OCS Study
 

BOEM 2018-006 

US Outer Continental Shelf 

Oil Spill Statistics 

US Department of the Interior 

Bureau of Ocean Energy Management 

Alaska OCS Region 
OCS Study
 

BOEM 2018-006 

This page intentionally left blank. 
OCS Study 

BOEM 2018-006 

US Outer Continental Shelf 

Oil Spill Statistics 

March 2018
 

Authors:
 

Benjamin Roberts and Joseph Myers
 

Prepared under BOEM Award 

TO Contract # M17PD00066, Deliverable #C1 

IDIQ Contract # M17PC00015 

By 

ABSG CONSULTING INC. 

1525 Wilson Blvd., Suite 625 

Arlington, VA 22209 

US Department of the Interior 

Bureau of Ocean Energy Management 

Alaska OCS Region 
 

OCS Study
 

BOEM 2018-006 

This page intentionally left blank. 
Disclaimer 

Study concept, oversight, and funding were provided by the US Department of the Interior 

(DOI), Bureau of Ocean Energy Management (BOEM), Environmental Studies Program, 

Washington, DC, under Contract Number # M17PC00015. This report has been technically 

reviewed by BOEM, and it has been approved for publication. The views and conclusions 

contained in this document are those of the authors and should not be interpreted as representing 

the opinions or policies of the US Government, nor does the mention of trade names or 

commercial products constitute endorsement or recommendation for use. 

Report Availability 

To download a PDF file of this report, go to the US Department of the Interior, Bureau of Ocean 

Energy Management Environmental Stewardship webpage (https://www.boem.gov/ESPIS/), 

click on the link for the Environmental Studies Program Information System (ESPIS), and search 

on 2018-006 The report is also available at the National Technical Reports Library at 

https://ntrl.ntis.gov/NTRL/. 

Citation 

ABSG Consulting Inc. 2018. US Outer Continental Shelf Oil Spill Statistics. Arlington (VA): 

Prepared for US Department of the Interior, Bureau of Ocean Energy Management. OCS Study 

BOEM 2018-006. 

Acknowledgements 

The following BOEM offices or programs contributed to this document: Alaska OCS Region. 
 

Contents 

List of Figures................................................................................................................................. ii
 

List of Tables .................................................................................................................................. ii
 

Abbreviations and Acronyms ........................................................................................................ iii
 

1 Introduction......................................................................................................................... 4
 

1.1 Analysis Scope ................................................................................................................. 4
 

1.2 Causal Factors .................................................................................................................. 5
 

1.3 Data Sources..................................................................................................................... 5
 

2 OCS Platform Spills............................................................................................................ 7
 

2.1 OCS Platform Exposure ................................................................................................... 7
 

2.2 Platform Spills .................................................................................................................. 9
 

2.3 OCS Platform Spill Statistics ......................................................................................... 11
 

2.4 Loss of Well Control Spills............................................................................................ 11
 

3 OCS Pipeline Spills .......................................................................................................... 12
 

3.1 OCS Pipeline Exposure.................................................................................................. 12
 

3.2 OCS Pipeline Spills........................................................................................................ 13
 

3.3 Pipeline Spill Statistics................................................................................................... 15
 

4 Confidence Intervals ......................................................................................................... 17
 

5 References......................................................................................................................... 21
 

Appendix A: OCS Platform Exposure .......................................................................................... 22
 

Appendix B: OCS Platform Spills ................................................................................................ 23
 

Appendix C: OCS Pipeline Exposure ........................................................................................... 29
 

Appendix D: OCS Pipeline Spills................................................................................................. 33
 

Appendix E: Additional Spill Documents .................................................................................... 36
 
 

 

List of Figures 

Figure 1. Platform spills ≥ 50 bbl of petroleum.............................................................................. 9
 

Figure 2. Pipeline Spills ≥ 50 bbl of petroleum ............................................................................ 13
 

List of Tables 

Table 1. Scope of the report............................................................................................................ 4
 

Table 10. GOM and PAC pipeline hydrocarbon spill statistics by spill size and pipeline diameter 

Table 11. Confidence intervals for GOM and PAC OCS platform hydrocarbon spill statistics 

Table 13. Confidence intervals for GOM and PAC pipeline hydrocarbon spill statistics by cause 

Table 14. Confidence intervals for GOM and PAC pipeline hydrocarbon spill statistics by spill 

Table 2. Annual count of active wells in GOM and PAC OCS (1972 to 2017) ............................. 8
 

Table 3. Platform spill size distribution summary ........................................................................ 10
 

Table 4. Platform spill summary by spill size (1972 to 2017) ...................................................... 10
 

Table 5. GOM and PAC OCS platform hydrocarbon spill statistics (1972 to 2017) ................... 11
 

Table 6. LOWC Spill Summary.................................................................................................... 11
 

Table 7. Count of pipeline spills by NPS categories (1972 to 2017) ............................................ 14
 

Table 8 Count of pipeline spills by causal factors (1972 to 2017) ............................................... 14
 

Table 9. GOM and PAC pipeline hydrocarbon spill statistics by cause (1972 to 2017) .............. 15
 

(1972 to 2017)............................................................................................................................... 16
 

(1972 to 2017)............................................................................................................................... 18
 

Table 12. LOWC Spill Summary .................................................................................................. 18
 

(1972 to 2017)............................................................................................................................... 19
 

size and pipeline diameter (1972 to 2017) .................................................................................... 20
 

Table 15. GOM and PAC OCS Platform Spills ≥ 50 bbls (1972 to 2017)................................... 23
 

Table 16. Miles of GOM and PAC oil pipeline segments by year and size (1972 to 2017) ........ 31
 

Table 17. GOM and PAC OCS pipeline spills ≥ 50 bbls (1972 to 2017)..................................... 33
 
 

 

 

 

Abbreviations and Acronyms 

ABSG ABS Group 

API American Petroleum Institute 

bbl Barrel (42 US gallons, 0.159 kiloliters, 0.159 m3

, or 0.136 metric tonnes) 

BOEM Bureau of Ocean Energy Management 

BSEE Bureau of Safety and Environmental Enforcement 

DOI US Department of Interior 

ESPIS Environmental Studies Program Information System 

GOM Gulf of Mexico 

LOWC Loss of Well Control 

MISLE Marine Information for Safety and Law Enforcement 

NPS Nominal Pipeline Size 

NRC National Response Center 

OCS Outer Continental Shelf 

O&G Oil and Gas 

PAC Pacific Ocean 

PHMSA Pipeline and Hazardous Material Safety Administration 

TIMS Technical Information Management System 

USCG US Coast Guard 
 

1 Introduction 

On 26 September 2017, the Bureau of Ocean Energy Management (BOEM) contracted ABSG 

Consulting, Inc.(ABSG) in an Indefinite Delivery/Indefinite Quantity contract to perform fault 

tree analysis to develop oil-spill occurrence frequencies for size ranges of crude oil, condensate, 

and refined petroleum spills for use in environmental analyses related to proposed oil and gas 

leasing, exploration, development, and production activities in the Alaska Outer Continental 

Shelf (OCS) Arctic Planning Areas. Task 1 of the first task order in the contract involves 

estimation of spill occurrence frequencies. This analysis includes: 

 Collation of historical data from the Gulf of Mexico (GOM) and Pacific (PAC) OCS oil 

spills 

 Calculation of spill exposure metrics 

 Review of spill causal factors 

 Calculation of spill occurrence frequencies 

 Estimation of uncertainty metrics such as confidence intervals 

This report documents the approach and statistical results to be used in subsequent fault tree 

analyses. Spill occurrence frequencies are calculated for an array of spill categories. The results 

are reported in a format compatible with prior oil-spill occurrence analyses, in particular the 

2013 report produced by Bercha International, Inc. 

1.1 Analysis Scope 

The data analysis and calculations presented in this report are designed to provide oil-spill 

frequency estimates for different spill sizes, fluids, and facility types associated with OCS oil and 

gas (O&G) operations. Table 1 summarizes the scope of the analysis. 

Table 1. Scope of the report 

Scope Categories (bbl) Specific Exclusions 

Spill 

Volumes 

≥50 barrels 

(bbls) 

50 to <100; 

100 to <1,000 

1,000 to <10,000; 

≥10,000 

NA 

Fluids Petroleum Crude oil, 

condensate, refined 

petroleum 

Synthetic/vegetable oilbased drilling fluids 

Facilities Offshore O&G 

exploration, 

development, and 

production 

Pipelines, 

platforms 

Workboats 

Geography US OCS GOM and 

PAC 

State waters 

4 
The analysis is limited to spill volumes greater than or equal to 50 bbls. Spills of this size have 

been consistently reported and documented throughout the historical period of data collected. 

