January 2025
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Fractal and Fractional
To analyze the pore structure and fractal characteristics of marine shale in the lower Cambrian Niutitang Formation in northwestern Hunan Province, China, the pore characteristics of shale were characterized using total organic carbon (TOC) content, field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), low temperature nitrogen adsorption (LT-N2GA) and methane adsorption experiments. The pore surface and pore space fractal dimensions of samples were calculated, respectively. The influencing factors of fractal dimensions and their impact on the adsorption of shale reservoirs were discussed. The results indicate the Niutitang Formation shale mainly develops four types of pores: organic pores, intragranular pores, intergranular pores and microcracks. The pores have a large specific surface area (SSA), primarily consisting of mesopores. The fractal dimensions are calculated using the FHH model and the XS model. The fractal dimensions (D2 and Df) are greater than D1, indicating that the pore surface with larger pore size is rougher, and the pore structure of shale is complex. The pore volume (PV), SSA, and TOC show positive correlations with the fractal dimensions but negative correlations with APS. There is no obvious correlation between fractal dimensions and quartz content, while clay minerals show a negative correlation with D2 and Df. This is mainly because clay mineral particles are small in size and have weak resistance to compaction. The pyrite content is positively correlated with the fractal dimensions because pyrite promotes the development of organic, intergranular, and mold pores. According to Pearson correlation analysis, the main influencing factors of the pore surface fractal dimension are PV, SSA, and APS. The main influencing factors of the pore space fractal dimension are APS and the content of clay minerals. Further analysis of the influence of the fractal dimension on the adsorption capacity of shale reveals that the fractal dimensions are positively correlated with Langmuir volume, indicating that fractal dimensions can be used as a quantitative target for evaluating shale gas reservoirs.