ACCESS NUMBER: 36507

STUDY TITLE: Improvements in the Fault Tree Approach to Oil Spill Occurrence Estimators for the 

Beaufort and Chukchi Seas 

REPORT TITLE: Alternative Oil Spill Occurrence Estimators and Their Variability for the Beaufort Sea – 

Fault Tree Method, Volume I and Volume II: Appendices

CONTRACT NUMBER: 1425-01-04-PO-36507 

SPONSORING OCS REGION: Alaska 

APPLICABLE PLANNING AREA: Beaufort and Chukchi Seas 

FISCAL YEARS OF PROJECT FUNDING: 2004 

COMPLETION DATE OF REPORT: January 2006 

COST: FY 2004: $65,000 CUMULATIVE PROJECT COST: $65,000 

PROJECT MANAGER: Frank G. Bercha 

AFFILIATION: Bercha International Inc. 

ADDRESS: 2926 Parkdale Blvd. NW, Calgary, Alberta, Canada, T2N 3S9 

PRINCIPAL INVESTIGATOR*: Frank G. Bercha 

KEY WORDS: Oil spill occurrence, Beaufort Sea, fault tree analysis 

BACKGROUND: The MMS Alaska Offshore Continental Shelf (OCS) Region uses oil spill occurrence 

predictions for National Environmental Protection Act assessments for all parts of their area of jurisdiction, 

ranging from the shore through shallow water, to deeper water. Although land to 3 miles is not within 

MMS jurisdiction, it is included in the MMS environmental impact analysis; hence it is also included in the 

study area here. In 2000 to 2002, a study was carried out by Bercha International Inc. (OCS Study MMS 

2002-047) to assess and quantify oil spill occurrence indicators for the Beaufort and Chukchi Seas. In this 

study, methodologies based on fault tree analysis were developed for the assessment of oil spill rates 

associated with exploration and production facilities and operations in deeper waters in the Chukchi and 

Beaufort Seas. In the present study, these methodologies are further applied to specific Beaufort Sea 

development scenarios. As there is a paucity of offshore Arctic oil spill occurrences, associated data 

worldwide and from the Gulf of Mexico (GOM) were used as a starting point to develop a simulation 

model of oil spill occurrence probabilities. The model for non-Arctic occurrence probabilities was then 

modified to include Arctic effects and their variabilities. Because variability information for the non-Arctic 

data was not available at the time of the previous study the resultant spill occurrence probabilities only 

reflected the variability associated with Arctic effects. In the present study, on the other hand, both the 

variability of the non-Arctic database used as a starting point and the variability of Arctic effects are 

included. Then, with the inclusion of the variability of both the Arctic and non Arctic inputs, oil spill 

occurrence estimators were generated for several expected future oil and gas development scenarios 

(including exploration, production, and abandonment) in the Beaufort Sea Offshore Continental Shelf 

(OCS) lease sale regions. 

OBJECTIVES: The objectives of this study are as follows: 

Assimilate and analyze world-wide and US OCS oil spill statistics and evaluate their 

applicability to deeper lease tracts which could be offered in the upcoming Beaufort Sea 

sales. 

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• Develop the fault tree method for estimating oil spill occurrences from Beaufort Sea 

developments associated with spills of different size categories. 

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Using the fault tree approach, develop alternative oil spill indicators and assess their 

variability. 

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•

•

Provide statistical support to MMS in evaluation of statistical issues in estimation of oil spill 

rates. 

One of the specific objectives of this study was to include the variability of the non-Arctic 

factors. 

DESCRIPTION: Oil spill occurrence estimators were generated for several expected future oil and gas 

development scenarios (including exploration, production, and abandonment) in the Beaufort Sea 

Offshore Continental Shelf (OCS) lease sale regions. Because sufficient historical data on offshore oil 

spills for these regions do not exist, an oil spill occurrence model based on fault tree methodology was 

developed and applied. Using the fault trees, base data from the Gulf of Mexico, including their variability, 

were modified and augmented to represent expected Arctic offshore oil spillage frequencies. Three 

principal spill occurrence indicators, as follows, were quantified for each year of each scenario, as well as 

for each scenario life of field averages: 

• Spill frequency 

• Spill frequency per barrel produced 

• Spill index, the product of spill size and spill frequency 

These indicators were quantified for the following spill sizes, where fractional spill sizes were rounded up 

or down to the nearest whole number, with rounding up for any decimal ending in 5: 

: 

 Small (S): ≥50 to <100 bbl 

 Medium (M): ≥100 to <1,000 bbl 

 Large (L): ≥1,000 to <10,000 bbl 

 Huge (H): ≥ 10,000 bbl 

Quantification was carried out for each future year for four different Beaufort Sea exploration and 

development scenarios, ranging in duration up to year 2038. Three scenarios represented developments 

associated with three different sales (Sales 1, 2, and 3), and the fourth was for a composite scenario: 

“Sale All”, consisting of a composite development from all three sales. In addition, a comparative scenario 

for non-Arctic locations was formulated and analyzed for oil spill occurrence for the composite 

development. The computations were carried out using a Monte Carlo process to permit the inclusion of 

estimated uncertainties in all the input data. A wide range of details for each scenario was generated, 

including the following: 

• Expected time history of spill occurrences over the scenario life. 

