Study on an improved saturation parameter method based on joint inversion of NMR and resistivity data in porous media

CO₂ storage capacity is significantly influenced by the saturation levels of reservoir rocks, with underground fluid saturation typically evaluated using resistivity data. The conductive pathways of fluids in various states within rock pores differ, alongside variations in conductive mechanisms. To clarify the conductivity of water in rocks across different states, this study employed a three–pore segment saturation model, which corrected for the additional conductivity of clay by categorizing water into large–pore segment, medium–pore segment, and small–pore segment types. Addressing the heterogeneity of tight sandstone reservoirs, we classified distinct pore structures and inverted Archie equation parameters from NMR logging data using a segmented characterization approach, yielding dynamic Archie parameters that vary with depth. Ultimately, we established an improved saturation parameter method based on joint inversion of NMR and resistivity data, which was validated through laboratory experiments and practical downhole applications. The results indicate that this saturation parameter inversion method has been effectively applied in both settings. Furthermore, we discussed the varying conductive behaviors of fluids in large and medium pore segment under saturated and drained states. Lastly, we proposed a workflow for inverting saturation based on downhole data, providing a robust foundation for CO₂ storage and predicting underground fluid saturation.