Studies and Applications of Dual Pore Saturation Model Based on Pore Structure Classification in Tight Reservoirs

The complex pore structure of rock may influence resistivity logs and make it challenging to perform saturation estimations with better precision. For example, water saturation may go higher or lower when Archie’s formulae are used to obtain the saturation as the logging resistivity may become greater or smaller, due to the influences of complex pore structures in the reservoirs. In this paper, having considered the influences of pore structure on logging resistivity, we have developed a different algorithm to improve the equivalent rock element model (EREM, a rock conduction model) to have better water saturation. First of all, the nuclear magnetic resonance (NMR) echo data of cores are inverted by using the optimized inversion to calculate pore parameters, such as the average radius of spherical pore tubular pore, Cd path, and sorting coefficient. Secondly, according to the parameters derived from the optimization inversions, the pore structures of the core are divided into different groups. Based on the classifications of the pore structure, the conduction parameters of rock for different pore structures are determined by fitting the experimental conduction data of rock with a damping factor. Finally, the working flow of calculating fluid saturation according to the EREM model is determined for different conduction parameters. The key feature of the improved EREM saturation model is to eliminate the influence of pore structure on rock conduction, highlight the influence of pore fluid on rock conduction, and then improve the calculation accuracy of saturation in it. The applications of our research show that the saturation estimations derived from the improved EREM model appear to be more reasonable in terms of the saturation value and its numerical trend. Thus, the improved EREM model has potential in petroleum exploration and exploitation.