Proceedings of The 4th International Conference on Research in Applied Science
Selecting The Optimal Ranking Strategy and Scheduling of Eor Processes in an Oil Field Through Stochastic Mixed Integer Programing
Enhanced Oil Recovery with their application methods in an oil field increases the recovery. The additional recovery of oil is made possible economically from advances in technology. The scheduling and planning must be taken in consideration in rapid time for the lifespan of a of a project of an oil reservoir
Demands for oil are growing up rapidly specially in countries in development (including even China and India). Declining oilfield productivity on the other side is taking place rapidly. Experience for these methods and technics yield that they are very complex. Improving the profits or the overall cumulative oil production can be obtained only if there is an optimal planning and scheduling from the beginning of the development oil field. The optimal result can be obtained if only we know from the beginning of the life of reservoirs. A crucial point is that we must know the duration of each of them and the time period or interval these EOR technics must be applied. We need to do the computer simulations, after the problem is conceptualized, to perform the right hierarchy selection procedure. Sometime it happens that we may have not chosen the right selection strategy from the beginning, giving rise to non-optimal profitable EOR methods. We must be able in these conditions to reallocate the problem again, and run again and again the stochastic simulations in computer. To perform all these activities, there exists no mathematical algorithm in space and time, so we have to choose the right method for the oil reservoir, that might be different for another oil reservoir. To choose the proper hierarchy and scheduling for a certain oil field is challenge in itself. In this work we will make use of stochastic mixed integer programing to address this complex and challenge problem.
Keywords: Enhanced Oil Recovery; optimal hierarchy and scheduling of EOR; stochastic computer simulations; stochastic mixed integer programing.