Radial inversion method of oil saturation using combined nuclear magnetic resonance and resistivity logging for application to low-resistivity-contrast reservoirs

Estimation of oil saturation in low-resistivity-contrast reservoirs using resistivity-log analysis is an inherently challenging process. However, nuclear magnetic resonance (NMR) logging is less sensitive to formation-water salinity and rock matrix variations when predicting fluid properties. Integrating a greater volume of well logging data to effectively address the issue of reservoir parameter calculation represents the trend of big data development. This feature allows NMR logging to have significant advantages over conventional resistivity-based methods in evaluating low-resistivity-contrast reservoirs. The proposed method of estimating oil saturation integrates both NMR and resistivity logging data through two key steps. First, the oil saturation of the invaded zone is estimated using an NMR-based oil saturation model, which has been validated through experimental NMR data obtained from oil-bearing rock samples. Second, the oil saturation of the uninvaded zone is derived by inverting a resistivity-based oil saturation model. Based on analyses of the experimental data and thin sections, the primary reason for low resistivity-contrast in the study area is attributed to the presence of montmorillonite and illite–montmorillonite mixed-layer minerals. The application results demonstrate that the oil saturation calculated using this new method aligns well with both experimental measurements and production test data. Compared to the Archie model that is normally applied in resistivity-contrast reservoirs, the proposed method shows improved accuracy, indicating its effectiveness for such reservoir evaluations.