STUDY TITLE: Alaska Oil Spill Occurrence Estimators Study

REPORT TITLE: Oil Spill Occurrence Rates for Cook Inlet, Alaska Oil and Gas Exploration,

Development, and Production

OCS STUDY NUMBER: 2020-051

NUMBER OF PAGES: 78

CONTRACT NUMBER: #140M0119F0003

SPONSORING OCS REGION: Alaska

APPLICABLE PLANNING AREA: Cook Inlet

FISCAL YEAR(S) OF PROJECT FUNDING: FY 2018

COSTS BY FISCAL YEAR: FY 2018: $224,658

CUMULATIVE PROJECT COST: $224,658

COMPLETION DATE OF REPORT: October 2020

PROJECT MANAGER(S): Tim Robertson

AFFILIATION (OF PROJET MANAGER): Nuka Research and Planning Group, LLC

ADDRESS: PO Box 175, Seldovia, AK 99663

PRINCIPAL INVESTIGATOR(S)*: Tim Robertson

KEY WORDS: pipeline, oil field, oil spills, Cook Inlet, occurrence estimators

BRIEF ABSTRACT: Under contract to the Bureau of Ocean Energy Management (BOEM), Nuka 

Research and Planning Group, LLC developed statistical methods to estimate oil spill occurrence based 

on past spills in Cook Inlet, Alaska. While the all spills large than one barrel from 1966-2019 were 

characterized, only spills from 1996-2019 were used to evaluate trends and develop the occurrence 

estimators. The following independent variables were considered: annual volume of gas produced from 

gas wells, annual volume of oil produced from oil wells, annual volume of water produced from oil wells, 

and the average inflation-adjusted price of Alaskan crude each year. A suitable regression model was 

identified for the annual number of spills overall and crude spills using oil production. By contrast, it was 

not possible to develop a regression model to estimate the annual volume of oil spills in Cook Inlet. 

Instead, a bootstrapping method and Monte Carlo simulation was used to estimate the spill volume.

Similarly, the number of refined spills did not correspond well with any of the independent variables 

considered.

BACKGROUND: This information was sought for use in future assessment of potential spills from oil and 

gas exploration, development, and production in the Outer Continental Shelf managed by BOEM, though 

the current oil and gas production infrastructure is all based onshore or in state waters.

OBJECTIVES: The objectives of this analysis were to:

• Develop a dataset of crude and refined oil spill records for Cook Inlet, Alaska.

• Develop a dataset of crude oil and gas production, and other possible independent variables for 

developing an oil spill occurrence rate model for Cook Inlet, Alaska.
• Provide statistical measures of crude and refined oil spills such as mean and median spill sizes 

with confidence intervals as appropriate;

• Use statistical analysis to identify trends in spill rates and volumes;

• Categorize Cook Inlet, Alaska spills into size classes; 

• Apply statistical procedures to develop occurrence rate estimator models for crude and refined oil 

spills, as well as all spills; and

• Develop an appropriate confidence interval for occurrence rate estimators.

METHODS: Past spills larger than one barrel associated with oil and gas exploration, development, and 

production were compiled. While 272 in-scope spills were identified between 1966-2019, only those 

between 1996-2019 were used to identify trends and develop occurrence estimators. These years were 

selected because they included the most consistent dataset in terms of collection and record keeping. 

Several approaches were tested to develop occurrence estimators. The dependent variables were the 

total volume of oil spilled each year and the total number of spills each year. The following independent 

variables were considered: annual volume of gas produced from gas wells, annual volume of oil 

produced from oil wells, annual volume of water produced from oil wells, and average inflation-adjusted 

price of Alaskan crude each year. Natural gas liquid production was not considered as an independent 

variable. Occurrence estimates were also sought for crude and refined spills separately.

RESULTS: A suitable regression model was identified for the annual number of spills using oil 

production and adjusted price as independent variables. The model indicated that for every increase of 

one million bbl of oil production, the number of annual spills is expected to increase 0.36 units (number of 

spills). This model explains 23% of the variation observed in the annual number of spills. The model’s 

calculated multivariate power was 0.7199. The power is adequate but not exceptional. This is attributed to 

the relatively small sample size.

By contrast, it was not possible to develop a regression model to estimate the annual volume of oil spills. 

Instead, a bootstrapping procedure and Monte Carlo simulation was used to estimate the spill volume.

This method resulted in an estimated 87 bbl of annual oil spill volume with a 95% confidence interval of 6 

to 226 bbl at an annual level of 7.5 million bbl of oil production.

The occurrence model to predict annual number of crude oil spills is very similar to the model developed 

to predict annual number of all types of oil. That model indicates that for every increase of one million bbl 

of oil production the number of annual crude oil spills is expected to increase 0.32 units. The model 

explains 25.58% of the variation observed in the annual number of spills. The model was not useful for 

predicting annual numbers of refined spills, however. There was no significant relationship between 

annual number of refined oil spills and any of the independent variables investigated. The best estimator 

of the annual number of refined oil spills is the mean value, which is equal to 2.6 refined spills per year. A 

valid model to predict the annual volume of crude oil or refined oil spills was not identified, leaving the 

best estimator of these values to be the median spill volume, 6.3 bbl of crude oil and 13.0 bbl of refined 

oil.

CONCLUSIONS: Based on past spills it is possible to develop a regression model to predict the number 

of annual spills based on oil production. This held true when looking only at crude oil spills, but did not 

work for refined spills. A bootstrapping method and Monte Carlo simulation were used to estimate spill 

volume as the regression approach was not successful.

STUDY PRODUCT(S):

1. BOEM study report: Robertson, T., Campbell, L.K. 2020. Crude and refined oil spill occurrence 

rates for Cook Inlet, Alaska oil and gas exploration, development, and production. Anchorage 

(AK): US Department of the Interior, Bureau of Ocean Energy Management. OCS Study BOEM 

2020-051. 78 p.
MAP SHOWING AREA OF STUDY

Figure 1. Study area