil Production, Subcategory. 

Source: USDOI, MMS, 2008. 
170

 Figure F.5. Average Annual Production Profiles in the Caisson, 60-200 ft Water Depth, 

 Gas Production, Subcategory. 

Figure F.6. Average Annual Production Profiles in the Well Protector, 60-200 ft Water 

Depth, Oil Production, Subcategory. 
171

 Figure F.7. Historical and Forecast Production of Structure 587. 

 Figure F.8. Annual Production Curve and Best-Fit Regression of Structure 33. 
172

Figure F.9. Historical and Projected BOE Production of Structure 33. 

Figure F.10. Historical and Projected Oil and Gas Production of Structure 33. 
173

 Figure F.11. Historical and Projected BOE Production of Structure 152. 

 Figure F.12. Production Profile of Structure 23266. 
174

 Figure F.13. Historical Production and Best-Fit Regression Curve of Structure 23266. 

 Figure F.14. Projected BOE Production of Structure 10042. 
175

 Figure F.15. Forecast of Committed Shallow Water Structures in the GOM (2007-2047). 

 Figure F.16. Annual Oil Production from Active Structures (2007-2047). 
176

 Figure F.17. Annual Gas Production from Active Structures (2007-2047). 

 Figure F.18. Annual BOE Production of Active Structures (2007-2047). 
177

 Figure F.19. Annual BOE Production per Asset Category (2007-2047). 

 Figure F.20. Cumulative BOE Production per Asset Category (2007-2047). 
178

 Figure F.21. Annual Gas Production per Asset Category (2007-2047). 

 Figure F.22. Cumulative Gas Production per Asset Category (2007-2047). 
179

 Figure F.23. Annual Oil Production per Asset Category (2007-2047). 

 Figure F.24. Cumulative Oil Production per Asset Category (2007-2047). 
181

APPENDIX G. 

CHAPTER 7 TABLES AND FIGURES 

 
183

Table G.1. 

 

Classification of Shallow Water Structures in the Gulf of Mexico (2006) 

Structure Class Production Type Total 

Gas Oil 

Young 462 63 525 

Normal 854 426 1,280 

Chaotic 64 26 90 

Latecomer 328 99 427 

Unknown 27 15 42 

Total 1,735 629 2,364 

Table G.2. 

 

Model Parameters and Distribution Functions 

Parameter Notation (Unit) Distributiona

Decline rate d (%) U(5, 30)

Oil price Po ($/bbl) N(120, 20)

Gas price Pg ($/Mcf) N(12, 2)

Marginal threshold multiplier m U(a,6)

Economic limit multiplier a U(0.5, 3)

Discount rate D (%) U(8, 14)

Footnote: (a) U(a, b) denotes the Uniform distribution with endpoint (a, b). N(μ, 

 σ2

) represents the Normal distribution with mean μ and variance σ2. 
184

Table G.3. 

Summary Statistics for Shallow Water Committed Assets in the GOM (2006) 

Production (unit) Economic Marginal Total 

Oil (MMbbl) 1,013 44 1,056 

Gas (Bcf) 12,622 717 13,338 

BOE (MMBOE) 3,116 163 3,279 

PV ($ billion) 147.7 1.7 149.4 

Table G.4. 

Model Results for Total (Cumulative) BOE Production (BOE) 

Qi = α1d + α2Po + α3 Pg + α4m + α5 a

Coefficient Economic Marginal Total 

α1 -5.3E9(-8.2) -1.8E8(-5.1) -5.6E9(-8.2)

α2 1.5E7(6.7) 4.2E5(3.4) 1.6E7(6.8)

α3 1.7E8(7.5) 1.1E6(0.9) 1.7E8(7.3)

α4 2.9E7(0.9) 7.7E7(38.2) -

α5 - -9.1E7(-24.1) 8.3E7(1.3)

R2 0.89 0.69 0.82

Table G.5. 

