Multi-Objective Schedule Optimization for Intermittent Pumping Wells Based on NSGA-II

Abstract

Abstract Intensive production over time can lead to wells with low productivity and efficiency in oil wells. To address this issue, intermittent pumping has become a popular solution, involving temporary cessation of production to allow for fluid level recovery and achieve optimal submergence depth before resuming pumping. However, determining the appropriate schedule for intermittent pumping wells is challenging. This paper proposes a multi-objective schedule optimization method for intermittent pumping wells using the non-dominated sorting genetic algorithm II (NSGA-II). The method considers multiple objectives such as production rates, electricity costs, and the solar energy utilization. Two case studies are presented, optimizing schedules with stepped electricity tariffs and integrating solar power. The results demonstrate significant reductions in electricity costs by 13.5%, while maintaining production rates. With the assistance of solar energy, the proposed method achieves over 45% reduction in electricity costs and a solar energy absorption rate exceeding 90%.