基于量子混合蛙跳算法的油田开发规划多目标优化

Multi-objective Optimization of Oilfield Development Plan Based on Quantum-Shuffled Frog-Leaping Algorithm

  • 摘要: 针对油田传统人为安排措施工作计算量大、耗时多且经济效益不高的缺点,建立了以经济效益最大化为目标,以年度增注目标、增产目标、含水目标、递减目标以及保持注采平衡为约束条件的多目标综合调整方案优化模型,并提出一种量子混合蛙跳算法求解优化模型,计算不同工作量组合实施效果,优选出满足目标和约束条件的综合调整方案作为实施方案,取得了很好的实际应用效果.

     

    Abstract: Addressing the shortcomings in the traditional oilfield measures with artificial arrangement is computationally intensive, time consuming, and has a low financial profitability. Therefore, a multi-objective comprehensive adjustment plan optimization model is established. This model maximizes the economic benefits of the target. It is also used for the annual targets of increasing the injection and production. It is further characterized as hydrous, has a minimum lapse rate, and keeps the injection balance under constraint conditions. A quantum-shuffled frog-leaping algorithm is proposed to solve the optimization model problem. The different workload implementation effects are calculated by the algorithm. A scheme that meets the objective and constraint conditions of the comprehensive adjustment and yields very good effect in practical application is selected.

     

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