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.