The results from this analysis are intended to support oil-spill occurrence estimates associated 

with offshore exploration or development and production plans for individual facilities. To make 

the output relevant, oil-spill occurrence frequencies are considered relative to exposure metrics 

for pipelines and platforms. Other entities, such as dive support vessels, geological survey 

vessels, workboats, and supply boats are not permanent facilities and so are not considered a 

persistent risk in the same way as platforms (including drilling platforms) and pipelines. 

Finally, the analysis is confined to spills occurring on the US OCS for two reasons. First, OCS 

spill rates are relevant for estimating future oil-spill occurrence frequencies on the US OCS. 

Second, the US Government has long maintained consistent data describing these kinds of 

incidents as well as exposure. 

1.2 Causal Factors 

BOEM’s most recent oil spill analysis study estimates statistics for spill occurrence for a broad 

scope of spill volumes as well as additional facility types (ABSG Consulting Inc., 2016). This 

report narrows the focus to petroleum spills of 50 bbls or more, which typically have more 

documentation, allowing for more detailed review of the causes of oil spills. This additional 

information enables the users to break down the overall spill frequency into component 

estimates, split by causal factor category. These component estimates will then directly support 

the fault tree analysis for developing Arctic-specific spill frequencies, extrapolating spill 

information from GOM and PAC experience. 

1.3 Data Sources 

This report estimates spill occurrence frequencies based on historical incident data from 1972 to 

2017. Spill frequencies decreased substantially after 1973 (ABSG Consulting Inc., 2016), 

making prior years less relevant for calculating future expected occurrence. The frequencies are 

calculated as counts of incidents divided by metrics for spill exposure. 

ABSG collated spill data from the following sources to develop incident counts: 

 Historical incident tables (1972 to 2010) provided in a prior BOEM report by Bercha 

(Bercha International Inc., 2013) 

 Data collected by ABSG (1964 to 2015) for prior spill study for BOEM and Bureau of 

Safety and Environmental Enforcement (BSEE) (ABSG Consulting Inc., 2016) 

 Spill-related documents (2010 to 2017) provided by BOEM (Crowley, 2017) 

 Spill tables (1972 to 2012) provided by BOEM (BSEE, 2013) 

The ABSG spill study (ABSG Consulting Inc., 2016), conducted for BOEM/BSEE, screened 

thousands of spills from various sources including multiple spill tables compiled by BSEE from 

Anderson, Mayes, and LaBelle (2012) and many others cited in that report. In addition, data 

extracted from the BOEM/BSEE Technical Information Management System (TIMS) database, 

public Pipeline and Hazardous Material Safety Administration (PHMSA) pipeline spill data, 

5 
 

public USCG National Response Center (NRC) data, and US Coast Guard (USCG) data from the 

Marine Information for Safety and Law Enforcement (MISLE) database were used (ABSG 

Consulting Inc., 2016). 

For exposure, ABSG queried data found on the BSEE website: 

 O&G Operations Reports (BSEE, 2017a; BSEE, 2017b) 

 Pipeline Masters (BSEE, 2017c; BSEE, 2017d) 

Appendices A and C describe the methodology used to query these sources, respectively, to 

develop the data used in this report’s analysis. 

6 
 

2 OCS Platform Spills 

In this report, platform spills include petroleum spills of 50 bbls or more occurring from rig and 

platform facilities performing exploration and development operations, including production, on 

the GOM and PAC OCS. From 1972 to 2017, ABSG has identified 149 spills of crude oil, 

condensate, or refined petroleum, equal to or greater than 50 bbls. 

2.1 OCS Platform Exposure 

Platforms can take many shapes, ranging from a simple caisson platform in shallow water to a 

deep water tension-leg facility with dozens of well bays and permanent drilling equipment. The 

variation in size for platforms makes a simple count of platforms a poor exposure variable for 

estimating future spill occurrence in the US Arctic OCS. 

Instead, this analysis uses counts of active well-years (the mean number of wells that are active 

for each year of the analysis). This metric fairly accommodates the variety of OCS platform 

types by assuming that large facilities with potentially higher chances of spill will have large 

numbers of wells while a small platform may have only one. Furthermore, it is consistent with 

prior works upon which this analysis is based. 

A well is deemed active if it has produced crude or condensate within a given year. Publicly 

available data does not include well production information back to 1972. To estimate exposure 

over the entire period, this report combines the historical estimates for active well counts through 

2010 (Bercha International Inc., 2013) with estimates based on the publicly available data for the 

remaining period (2011 to 2017) (BSEE, 2017a; BSEE, 2017b). Table 2 summarizes these 

results. Appendix A provides a summary of the logic used to compile the publicly available data. 

7 
Table 2. Annual count of active wells in GOM and PAC OCS (1972 to 2017) 

Year GOM PAC Total 

1972 to 2017 258,054 16,714 274,768 

1972 4,278 191 4,469 

1973 4,512 187 4,699 

1974 4,546 182 4,728 

1975 4,604 179 4,783 

1976 4,763 179 4,942 

1977 4,981 195 5,176 

1978 5,228 204 5,432 

1979 5,510 208 5,718 

1980 5,715 225 5,940 

1981 5,969 277 6,246 

1982 6,326 317 6,643 

1983 6,459 349 6,808 

1984 6,724 367 7,091 

1985 6,988 378 7,366 

1986 6,934 385 7,319 

1987 6,902 408 7,310 

1988 6,904 396 7,300 

1989 6,900 406 7,306 

1990 6,927 406 7,333 

1991 6,932 437 7,369 

1992 6,789 427 7,216 

1993 6,725 434 7,159 

1994 6,721 447 7,168 

1995 6,615 445 7,060 

1996 6,681 457 7,138 

1997 6,636 470 7,106 

1998 6,442 459 6,901 

1999 6,313 433 6,746 

2000 6,288 403 6,691 

2001 6,409 407 6,816 

2002 6,174 414 6,588 

2003 6,004 412 6,416 

2004 5,926 412 6,338 

2005 5,536 411 5,947 

2006 4,824 401 5,225 

2007 5,251 408 5,659 

2008 5,074 419 5,493 

2009 4,520 417 4,937 

2010 4,490 414 4,904 

2011 4,350 418 4,768 

2012 4,093 432 4,525 

2013 3,905 428 4,333 

2014 3,810 430 4,240 

2015 3,659 438 4,097 

2016 3,459 305 3,764 

2017 3,258 297 3,555 

8 
 

2.2 Platform Spills 

This report considers 149 platform spill events that were determined to be within the scope of the 

project. Table 15 in Appendix B summarizes these spills. It focuses on features of the context of 

the incident, including causal factors. The “Primary Cause of Incident” column includes the 

original cause identified in the data. The table expands on the spill list developed in the most 

recent update of this analysis (Bercha International Inc., 2013). 

After a thorough, line-by-line review of the prior list and other available data, several updates 

were made: 

 Bercha spill number 69 from (from Table 3.2 of Bercha International Inc., 2013) was 

removed because it was associated with a maritime vessel rather than a platform or rig. 

 Spill numbers 147 and 148 were added from data provided by BOEM for the years 2010 

to 2017 (BSEE, 2013; Crowley, 2017). 

 Spills numbers 55, 64, 68, 69, 73, 111, 118, 119, 120, 142, 143, and 149 were added after 

collating the existing data with previous ABSG results (ABSG Consulting Inc., 2016) 

Figure 1 provides a visual summary of the platform spills. The Deepwater Horizon spill 

(included in the “Unknown” category) is not shown proportionally to the other spills. 

Figure 1. Platform spills ≥ 50 bbl of petroleum 

9 
 

Table 3 and Table 4 summarize counts of spills by spill size, by causal factor, and by both factors 

simultaneously, respectively. 

Table 3. Platform spill size distribution summary 

Size (bbls) Spill Count 

Small 50 to <100 62 

Medium 100 to <1,000 79 

Large 1,000 to <10,000 7 

Huge ≥10,000 1 

Total 149 

Table 4. Platform spill summary by spill size (1972 to 2017) 

Cause 

Classification 

Detailed Size Category 

(bbls) 

Summary 

Categories 

(bbls) 

Total 

SmallMediumLargeHuge50 to <1,000≥1,000 

Equipment Failure 25 18 1 0 43 1 44 

Human Error 6 10 0 0 16 0 16 

Collision 0 1 0 0 1 0 1 

Weather 1 4 2 0 5 2 7 

Hurricane 29 40 4 0 69 4 73 

Unknown 1 6 0 1 7 1 8 

TOTAL 62 79 7 1 141 8 149 

10 
 

 

 

 

 

2.3 OCS Platform Spill Statistics 

Combining the spill count results with well-year exposure, 

Table 5 presents spill frequency estimates for platform spills. Hurricanes are the biggest causal 

factor. Next, equipment failure accounts for many small and medium spills. And, then, weather 

(other than hurricanes) is the next most common causal factor of large and huge spills. 

