一种物理约束的多参数耦合储层有效性评价方法

A Physically Constrained Multi-Parameter Coupling Method for Reservoir Effectiveness Evaluation

摘要: 致密气藏具有低孔、低渗和强非均质性特征，有效储层识别难度大。针对S致密气藏某区块，本文在分析储层地质特征及参数响应规律的基础上，综合采用Spearman相关分析、距离相关系数和互信息方法刻画参数关联特征，结合随机森林与SHAP分析筛选关键控制因素，构建融合物性主控作用、测井响应调节及泥质削弱影响的储层有效性综合指数(REI)，并通过统计检验与实际井资料进行验证。结果表明，渗透率和孔隙度为主控因素，泥质含量对储层品质具有显著负向影响；REI与岩心渗透率的相关系数为0.78，有效储层识别的AUC达0.89，较传统单参数方法精度提升10%以上，该方法可为同类致密气藏的有效评价与有利区优选提供技术支持。

Abstract: Tight gas reservoirs are characterized by low porosity, low permeability, and strong heterogeneity, which make the identification of effective reservoirs challenging. Taking a block of the S tight gas field as a case study, this paper analyzes reservoir geological characteristics and petrophysical response patterns. Spearman correlation, distance correlation, and mutual information were jointly applied to characterize parameter relationships. Random forest and SHAP analyses were then used to identify key controlling factors. Based on these results, a Reservoir Effectiveness Index (REI) was developed by integrating the dominant control of petrophysical properties, the regulatory effect of logging responses, and the attenuation effect of shale content under physical constraints. The model was validated using statistical tests and production data from actual wells. The results indicate that permeability and porosity are the primary controlling factors, while shale content exerts a significant negative impact on reservoir quality. The REI shows a correlation coefficient of 0.78 with core permeability, and the AUC for effective reservoir identification reaches 0.89, representing an improvement of more than 10% over traditional single-parameter methods. The proposed approach provides technical support for effective reservoir evaluation and favorable zone selection in similar tight gas reservoirs.