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Geophysical Monograph Series



  • oil spill
  • Monte Carlo
  • modeling
  • Deepwater Horizon
  • Gulf of Mexico
  • Loop Current

Index Terms

  • 4251 Oceanography: General: Marine pollution
  • 4255 Oceanography: General: Numerical modeling
  • 1922 Informatics: Forecasting
  • 4263 Oceanography: General: Ocean predictability and prediction



A Statistical Outlook for the Deepwater Horizon Oil Spill

C. H. Barker

In the first few days after the Deepwater Horizon drilling rig sank in the Gulf of Mexico, it was apparent that there was the potential for a very large spill of long duration. The NOAA Emergency Response Division (ERD) was asked by the secretary of Homeland Security to provide an analysis of the long-term outlook for oil transport if the well was to be uncontrolled for many months. The results of this analysis were required to help determine where efforts should be focused to prepare for response activities and to determine whether foreign governments should be notified. NOAA developed a Monte Carlo simulation, running an oil spill trajectory model hundreds of times, each with a different set of possible conditions based on historical data. To develop this simulation, a hindcast of the surface currents in the Gulf was provided by the US Minerals Management Service (now the Bureau of Ocean Energy Management, Regulation and Enforcement), developed by L. Oey's group at Princeton University. Five hundred individual oil trajectory scenarios were developed by sampling the historical data using random start times from April and May to capture the seasonality of the winds and river flows. A 90 day release was used, with the model run for a total of 120 days. The result was a statistical view of where oil from the spill might go and when it might have gotten there, an analysis valuable to the response community and the general public.

Citation: Barker, C. H. (2011), A statistical outlook for the Deepwater Horizon oil spill, in Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record-Breaking Enterprise, Geophys. Monogr. Ser., vol. 195, edited by Y. Liu et al., 237–244, AGU, Washington, D. C., doi:10.1029/2011GM001129.

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