Statistical analysis of determining porosity factor of oil and gas reservoir rocks using gas volumetry and X-Ray tomography methods

To address the current challenges in oil industry related to modeling a pore space structure in a 3D core model and evaluating permeability and porosity ("Digital Core"), it is necessary to obtain representative characteristics of the void space. A similar characteristic is required to solve geotechnical problems related to modeling and evaluating the strength properties of heterogeneous rocks. In addition, it is also important for research on capillary processes in porous media. The paper is devoted to the comparative analysis of the values of porosity of oil and gas reservoir rocks obtained by gas volumetry and X-ray computer tomography methods. The aim of this work is to develop statistical models for assessing the discrepancy between the porosity factor K p determined using computer tomography (CT) data and more reliable laboratory petrophysical data for two lithological rock types: terrigenous and carbonate. The research objectives include: assessing the impact of lithology on the K p evaluation using various methods (petrophysics and CT); examining and evaluating the impact of the reservoir rocks porosity factor range on the convergence of the results from these two methods for different lithological rock types; building statistical models to adjust the K p values based on CT results for different lithological rock types. The solution to these problems is based on a detailed statistical analysis of the studies of terrigenous and carbonates rocks in oil fields in the Perm region. Porosity measurement was carried out on a AP-608 automated porosimeter-permeameter and a Nikon XT H 225 X-ray tomography system. The techniques for measuring the volume of pores in samples using the gas volumetry method, image binarization, and porosity calculation using the X-ray tomography method are described. The results of the analysis showed that the studied methods give different values of porosity factors depending on the lithology. For carbonate rocks, a greater correspondence of the porosity factor estimates obtained by different methods is characteristic that is due to the structural features of the pore space. Significant differences were found for terrigenous rocks, which are explained by the limited resolution of X-ray tomography. The analysis resulted in statistical models for evaluating and correcting K p data obtained by X-ray tomography for terrigenous and carbonate rocks in various K p value ranges. The results of the study can be used for petrophysical substantiation of the permeability and porosity of reservoir rocks in oil and gas fields.