Thirty-eight samples from tight sandstone reservoir in the upper Paleozoic layer of Ordos Basin, China were examined. The micropore structure of the reservoir was observed by casting thin sections, which were analyzed via scanning electron microscopy. The pore size distribution characteristics of the reservoir were studied via high-pressure mercury injection. The fit of five different models to the fractal characteristics of the tight gas sandstone reservoir were analyzed, and the fractal characteristics of pores in tight sandstone reservoirs were further revealed. Pores were divided into microscale macropores (P 1 ) (>10 μm), microscale micropores (P 2 ) (1−10 μm), submicron pores (P 3 ) (100 nm−1 μm), and nanopores (P 4 ) (2−100 nm). The results show that P 2 account for 63.24% of the total pore volume in type I reservoirs. P 3 are dominant in type II reservoirs, accounting for 51.74% of the total pore volume. Type III reservoirs are mainly composed of P 3 and P 4 , accounting for 48.96% and 41.88% of pore volume, respectively. In type IV reservoirs, P 4 is the main pore size followed by P 3 , accounting for 54.98% and 36.96%, respectively. The Brooks−Corey model can characterize the pore fractal characteristics of the tight sandstone reservoir effectively, while other models presented some limitations. The evaluation of fractal characteristics showed that the three-segment fractal fitting curve was closely related to the inflection point of the S Hg /P c −S Hg curve. The fractal dimensions of P 1 , P 2 , P 3 , and P 4 were 2.904−2.998, 2.384−2.999, 2.155−2.951, and 2.151−2.911, with average values of 2.9826, 2.951, 2.69, and 2.604, respectively. The correlation between the stage pore fractal dimensions and reservoir parameters showed that the fractal dimensions of P 3 and P 4 better reflected the complexity of the pore throats and were more suitable for pore throat heterogeneity characterization. In tight gas sandstone reservoirs, porosity shows relatively low sensitivity to fractal dimensions, while permeability is controlled by the fractal dimensions of P 1 to a great extent. Thus, reservoirs featuring regular macropores are favorable target areas for oil and gas filling.

Nuclear magnetic resonance (NMR) T2 cutoff value is an important parameter for pore structure evaluation. It is complicated and uneconomical to obtain T2 cutoff value by an experimental method; therefore, it is necessary to explore a prediction method of T2 cutoff value. In this paper, 10 samples of tight gas reservoirs in the eastern Ordos Basin were selected, and then saturation and centrifugal experiments of nuclear magnetic resonance were carried out. On this basis, multifractal theory was introduced to calculate the multifractal characteristics of the NMR T2 spectrum of each sample, and the relationship between multifractal parameters and T2 value was analyzed. The influencing factors of the T2 cutoff value were clarified, and the prediction model of the T2 cutoff value was constructed accordingly. The results show that the T2 spectra of sandstones in the study area can be divided into three types: single steeple peak, double steeple peak, and irregular double peak. The pore diameter of the three types is 1 nm ~ 3×104 nm, 1 nm ~ 104 nm and 1 nm ~ 4×103 nm, respectively. The T2 cutoff value ranges from 9.72 to 35.16 ms. The correlation analysis suggests that the symmetrical fractal dimension difference and symmetrical multifractal dimension ratio (Dmin−Dmax, Dmin/Dmax) shows a positive linear correlation with the T2 cutoff value. The value of T2 cutoff gradually decreases with the increase of the flow zone indicator (FZI). Therefore, three parameters, including symmetrical fractal dimension difference, symmetrical multifractal number ratio, and FZI are optimized, and the prediction model for the NMR T2 cutoff value of sandstone samples in the study area is proposed. The introduction of porosity‐related parameters compensates for the shortcomings of previous T2 cutoff value prediction models. At the same time, the prediction model is proven to be accurate and reliable by testing the measured data of the samples near the study area. The results of this paper can be used for further study of the NMR T2 cutoff value prediction of tight sandstone reservoirs in different areas.