• Spill occurrence variations by spill volumes in the above spill size ranges. 

• Spill occurrence variation by spill cause such as boat anchoring or ice gouging. 

• Spill occurrence contribution from each main facility type, including pipelines, platforms, and 

wells. 

• Comparison of spill occurrence predictions between Arctic and non-Arctic scenarios. 

• The variability in the results due to uncertainties in the input data is expressed as cumulative 

distribution functions and statistical measures. 

In the final report, a detailed description of the methodology, results, and conclusions and 

recommendations is given, as well as a section on limitations of the study. 

SIGNIFICANT CONCLUSIONS: 

1. All non-Arctic scenario spill indicators are greater than their Arctic counterparts. Non-Arctic spill 

indicators are approximately 45% greater than their Arctic counterparts. 

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2. Spill frequencies and the spill index follow the facility build-up and phase-out, as they are directly 

proportional to facility quantities. 

3. Spill frequency per barrel produced continues to rise beyond the peak production year due to the 

rate of production decline being disproportionately higher than the rate of abandonment chosen 

for the scenarios. 

4. Spill frequency per year and per barrel produced decreases with increasing spill size for all 

scenarios. The spill index gives the opposite trend, increasing with spill size. 

5. Each spill indicator for Beaufort Sea Sale 1, 2, and 3 is similar in value. The indicators are higher 

for the composite “Sale All” scenario. 

6. Platforms contribute the most (43%) the two spill frequency indicators, but the least (3%) to the 

spill index. 

7. Wells are by far the highest contributors to spill index 89% while platforms and wells are 

responsible for 3% and 8%, respectively. 

8. Uncertainties in the Arctic spill variations resulting from uncertainties expressed as numerical 

distributions of the Arctic effect inputs were quantified using the Monte Carlo method. The 

variance in the spill indicators ranged for upper bounds from 20 to 50% of the mean, and for 

lower bounds from 20 to 35% of the mean. 

STUDY RESULTS: The following principal groups of results, illustrated by attachments, were generated: 

• Expected time history of spill occurrences over the scenario life. 

• Spill occurrence variations by spill volumes in the main spill size ranges). 

• Spill occurrence variation by spill cause such as boat anchoring or ice gouging. 

• Spill occurrence contribution from each main facility type, including pipelines, platforms, and 

wells. 

• Comparison of spill occurrence predictions between Arctic and non-Arctic scenarios. 

• The variability in the results due to uncertainties in the Arctic effects introduced, expressed as 

cumulative distribution functions and statistical measures. 

In the final report, a detailed description of the methodology, results, and conclusions and 

recommendations is given, as well as a section on limitations of the study. 

STUDY PRODUCTS: Bercha Group. 2006. “Alternative Oil Spill Occurrence Estimators and Their 

Variability for the Beaufort Sea – Fault Tree Method”, Volumes I and II, Final Report to US Department of 

the Interior, Minerals Management Service, Alaska OCS Region, OCS Study MMS 2005-061. 

 

Bercha, F. G.; Prentki, R.T.; Smith, C.; and Cerovšek, M. 2006. “Prediction of Oil Spill Occurrence 

Probabilities in the Alaskan OCS” accepted for presentation at ICETECH 2006, Banff, Alberta July 17-19, 

2006. 

Bercha, F. G. 2003. Oil Spill Occurrence in the Beaufort and Chukchi Seas Fault-Tree Approach. MBC 

Applied Environmental Sciences. Alaska OCS Region Ninth Information Transfer Meeting Proceedings, 

pp. 85-86. OCS Study MMS 2003-042. Anchorage, USDOI, MMS, Alaska OCS Region. 

 

Bercha, F. G. 2005. Oil Spill Occurrence in the Beaufort and Chukchi Seas Fault-Tree Approach. MBC 

Applied Environmental Sciences. Alaska OCS Region Ninth Information Transfer Meeting Proceedings, 

pp. 85-86. OCS Study MMS 2003-042. Anchorage, USDOI, MMS, Alaska OCS Region. 

Bercha, F.G., Prentki, R. T., and Cerovšek, M. 2003. “Arctic Subsea Pipeline Oil Spill Probabilistic 

Analysis. In: The Proceedings of the Thirteenth (2003) International Offshore and Polar Engineering 

Conference, pp. 510-517. Honolulu, HI, May 25-30, 2003. International Society of Offshore and Polar 

Engineers.

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Figure 1 

Beaufort Sea Study Area 

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