| Popis: |
Water flooding is one of the most important techniques of improved oil recovery. However, two major problems, loss of injected water to the aquifer and unwanted water production, reduce the efficiency of water flooding. An improper allocation of water to injection wells usually is the main reason of these problems. In this paper, both multi-objective genetic algorithm (MOGA) optimization, which is more rapid and accurate than conventional GA, and streamline simulation with the unique advantages of determination of flow path and participation of each injection well in total field oil production, were used in order to appease the mentioned problems. All previous studies have tried to optimize the injection rates based on injection efficiencies that were defined with the application of streamline simulation, while using MOGA optimization and Pareto concept always let us select the best global solutions with regard to the other defined criterions. Final solution in MOGA optimization is a set of correct answers. So, five scenarios, including different restrictions and economic situations were introduced. Best solution was obtained and compared with the common method of water injection optimization exclusively based on improving the efficiencies of injection wells. Results show that MOGA optimization always offers the best solution and all MOGA scenarios have better proficiencies than common optimization methods. Comparison of the proposed methodology in this paper with conventional workflow shows that MOGA, in the best case, can increase total oil production up to 6.5 %, and after considering all limitations, it can increase total oil production up to 4 % and decrease the loss of water to the aquifer to about 26 % in comparison with the common workflows. |
