Oil Spill Risk Analysis Model Research Articles

Progress of the Oil Spill Risk Analysis (OSRA) Model and Its Applications

The Bureau of Ocean Energy Management (BOEM) is responsible for managing the development of US Outer Continental Shelf (OCS) energy and mineral resources. Because oil spills may occur from offshore oil and gas activities, BOEM conducts oil spill risk analysis (OSRA) prior to oil and gas lease sales. Since the 1970s, BOEM has developed and applied the OSRA model to evaluate the risk of potential oil spills to environmental resources. This paper summarizes some of the OSRA model progress and applications in the past decade: (1) calculation of the risk of catastrophic oil spills (with a volume over one million barrels), which concludes that the return period of a catastrophic oil spill in OCS areas is estimated to be 165 years; (2) a more efficient way to estimate the probability of oil spill contact to environmental resources in the Gulf of Mexico; (3) weathering calculations in OSRA, which enhances the accuracy of the OSRA model results; and (4) application of OSRA to the Ixtoc I oil spill as an example of how the OSRA model simulates large oil spills for oil spill preparedness and response.

An Improved Method to Estimate the Probability of Oil Spill Contact to Environmental Resources in the Gulf of Mexico

The oil spill risk analysis (OSRA) model is a tool used by the Bureau of Ocean Energy Management (BOEM) to evaluate oil spill risks to biological, physical, and socioeconomic resources that could be exposed to oil spill contact from oil and gas leasing, exploration, or development on the U.S. Outer Continental Shelf (OCS). Using long-term hindcast winds and ocean currents, the OSRA model generates hundreds of thousands of trajectories from hypothetical oil spill locations and derives the probability of contact to these environmental resources in the U.S. OCS. This study generates probability of oil spill contact maps by initiating trajectories from hypothetical oil spill points over the entire planning areas in the U.S. Gulf of Mexico (GOM) OCS and tabulating the contacts over the entire waters in the GOM. Therefore, a probability of oil spill contact database that stores information of the spill points and contacts can be created for a given set of wind and current data such that the probability of oil spill contact to any environmental resources from future leasing areas can be estimated without a rerun of the OSRA model. The method can be applied to other OCS regions and help improve BOEM’s decision-making process.

Oil Spill Risk Analysis for Assessing Environmental Contact Probabilities in the Gulf of Mexico

ABSTRACT 2017-051: The U.S. Department of the Interior (DOI) Bureau of Ocean Energy Management (BOEM) maintains a leasing program for commercial oil and gas development on the Outer Continental Shelf in U.S. territorial waters. To evaluate the potential impacts of these activities, BOEM performs oil spill risk analysis (OSRA) using, in part, a statistical model for estimating the movement of hypothetical oil spills on the ocean surface based on model-generated surface wind and surface current. OSRA examines oil spill risks over long periods of time ranging from 5 years to decades. The latest OSRA analysis estimated the contact probabilities of oil spills in the Gulf of Mexico (GOM) region by modeling over 40 million hypothetical oil spill trajectories over extended areas of the U. S. continental shelf and tabulating the frequencies with which the simulated oil spills contacted designated natural resources within a specified number of days. The modeled ocean currents and wind fields used in the GOM analysis are from 1993 to 2007 (15 years). The OSRA model was also applied to analyze the contact probabilities of the Ixtoc Oil Spill, which happened on June 3, 1979 in the Bay of Campeche of the GOM and lasted for 10 months. The Ixtoc I Oil Well suffered a blowout, resulting in one of the largest oil spills in history and 3 million barrels of oil spilled. The OSRA model was applied to simulate particle trajectories released at the Ixtoc location using the same GOM current and wind field data from 1993 through 2007. The model results for the Ixtoc simulation were consistent with the descriptions of the oil spill by Hooper (1982), which shows that the OSRA model can provide a reasonable projection of the contact probabilities of hypothetical oil spills.

Arctic climate change and oil spill risk analysis

The purpose of this project was to: 1) describe the effects of climate change in the Arctic and its impact on circulation, 2) describe hindcast data used in the Ocean Energy Management, Regulation and Enforcement (BOEMRE) Oil Spill Risk Analysis (OSRA) model, 3) evaluate alternatives such as using forecast results in the OSRA model, and 4) recommend future studies. Effects of climate change on winds, sea ice, ocean circulation and river discharge in the Arctic and impacts on surface circulation can be evaluated only through a series of specially designed numerical experiments using highresolution coupled ice-ocean models to elucidate the sensitivity of the models to various parameterizations or forcings. The results of these experiments will suggest what mechanisms are most important in controlling model response and guide inferences on how OSRA may respond to different climate change scenarios. Climatological change in the Arctic could lead to drastic alterations of wind, sea ice cover and concentration, and surface current fields all of which would influence hypothetical oil spill trajectories. Because of the pace at which conditions are changing, BOEMRE needs to assess whether forecast ice/ocean model results might contain useful information for the purposes of calculating hypothetical oil spill trajectories.

