利用C5.0决策树算法解释碳酸盐岩储层渗透率

Application of C5.0 Decision-tree Algorithm to Interpret Permeability of Carbonate Reservoir

以某油田孔隙型碳酸盐岩为例,提出利用C5.0决策树算法解释储层渗透率。在常规物性分析和测井资料基础上,根据孔隙结构表征参数建立储层分类标准并回归渗透率计算公式。通过多个测井曲线资料组合构建及决策树建模分析,优选出储层分类表现最佳的资料组合和模型,使用该模型将取心段储层分类标准和渗透率计算公式推广到非取心段,完成测井解释。通过与岩心渗透率相比较,该方法得到的渗透率误差整体较小,并且非含水采油井射孔段渗透率与米采油指数呈正相关关系,说明该方法的有效性。所使用的常规物性分析和测井资料是最常见的油气田静态资料,该方法具有一定的普适性。

Based on a case study of porous-type carbonate rock,application of C5.0 decision-tree to logging permeability interpretation is proposed.According to parameter characterizing pore configuration,rock typing standard is constructed and computing formula of permeability is obtained,both of which are on the basis of conventional cored physical property analysis in laboratory and well logging data.Several composites of well logging data are designed and used to build decision-tree model,from which the one with best performance is selected.With the chosen composite and corresponding model,the classification criterion and computing formula of permeability are extended from cored intervals to uncored ones,achieving the goal of interpreting logging permeability.Compared with core permeability in laboratory,the resulting permeability has a relatively minor error.Furthermore,on producers without water production the interpreted permeability of perforation interval shows a good relationship with productivity index,indicating the effectiveness of the approach.Due to availability of conventional physical property and well logging data,the proposed method shows its universality on permeability interpretation.