摘要
为了提高页岩气开采效率和经济性,提出基于非支配排序遗传算法的页岩气压裂工艺参数优化研究。综合考量压裂液注入体积流量、支撑剂用量、压裂段长度及其他相关参数,设计多目标函数。在此基础上,设定涵盖地质条件、工艺参数及经济效益的详尽约束条件。通过非支配排序遗传算法(NSGA-Ⅱ)结合独特的实数编码方案,对复杂工艺参数组合进行精确表征与优化,最终输出一系列帕累托最优解,实现页岩气压裂工艺参数的自动优化。实验结果表明,该研究方法能够自动找到最优的工艺参数组合,显著提升页岩气的开采效率并降低开采成本,增强整体经济性。
In order to improve the efficiency and economy of shale gas extraction,a study on automatic optimization of shale gas fracturing process parameters based on non dominated sorting genetic algorithm is proposed.Design a multi-objective function based on comprehensive considerations of fracturing fluid injection rate,proppant concentration,fracturing section length,and other relevant parameters.On the basis,detailed constraints covering geological conditions,process parameters,and economic benefits are set.By combining the NSGA-Ⅱ algorithm with a unique real number encoding scheme,complex process parameter combinations are accurately characterized and optimized,ultimately a series of Pareto optimal solutions are output to achieve automatic optimization of shale gas fracturing process parameters.The experimental results show that the research method can automatically find the optimal combination of process parameters,significantly improve the efficiency of shale gas extraction,reduce extraction costs,and enhance overall economy.
作者
丛颜
Cong Yan(Sinopec East China Petroleum Engineering Co.Ltd.,Nanjing,210019,China)
出处
《石油化工自动化》
CAS
2024年第6期38-42,共5页
Automation in Petro-chemical Industry
关键词
非支配排序遗传算法
页岩气
压裂工艺
参数优化
自动优化
non dominated sorting genetic algorithm
shale gas
fracturing technology
parameter optimization
automatic optimization