STATISTICAL ESTIMATES OF SHORELINE OIL CONTACT IN THE GULF OF MEXICO

ABSTRACT As steward of the Federal offshore lands known as the Outer Continental Shelf (OCS), the U.S. Department of the Interior (DOI), Minerals Management Service (MMS), is responsible for balancing the Nation's search for commercial oil and gas with protection of the human and marine environments. The MMS regulates the development of mineral resources in an environmentally safe manner by analyzing environmental consequences of the OCS program prior to lease sales or approval of industry's plans. The Oil-Spill Risk Analysis (OSRA) model was developed by the DOI for the analysis of possible oil-spill impact from offshore oil and gas operations. The OSRA model produces statistical estimates of hypothetical oil-spill occurrence and contact from projected OCS operations. The model generates an ensemble of sea surface oil-spill trajectories by initiating thousands of oil-spill simulations at hypothetical spill locations to statistically characterize oil-spill risk in areas of prospective drilling and production and along projected pipeline routes. The hypothetical spills are initiated every day and move at the velocity of the vector sum of the surface ocean currents plus an empirical wind-induced drift of speed equal to 3.5% of the local wind speed, with a wind-speed-dependent direction (Samuels et al., 1982). The model generates oil-spill trajectories by integrating interpolated values of the wind and ocean current fields at intervals short enough to use the full spatial resolution of the ocean current and wind fields. The OSRA model, as applied to the Gulf of Mexico, uses 3-hourly ocean current fields over 7 years (1993–1999) generated by the Princeton Regional Ocean Forecast System (PROFS) (Oey et al., 2004). The PROFS is driven by synoptic winds, heat flux, and river flows. The wind field is based on the European Center for Medium-Range Weather Forecasts surface winds enhanced by observations from meteorological buoys and Coastal-Marine Automated Network stations. The same wind field used to force the ocean model is used to move the oil in the spill trajectories. As an example of environmental assessment, the OSRA model was used to estimate the spreading of oil spills by simultaneously modeling fractions of each spill, referred to as spillets. The spillets were used to calculate additional statistics, in particular, the length of coastline contacted by a large spill. The coastline was divided into equal length segments. Assumptions were made regarding what fraction of the spill (i.e., the number of spillets) that contacted a land segment would constitute a contact larger than the “level of concern.” Sensitivity of the analysis to key assumed parameters, such as the number of spillets and the level of concern, were tested.

A simple rapid approach using coupled multivariate statistical methods, GIS and trajectory models to delineate areas of common oil spill risk

Currently, the Minerals Management Service uses the Oil Spill Risk Analysis model (OSRAM) to predict the movement of potential oil spills greater than 1000 bbl originating from offshore oil and gas facilities. OSRAM generates oil spill trajectories using meteorological and hydrological data input from either actual physical measurements or estimates generated from other hydrological models. OSRAM and many other models produce output matrices of average, maximum and minimum contact probabilities to specific landfall or target segments (columns) from oil spills at specific points (rows). Analysts and managers are often interested in identifying geographic areas or groups of facilities that pose similar risks to specific targets or groups of targets if a spill occurred. Unfortunately, due to the potentially large matrix generated by many spill models, this question is difficult to answer without the use of data reduction and visualization methods. In our study we utilized a multivariate statistical method called cluster analysis to group areas of similar risk based on potential distribution of landfall target trajectory probabilities. We also utilized ArcView™ GIS to display spill launch point groupings. The combination of GIS and multivariate statistical techniques in the post-processing of trajectory model output is a powerful tool for identifying and delineating areas of similar risk from multiple spill sources. We strongly encourage modelers, statistical and GIS software programmers to closely collaborate to produce a more seamless integration of these technologies and approaches to analyzing data. They are complimentary methods that strengthen the overall assessment of spill risks.

Sensitivity testing for improved efficiency of a statistical oil-spill risk analysis model

The US Minerals Management Service performs oil-spill risk analyses using, in part, a statistical model of hypothetical oil-spill trajectories. The “Oil-spill Risk Analysis” (OSRA) model is driven by analyzed sea surface winds and model-generated ocean surface currents. The OSRA model calculates thousands of oil-spill trajectories over extended areas of US waters and tabulates the frequencies with which the simulated oil spills contact the geographic boundaries of designated natural resources within a specified number of days after the simulated spill events are initiated. The limits of computer mass storage and speed impose constraints on the number of oil-spill trajectory simulations and the time step of the numerical integration generating the spill trajectories. Also, the model winds and ocean currents have limited spatial and temporal resolution, producing sensible limits on the spatial density of the simulated oil spills and on the numerical integration time step. This investigation attempted to determine the smallest practical spatial interval between simulated oil spill release sites and the shortest integration time step beyond which the frequencies of oil-spill contact essentially do not change. In addition, we investigated the number of hypothetical oil spills initiated per day from a single location and two methods of numerical integration to generate the spill trajectories—simple forward time stepping and the fourth order Runge–Kutta method. Applying the OSRA model to the Gulf of Mexico using 9 years of winds and ocean current data, we found a smallest distance between simulated spills of 6 nautical miles and a shortest integration time step of 1 h using the fourth order Runge–Kutta integration method. A 20-min time step would be needed with simple forward time stepping. Initiating hypothetical spills eight times per day produced essentially the same contact probabilities as initiating spills once per day. These intervals were practical for OSRA model runs over the US portion of the Gulf of Mexico using commonly available desktop personal computers.

