数据驱动的复杂油藏注采生产优化技术研究进展  

Research progress of data-driven injection production optimization of complex oil reservoirs

作　　者：宋来明 王春秋 卢川 丁祖鹏 李桂亮 檀朝东[2] 程时清[2] SONG Laiming;WANG Cunqiu;LU Chuan;DING Zupeng;LI Guiliang;TAN Chaodong;CHENG Shiqing(CNOOC Research Instiule,Beijing 100028,China;School of Petroleum Enginerig,China University of Petroleum(Bejing),Beijing 102249,China;Xi'an SUPCON Tiandi Science&Technology Development co.Ltd,Xi'an 710021,Shanxi,China)

机构地区：[1]中海油研究总院有限责任公司,北京100028 [2]中国石油大学(北京)石油工程学院 [3]西安中控天地科技开发有限公司

出　　处：《石油钻采工艺》2022年第2期253-260,共8页Oil Drilling & Production Technology

基　　金：中国海洋石油有限公司综合科研项目“地质油藏大数据深度挖掘及应用研究”(编号:2020-YXKJ-016);国家自然科学基金“基于大数据解析的大规模非集输油井群生产及拉运调度协同优化”(编号:51974327)。

摘　　要：水驱开发老油田由于注采关系复杂、驱替场动态变化频繁,地下油水分布的格局发生了显著的变化,已进入到深度精细开发的新阶段。为促进石油工业智能化升级,综述了数据驱动的复杂油藏注采生产优化技术研究与应用,重点讨论了油藏注采连通性分析及生产优化的大数据驱动模型和智能算法研究进展。研究表明,复杂油藏精准构建和快速优化求解是油田生产开发智能化的关键,数据、机理与智能算法的交叉融合是未来智能油田开发研究的发展趋势。Due to the complicated injector-producer correlation and frequent variation of the displacement field,the mature oilfield after water flooding is found with drastic variation of the underground oil/water distribution pattern and requires refined recovery.To promote the intelligentization of the petroleum industry,the research and application of data-driven injection-production optimization of complex oil reservoirs were reviewed,which highlighted big data-driven models and artificial intelligence algorithms for injector-producer connectivity analysis and production optimization.This review indicates that precise modelling of complex oil reservoirs and rapid solving of relevant optimization problems are key to intelligentization of oilfield production and recovery and the crossing and fusion of data,mechanisms,and artificial intelligence algorithms is the development orientation of future research on smart oilfield recovery.

关 键 词：复杂油藏 注采连通性 生产优化 数据驱动 智能算法 

分 类 号：TE35[石油与天然气工程—油气田开发工程] TP399[自动化与计算机技术—计算机应用技术]