Abstract
Ultra-low permeability argillaceous sandstone reservoirs have become a significant focus for exploration and development. Saturation is a crucial parameter in evaluating such reservoirs. Due to the low porosity, low permeability, complex pore structure, and strong heterogeneity in ultra-low permeability argillaceous sandstone reservoirs, traditional evaluation methods are unable to achieve the required level of interpretation accuracy. To improve the accuracy of gas saturation calculations in ultra-low permeability argillaceous sandstone gas reservoirs, the conductivity characteristics of the ultra-low permeability argillaceous sandstone gas reservoirs in the Huangliu Formation in the Dongfang area, China, were analyzed through rock physics experimental data and geological information. The results revealed the clay content in the study area to range from 6% to 33.4%. Influenced by burial depth and temperature, kaolinite and montmorillonite transform into illite and chlorite, and the cation exchange capacity is not correlated with the clay content. This suggests that the effects of cation-attached conductivity can be ignored. The regional variation in rock electrical parameters is significant. When the lithology coefficient is a = 1, the consolidation index m varies between 1.25 and 1.75. When the lithology coefficient is b = 1, the saturation index n varies between 1.6 and 1.96. Under the influence of high temperature and pressure, the reservoirs in the study area exhibit two distinct characteristics on the capillary pressure curve, fractal dimension, and effective porosity index intersection diagram, (1) In Class I reservoirs, there is a strong correlation between the formation factor and natural gamma, as well as porosity, and a logarithmic relationship between the saturation exponent and the formation factor; and (2) in Class II reservoirs, there is a strong power-law relationship between the formation factor and porosity, as well as a logarithmic relationship between the saturation exponent and formation factor. Based on experimental and logging data, reservoir classification was conducted using core-scale logging and principal component analysis. Additionally, a saturation interpretation model was developed using multivariate regression, based on rock electrical parameters. The actual application results demonstrate that compared to the fixed rock resistivity saturation model, this model has reduced the average absolute error by 5.9%. The calculated values are consistent with the gas saturation analysis of the core at the pure gas section as determined by cable testing sampling. This model meets the requirements of practical production. The study of this interpretation method is of great significance for the formulation of development plans for ultra-low permeability offshore argillaceous sandstone gas reservoirs.