Abstract
Bituminous coal reservoirs exhibit pronounced heterogeneity, which significantly impedes the production capacity of coalbed methane. Therefore, obtaining a thorough comprehension of the pore characteristics of bituminous coal reservoirs is essential for understanding the dynamic interaction between gas and coal, as well as ensuring the safety and efficiency of coal mine production. In this study, we conducted a comprehensive analysis of the pore structure and surface roughness of six bituminous coal samples (1.19% < R(o,max) < 2.55%) using various atomic force microscopy (AFM) techniques. Firstly, we compared the microscopic morphology obtained through low-pressure nitrogen gas adsorption (LP-N(2)-GA) and AFM. It was observed that LP-N(2)-GA provides a comprehensive depiction of various pore structures, whereas AFM only allows the observation of V-shaped and wedge-shaped pores. Subsequently, the pore structure analysis of the coal samples was performed using Threshold and Chen's algorithms at ×200 and ×4000 magnifications. Our findings indicate that Chen's algorithm enables the observation of a greater number of pores compared to the Threshold algorithm. Moreover, the porosity obtained through the 3D algorithm is more accurate and closely aligns with the results from LP-N(2)-GA analysis. Regarding the effect of magnification, it was found that ×4000 magnification yielded a higher number of pores compared to ×200 magnification. The roughness values (R(q) and R(a)) obtained at ×200 magnification were 5-14 times greater than those at ×4000 magnification. Interestingly, despite the differences in magnification, the difference in porosity between ×200 and ×4000 was not significant. Furthermore, when comparing the results with the HP-CH(4)-GA experiment, it was observed that an increase in R(a) and R(q) values positively influenced gas adsorption, while an increase in R(sk) and R(ku) values had an unfavorable effect on gas adsorption. This suggests that surface roughness plays a crucial role in gas adsorption behavior. Overall, the findings highlight the significant influence of different methods on the evaluation of pore structure. The 3D algorithm and ×4000 magnification provide a more accurate description of the pore structure. Additionally, the variation in 3D surface roughness was found to be related to coal rank and had a notable effect on gas adsorption.