The Deepwater Horizon spill is shown in Table 6 below as the one spill larger than 1,000 barrels 

and is included as an “Unknown” cause. This category has been selected to allow individual 

analysis of this important spill. The environmental and safety impact of this one spill drastically 

outweighs the other spills shown, despite its relatively low occurrence rate (0.04 spills per 

10,000 well years). The investigation conducted by DOI identified critical equipment failure and 

human error factors that contributed to the spill (DOI, 2011). 

Table 5. GOM and PAC OCS platform hydrocarbon spill statistics (1972 to 2017) 

Cause 

Classification 

50 to 999 bbl ≥ 1,000 bbl 

Historical 

Distribution 

% 

Number 

of Spills 

Exposure 

(wellyears) 

Frequency 

(spill per 

104 wellyears) 

Historical 

Distribution 

% 

Number 

of Spills 

Exposure 

(wellyears) 

Frequency 

(spill per 

104 wellyears) 

Equipment 

Failure 30.5 43 

274,768 

1.56 12.5 1 

274,768 

0.04 

Human 

Error 

11.3 16 0.58 0.0 0 0.00 

Collision 0.7 1 0.04 0.0 0 0.00 

Weather 3.5 5 0.18 25.0 2 0.07 

Hurricane 48.9 69 2.51 50.0 4 0.15 

Unknown 5.0% 7 0.25 12.5% 1 0.04 

Total 100.0% 141 5.13 100.0% 8 0.29 

2.4 Loss of Well Control Spills 

Many spills have a maximum plausible spill size based on quantities of petroleum stored or 

processed at a facility. Loss of well control (LOWC) spills are of particular interest because a 

freely flowing well has the potential for much higher spill volumes. Table 6 summarizes the 

subset of spills in the data for which a LOWC was reported. 

Table 6. LOWC Spill Summary 

Size (bbls) Spill Count Exposure 

(well-years) 

Frequency 

(spill per 104 

well-years) 

Small 50 to <100 5 0.18 

Medium 100 to <1,000 6 0.22 

Large 1,000 to <10,000 0 274,768 0.00 

Huge ≥10,000 1 0.04 

Total 12 0.44 

11 
 

3 OCS Pipeline Spills 

O&G operations in the GOM and PAC OCS often rely on pipelines to transfer oil and gas to 

market onshore. In 2017, there were over 9,000 miles of active oil pipeline in the GOM OCS 

waters. These pipelines are the source of 70 spills since 1972 identified as greater than 50 

barrels. External factors such as hurricanes and third-party vessels operating in the domain are 

particularly important threats to pipeline integrity. 

The pipeline facility category encompasses many pipeline types ranging from smaller subsea 

well riser segments to large-diameter transport pipelines. In addition, pipelines can carry a 

variety of fluids. This analysis considers only pipelines carrying crude, condensate, or refined 

petroleum. Pipelines for refined petroleum, such as diesel fuel, appeared very rarely. 

3.1 OCS Pipeline Exposure 

The frequency of pipeline spills is a function of a variety of factors including the pipeline’s water 

depth, diameter, and distance from shore. These features affect the likelihood of a spill as well as 

the probable spill volume. 

This report uses pipeline mile-years (the mean of the total length of pipeline in use for each year) 

as the exposure metric for pipelines, which is consistent with prior analyses (ABSG Consulting 

Inc., 2016; Bercha International Inc., 2013). This exposure metric is justified because of the 

pipeline hazards that are typical in the OCS. Many common causes for pipeline spills are 

external forces, such as third-party vessels, anchor drags, and trawl nets. For these types of 

causal factors, a long pipeline suggests a greater chance of accidental contact and spill. 

The pipeline spill frequency estimates in this report distinguish spills from different pipeline 

diameters. To support this calculation, Table 17 in Appendix C presents annual exposure 

estimates for an array of nominal pipeline size (NPS) categories. 

12 
3.2 OCS Pipeline Spills 

The 70 pipeline spills in this report are consolidated from the data sources described in Section 

1.3 (after filtering them based on the established scope). This section summarizes features of the 

context of the incident, including causal factors. Table 17 in Appendix D lists all of the pipeline 

spills. 

This table expands on the spill list developed in the most recent study (Bercha International Inc., 

2013). After a thorough line-by-line review of the prior list and other available data, several 

updates were made: 

 Bercha spill numbers 31,34, 38, and 47 (from Table 2.2 of the Bercha International Inc., 

2013 report) were removed since they were chemical rather than petroleum spills 

 Spill numbers 25, 35, 56, 66, 67, and 68 were added after collating the existing data with 

ABS Consulting results (ABSG Consulting Inc., 2016) 

 Spill numbers 69 and 70 were added based on spills recently reported on by public news 

outlets (Knodel, 2016; Grant, 2017) 

Figure 2 summarizes these spills in a timeline format, emphasizing the spill cause and spill size. 

Importantly, this visual does not adjust for exposure differences year to year. However, it does 

seem to reveal an interesting trend: most spills since the turn of the century have been hurricanerelated spills. In addition, spill sizes appear to be getting smaller. Adjusting for exposure, the 

data reveal a very weak statistical trend over this period for spills ≥50 bbls but a strong trend 

when looking at the total number of reported pipeline spills (including very small spills) (ABSG 

Consulting Inc., 2016). 

Removing hurricane-related spills further emphasizes this trend, suggesting that the operationsrelated spill rate has been decreasing. For the purposes of this report, this finding suggests that 

our estimated rates, calculated using data since 1972, may be substantially conservative. 

Figure 2. Pipeline Spills ≥ 50 bbl of petroleum 

13 
 

 

                       

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7 and Table 8 provide basic summaries of spill counts by pipeline diameter measured in 

NPS and by causal factor categories. 

Table 7. Count of pipeline spills by NPS categories (1972 to 2017) 

Category Spill Size 

(bbl) All NPS NPS ≤10 NPS >10 Unknown. NPS 

Small 50-99 16 12 4 0 

Medium 100-999 35 21 11 3 

Large 1,000-9,999 15 7 7 1 

Huge ≥10,000 4 1 2 1 

Total 70 41 24 5 

Table 8. Count of pipeline spills by causal factors (1972 to 2017)

Cause Classification 

Detailed Size Category 

(bbls) 

Summary 

Categories 

(bbls) 

Total 

SmallMediumLargeHuge50 to <1,000≥1,000 

Corrosion 1 2 1 0 3 1 4 

 External 1 0 0 0 1 0 1 

 Internal 0 2 1 0 2 1 3 

Third-Party Impact 2 8 7 3 10 10 20

 Anchor Impact 2 5 3 2 7 5 12

 Jackup Rig or Spud Barge 0 2 1 0 2 1 3 

 Trawl/Fishing Net 0 1 3 1 1 4 5 

Operation Impact 3 0 1 0 3 1 4 

 Rig Anchoring 1 0 0 0 1 0 1 

 Workboat Anchoring 2 0 1 0 2 1 3 

Mechanical 0 3 0 0 3 0 3 

 Connection Failure 0 2 0 0 2 0 2 

 Material Failure 0 1 0 0 1 0 1 

Natural Hazard 9 15 4 0 24 4 28

 Mud Slide 1 1 1 0 2 1 3 

 Hurricane 8 14 3 0 22 3 25 

Unknown 1 7 2 1 8 3 11 

Total 16 35 15 4 51 19 70 

14 
 

 

 

 

 

 

 

 

 

 

 

 

 

3.3 Pipeline Spill Statistics 

The estimates of spill frequency presented in this section provide frequencies broken down by 

cause classification category to support future fault tree rates assumptions of specific spill rate 

causal factors or pipeline diameters, or spill size. Table 9 and Table 10 summarize these 

estimates. 

