补偿模型误差的采油过程多目标优化-控制理论与应用.PDF

32 5 Vol. 32 No. 5 2015 5 Control Theory Applications May 2015 DOI: 10.7641/CTA.2015.40901 , , (, 110819) : , . , (GMM) , , , . , (NSGA--II) . , , . : ; ; ; ; ; : TP273 : A Multi-objective optimization for oil production process with compensating model error LIU Tan, GAO Xian-wen , WANG Li-na (College of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110819, China) Abstract: Through analyzing the oil production process, we build an optimization model for maximizing the oil pro- duction of block and minimizing comprehensive energy consumption for per-ton oil as the performance index. Considering the large difference between the model output of comprehensive energy consumption for per-ton oil and the actual value, we adopt a Gaussian mixture model (GMM) to describe the error characteristics of comprehensive energy consumption for per-ton oil hybrid model. The model error compensation is first implemented, and then the comprehensive energy con- sumption for per-ton oil is introduced into the built optimization model to make the optimization results further closer to the actual optimum. On this basis, a fast elitist non-dominated sorting genetic algorithm (NSGA-II) is adopted for solving the established multi-objective optimization model. A production process in a block of an oil production operation area is taken as an example for simulation; the results show the effectiveness of the built model and the proposed optimization algorithm. Key words: oil production process; multi-objectiv