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.

There are abundant igneous gas reservoirs in the South China Sea with significant value of research, and lithology classification, mineral analysis and porosity inversion are important links in reservoir evaluation. However, affected by the diverse lithology, complicated mineral and widespread alteration, conventional logging lithology classification and mineral inversion become considerably difficult. At the same time, owing to the limitation of the wireline log response equation, the quantity and accuracy of minerals can hardly meet the exploration requirements of igneous formations. To overcome those issues, this study takes the South China Sea as an example, and combines multi-scale data such as micro rock slices, petrophysical experiments, wireline log and element cutting log to establish a set of joint inversion methods for minerals and porosity of altered igneous rocks. Specifically, we define the lithology and mineral characteristics through core slices and mineral data, and establish an igneous multi-mineral volumetric model. Then we determine element cutting log correction method based on core element data, and combine wireline log and corrected element cutting log to perform the lithology classification and joint inversion of minerals and porosity. However, it is always difficult to determine the elemental eigenvalues of different minerals in inversion. This paper uses multiple linear regression methods to solve this problem. Finally, an integrated inversion technique for altered igneous formations was developed. The results show that the corrected element cutting log are in good agreement with the core element data, and the mineral and porosity results obtained from the joint inversion based on the wireline log and corrected element cutting log are also in good agreement with the core data from X-ray diffraction. The results demonstrate that the inversion technique is applicable and this study provides a new direction for the mineral inversion research of altered igneous formations.