In recent years, nuclear magnetic resonance (NMR) logging has become increasingly prevalent in the characterization of rock properties such as porosity, permeability, saturation, and pore size distribution. However, interpreting such properties accurately from NMR logging data is challenging for some reservoirs. In particular, the impact of salinity, viscosity, and saturation on NMR measurements is not always clear, which can lead to inaccuracies in the resulting data interpretation. Properly accounting for these factors is essential in order to obtain accurate and reliable measurements for effective characterization of subsurface formations. This study utilized a random walk technique to simulate the NMR response of homogeneous sandstones using 3D CT images and conducted a sensitivity analysis under various salinity, crude oil viscosity, and water saturation conditions. The results indicate that the T₂ relaxation time slightly shifts toward the short relaxation direction as the salinity of the formation water increases. In addition, longer echo intervals result in a more significant forward shift in the T₂ value than shorter intervals. Whereas, for crude oil, the T₂ relaxation time becomes shorter as its viscosity increases. Furthermore, the effect of echo interval on the forward T₂ shift is less pronounced for crude oil than it is for formation water. Under water wet conditions, the T₂ spectrum of crude oil exhibits a peak at the volume relaxation position. As the water saturation decreases, the left two peaks in the T₂ spectrum shift toward shorter relaxation times. Under oil wet conditions, the T₂ spectrum exhibits a complex three-peak structure. The method provides a physical basis for interpreting NMR macroscopic responses, and the simulated NMR responses can help identify fluids in reservoirs.

The Pinghu Formation is a low permeability sandstone reservoir in the KQT Region, East China Sea. Its porosity ranges from 3.6 to 18.0%, and permeability is distributed from 0.5 to 251.19 mD. The relationship between porosity and permeability was poor due to strong heterogeneity. This led to the difficulty of quantitatively evaluating effective reservoirs and identifying pore fluids by using common methods. In this study, to effectively evaluate low permeability sandstones in the Pinghu Formation of KQT Region, pore structure was first characterized from nuclear magnetic resonance (NMR) logging based on piecewise function calibration (PFC) method. Effective formation classification criteria were established to indicate the “sweet spot”. Afterwards, several effective methods were proposed to calculate formation of petrophysical parameters, e.g., porosity, permeability, water saturation (S_w), irreducible water saturation (S_wirr). Finally, two techniques, established based on the crossplots of mean value of apparent formation water resistivity (R_wam) versus variance of apparent formation water resistivity (R_wav)—S_w versus S_wirr—were adopted to distinguish hydrocarbon-bearing formations from water saturated layers. Field applications in two different regions illustrated that the established methods and techniques were widely applicable. Computed petrophysical parameters matched well with core-derived results, and pore fluids were obviously identified. These methods were valuable in improving low permeability sandstone reservoirs characterization.

Summary: Nuclear magnetic resonance (NMR) logging has been extensively utilized for identifying pore fluids in recent years. However, after oil-based mud (OBM) invasion, OBM filtrate partially takes the place of the original fluid in the reservoir and the morphology of the NMR T2 (transverse relaxation time) spectrum changes. OBM invasion makes it difficult to identify the formation fluid using routine NMR fluid identification methods. In this study, we took heterogeneous conglomerate formation in the northwestern Junggar Basin as a case study and carried out core experiments under four conditions (viz., water-saturated, OBM displacing water, oil-saturated, and OBM displacing oil) and simulated the states of OBM invasion into water and hydrocarbon-bearing formation. Comparative analysis finds that when the OBM invades the water layer, the movable peak of the T2 spectrum primarily reflects the bulk relaxation characteristics of OBM filtrate, whereas when the OBM invades into the oil layer, the T2 spectrum may exhibit a three-peak distribution, where the first peak mainly indicates irreducible water, the second peak reflects OBM filtrate, and the third peak primarily reflects nondisplaced oil. To facilitate fluid identification, two T2 cutoffs are adopted to divide the T2 spectrum into three segments, and combined with the T2 geometric average, a fluid identification factor (ifluid) is proposed. Finally, identification criteria for reservoir type are established on the NMR logging and drillstem test data. The field application verifies the reliability of the proposed methods. These methods realize the identification of oil layers under OBM drilling and guide the subsequent production and development of oil reservoirs.