A quantitative analysis of the porosity, pore size distribution, and fractal dimensions of pores is significant for studying the pore structure characteristics of coal. This study utilized 12 anthracite coal samples from the Sihe mining area to explore the pore structure characteristics of the coal therein. Hundred randomly selected points on each sliced coal sample were imaged via scanning electron microscopy, and a total of 1200 images were used for the analysis. The porosity and fractal dimensions of the coal samples were analyzed via digital image processing and box-counting dimension methods. This method is characterized by extensive graphical analysis, and the results are based on statistical methods. These were also used to analyze the structural and development characteristics of the microscopic pores in the coal. The results reveal that the surface porosity obtained via digital image processing was 16.11% lower than that measured experimentally. The fractal dimension and porosity of the pore surface were fitted to a natural logarithmic curve. The rate of change in the pore fractal dimension depends on the porosity such that, to some degree, a greater porosity is associated with more complex pore structures, a higher degree of micropore development, and improved pore connectivity.

Permeability of coal reservoirs influence the extraction of coal gas from coal seams. Twelve coal samples were collected at an anticline and a syncline of the No. 3 coal seam in the Sihe coal mine. Porosity, permeability, pore size, vitrinite reflectance, and liquid nitrogen adsorption of the samples were evaluated. Structural curvatures at the sample locations, and the distance between the sampling locations and the nearest faults were calculated based on seismic data. The influences of the evaluated parameters on permeability were analyzed. Major factors that influence permeability of the No. 3 coal seam were extracted using principal component analysis (PCA). Based on the porosity–permeability model derived from the Archie formula and classic Kozeny–Carman equation, we deduced that the permeability of coal increased with an increase in porosity. With an increase in average vitrinite reflectance, permeability decreases first and then increases. PCA results showed that coal permeability was regulated by three key components representing three modes. The first component included pore size, depth, and pore complexity accounting for 52.59% of the variability indicating that it was the most important in controlling permeability. The second component included specific surface area, structural curvature, and porosity, and the third component comprised of specific surface area, porosity, and average vitrinite reflectance. Overall, pore diameter and complexity had significant effects on coal permeability. The results show that researchers and stakeholders must consider the interactions among multiple factors rather than single factors to understand the influences on permeability to facilitate efficient utilization of coalbed methane resources.

The refinement of nanoscale physical parameters of source rocks has benefitted from continuous innovations in technology and methods. Traditional methods for detecting reservoir physical properties are limited by the properties of the instruments. Atomic force microscopy (AFM) provides new methods and approaches for furthering our understanding and exploring the nanoscale world. Its wide range of applications and gradually developed multiscenario application modes make it an ideal tool for the characterization of nanoscale physical properties of source rocks (coal, shale, mudstone, sandstone, etc.). We highlight the advantages of AFM in regard to performing nondestructive 3D imaging and mechanical property measurements with nanoscale resolution in any desired environment (air, vacuum, liquid). The limitations of AFM applied to source rocks are also summarized. The process has great potential in micro/nanopore characterization, surface morphology characterization, in situ micromechanical property acquisition, wettability research, and so on. The gradual development and improvement of this new model will expand new methods, bring enlightenment to basic research on unconventional oil and gas resources, and provide a scientific basis for the exploration and development of unconventional oil and gas resources.

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Complex pores and fissures are the main transportable channels of coal reservoir resources and key factors affecting the permeability of coal seams. Owing to different tectonic stresses, the development characteristics of pores and fissures in coal can differ significantly, which also results in differences in reservoir permeability. Therefore, analysing the influence of pore structure characteristics on coal-rock permeability is needed. In this study, four samples from the DaTong Coal Mine in the central and southern Qinshui Basin of Shanxi Province were selected for analysis. Combined computerised tomography (CT) scanning and digital image processing technology revealed the development characteristics, distribution rules, morphology, and structural differences of different coals. Based on the capillary seepage channel model and fractal geometry theory combined with the pore structure parameters obtained by CT scanning, the permeability was predicted. Furthermore, the control mechanism of the pore structure on coal permeability is discussed. The results showed that the coal porosity is positively correlated with pore diameter, pore volume, connectivity factor, and connectivity strength at the micrometer scale. Coal reservoir permeability is controlled by multiple factors, including pore size, pore volume, porosity, connectivity factor, connectivity strength, and fractal dimension, among which pore size has the most significant influence. After the complexity and connectivity of the micropore structure in coal rock were considered, the accuracy and applicability of the pore structure parameters obtained by CT scanning to predict the permeability were verified by comparing with the measured permeability.