Oil-Spill Risk Analysis for Assessing Environmental Impacts

ABSTRACT The Minerals Management Service (MMS), an agency of the U.S. Department of the Interior, maintains a leasing program for commercial oil and gas development on the Outer Continental Shelf in U.S. territorial waters. The MMS performs an oil-spill risk analysis (OSRA) using, in part, a statistical model of hypothetical oil-spill trajectories. The OSRA Model is driven by analyzed sea surface winds and model-generated ocean surface currents. Instead of focusing on individual oil-spill events, the OSRA examines oil-spill risks over long periods of time, ranging from 5 years to decades. The OSRA Model calculates thousands of oil-spill trajectories over extended areas of the U. S. continental shelf and tabulates the frequencies with which the simulated oil-spills contact the geographic boundaries of designated natural resources within a specified number of days after the simulated spill events. A key element of OSRA Model runs is the particle trajectory simulation based on wind velocities and surface ocean currents. It is critical that the trajectory model has a numerical scheme that is stable, accurate, and efficient. Currently, two numerical schemes are incorporated into the model: the Eulerian scheme and the 4th order Runge-Kutta scheme. To test the numerical schemes, a set of analytical solutions to the Navier-Stokes equations is developed. The analytical velocities and particle trajectories are compared with the numerical solutions from the two numerical schemes. The stability and efficiency of the two schemes are discussed. Applying the model to the Gulf of Mexico using 9 years of winds and ocean currents, we find that the OSRA Model with the 4th order Runge-Kutta scheme is much more efficient and able to better represent the circulation patterns and particle movements in the Gulf of Mexico.

EXPORTING ALASKAN NORTH SLOPE CRUDE OIL: EVALUATION OF OIL SPILL RISKS

ABSTRACT On November 28, 1995, President Clinton signed legislation (S.395, Public Law 104-58) that authorizes the exporting of Alaskan North Slope crude oil. The oil would be shipped in U.S. flag vessels through the Gulf of Alaska and along a route 200 miles offshore the Aleutian Islands to the Far East. Implementation of this law is subject to a Determination of National Interest, which considers potential effects to the environment and economy. An interagency group, including the Department of Commerce, the Department of Energy, and the U.S. Coast Guard, was formed to analyze such effects, one of which is oil spill risk. The Minerals Management Service's Oil-Spill Risk Analysis model was used to track and analyze simulated spills from two tanker routes: a proposed route offshore the Aleutian Islands, and the existing domestic tanker routes through the Gulf of Alaska and along the coasts of Washington, Oregon, and California. The model results reflect the estimated risk to coastal areas over the various seasons from spills at large for up to 30 days’ travel time. The information generated was used to support planning for mitigation of potential risk and impacts.

COMPARISON OF TECHNIQUES FOR FORCING AN OIL SPILL TRAJECTORY MODEL

ABSTRACT The Oil Spill Risk Analysis model used by the U.S. Department of the Interior simulates trajectories of hypothetical oil spills on the outer continental shelf. The trajectories are calculated from surface current fields provided by a general circulation model with a superimposed wind-drift simulation. This paper compares two techniques for driving the wind-drift portion of the trajectory model. In this comparison, a statistical model of the wind, utilizing a first-order Markov approach, is used to simulate wind records to drive the model; these results are compared with trajectories forced by the observed winds. The comparison shows that trajectories resulting from the two forcing techniques differ; the trajectories forced by the observed winds are more variable and have directional differences as compared with the trajectories forced by modeled winds. The differences appear to be due to the inability of the first-order Markov approach to simulate wind history and the duration of wind events.

Panel recommendations on Oil Spill Risk Assessment

A technical panel was convened by the Minerals Management Services (MMS) of the Department of Interior to identify deficiencies and recommend improvements in their Oil Spill Risk Analysis (OSRA) model. Members of the panel were J. M. Bane, Jr. (University of North Carolina, Chapel Hill), G. S. Janowitz (North Carolina State University, Raleigh), T. H. Lee (University of Miami, Miami, Fla.), G. L. Mellor (Princeton University, Princeton, N.J.), M. L. Spaulding (University of Rhode Island, Kingston), and F. M. Vukovich (Research Triangle Institute, Raleigh‐Durham, N.C.).The present OSRA model uses climatologically derived near‐surface velocity fields on which are superposed oil trajectory velocities derived from the so‐called “3.5% rule”: this uses a wind series derived from a “transition probability matrix” statistical approach.