Table 9. GOM and PAC pipeline hydrocarbon spill statistics by cause (1972 to 2017) 

Cause Classification 

50 to <1,000 ≥1000 

Historical 

Distribution 

% 

Number 

of Spills 

Exposure 

(km-year) 

Frequency 

Spills per 

105

 kmyear 

Historical 

Distribution 

% 

Number 

of Spills 

Exposure 

(kmyears) 

Frequency 

Spill Per 

105

 kmyear 

Corrosion 5.9% 3 

444,901 

0.674 5.3% 1 

444,901 

0.225

 External 2.0% 1 0.225 0.0% 0 0.000

 Internal 3.9% 2 0.450 5.3% 1 0.225 

Third-Party Impact 19.6% 10 2.248 52.6% 10 2.248

 Anchor Impact 13.7% 7 1.573 26.3% 5 1.124

 Jackup Rig 

 or Spud Barge 

3.9% 2 0.450 5.3% 1 0.225

 Trawl/Fishing Net 2.0% 1 0.225 21.1% 4 0.899 

Operation Impact 5.9% 3 0.674 5.3% 1 0.225

 Rig Anchoring 2.0% 1 0.225 0.0% 0 0.000 

Workboat Anchoring 3.9% 2 0.450 5.3% 1 0.225 

Mechanical 5.9% 3 0.674 0.0% 0 0.000

 Connection Failure 3.9% 2 0.450 0.0% 0 0.000

 Material Failure 2.0% 1 0.225 0.0% 0 0.000 

Natural Hazard 47.1% 24 5.394 21.1% 4 0.899

 Mud Slide 3.9% 2 0.450 5.3% 1 0.225

 Hurricane 43.1% 22 4.945 15.8% 3 0.674 

Unknown 15.7% 8 1.798 15.8% 3 0.674 

Total 100.0% 51 11.463 100.0% 19 4.271 

The two largest causal categories are natural hazards and third-party impacts; these two 

categories combined make up about two thirds of the known causal factors shown, suggesting 

that the pipeline technology is not typically at fault. 

15 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10. GOM and PAC pipeline hydrocarbon spill statistics by spill size and pipeline diameter 

(1972 to 2017) 

GOM and PAC Pipeline Spills, 

Categorized 1972 to 2017 Number 

of Spills 

Exposure (kmyears) 

Frequency 

(spills per 

105 kmyears) 

By Pipe Diameter ≤10" 41 292,206 14.031 

>10" 24 152,695 15.718 

Unk. 5 444,901 1.124 

By Spill Size Small 16 444,901 3.596 

Medium 35 444,901 7.867 

Large 15 444,901 3.372 

Huge 4 444,901 0.899 

By Pipe 

Diameter, 

By Spill 

Size 

≤10" Small 12 292,206 4.107 

Medium 21 292,206 7.187 

Large 7 292,206 2.396 

Huge 1 292,206 0.342 

>10" Small 4 152,695 2.620 

Medium 11 152,695 7.204 

Large 7 152,695 4.584 

Huge 2 152,695 1.310 

Unk. Small 0 444,901 0.000 

Medium 3 444,901 0.674 

Large 1 444,901 0.225 

Huge 1 444,901 0.225 

Pipeline size appears to have a slight correlation with spill frequency. Overall, larger pipelines 

have a slightly higher spill frequency. Furthermore, larger pipelines have higher spill rates in the 

medium, large, and huge spill size categories while smaller pipelines have the higher rate in the 

small spills category. 

16 
4 Confidence Intervals 

To estimate confidence intervals, ABSG assumes that spill occurrences are a Poisson process. 

The Poisson distribution models the number of events to take place in a specified time interval 

when the events occur independently of each other and at a given rate. This is the ideal 

distribution for modeling independent spill events. 

The Poisson process is defined by the parameter λ. When estimating λ using historical data, it 

can be assumed without loss of generality that the historically observed events all occur in a 

single time interval. In this simple case, the best estimate of λ is equal to the number of events 

observed, x. Confidence intervals for λ can then be computed using a variety of statistical 

estimates. Two of these estimates were used to calculate the 90% confidence intervals used in 

this report, based on recommendations found in Comparison of Confidence Intervals for the 

Poisson Mean (Patil & Kulkarni, 2012): 

Equation 1 

૛ ૛

ቆ

ሻ૙૞.૙,࢞૛ሺ࣑

൘

૛ ,

࣑ሺ૛ሺ࢞ା૚ሻ,૙.ૢ૞ሻ

൘

૛ቇ

Equation 2 

൬ሺ࢞ െ ૙. ૞ሻ ൅ ࢆ૙.૞૙ඥሺ࢞ െ ૙. ૞ሻ, ሺ࢞૙ ൅ .૞ ሻ ൅ ࢆ૙.૞૙ඥሺ࢞૙ ൅ .૞ ሻ൰

Equation 1 is an ideal estimate when x equals 4 or more, and Equation 2 is ideal when x equals 2 

or less. Equation 1 was used in the x equals 3 case. When x equals 0, the lower bound of the 

interval in Equation 2 cannot be evaluated. Of course, the lower bound should be 0 in this case. 

After computing the confidence interval for λ, the results were then converted to spill rate 

confidence intervals by dividing by the exposure. 

These results include a minor caveat related to the effect of hurricanes. Hurricanes tend to cause 

multiple oil spills at once as multiple platforms or pipelines are damaged simultaneously, which 

violates an assumption of the Poisson distribution that spill occurrences are independent events. 

A more thorough analysis of the covariance of hurricane spills is beyond the scope of this 

analysis. In addition, the number of spill occurrences during a hurricane can be hard to estimate. 

Multiplicative spill reports and unreported spills are can be difficult to track following a 

devastating storm. As such, hurricane spill rates and their confidence intervals may not account 

for some data uncertainty, though they have been painstakingly analyzed. 

Table 11, Table 12, Table 13, and Table 14 summarize the confidence intervals for all of the spill 

rates presented in the report. 

17 
 

Table 11. Confidence intervals for GOM and PAC OCS platform hydrocarbon spill statistics 

(1972 to 2017) 

Cause 

Classification 

50 to <1,000 bbls ≥1,000 bbls 

Frequency 

(spills per 

104 wellyear) 

Lower Upper 

Frequency 

(spills per 

104 wellyear) 

Lower Upper 

Equipment Failure 1.56 1.3 2.28 0.04 0 0.12 

Human Error 0.58 0.41 1.02 0 0 0.04 

Collision 0.04 0 0.12 0 0 0.04 

Weather 0.18 0.04 0.45 0.07 0 0.2 

Hurricane 2.51 2.24 3.46 0.15 0.04 0.41 

Unknown 0.25 0.12 0.57 0.04 0 0.12 

Total 5.13 4.97 6.64 0.29 0.12 0.61 

Table 12. LOWC Spill Summary 

Size (bbls) 

Frequency 

(spills per 104 

well-year) 

Lower Upper 

Small 50 to <100 0.18 0.04 0.40 

Medium 100 to <1,000 0.22 0.07 0.44 

Large 1,000 to <10,000 0.00 0.00 0.04 

Huge ≥10,000 0.04 0.00 0.20 

Total 0.44 0.22 0.73 

18 
 

Table 13. Confidence intervals for GOM and PAC pipeline hydrocarbon spill statistics by cause 

(1972 to 2017) 

Cause Classification 

50 to <1,000 bbls ≥1,000 bbls 

Frequency 

(spills per 

105

 kmyear) 

Lower Upper 

Frequency 

(spills per 

105 kmyear) 

Lower Upper 

Corrosion 0.67 0.00 1.80 0.23 0.00 0.68

 External 0.23 0.00 0.68 0.00 0.00 0.23

 Internal 0.45 0.00 1.13 0.23 0.00 0.68 

Third-Party Impact 2.25 1.12 3.82 2.25 1.12 3.82

 Anchor Impact 1.57 0.67 3.15 1.12 0.22 2.47

 Jackup Rig or Spud Barge 0.45 0.00 1.13 0.23 0.00 0.68

 Trawl/Fishing Net 0.23 0.00 0.68 0.90 0.22 2.25 

Operation Impact 0.67 0.00 1.80 0.23 0.00 0.68

 Rig Anchoring 0.23 0.00 0.68 0.00 0.00 0.23

 Work Boat Anchoring 0.45 0.00 1.58 0.23 0.00 0.68 

Mechanical 0.67 0.00 1.80 0.00 0.00 0.23

 Connection Failure 0.45 0.00 1.13 0.00 0.00 0.23

 Material Failure 0.23 0.00 0.68 0.00 0.00 0.23 

Natural Hazard 5.39 3.60 7.64 0.90 0.22 2.25

 Mud Slide 0.45 0.00 1.13 0.23 0.00 0.68

 Storm/ Hurricane 4.95 3.15 7.19 0.67 0.00 1.80 

Unknown 1.80 0.67 3.37 0.67 0.00 1.80 

Total 11.46 8.77 14.61 4.27 2.70 6.29 

19 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 14. Confidence intervals for GOM and PAC pipeline hydrocarbon spill statistics by spill size 

and pipeline diameter (1972 to 2017) 

Frequency 

(spills per 105 

km-year) 

Lower Upper 

By Pipe Diameter ≤10" 14.03 10.61 18.48 

>10" 15.72 10.48 22.27 

Unknown 1.12 0.22 2.47 

By Spill Size Small 3.60 2.25 5.62 

Medium 7.87 5.62 10.56 

Large 3.37 2.02 5.39 

Huge 0.90 0.22 2.25 

By Pipe 

Diameter, 

By Spill 

Size 

≤ 10" Small 4.11 2.05 6.84 

Medium 7.19 4.79 10.61 

Large 2.40 1.03 4.79 

Huge 0.34 0.00 1.03 

> 10" Small 2.62 0.65 6.55 

Medium 7.20 3.93 12.44 

Large 4.58 1.96 9.17 

Huge 1.31 0.00 3.27 

Unk. Small 0.00 0.00 0.22 

Medium 0.67 0.00 1.80 

Large 0.22 0.00 0.67 

Huge 0.22 0.00 0.67 

20 
 

 

 

 

 

 

 

5 References 

ABSG Consulting Inc. (2016). 2016 Update of Occurrence Rates for Offshore Oil Spills. 

