Experimental and Fractal Characterization of the Microstructure of Shales from Sichuan Basin, China

Abstract

Comprehensive characterization and analysis of the microstructure characteristics of shale are significant for understanding its transport mechanisms and determining highly efficient production programs. In this study, composition analysis, scanning electron microscopy imaging, and gas adsorption–desorption measurements are first conducted on 29 marine shale samples from the Longmaxi Formation, Sichuan Basin, China, to obtain their petrophysical properties and microstructure characteristics. Then, surface fractal dimension, pore fractal dimension, lacunarity, and succolarity are introduced to analyze the microstructure of these shale samples. Finally, the correlations between total organic carbon (TOC) content and microstructures and the relationships among the microstructures are analyzed systematically. The results show that the complex pore network in these shales is constituted by microfractures, intergranular pores, intragranular pores, dissolved pores, and organic pores. The typical type IV adsorption isotherm and type H3 hysteresis loop are identified from nitrogen adsorption–desorption data. TOC content has positive influences on the adsorption capacity and nanopore distribution. The surface fractal dimensions under low and high relative pressure are similar in these marine shale samples, which is different from the two-section characteristic of continental and marine-continental shale. The statistical self-similarity characteristic of the pore-size distribution in these shales is further confirmed based on the analytical fractal dimension equation. The normalized lacunarity can quantitatively characterize the heterogeneity of the pore-size distribution of these shales in two-dimensional space. The succolarity analysis in two-dimensional space explains the low fluid transport capacity of these shales. Universal and logically explained correlations are found between TOC content and microstructures. Moreover, logically explained correlations also exist among the microstructures of the shale samples evaluated.