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

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.