Arlington, VA: Prepared by ABS Consulting Inc. for USDOI, BOEM/BSEE. 95 pp. 

Anderson, C. M., Mayes, M., & LaBelle, R.P. (2012). Update of Occurrence Rates for Offshore 

Oil Spills. Bureau of Ocean Energy Management OCS Report 2012-069. Herndon, VA: Bureau 

of Ocean Energy Management. 

Bercha Group Inc. (2013). Updates to Fault Tree for Oil Spill Occurrence Estimators, Update of 

GOM and PAC OCS Statistics to 2012. OCS Study BOEM 2013-0116. Anchorage, Alaska. 

Prepared by Bercha International Inc. for USDOI, BOEM, Alaska OCS Region. 35 pp. 

BSEE. (2013). Spill 50 bbl 1964-2012 for Web. BSEE. Available from 

https://www.bsee.gov/sites/bsee.gov/files/reports/incident-and-investigations/spills-greater-than50-barrels1964-2012-as-of-august-3-2012.pdf 

BSEE. (2017a). Oil & Gas Operations Reports (GOM). BSEE. Retrieved December 26, 2017, 

from https://www.data.bsee.gov/Main/OGOR-A.aspx 

BSEE. (2017b). Oil & Gas Operations Reports (PAC). BSEE. Retrieved December 26, 2017, 

from https://www.data.bsee.gov/Main/PacificProduction.aspx 

BSEE. (2017c). Pipeline Masters (GOM). BSEE. Retrieved December 26, 2017, from 

https://www.data.bsee.gov/Pipeline/Files/pplmastdelimit.zip 

BSEE. (2017d). Pipeline Masters (PAC). BSEE. Retrieved December 26, 2017, from 

https://www.data.bsee.gov/Pipeline/Files/pplmastpacdelimit.zip 

Crowley, H. (2017, November 22). M17PD00066 -- Transfer of Information from BOEM. 

BOEM. (Electronic Correspondence. See Appendix E). 

DOI. (2011). Report Regarding the Causes of the April 20, 2010 Macondo Well Blowout. 

Retrieved January 10, 2018, from https://www.bsee.gov/sites/bsee.gov/files/reports/blowoutprevention/dwhfinaldoi-volumeii.pdf . pp 212. 

Grant, N. (2017, October 16). Gulf Coast Oil Spill May Be Largest Since 2010 BP Disaster. 

Bloomberg. Retrieved March 1, 2018, from https://www.bloomberg.com/news/articles/2017-10-

16/gulf-of-mexico-oil-spill-may-be-largest-since-2010-bp-disaster 

Knodel, M. (2016). Coast Guard, Shell wrap up skimming of Gulf of Mexico oil spill. Offshore 

Energy Today. Retrieved March 6, 2018, from https://www.offshoreenergytoday.com/coastguard-shell-wrap-up-skimming-of-gulf-of-mexico-oil-spill/ 

V. V. Patil, H. V. Kulkarni. (2012). Comparison of Confidence Intervals for the Poisson Mean: 

Some New Aspects. REVSTAT. Retrieved from https://www.ine.pt/revstat/pdf/rs120203.pdf . pp 

17. 

21 
 

 

Appendix A: OCS Platform Exposure 

The platform exposure metric is the number of active wells each year. The approach was 

determined to replicate the metric used in prior analyses (Bercha International Inc., 2013). It was 

calculated using data that is publicly available on BSEE’s website (BSEE, 2017a). 

The metric estimates the number of active wells as the number of unique American Petroleum 

Institute (API) well ID numbers associated with non-zero oil production volumes. The pseudoSQL code below documents this logic. The output variable “Well_Count” is the exposure metric. 

This logic is for the GOM region. Similar data and logic were used for the PAC region. 

Select Year, Count(*) AS Well_Count 

From 

(Select * 

From 

(Select *, 2017 as YEAR From ogora2017 UNION ALL 

Select *, 2016 as YEAR From ogora2016 UNION ALL 

Etc...) 

Where MON_O_PROD_VOL <> 0 

Group by Year, API_WELL_NUMBER) 

Group by Year 

22 
Appendix B: OCS Platform Spills 

Table 15. GOM and PAC OCS Platform Spills ≥ 50 bbls (1972 to 2017)

Spill # 

* 

Bercha 

Spill # Year Water Depth (ft) Primary Cause of Incident ** Operation LOWC Spill Total (bbl) Crude & Cond. (bbl) Ref

1 1 1973 110 Equipment Failure Production 9935 9935 

2 2 1973 61 Weather Production/Barge 7000 7000 

3 3 1973 300 Weather Drilling/Vessel 239 0 

4 4 1973 103 Human Error Drilling/Vessel 95 0 

5 5 1974 60 Equipment Failure Production 130 130 

6 6 1974 29 Hurricane Hurricane YES 75 75 

7 7 1974 27 Equipment Failure Production 50 50 

8 8 1974 140 Human Error Production 120 120 

9 9 1974 30 Hurricane Hurricane - Repair YES 200 200 

10 10 1975 200 Weather Drilling/Vessel 100 0 

11 11 1976 127 Equipment Failure Drilling/Vessel 300 0 

12 12 1977 55 Equipment Failure Drilling/Vessel 77 0 

13 13 1978 105 Equipment Failure Production 104 104 

14 14 1979 311 Equipment Failure Drilling/Vessel 321 0 15 15 1979 210 Equipment Failure Production 60 60 

16 16 1979 280 Weather Drilling/Vessel 1500 0 

17 17 1980 156 Human Error Drilling 286 0 18 18 1980 140 Equipment Failure Drilling 95 0 

19 19 1980 220 Weather Drilling/Vessel 80 0 

20 20 1980 187 Equipment Failure Production 83 0 

21 21 1980 60 Hurricane Hurricane 1456 1456 

22 22 1980 99 Equipment Failure Drilling/Vessel 118 0 

23 23 1981 54 Human Error Production 58 58 

24 24 1981 49 Equipment Failure Drilling 210 0 

25 25 1981 350 Equipment Failure Drilling/Vessel 50 0 26 26 1981 340 Equipment Failure Completion/Workover YES 64 64 

23 
Spill # 

* 

Bercha 

Spill # Year Water Depth (ft) Primary Cause of Incident ** Operation LOWC Spill Total (bbl) Crude & Cond. (bbl) Ref

27 27 1982 180 Human Error Drilling/Vessel 400 0 

28 28 1982 394 Equipment Failure Drilling/Vessel 228 0 

29 29 1982 60 Weather Drilling/Vessel 214 0 

30 30 1983 43 Equipment Failure Drilling/Barge 600 0 

31 31 1983 48 Equipment Failure Drilling/Vessel 77 0 

32 32 1983 50 Equipment Failure Drilling/Vessel 320 0 

33 33 1983 65 Equipment Failure Drilling/Vessel 200 0 

34 34 1983 48 Equipment Failure Drilling/Vessel 77 0 

35 35 1983 105 Collision Production/Vessel 119 0 

36 36 1984 94 Equipment Failure Production 50 50 

37 37 1984 307 Human Error Drilling/Vessel 100 0 

38 38 1985 130 Equipment Failure Drilling/Fuel Transfer 107 0 

39 39 1985 50 Human Error Deactivation 60 0 

40 40 1985 196 Equipment Failure Production/Workover YES 50 50 41 41 1985 3115 Equipment Failure Drilling/Vessel 643 0 

42 42 1985 200 Equipment Failure Drilling 50 0 

43 43 1985 55 Hurricane Hurricane 66 66 

44 44 1985 103 Equipment Failure Drilling/Vessel 58 0 

45 45 1986 750 Equipment Failure Construction 52 0 

46 46 1987 126 Equipment Failure Drilling YES 60 60 

47 47 1988 172 Equipment Failure Production 50 50 

48 48 1988 200 Human Error Drilling 64 0 

49 49 1988 140 Equipment Failure Production 55 55 

50 50 1989 112 Equipment Failure Production 400 400 

51 51 1989 206 Equipment Failure Production 55 55 

52 52 1990 290 Human Error Drilling 100 0 53 53 1991 50 Equipment Failure Production 280 280 

