石油学报 ›› 2023, Vol. 44 ›› Issue (9): 1574-1586.DOI: 10.7623/syxb202309014

• 综述 • 上一篇    下一篇

人工智能在注水开发方案精细化调整中的应用现状及展望

刘合1,2, 李艳春1, 贾德利2, 王素玲1, 乔美霞1, 屈如意1, 温鹏云1, 任智慧1   

  1. 1. 东北石油大学机械科学与工程学院 黑龙江大庆 163318;
    2. 中国石油勘探开发研究院 北京 100083
  • 收稿日期:2023-03-30 修回日期:2023-07-09 出版日期:2023-09-25 发布日期:2023-10-09
  • 通讯作者: 李艳春,女,1994年4月生,2017年获东北石油大学硕士学位,现为东北石油大学博士研究生,主要从事人工智能在油藏开发中的应用研究。Email:Yachne_Li@163.com
  • 作者简介:刘合,男,1961年3月生,2002年获哈尔滨工程大学博士学位,现为中国石油勘探开发研究院副总工程师、中国工程院院士,主要从事低渗透油气藏增产改造、机采系统提高系统效率、分层注水和井筒工程控制技术等方面的研究。Email:liuhe@petrochina.com.cn
  • 基金资助:
    国家自然科学基金面上项目"大数据驱动下的老油田水驱精细分析方法"(No.52074345)和国家自然科学基金科学中心项目"数字经济时代的资源环境管理理论与应用"(No.72088101)资助。

Application status and prospects of artificial intelligence in the refinement of waterflooding development program

Liu He1,2, Li Yanchun1, Jia Deli2, Wang Suling1, Qiao Meixia1, Qu Ruyi1, Wen Pengyun1, Ren Zhihui1   

  1. 1. School of Mechanical Science and Engineering, Northeast Petroleum University, Heilongjiang Daqing 163318, China;
    2. PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China
  • Received:2023-03-30 Revised:2023-07-09 Online:2023-09-25 Published:2023-10-09

摘要: 水驱开发油田由于注采关系复杂、驱替场动态变化频繁以及长期注水,导致层间矛盾加剧,已进入到深度精细注水开发的新阶段。结合静态与动态生产数据进行注水开发方案调整,有利于掌握油藏的动态变化与实现有效剩余油挖潜。为保证优化的注水方案和先进的分注工艺相结合,系统综述了油藏动态分析技术发展现状,重点阐述了人工智能方法与油藏工程交叉融合辅助注水开发方案调整的核心问题,同时结合前沿智能化理论与方法对未来注水开发方案智能精细化调整趋势进行了探讨和展望,即充分利用精细智能分层注水工艺实时监测的大量动态生产数据。未来注水开发方案优化的研究重点将聚焦于"动态数据+物理约束+人工智能算法"的深度融合,进一步推动水驱开发油田监测数据实时采集、油藏动态实时预测和注水方案实时优化的智能优化应用落地,最终实现注水方案设计与优化和井下分层注水实时调整同步的油藏和采油工程一体化。

关键词: 水驱开发, 注水方案优化, 分层注水, 油藏动态分析, 人工智能

Abstract: Waterflooding development oilfields have entered a new stage of deep and fine waterflooding exploitation due to complex relationships between injection and production, frequent dynamic changes in the displacement field, and aggravated inter-layer conflicts caused by long-term waterflooding. The waterflooding development program was adjusted based on static and dynamic engineering production data, which can help researchers master the dynamic changes in oil reservoirs and achieve effective tapping of residual oil. To realize the combination of waterflooding development program optimization and advanced separated zone waterflooding process, the paper systematically summarizes the development status of dynamic analysis technology for oil reservoirs, and mainly elaborates the core issues of waterflooding development program adjustment based on the intercombination of AI methods and reservoir engineering. Meanwhile, the cutting-edge intelligent theories and methods are used to explore and prospect the trend of intelligent and fine adjustments to future waterflooding development program, namely to make full use of the refined and intelligent separated zone waterflooding process to monitor a large amount of dynamic production data in real time. In the future, the study of waterflooding development program optimization will focus on the deep integration of "dynamic data, physical constraints, and AI algorithm"; it is also suggested to further promote the implementation of the intelligent optimization application, i.e., real-time acquisition of monitoring data of waterflooding development oilfields, real-time dynamic forecasts of oil reservoirs and real-time optimization of waterflooding program, and finally achieve the integration of reservoir and oil recovery engineering based on synchronously implementing the design and optimization of waterflooding program and the real-time adjustment of downhole separated zone waterflooding.

Key words: waterflooding development, waterflooding program optimization, separated zone waterflooding, dynamic analysis of oil reservoir, artificial intelligence

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