气藏水侵动态评价与预测方法研究进展及应用展望

Research Progress and Application Prospects of Dynamic Evaluation and Prediction Methods for Water Invasion in Gas Reservoirs

摘要: 气藏水侵是影响有水气藏开发效果和采收率的关键因素，其动态受储层非均质性、裂缝发育、生产制度及气水界面演化等多因素控制。近年来，随着边底水、裂缝性及超深层气藏开发深入，在水侵机理、实验模拟、动态评价与预测优化方面取得显著进展。本文系统综述了该领域研究现状：水侵机理由均质理论发展为考虑非均质性、裂缝导流及多场耦合的综合认识；实验从常规岩心驱替拓展到大型物理模拟、多尺度与实时监测；评价预测方法由经典解析模型演进至数值模拟、智能优化与数字化分析。总体而言，气藏水侵研究正从单尺度、经验化向多尺度、多场耦合与智能化方向发展。未来应强化实验、监测、机理与人工智能的深度融合，构建机理约束下的智能预测体系，实现复杂气藏水侵的实时识别、动态预测与开发优化，支撑有水气藏高效开发。

Abstract: Gas reservoir water invasion is a key factor affecting the development performance and ultimate recovery of water-bearing gas reservoirs. Its dynamics are jointly controlled by multiple factors, including reservoir heterogeneity, fracture development, production strategy, and gas-water interface evolution. In recent years, with the increasing development of edge-bottom water gas reservoirs, fractured gas reservoirs, and ultra-deep complex gas reservoirs, significant progress has been made in water invasion mechanisms, experimental simulation techniques, dynamic evaluation methods, and prediction and optimization theories. This paper systematically reviews the current research status in this field. The understanding of water invasion mechanisms has evolved from homogeneous medium theory to a comprehensive understanding incorporating reservoir heterogeneity, fracture conductivity, and multi-field coupling effects. Experimental studies have expanded from conventional core displacement to large-scale physical simulation, multi-scale experiments, and real-time monitoring. Evaluation and prediction methods have advanced from classical analytical models to numerical simulation, intelligent optimization, and digital analysis. Overall, research on gas reservoir water invasion is transitioning from single-scale, empirical analysis toward multi-scale, multi-field coupling, and intelligent prediction. Future efforts should strengthen the deep integration of experiments, dynamic monitoring, mechanistic models, and artificial intelligence to establish a mechanism-constrained intelligent prediction system, enabling real-time identification, dynamic prediction, and development optimization of water invasion processes in complex gas reservoirs, thereby providing theoretical support for the efficient development of water-bearing gas reservoirs.