Characteristics of Pore Oil-Water Occurrence in Shale Oil Reservoirs Using NMR Technique

Efficient exploration and development of shale oil heavily rely on the precise evaluation of multiphase pore fluids within reservoirs. Currently, two-dimensional (2D) nuclear magnetic resonance (NMR) T₁-T₂ spectra effectively characterize multiphase pore fluids, but prolonged acquisition times restrict their routine application. Conversely, one-dimensional (1D) NMR T₂ measurements offer rapid acquisition but suffer from severe signal overlap. To address this limitation, a T₂ spectral fluid identification method based on a skewed Gaussian mixture model is introduced in this study. NMR T₂ and T₁-T₂ experiments were conducted on shale samples from the Qingshankou Formation in the Sanzhao Sag under five specific states: as received (AR), water restoration (WR), water and oil restoration (WOR), solvent extracted and dried (Dry), and oil saturated (SO). By extracting T₂ projection spectra from the 2D T₁-T₂ spectra, conversion coefficients between the projections and 1D T₂ spectra were established to decouple the overlapping fluid signals. The results indicate that, in the SO state, the ratio of adsorbed oil to bound oil in the 1D T₂ spectrum is 2.4999 times that in the T₂ projection spectrum, with a conversion coefficient of 0.1179 determined for the (pseudo)-solid component. By applying these conversion factors, the pore fluid signals within the T₂ spectra at the WOR state were successfully identified. Under the WOR conditions, capillary-bound water exhibits the highest conversion coefficient (0.5171). Notably, the presence of pore water significantly lowers the conversion factors for adsorbed and bound oil (0.3663 and 0.1491, respectively) compared to the SO state, whereas movable oil demonstrates no significant correlation. Furthermore, the pore size distributions associated with each fluid type were delineated. These findings facilitate more accurate identification of multiphase pore fluids from 1D T₂ spectra, providing novel insights into NMR-based fluid evaluation in shale oil reservoirs.