Model Results for Total (Cumulative) Gas Production (Mcf) 

Qg = α1d + α2Po

 + α3 Pg + α4m + α5 a

Coefficient Economic Marginal Total 

α1 -2.0E10(-7.8) -8.4E8(-5.1) -2.1E10(-7.7)

α2 5.9E7(6.7) 2.4E6(4.2) 6.4E7(6.8)

α3 6.9E8(7.8) 8.0E5(0.1) 7.0E8(7.5)

α4 8.6E7(0.7) 3.4E8(36.9) -

α5 - -4.0E8(-23.5) 2.9E8(1.1)

R2 0.97 0.97 0.97
185

Table G.6. 

Model Results for Total (Cumulative) Oil Production (bbl) 

Qo = α1d + α2Po

 + α3 Pg + α4m + α5 a

Coefficient Economic Marginal Total 

α1 -2.0E9(-9.1) -4.3E7(-4.7) -2.1E9(-9.0)

α2 5.3E6(6.7) 2.0E4(0.6) 5.5E6(6.8)

α3 5.4E7(6.9) 9.4E5(3.0) 5.6E7(6.9)

α4 1.5E7(1.3) 2.1E7(41.1) ‐

α5 ‐ -2.4E7(-25.0) 3.5E7(1.6)

R2 0.97 0.97 0.97
186

Table G.7. 

Model Results for Present Value of Total Hydrocarbon (Oil and Gas) Production ($1,00

PV = α0 + α1d + α2Po + α3 Pg + α4 m + α5a + α6D

Economic Marginal Total

Coefficient α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 

α0 8.86E7 (13.3) 1.69E6 (2.2) 9.64E7 α1 -1.90E8 (-14.8) -1.86E8 (-24.5) 4.45E5 (0.5) 5.58E5 (0.6) -1.86E8 (-14.3) -1.79E8 (α2 8.06E5 (17.4) 5.87E5 (18.4) 2.21E3 (0.7) -2.01E3 (-0.5) 8.12E5 (17.4) 5.61E5 α3 9.64E6 (21.2) 7.29E6 (22.7) 7.91E4 (2.5) 3.55E4 (1.0) 1.00E7 (22.0) 7.36E6 α4 -2.64E5 (-0.4) -2.11E6 (-5.2) 1.28E6 (26.2) 1.25E6 (25.2) α5 -1.82E6 (19.8) -1.85E6 (-20.4) -3.67E6 (-3.0) -6.59E6 (α6 -3.20E8 (-7.6) -5.62E8 (-18.2) -1.07E7 (-3.7) -1.52E7 (-4.3) -3.08E8 (-7.2) -5.70E8 (

R2 0.99 0.96 0.93 0.90 0.99 0.98 
187

Table G.8. 

Model Results for Present Value of Gas Production ($1,000) 

PV = α0 + α1d + α2Po + α3 Pg + α4 m + α5a + α6D

Economic Marginal Total

Coefficient α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 

α0 4.4E7(8.9) 5.4E5(0.7) 5.1E7α1 -9.8E7(12.7) -9.6E7(-16.8) 3.6E5(0.4) 4.0E5(0.5) -9.3E7(13.5) -8.9E7α2 1.2E5(4.4) 1.3E4(0.5) -3.9E3(-1.3) -5.2E3(-1.5) 1.2E5(4.7) -1.7E4α3 8.4E6(30.9) 7.2E6(29.9) 8.8E4(3.0) 7.4E4(2.1) 8.7E6(36.1) 7.3E6α4 -5.1E5(-1.3) -1.4E6(-4.7) 5.6E5(12.4) 5.5E5(11.7) α5 -1.2E6(-14.6) -1.3E6(14.5) -4.5E6(-6.9) -6.0E6α6 -1.8E8(-7.1) -3.0E8(-13.0) -1.6E6(-0.6) -3.0E6(-0.9) -1.6E8(-6.9) -3.0E8

R2 0.94 0.99 0.73 0.75 0.98 
188

Table G.9. 

