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<p>In the process of heavy oil steam injection development, the production performance of well groups often exhibits nonlinearity and high uncertainty. Traditional decision-making methods for steam injection timing, which rely on manual experience and static analysis, fail to meet the dynamic needs of reservoir development. To address this issue, this study establishes a production data mining model and, based on full utilization of production data, builds an intelligent decision-making model for steam injection timing. Through case analysis, the study demonstrates the advancement of the intelligent decision-making model and lays a foundation for further promoting the development of heavy oil steam injection. Research results show that by applying the system to five typical well groups in a certain oilfield, the average production increase reached 17.6%, steam injection savings were between 15% and 25%, and the decision accuracy exceeded 90%. This significantly improved recovery efficiency and economic benefits. The conclusion indicates that the intelligent decision system can provide scientific, precise, and efficient technical support for heavy oil thermal recovery and has broad prospects for application and promotion.</p>

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Research on Production Data Mining and Steam Injection Timing Intelligent Decision System for Heavy Oil Thermal Recovery Well Groups

  • 期刊论文

  • 发表日期：

    2026年3月1日

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  • Lu Jia,
  • Guowei Shi,
  • Sixu Li,
  • Guorong Li,
  • Peng Chen,
  • Xin Wang

摘要

In the process of heavy oil steam injection development, the production performance of well groups often exhibits nonlinearity and high uncertainty. Traditional decision-making methods for steam injection timing, which rely on manual experience and static analysis, fail to meet the dynamic needs of reservoir development. To address this issue, this study establishes a production data mining model and, based on full utilization of production data, builds an intelligent decision-making model for steam injection timing. Through case analysis, the study demonstrates the advancement of the intelligent decision-making model and lays a foundation for further promoting the development of heavy oil steam injection. Research results show that by applying the system to five typical well groups in a certain oilfield, the average production increase reached 17.6%, steam injection savings were between 15% and 25%, and the decision accuracy exceeded 90%. This significantly improved recovery efficiency and economic benefits. The conclusion indicates that the intelligent decision system can provide scientific, precise, and efficient technical support for heavy oil thermal recovery and has broad prospects for application and promotion.