A Prediction Method of Compacted Rock Hydraulic Permeability Based on the MGEMTIP Model

The permeability of the fluid-bearing rock is an important parameter for reservoir prediction. The Kozeny-Carman (K-C) formulation based on electrical measurements effectively characterizes the permeability-resistivity relationship of rocks with a single mineral composition or high porosity. The complex pore structure and mineral composition of compacted reservoirs affect induced polarization (IP) characteristics, indirectly limiting the applicability of conventional electrical K-C models. The permeability of fluid-bearing rocks is an important parameter for reservoir prediction. The theoretical chargeability of the modified generalized effective medium theory of induced polarization (MGEMTIP) model includes the effects of various conductive minerals. Due to the disconnection assumption of the disturbed medium in the MGEMTIP, there is a significant difference between the theoretical chargeability and the measured chargeability, and the difference is a sensitive parameter of rock permeability. A semi-empirical reservoir permeability prediction model is proposed based on the MGEMTIP. Theoretically and experimentally, the prediction model based on MGEMTIP is compared with the two electrical K-C models. Under the condition that the rock does not contain low-resistivity minerals, the prediction model based on MGEMTIP is theoretically equivalent to the K-C model. The experimental results show that this prediction model is more suitable for low-porosity and low-permeability rocks containing low-resistivity minerals, and the prediction results can be effectively restricted to the same order of magnitude. From the perspective of differences between model assumptions and natural rocks, the prediction model provides a semi-empirical relationship between complex mineral IP characteristics and permeability. Combined with the geological information of the survey area, the permeability prediction model can provide a theoretical basis for reservoir permeability prediction based on electromagnetic exploration.