54 54 1992 187 Human Error Drilling YES 100 100 

55 - 1993 8 Equipment Failure Unknown YES 250 250 

24 
Spill # 

* 

Bercha 

Spill # Year Water Depth (ft) Primary Cause of Incident ** Operation LOWC Spill Total (bbl) Crude & Cond. (bbl) Ref

56 55 1994 150 Equipment Failure Production 50 50 

57 56 1995 50 Human Error Drilling/Vessel 600 600 

58 57 1995 116 Equipment Failure Production 75 75 

59 58 1995 56 Equipment Failure Production 435 435 

60 59 1996 705 Equipment Failure Construction 62 0 

61 60 1997 40 Human Error Production 170 170 

62 61 1998 700 Weather Production 100 0 

63 62 1999 463 Equipment Failure Workover YES 125 125 

64 - 1999 150 Human error Unknown 83 0 

65 63 2000 2223 Human Error Drilling YES 200 200 

66 64 2000 172 Human Error Production 60 60 

67 65 2001 243 Equipment Failure Production 127 127 

68 - 2001 Unk. Unknown Unknown 225 225 

69 - 2001 Unk. Unknown Unknown 100 100 

70 66 2002 50 Hurricane Hurricane YES 350 350 

71 67 2002 37 Hurricane Hurricane 497 0 

72 68 2002 94 Hurricane Hurricane 741 0 

73 - 2002 Unk. Human Error Completion/Workover 230 0 

74 70 2004 277 Hurricane Hurricane 52 0 

75 71 2004 302 Hurricane Hurricane 55 0 76 72 2004 305 Hurricane Hurricane 264 133 

77 73 2004 244 Hurricane Hurricane 106 77 

78 74 2004 255 Hurricane Hurricane 66 27 

79 75 2004 479 Hurricane Hurricane 510 410 

80 76 2005 86 Hurricane Hurricane 141 141 

81 77 2005 83 Hurricane Hurricane 242 242 

82 78 2005 91 Hurricane Hurricane 204 204 

83 79 2005 88 Hurricane Hurricane 195 195 

84 80 2005 1023 Hurricane Hurricane 325 325 

25 
Spill # 

* 

Bercha 

Spill # Year Water Depth (ft) Primary Cause of Incident ** Operation LOWC Spill Total (bbl) Crude & Cond. (bbl) Ref

85 81 2005 140 Hurricane Hurricane 380 0 

86 82 2005 255 Hurricane Hurricane 130 106 

87 83 2005 322 Hurricane Hurricane 110 85 88 84 2005 340 Hurricane Hurricane 195 180 

89 85 2005 153 Hurricane Hurricane 307 307 

90 86 2005 223 Hurricane Hurricane 71 50 

91 87 2005 228 Hurricane Hurricane 159 130 

92 88 2005 285 Hurricane Hurricane 94 75 

93 89 2005 116 Hurricane Hurricane 51 48 

94 90 2005 137 Hurricane Hurricane 101 48 

95 91 2005 128 Hurricane Hurricane 51 48 

96 92 2005 137 Hurricane Hurricane 50 48 

97 93 2005 117 Hurricane Hurricane 51 50 

98 94 2005 140 Hurricane Hurricane 97 95 

99 95 2005 2107 Hurricane Hurricane 614 536 

100 96 2005 182 Hurricane Hurricane 1572 0 

101 97 2005 204 Hurricane Hurricane 77 44 

102 98 2005 230 Hurricane Hurricane 2000 2000 103 99 2005 254 Hurricane Hurricane 181 150 104 100 2005 231 Hurricane Hurricane 188 150 

105 101 2005 472 Hurricane Hurricane 101 101 

106 102 2005 238 Hurricane Hurricane 1494 0 

107 103 2005 182 Hurricane Hurricane 67 0 

108 104 2005 230 Hurricane Hurricane 659 582 

109 105 2005 230 Hurricane Hurricane 166 166 

110 106 2005 230 Hurricane Hurricane 53 53 

111 - 2005 Unk. Hurricane Completion/Workover 119 119 

112 107 2006 230 Hurricane Hurricane 51 51 

113 108 2006 240 Hurricane Hurricane 63 63 

26 
Spill # 

* 

Bercha 

Spill # Year Water Depth (ft) Primary Cause of Incident ** Operation LOWC Spill Total (bbl) Crude & Cond. (bbl) Ref

114 109 2006 240 Hurricane Hurricane 528 528 

115 110 2006 88 Hurricane Hurricane 59 59 

116 111 2006 240 Hurricane Hurricane 133 133 

117 112 2006 230 Hurricane Hurricane 51 51 

118 - 2006 240 Hurricane Hurricane 120 120 

119 - 2007 Unk. Unknown Unknown 71 71 120 - 2007 Unk. Equipment Failure Unknown 70 0 

121 113 2008 88 Hurricane Decommissioning 54 54 122 114 2008 187 Hurricane Hurricane 685 685 

123 115 2008 210 Hurricane Hurricane 103 20 

124 116 2008 262 Hurricane Hurricane 62 55 

125 117 2008 415 Hurricane Hurricane 205 150 

126 118 2008 414 Hurricane Hurricane 52 52 

127 119 2008 472 Hurricane Hurricane 513 513 

128 120 2008 541 Hurricane Hurricane 200 200 

129 121 2008 235 Hurricane Hurricane 550 0 

130 122 2008 175 Hurricane Hurricane 140 138 

131 123 2008 76 Hurricane Hurricane 50 48 

132 124 2008 169 Hurricane Hurricane 127 126 

133 125 2008 176 Hurricane Hurricane 70 40 

134 126 2008 186 Hurricane Hurricane 194 112 

135 127 2008 220 Hurricane Hurricane 170 170 

136 128 2008 324 Hurricane Hurricane 196 31 

137 129 2008 479 Hurricane Hurricane 72 72 

138 130 2008 472 Hurricane Hurricane 58 58 

139 131 2009 415 Hurricane Hurricane 54 54 

140 132 2009 4420 Equipment Failure Drilling 50 50 

141 133 2009 6050 Equipment Failure Abandonment YES 62 62 

142 - 2009 254 Hurricane Hurricane 70 70 

27 
Spill # 

* 

Bercha 

Spill # Year Water Depth (ft) Primary Cause of Incident ** Operation LOWC Spill Total (bbl) Crude & Cond. (bbl) Ref

143 - 2009 340 Unknown Unknown 186 186 144 - 2009 Unk. Unknown Unknown 100 100 

145 134 2010 4992 Unknown Drilling/Abandonment YES 4900000 4900000 146 135 2010 475 Hurricane Hurricane 62 62 

147 - 2011 541 Equipment Failure Drilling 67 67 

148 - 2012 63 Unknown Production 480 480 

149 - 2015 125 Unknown Unknown 125 0 

* This list only includes spills within the scope of the analysis described within this report. Spills from facility types, volume categories, fluid t

of this scope are excluded. Some years do not include any spills within the scope criteria. 

** “Hurricane” is listed under both cause and operation for spills associated with named hurricanes. The cause “Weather” identifies spills cause

as strong tides, rough seas, and waves. 

28 
Appendix C: OCS Pipeline Exposure 

Pipeline exposure was estimated using the pipeline data available on BSEE’s website (BSEE, 

2017c; BSEE, 2017d). Pipeline lengths were queried in miles and converted to kilometers for the 

calculation of frequencies. Table 16 provides the pipeline exposure results. Values have been 

rounded. 

The metric estimates the number of miles of oil-bearing pipeline in Federal waters in each year 

which have been installed or approved and have not yet been abandoned. This pseudo-SQL code 

describes the logic. 

