Fractal Analysis of the Pore Structure of Marine Shale in the Sichuan Basin

The fractal characteristics of shale significantly influence pore distribution patterns and surface roughness, thus impacting reservoir properties such as permeability, porosity, and diffusion coefficients. However, existing studies have not fully characterized these fractal features, particularly in ultralow-pressure regions. This study comprehensively investigated the fractal characteristics of shale by integrating low-pressure N2 adsorption, CO2 adsorption, mercury intrusion, focused ion beam-scanning electron microscopy (FIB-SEM), and three-dimensional reconstruction techniques. The Sierpinski fractal model was employed to determine fractal dimensions in the ultralow-pressure interval based on the N2 isotherms and adsorption mechanism. By extracting pores from images obtained using the FIB-SEM technique, the fractal dimensions (D3) of the three-dimensional digital cores were calculated based on the box-counting model. Additionally, investigating the correlation between porosity and D3 values revealed a direct logarithmic relationship between porosity and D3 values. This correlation suggests that the fractal dimensions in shale can extend to other physical parameters associated with porosity. A machine learning algorithm was applied to predict the fractal dimensions of shale from the Sichuan Basin. These findings not only deepen the understanding of shale reservoir properties but also offer a solid theoretical foundation for shale gas development and enhanced recovery.