Application of Multifractal Analysis Theory to Interpret T-2 Cutoffs of NMR Logging Data: A Case Study of Coarse Clastic Rock Reservoirs in Southwestern Bozhong Sag, China

The Paleocene Kongdian Formation coarse clastic rock reservoir in Bozhong Sag is rich in oil and gas resources and has huge exploration potential. However, the coarse clastic rock reservoir has the characteristics of a complex pore structure and strong heterogeneity, which restrict the accuracy of evaluating the reservoir's physical properties, such as porosity and permeability, for field evaluation. Nuclear magnetic resonance (NMR) technology has become a popular methods for unconventional reservoir evaluation because it can obtain abundant reservoir physical property information and because of its ability to identify fluid characteristics information. The transverse relaxation time (T-2) cutoff (T-2C) value is an important input parameter in the application of NMR technology. The accuracy of the T-2C value affects the accuracy of the reservoir evaluation. The standard method for determining the T-2C value requires a series of complicated centrifugation experiments in addition to the NMR experiments, and its application scope is limited by obtaining enough core samples. In this study, 14 core samples from the coarse clastic rock reservoir in the southwestern Bozhong sag of the Bohai Bay Basin were selected, and NMR measurements were carried out under the conditions of fully saturated water and irreducible water to determine the T-2C value. Based on the multifractal theory, the NMR T-2 spectrum of the saturated sample was analyzed, and the results show that the NMR T-2 distribution of the saturated sample has multifractal characteristics, and the multifractal parameter D-q and the singular intensity range Delta alpha have a strong correlation with the T-2C value. Thus, based on multiple regression analyses of the multifractal parameters with the experimental T-2C value of 10 core samples, we propose a method to predict the T-2C value. After applying this method to 4 samples that were not used in the modeling, we confirmed that this method can be used to predict the T-2C value of core samples. Furthermore, we expanded this method to the field application of a production well in Bozhong sag by adding an empirical index in the model. The new model can be used to directly calculate the T-2C value of NMR logging data, and it does not require any other extra data, such as those from core analysis. This method is applicable in fast reservoir evaluations by only using NMR logging data in the field. The research results improve the accuracy of field NMR logging reservoir evaluations.