Classification of Tight Sandstone Reservoirs Based on the Nuclear Magnetic Resonance T2 Distribution: A Case Study on the Shaximiao Formation in Central Sichuan, China

Abstract

The classification of tight sandstone reservoirs is of significance for hydrocarbon exploration and production. Different from conventional reservoirs, tight sandstone reservoirs are characterized by a complex pore structure and strong heterogeneity. Tight sandstone reservoir classification may not be reliable with conventional reservoir classification methods. In this paper, a classification method of tight sandstone reservoirs was proposed on the basis of the nuclear magnetic resonance (NMR) transverse relaxation (T2) distribution, and it was employed for reservoir classification on the Shaximiao Formation in central Sichuan, China. As a result of the complex pore structure of a tight sandstone reservoir, the NMR T2 distribution is characterized by the presence of multiple peaks. Therefore, the three-peak Gaussian function was used to fit the T2 distribution and obtain the characteristic parameters. On the basis of high-pressure mercury intrusion (HPMI) experiments, the correlation between the characteristic parameters of the NMR T2 distribution and pore structure parameters and petrophysical properties was analyzed, and then the optimal characteristic parameters of the NMR T2 distribution were selected according to the results of correlation analysis and used to establish the pore structure index. In combination of petrophysical properties with the pore structure index, the model for classification of tight sandstone reservoirs was established by the naive Bayesian method based on hierarchical clustering, and the accuracy of the model was verified by k-fold cross-validation. Finally, the effectiveness of the proposed method was verified using the actual NMR logging data in conjunction with the oil test data. The results showed that the method for classification of tight sandstone reservoirs based on the NMR T2 distribution can provide effective guidance for production capacity evaluation.