X气藏为受背斜构造控制的块状裂缝性边水气藏，受边水水侵的影响，气藏见水迅速，严重降低采收率，亟待科学的理论与方法指导开发实践。为此，研究在系统分析关键参数对采收率的影响规律基础上，构建裂缝水驱气藏采收率预测方法，为动态优化开发方案提供科学依据。基于气藏基础地质与生产数据，运用EDFM（嵌入式离散裂缝模型）建立单井机理模型，通过单因素敏感性分析，揭示水体倍数、采气速度、基质渗透率、渗透率各向异性的作用规律：水体倍数与采收率呈负相关，随着水体倍数增加，气井水气比上升速率显著加快，稳产时间大幅缩短；采气速度对气藏稳产时间影响尤为突出，存在特定的最佳采气速度阈值，可使采收率达到最大值；基质渗透率与采收率呈正相关，基质渗透率越低，气藏采收率越低，水气比上升速度越快，稳产时间越短；渗透率各向异性过低时，由于渗流能力较差导致采收率降低，比值增大则加速水侵使采收率降低。在此基础上，设计125组交叉实验方案，通过数值模拟获取基础数据，进而建立裂缝性水驱气藏采收率预测模型。为提升模型预测精度，对原始数据进行离散化处理，并采用决策树算法构建预测模型。经参数优化后，模型预测精度达到96%。基于X气藏2口生产井的实际动态数据，将该模型预测结果与Blasingame产量递减分析法进行对比验证，结果表明：该模型预测结果与实际生产数据高度吻合，具有较高的可靠性与实用性，为裂缝性水驱气藏采收率预测提供了一种高效、精准的技术手段。

Gas reservoir X is a block-fractured edge-water gas reservoir controlled by anticline structures. Due to edge-water invasion, rapid water breakthrough severely reduced recovery efficiency, highlighting the urgent need for theoretical and methodological guidance for reservoir development. To address this, based on a systematic analysis of the influence patterns of key parameters on recovery rate, a recovery prediction model for fractured water-driven gas reservoirs was established. This model provides a scientific basis for the dynamic optimization of development schemes. Using basic geological and production data, a single-well mechanistic model was constructed with the embedded discrete fracture model (EDFM). Through single-factor sensitivity analysis, the influence patterns of water body multiple, gas production rate, matrix permeability, and permeability anisotropy were revealed. Recovery rate exhibited a negative correlation with water body multiple. As the water body multiple increased, the water-gas ratio of gas wells rose significantly faster, and the stable production time was greatly shortened. Gas production rate had a pronounced impact on the stable production time of the reservoir. An optimal gas production rate threshold existed that maximized the recovery rate. Matrix permeability was positively correlated with recovery rate. Lower matrix permeability led to lower recovery rate. The faster the increase in water-gas ratio, the shorter the stable production time. When permeability anisotropy was too low, poor seepage capacity resulted in a reduced recovery rate. An increased ratio accelerated water invasion, further decreasing the recovery rate. Based on these findings, 125 sets of cross-experimental schemes were designed, and basic data were obtained through numerical simulations. A recovery rate prediction model for fractured water-driven gas reservoirs was established. To improve the prediction accuracy of the model, the original data were discretized, and a decision tree algorithm was used. After parameter optimization, the prediction accuracy of the model reached 96%. The model was validated using actual dynamic data from two production wells in the gas reservoir X. The prediction results were compared with those from the Blasingame production decline analysis method. The results showed high consistency between model predictions and actual production data, indicating high reliability and practicality of the model. This provides an efficient and precise technical method for recovery rate prediction in fractured water-driven gas reservoirs.