This case study is on the Gulf of Mexico which has one of the worst oil spills history incidents; more recently this region experienced a massive oil spills that turned out to be an environmental disaster.
This case study intends to discuss a framework of responding to oil spillage operations occurring specifically in the Gulf of Mexico and how related factors impacts on such an operation; in this case the oil spill was Deepwater Horizon. The model that we shall refer to is known as “A bi-criterion, multiperiod mixed-integer linear programming (MILP) model” (Zhong and You, 2011).
In such a case where Oil spill is of Deepwater Horizon, the response operations are spread across three levels described as S1, S2 and S3 which are at peripheral distances from the point of oil spill indicated as 60km between each other (Zhong and You, 2011). For this case the MILP model was supposed to develop a cost-effective and efficient response operation for an oil spillage that was “25 degree API crude oil that had been spilling for 42 days at an average rate of 10,000 M3” (Zhong and You, 2011).
The expected end results and other variables needed to develop the response operation plan is to have a final of only 1500 M3 oil spill remaining after the clean up and have 3 types of mechanical systems that will be used in cleaning the oil spill (Zhong and You, 2011).
Other factors and variables were considered and included in the MILP model in developing the response operation while using 180 days as the base number of days that would achieve the same results if no response was implemented. In determining the optimal number of days that is the most cost-effective Pareto-optimal curve was utilized in this case which gave range of 75-180 days and cleaning costs that vary from $1095MM-162MM (Zhong and You, 2011).
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During this particular response, the model indicated 77 days to be the most economical compared to cleaning the oil spill in 75 days though they only vary by two days since the cost differences is very significant between these two points by almost 50% (Zhong and You, 2011).
Because oil spill cleanup is very costly, this model indicates that use of booms to protect coastline is a cheaper strategy than cleaning the spill on sea since natural process will clean most of the oil spillage anyway (Zhong and You, 2011). Finally, the model indicates that dispersant application is the most efficient method of oil cleanup in this case (Zhong and You, 2011).
Recommendation
Based on the analysis indicated by the MILP model, it would appear that oil spill cleanup should be hedged on specific critical times during the duration of the spill when the exercise is most economical to undertake. Thus, one recommendation for this study is that oil spill cleanup in this region be planned along these critical times so as to maximize resources in doing so and take advantage of the natural cleaning process that as we have seen is very effective in achieving the same.
Reference
Zhong, Z. & You, F. 2011. Oil spill response planning with consideration of physicochemical evolution of the oil slick: A multiobjective optimization approach. Computers and chemical engineering, 1: 1-17.