Saturation Model Based on Effective Medium Theory for Shale Oil Reservoirs

As an essential unconventional resource in the global energy transition, the development efficiency of shale oil plays a vital role in shaping the international oil and gas supply framework. The lacustrine shale oil reservoirs within the Qingshankou Formation of China’s Songliao Basin present unique challenges in petrophysical characterization, primarily due to their high clay content and complex heterogeneous pore architectures. Existing saturation models, which were initially developed for shaly sand formations, fail to adequately describe the electrical behavior in these clay-rich systems. This is largely due to their reliance on oversimplified conductivity assumptions that neglect pore-scale heterogeneity. To address this critical gap in understanding, we developed an innovative saturation model specifically designed for clay-rich shale reservoirs, leveraging effective medium theory. The proposed saturation model integrates a five-component petrophysical volume model, systematically developed through X-ray diffraction and two-dimensional nuclear magnetic resonance (2D NMR) experiments. These components include wet clay, nonconductive matrix (quartz), oil in organic pores, oil in inorganic pores, and pore water. To operationalize the model, 2D NMR logging and elemental logging were employed to resolve fluid-phase distributions within multiscale pore networks and mineral components, enabling the derivation of five-component profiles. The five-component integrated resistivity logging profiles were processed through an optimization algorithm to determine the percolation rate and percolation exponent in the saturation model. The model’s verification demonstrates high consistency between the effective medium theory saturation profile and the 2D NMR-derived data, with a mean absolute error of 7.47% across three wells, thereby validating both its scientific and practical robustness. This novel approach holds significant implications for reserve assessment, development plan optimization, and economic evaluation in shale oil reservoirs.