Note that the Field “Product” is defined as: 

IIf(InStr([PROD_CODE],"O")<>0 AND [PROD_CODE]<>"H2O","Oil",IIf([PROD_CODE] In 

("BLKG","GAS","BLGH","FLG","G/C","GASH")," Gas","OTHER")) AS Product 

Select 

m.YEAR_NUM, 

size.Size, 

Count(*) AS Segments, 

Sum([SEG_LENGTH])/5280 AS Miles, 

Product 

From PPL_MASTERS AS pm, MONTHS AS m, PipelineSizeRanges AS [size] 

Where 

(((pm.PPL_SIZE_CODE)>[size].[minsize] AND 

(pm.PPL_SIZE_CODE)<[size].[maxsize]) AND 

((m.YEAR_NUM)<Year(Date())) AND 

((pm.SEGMENT_NUM)<500000) AND 

((pm.STATUS_CODE) Not In ("PROP","CNCL","COMB")) AND 

((m.MONTH_NUM)=12) AND 

((IIf(IsNull([INIT_HS_DT])=False,[INIT_HS_DT],IIf(IsNull([APPROVED_DATE])= 

False,[APPROVED_DATE],#1/1/1964#)))<=[m].[end_date]) AND 

((IIf(IsNull([ABAN_APRV_DT])=False,[ABAN_APRV_DT],[ABAN_DATE])) Is Null 

OR (IIf(IsNull([ABAN_APRV_DT])=False, 

[ABAN_APRV_DT],[ABAN_DATE]))>=[m].[end_date])) 

29 
Group By 

m.YEAR_NUM, 

size.Size, 

Product 

Having [Product]="Oil" 

30 
Table 16. Miles of GOM and PAC oil pipeline segments by year and size (1972 to 2017) 

Year Summary NPS Categories Detailed NPS Categories (inches) 

≤10’’ >10’’ Total 2 3 4 5-6 7-8 9-10 

1972 1,439 373 1,812 68 95 378 467 314 117 1973 1,553 447 2,000 69 99 388 497 359 142 1974 1,643 461 2,104 76 99 392 499 435 142 1975 1,732 534 2,266 76 104 399 516 448 189 1976 1,814 702 2,516 82 108 406 524 499 195 1977 1,868 706 2,574 83 110 431 541 508 195 1978 2,031 773 2,804 83 118 445 601 550 234 1979 2,163 792 2,955 83 123 472 632 598 255 1980 2,257 815 3,073 85 126 499 655 635 257 1981 2,454 855 3,310 88 128 539 768 673 258 

1982 2,556 893 3,449 88 131 559 822 694 261 1983 2,686 936 3,622 88 151 580 911 695 261 1984 2,871 943 3,814 88 169 632 970 727 285 1985 3,012 948 3,960 86 197 669 1,013 756 292 1986 3,111 1,016 4,126 86 200 687 1,083 763 292 1987 3,227 1,044 4,271 86 208 721 1,108 777 327 1988 3,322 1,085 4,407 92 231 753 1,119 796 332 1989 3,379 1,133 4,512 93 257 772 1,119 806 332 1990 3,538 1,134 4,672 93 264 827 1,183 823 347 1991 3,634 1,133 4,767 95 293 868 1,194 829 354 1992 3,834 1,147 4,981 95 313 896 1,247 903 380 1993 3,871 1,153 5,024 89 321 922 1,256 904 380 1994 3,998 1,209 5,206 83 334 952 1,299 949 379 1995 4,122 1,281 5,403 84 346 985 1,343 979 385 1996 4,293 1,663 5,957 83 352 1,014 1,456 1,002 386 1997 4,402 1,866 6,268 82 354 1,035 1,508 1,021 402 1998 4,527 1,927 6,453 82 344 1,058 1,582 1,048 412 1999 4,745 2,142 6,887 82 339 1,085 1,674 1,127 438 2000 4,865 2,375 7,240 75 343 1,115 1,717 1,156 459 

31 
Year Summary NPS Categories Detailed NPS Categories (inches) 

≤10’’ >10’’ Total 2 3 4 5-6 7-8 9-10 

2001 4,983 2,435 7,418 74 337 1,160 1,763 1,177 472 2002 5,137 2,523 7,660 72 340 1,188 1,803 1,265 471 2003 5,087 2,804 7,890 69 323 1,164 1,791 1,273 467 2004 5,160 3,371 8,531 68 321 1,164 1,820 1,305 482 2005 5,270 3,491 8,761 67 304 1,163 1,877 1,351 507 2006 5,427 3,661 9,088 68 306 1,175 1,926 1,429 524 2007 5,415 3,711 9,126 68 304 1,242 1,912 1,369 520 2008 5,529 3,885 9,414 64 303 1,228 1,933 1,438 562 2009 5,519 3,967 9,485 62 297 1,178 1,943 1,453 586 2010 5,520 3,916 9,436 67 267 1,170 1,945 1,487 583 2011 5,618 4,001 9,619 65 279 1,226 1,990 1,475 582 2012 5,673 3,924 9,597 65 261 1,218 2,042 1,497 590 2013 5,650 4,006 9,656 59 234 1,195 2,067 1,502 593 2014 5,729 4,364 10,093 59 225 1,156 2,149 1,524 616 2015 5,782 4,395 10,177 58 225 1,122 2,143 1,595 639 2016 5,663 4,447 10,110 58 221 971 2,073 1,652 687 2017 5,459 4,491 9,951 58 217 972 1,875 1,658 679 TOTAL mile-yrs 

181,569 94,881 276,449 3,547 11,021 40,172 62,355 46,224 18,250 

TOTAL km-yrs 

292,206 152,695 444,901 5,708 17,737 64,651 100,350 74,390 29,370 

32 
Appendix D: OCS Pipeline Spills 

Table 17. GOM and PAC OCS pipeline spills ≥ 50 bbls (1972 to 2017)

# * Bercha Spill # Year Water Depth (feet) NPS Total Spilled (bbls) Product Spilled Cause of Incident Detailed Cause 

1 1 1972 140 12 100 Crude Oil Equipment Failure Internal Corrosion P

2 2 1973 168 16 5000 Crude Oil Equipment Failure Internal Corrosion P

3 3 1974 240 14 19833 Crude Oil External Forces, Equipment Failure Anchor Impact P

4 4 1974 246 12 65 Crude Oil Weather, External Forces, Equipment Failure Anchor Impact P

5 5 1974 141 8 3500 Crude Oil Weather, External Forces, Hurricane Carmen Hurricane H

6 6 1976 160 18 414 Crude Oil External Forces, Equipment Failure Internal Corrosion P7 7 1976 210 10 4000 Crude Oil External Forces, Equipment Failure Fish Net P

8 8 1977 105 13 250 Crude Oil External Forces, Equipment Failure Mud slide P

9 9 1977 247 14 50 Crude Oil External Forces, Equipment Failure Anchor Impact P

10 10 1977 210 8 300 Crude Oil External Forces, Equipment Failure Anchor Impact P

11 11 1978 177 9 135 Crude Oil Equipment Failure Connection P12 12 1978 103 9 900 Crude Oil External Forces, Equipment Failure Anchor Impact P13 13 1979 300 8 50 Crude Oil External Forces, Equipment Failure Workboat Anchor P

14 14 1980 137 8 100 Condensate External Forces, Equipment Failure Fish Net P

15 15 1981 54 4 80 Crude Oil Equipment Failure External Corrosion P

16 16 1981 190 8 5100 Crude Oil External Forces, Equipment Failure Workboat Anchor P

17 17 1983 184 8 80 Crude Oil Weather, External Forces, Equipment Failure Mud Slide P18 18 1985 162 13 323 Crude Oil External Forces, Equipment Failure Anchor Impact P

19 19 1985 17 12 200 Crude Oil External Forces, Equipment Failure Third Party Spud 

Barge 

P

20 20 1986 27 6 119 Crude Oil Equipment Failure Unknown P

21 21 1986 300 8 210 Crude Oil External Forces, Equipment Failure Material P22 22 1988 75 14 15576 Crude Oil Weather, Human Error, External Forces, 

Equipment Failure 

Anchor Impact P

23 23 1990 197 4 14423 Condensate External Forces, Equipment Failure Fish Net P

24 24 1990 230 8 4569 Crude Oil External Forces, Equipment Failure Fish Net P25 - 1990 Unk. Unk. 100 Crude Oil Unknown Unknown P

26 25 1991 90 11 50 Crude Oil Weather, External Forces, Equipment Failure Rig Anchor P

27 26 1992 90 12 190 Crude Oil Equipment Failure Unknown P

33 
# * Bercha Spill # Year Water Depth (feet) NPS Total Spilled (bbls) Product Spilled Cause of Incident Detailed Cause 

28 27 1992 30 20 2000 Crude Oil Weather, External Forces, Equipment 

Failure, Human Error, Hurricane Andrew 

Anchor Impact H

29 28 1993 116 4 50 Crude Oil External Forces, Equipment Failure Workboat Anchor P

30 29 1994 197 4 4533 Condensate External Forces, Equipment Failure Fish Net P

31 30 1996 1075 20 150 Crude Oil Equipment Failure, Human Error Connection P

32 32 1998 150 14 800 Crude Oil External Forces, Equipment Failure Anchor Impact P

33 33 1998 264 16 1211 Condensate Human Error, External Forces, Equipment 

Failure 

Anchor Impact P

34 35 1998 108 10 8212 Crude Oil Weather, External Forces, Human Error, 

Equipment Failure, Hurricane Georges 

Mud slide H

35 - 1998 170 8 738 Crude Oil Equipment Failure, External Forces Third Party Vessel P