Model Results for Present Value of Oil Production ($1,000) 

PV = α0 + α1d + α2Po + α3 Pg + α4 m + α5a + α6D

Economic Marginal Total

Coefficient α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 0 α0 = 0 α0 ≠ 

α0 4.4E7(14.8) 1.2E6(6.6) 4.5E7α1 -9.2E7(14.9) -9.0E7(-26.5) 8.1E4(0.3) 1.6E5(0.8) -9.3E7(-14.5) -9.0E7(α2 6.8E5(30.6) 5.7E5(40.1) 6.1E3(7.1) 3.2E3(3.9) 7.0E5(30.2) 5.8E5α3 1.2E6(5.6) 6.1E4(0.4) -8.4E3(-1.0) -3.8E4(-4.6) 1.3E6(5.6) 2.3Eα4 2.4E5(0.8) -6.8E5(-3.7) 7.1E5(54.4) 6.9E5(61.6) α5 -5.7E5(23.2) -5.9E5(28.7) 8.3E5(1.4) -5.5E5α6 -1.4E8(-6.9) -2.6E8(-18.9) -9.2E6(11.7) -1.2E7(15.3) -1.5E8(-7.1) -2.7E8(

R2 0.99 0.97 0.98 0.98 0.99 
189

 Figure G.1. Number of Producing Structures Decomposed According to Marginal and 

Economic Status (2007-2067). 

 Figure G.2. Marginal Structures as a Percentage of the Committed Asset Inventory 

Circa 2006 (2007-2067). 
190

Figure G.3. Average Producing Structure Count and One Standard Deviation Envelope 

 (2007-2067). 

 Figure G.4. Average Economic Structure Count and One Standard Deviation Envelope 

 (2007-2067). 
191

 Figure G.5. Average Marginal Structure Count and One Standard Deviation Envelope 

 (2007-2067). 

 Figure G.6. Average Annual BOE Production Profile of Producing Structures 

Decomposed According to Economic and Marginal Categories (2007-

2067).
192

 Figure G.7. Average Cumulative BOE Production of Producing Structures Decomposed 

 According to Economic and Marginal Categories (2007-2067). 

 Figure G.8. BOE Production Envelopes of Producing Structures (2007-2067). 
193

 Figure G.9. BOE Production Envelopes of Economic Structures (2007-2067). 

 Figure G.10. BOE Production Envelopes of Marginal Structures (2007-2067). 
194

 Figure G.11. BOE Production Contribution per Asset Category (2007-2067). 

Figure G.12. Cumulative BOE Production Contribution per Asset Category (2007-2067). 
The Department of the Interior Mission

As the Nation's principal conservation agency, the Department of the Interior has responsibility 

for most of our nationally owned public lands and natural resources. This includes fostering 

sound use of our land and water resources; protecting our fish, wildlife, and biological diversity; 

preserving the environmental and cultural values of our national parks and historical places; 

and providing for the enjoyment of life through outdoor recreation. The Department assesses 

our energy and mineral resources and works to ensure that their development is in the best 

interests of all our people by encouraging stewardship and citizen participation in their care. 

The Department also has a major responsibility for American Indian reservation communities 

and for people who live in island territories under U.S. administration. 

The Minerals Management Service Mission 

As a bureau of the Department of the Interior, the Minerals Management Service's (MMS) 

primary responsibilities are to manage the mineral resources located on the Nation's Outer 

Continental Shelf (OCS), collect revenue from the Federal OCS and onshore Federal and Indian 

lands, and distribute those revenues. 

Moreover, in working to meet its responsibilities, the Offshore Minerals Management Program 

administers the OCS competitive leasing program and oversees the safe and environmentally 

sound exploration and production of our Nation's offshore natural gas, oil and other mineral 

resources. The MMS Minerals Revenue Management meets its responsibilities by ensuring the 

efficient, timely and accurate collection and disbursement of revenue from mineral leasing and 

production due to Indian tribes and allottees, States and the U.S. Treasury. 

The MMS strives to fulfill its responsibilities through the general guiding principles of: (1) being 

responsive to the public's concerns and interests by maintaining a dialogue with all potentially 

affected parties and (2) carrying out its programs with an emphasis on working to enhance the 

quality of life for all Americans by lending MMS assistance and expertise to economic 

development and environmental protection.