Probabilistic estimates of oil spill occurrences are required for the development of environment impact assessments for possible future developments in the US Beaufort Sea. Due to the embryonic state of offshore oil development in this region, it was not possible to base these oil spill probability estimates on empirical data. Rather, statistically significant non-Arctic empirical data, together with their variance, was used as a starting point. Next, both the frequency distributions and spill causal distributions were modified to reflect specific effects of the Arctic setting and the resultant fault tree model was evaluated using Monte Carlo simulation to adequately characterize the combinations of probability distribution inputs to the fault tree. This paper summarizes the methodology and gives results of its application to the prediction of oil spill probabilities and their characteristics for the Beaufort Sea region for typical future offshore development scenarios.
Skip Nav Destination
SNAME 7th International Conference and Exhibition on Performance of Ships and Structures in Ice
July 16–19, 2006
Banff, Alberta, Canada
Prediction of Oil Spill Occurrence Probabilities in the Alaskan OCS
Paper presented at the SNAME 7th International Conference and Exhibition on Performance of Ships and Structures in Ice, Banff, Alberta, Canada, July 2006.
Paper Number:
SNAME-ICETECH-2006-115
Published:
July 16 2006
Citation
Bercha, Frank G., Prentki, Richard, Smith, Caryn, and Milan Cerovsek. "Prediction of Oil Spill Occurrence Probabilities in the Alaskan OCS." Paper presented at the SNAME 7th International Conference and Exhibition on Performance of Ships and Structures in Ice, Banff, Alberta, Canada, July 2006. doi: https://doi.org/10.5957/ICETECH-2006-115
Download citation file:
Sign in
Don't already have an account? Register
Personal Account
You could not be signed in. Please check your username and password and try again.
Could not validate captcha. Please try again.
Pay-Per-View Access
$35.00
Advertisement
1
Views
Advertisement
Suggested Reading
Advertisement