基于阵列感应测井电频散特征的碳酸盐岩储层油水识别方法OA

The salt lake carbonate rocks have the characteristics of strong heterogeneity and high formation water salinity,which easily leads to insignificant resistivity differences between oil and water layers,thereby causing difficulties in identifying reservoir fluids.In the traditional array induction logging data processing process,the electrical dispersion characteristics of the multi-frequency raw data are often eliminated during the skin effect correction,and thus are not effectively utilized.Therefore,starting from the microscopic mechanism of the inter-face polarization effect,this study reconstructs the real and imaginary parts of the conductivity spectrum based on the multi-frequency raw conductivity curves of the deep detection sub-array of array induction logging,achieving qualitative discrimination of the fluid properties of carbonate reservoirs in the study area.Meanwhile,the conductivity dispersion degree calculation formula is introduced,and the electrical dispersion characteristics of the insitu formation fluids are quantitatively evaluated based on the multi-frequency raw conductivity of the deep detection sub-array of array induction logging.A new set of fluid identification charts is constructed by com-bining the resistivity values after wellbore correction and porosity normalization.The results show that this method and model have good applicability in the identification of fluids in salt lake carbonate reservoirs,effec-tively compensating for the deficiency of traditional single reliance on the absolute value of resistivity for fluid discrimination,and have good application prospects.