Integration of core and pore-scale data for constructing a new saturation model in ultra-low permeability reservoirs

Abstract Ultra-low-permeability clastic reservoirs, characterized by poorly developed pore structures and extremely low permeability, pose significant challenges for accurately estimating oil saturation using the Archie equation and its derivative models. The primary limitation arises from the difficulty of oil–water displacement at the pore scale, which prevents reliable resistivity measurements under low water saturation conditions in laboratory experiments. These constraints ultimately hinder both sweet-spot identification and reserves evaluation. In this work, digital rock physics is applied to construct digital rocks with varying water saturations, enabling investigation of low-saturation resistivity through pore-scale numerical simulations. By integrating core-scale experimental results with pore-scale simulation data, we propose a two-scale integrated saturation model. The Wenchang Formation in the Huizhou region is selected as the case study. Digital rocks are reconstructed from X-CT images at two resolutions. The resistivity of fully saturated rock is simulated using the finite element method, and the formation factor–porosity relationship (F–ϕ) is established through cross-plots. The resistivity of cores at different water saturations is further simulated to derive the resistivity index, and the resistivity index–water saturation relationship (RI–Sw), which follows an exponential trend in double-logarithmic coordinates. Based on these results, a new saturation equation tailored for ultra-low-permeability reservoirs is developed by integrating pore-scale simulations with core-scale experiments. The calculated oil saturation values using this model are in good agreement with sealed-core measurements, whereas Archie-based results are underestimated. The proposed model substantially improves oil saturation prediction in ultra-low-permeability reservoirs, enabling more accurate hydrocarbon reserve assessment and enhancing exploration potential in the study area.