基于电成像测井资料的碳酸盐岩储层产能预测

Productivity Prediction Method of Carbonate Reservoir Based on Micro-resistivity Imaging Logging

介绍基于常规测井与微电阻率扫描成像测井资料相结合进行产能预测的方法。针对孔隙型碳酸盐岩储层厚度大、非均质性强的特点进行了储层单元划分;对多层合试及单一非均质厚层试油,应用计算累计孔隙空间体积及含油性对产能进行重新分配;通过提取孔隙非均质性特征参数构建产能贡献因子,建立了适合于孔隙型碳酸盐岩储层的产能预测模型。经2口井4个试油层段验证,平均相对误差为5.95%,效果良好。

This paper introduces a prediction method based on conventional logging data and the micro-resistivity imaging logging data.According to the porous carbonate reservoir with large thickness and high heterogeneity,we classified the reservoir units first;for thick oil multilayer and single layer testing,according to the calculation of accumulative total pore space and oiliness,the productivity is re-distributed; with extracting the characteristic parameters of pore heterogeneity,we build porosity contribution factor and capacity contribution factor,and establish a suitable porous carbonate reservoir productivity prediction model. After the verification from 4testing layers of 2wells,the average relative deviation we got is 5.95% which reveals good benefit.