Permeability Estimation Using Tensor Based on Critical Path Analysis for Anisotropy Media

Permeability is a crucial factor in oil and gas exploration and development, as it indicates a reservoir's ability to flow. To predict permeability from electrical exploration results, Critical Path Analysis (CPA) is commonly used by combining reservoir permeability and electrical conductivity. However, the accuracy of CPA decreases when unconventional reservoirs exhibit strong anisotropy, such as fractured shales. This study presents tensor-based CPA methods that utilize equivalent electrical parameters and permeability tensor to address this issue. The approach involves obtaining critical pore radius and permeability in tensor form through matrix operation. The accuracy of the CPA formula in calculating reservoir permeability is then compared with numerical simulation results. The findings indicate that the tensor-based CPA method significantly improves the permeability prediction accuracy of anisotropic media, and further improvements can be made using the revised tensor-based CPA.