36 36 1999 133 12 3200 Crude Oil External Forces, Human Error Third Party Jackup P

37 37 2000 435 24 2240 Crude Oil External Forces, Human Error, Equipment 

Failure 

Anchor Impact P

38 39 2004 479 6 1720 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H

39 40 2004 200 18 671 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H40 41 2004 305 6 126 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H41 42 2004 244 8 200 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H42 43 2004 255 6 250 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H43 44 2004 255 8 260 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H44 45 2004 185 8 95 Crude Oil Weather, External Forces, Hurricane Ivan Unknown H

45 46 2004 300 10 123 Crude Oil Weather, External Forces, Hurricane Ivan Hurricane H46 48 2005 1100 8 960 Crude Oil Weather, External Forces, Hurricane Katrina Hurricane H

47 49 2005 340 8 50 Crude Oil Weather, External Forces, Hurricane Katrina Hurricane H

48 50 2005 240 10 55 Crude Oil Weather, External Forces, Hurricane Katrina Hurricane H

49 51 2005 216 10 132 Crude Oil Weather, External Forces, Hurricane Katrina Hurricane H

50 52 2005 48 8 50 Condensate Weather, External Forces, Hurricane Katrina Hurricane H

51 53 2005 180 4 75 Crude Oil Weather, External Forces, Hurricane Rita Hurricane H

52 54 2005 17 14 100 Condensate Weather, External Forces, Hurricane Rita Hurricane H

53 55 2005 141 8 862 Crude Oil Weather, External Forces, Hurricane Rita Hurricane H

54 56 2005 152 12 67 Crude Oil Weather, External Forces, Hurricane Rita Hurricane H

55 57 2005 210 6 108 Crude Oil Weather, External Forces, Hurricane Rita Hurricane H

56 - 2005 322 8 99 Crude Oil Weather, External Forces, Hurricane Katrina Hurricane P

34 
# * Bercha Spill # Year Water Depth (feet) NPS Total Spilled (bbls) Product Spilled Cause of Incident Detailed Cause 

57 58 2006 126 14 870 Crude Oil External Forces, Human Error, Equipment 

Failure 

Anchor Impact P

58 59 2007 420 4 188 Crude Oil Human Error Unknown P59 60 2008 46 8 69 Crude Oil Weather, External Forces, Hurricane Ike Hurricane H60 61 2008 50 6 108 Condensate Weather, External Forces, Hurricane Ike Hurricane H61 62 2008 105 6 56 Crude Oil Weather, External Forces, Hurricane Ike Hurricane H62 63 2008 150 42 1316 Condensate Weather, External Forces, Hurricane Ike Hurricane H63 64 2008 324 4 209 Crude Oil Weather, External Forces, Hurricane Ike Hurricane H64 65 2008 324 8 268 Condensate Weather, External Forces, Hurricane Ike Hurricane H65 66 2009 50 20 1500 Crude Oil Equipment Failure Unknown P66 - 2011 Unk. Unk. 400 Diesel Equipment Failure Unknown P67 - 2013 Unk. 10 113 Crude Oil Equipment Failure Unknown P68 - 2013 Unk. Unk. 102 Crude Oil Equipment Failure Unknown P69 - 2016 2900 Unk. 2100 Crude Oil Unknown Unknown P70 - 2017 4463 Unk. 16152 Crude Oil Unknown Unknown P

* This list only includes spills within the scope of the analysis described within this report. Spills from facility types, volume categories, 

areas outside of this scope are excluded. Some years do not include any spills within the scope criteria. 

35 
Appendix E: Additional Spill Documents 

BOEM provided the following spill reports as part of their data transfer for the development of 

this report (Crowley, 2017). 

20100123-ZnBr2-6bbl_100123-pdf 

20100126-SBM-4bbl_100126-pdf 

20100306-SBM-21bbl_100306-pdf 

20100312-SBM-48bbl_100312-pdf 

20100407-SBM-125bbl_100407-pdf 

20100514-Oil-14bbl_100514-pdf 

20100521-Crude-LT30bbl_100521-pdf 

20100729-LiqHC-ukn_100729-pdf 

20100914-Oil-LT5bbl_100914-pdf 

20100929-OilCond-7bbl_100929-pdf 

20101201-SBM-98bbl_101201-pdf 

20110106-Oil-12gal_exxonmobil-wd-73a-06-january-2011 

20110722-SBM-79bbl_110722-pdf 

20110730-Oil-LT231gal_110730 

20110917-Cond-1gal_110917-pdf 

20111216-SBM-319bbl_12-18-11-shell-mc-348 

20120204-SBM-100bbl_sanitized-chevron-wr-29-4-feb-2012 

20120210-SBM-44bbl_sanitized-chevron-gc-205-a-10-feb-2012 

20120219-CompletionFluid-849bbl_sanitized-anadarko-eb-602-19-feb-2012 

20120515-Diesel-5gal_sanitized-mariner-hi-a-7-15-may2012 

20120622-Crude-35bbl_houchinreport6-22-2012 

20120708-Oil-16bbl_ankor-ss-229-a-7-jul-2012 

20120817-unk-unk_ew-921-eni-17-august-2012 

20120904-Cond-LT1gal_wd-70-gom-shelf-4-september-2012 

20120926-Oil-69gal_ss-233-b-w-t-offshore-26-sep-2012 

20120927-Oil-9gal_hi-a443-black-elk-27-sep-2012 

20121124-SBM-14bbl_kc-875-anadarko-24-november-2012 

20121208-SBM-31bbl_gb-386-hess-8-december-2012-1 

20130117-SBM-91bbl_hi-a-119-bp-17-jan-2013 

20130303-Oil-13gal_vk-817-flextrend-03-mar-2013 

20130403-CaBrZnBr-938bbl_gc-683-anadarko-03-april-2013 

20130419-SBM-50bbl_kc-93-bp-19-apr-2013 

20130516-SBM-21bbl_mc-762-shell-16-may-2013 

20130518-Oil-3bbl_sp-60f-ankor-energy-18-may-2013 

20130603-Oil-LT1gal_mc-243-w-t-offshore-03-jun-2013 

20130707-HC-unk_ss-225b-energy-resource-tech-07-jul-2013 

20130720-SBM-66bbl_mc-778-bp-20-jul-2013 

20131213-AviatFuel-390gal_gb-189-a-chevron-usa-inc-13-dec-2013 

20140211-Mud-144bbl_ac-857a-shell-offshore-11-feb-2014 

20140212-SBM-128bbl_mc-29-stone-energy-12-feb-2014 

20140325-SBM-42bbl_mc-503-llog-25-mar-2014 

20140523-SBM-61bbl_gb-213-apache-deepwater-23-may-2014 

20140830-SBM-12bbl_kc-829-chevron-30-aug-2014 

20140924-SBM-150bbl_gc-155-marubeni-oil-and-gas-24-sep-2014 

20141016-SBM-150bbl_gc-237-ert-16-oct-2014 

36 
20141113-ZnBr-66bbl_vr-342-arena-offshore-13-nov-2014 

20141203-Cond-LT1bbl_sm-27-sea-robin-pipeline-5-dec-2014 

20141211-SBM-142bbl_wr-508-shell-11-dec-2014 

20150213-SBM-260bbl_mc-726-hess-13-feb-2015 

20150216-Methanol-438bbl_mc-941a-bennu-oil-and-gas-16-feb-2015-sanitized 

20150323-SBM-2200bbl_gb-958-cobalt-rowan-reliance-23-mar-2015 

20150401-SBM-unk_kc-147-bp-01-apr-2015 

20150619-Oil-LT1gal_vr-279a-w-and-t-offshore-19-jun-2015 

20150620-SBM-12bbl_mc-772-eni-20-jun-2015 

20150702-SBM-368_mc-126-freeport-mcmoran-02-jul-2015 

20150808-SBM-6bblTotal_wr51-anadarko-08aug2015 

20150921-MethanolHW525-41bbl_eb-643-anadarko-21-sep-2015 

20151016-Oil-25bbl_gc-338a-murphy-exploration-and-production-16-oct-2015 

20160217-ZnBr2-22bbl_gb_216_hess_corporation_17_feb_2016 

20160303-BaseOil-10bbl_mc_778_bp_exploration_03_mar_2016 

20160527-Methanol-46bbl_ac_857_shell_offshore_25_may_2016 

20160921-Oil-8bbl_wd-32-energy-xxi-21-sep-2016 

20161106-SBM-12bbl_mc-778-bp-exploration-06-nov-2016 

20170607-SBM-94bbl_gb-427-shell-offshore-7-jun-2017 

20170627-SBM-29bbl_wr-778-chevron-27-jun-2017 

20170913-SBM-71bbl_gc-782-bp-exploration-13-sep-2017 

37 
38 
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