Pore structure heterogeneity of coal reservoirs restricts the diffusion-seepage process of coalbed methane, thereby restricting the production capacity of coalbed methane. Therefore, 10 coal samples from the Linxing area are taken as an objective, and high-pressure mercury intrusion testing was used to describe the pore structure distribution of all the coal samples. On this basis, four single and multifractal models were used to perform fractal calculations, and correlation analysis was conducted on the mercury advance and retreat fractal dimension values to clarify the physical significance of mercury removal fractal dimension values. Finally, the relationship between fractal dimension values of mercury curves and pore structure parameters was clarified, and the applicability of various fractal models in characterizing pore structure heterogeneity was explored. All the samples can be divided into type A and B by using pore volume percentage greater than 1000 nm and the mercury removal efficiency. The T model has universality and the strongest correlation in characterizing the heterogeneity of pore volume distribution in samples. A fractal parameter based on high-pressure mercury injection curve was obtained, and was then used to quantitatively characterize the pore and fracture structure of coal reservoirs. This parameter is used to characterize the complexity of gas and water transport during coalbed methane production, further elucidating the coalbed methane production process under the constraint of pore and fracture structure in coal reservoirs.

The nuclear magnetic resonance T₂ spectrum was used to identify the T_2 cut-off value, which is the key to determining the irreducible water saturation of a reservoir. In this paper, the saturation and centrifugal T₂ spectra of sandstone and coal samples were used to explore the correlation between each parameter and the T_2 cut-off value, using a single fractal dimension, a multifractal dimension and a spectral morphology discrimination method. The conclusions are as follows: (1) The T₂ spectra of nine sandstone samples in this paper can be divided into four types. Type A is represented by sample 2, wherein the T₂ spectrum shows a bimodal state and the area of the right T₂ spectrum (2.5~100 ms) is larger than that of the left T₂ spectrum (T₂ < 2.5 ms), indicating that the sample has good pore connectivity and belongs to the macroporous development sample. The B-type T₂ spectrum is unimodal, and the pore connectivity is poor, indicating that it is a large-pore development sample. The T₂ spectrum of the C-type sample is unimodal, and the pore connectivity is very poor, indicating that it is a mesoporous development sample. The T₂ spectrum of the D-type sample shows a single peak state, and the main T₂ is distributed within 0.1~2.5 ms. The pore connectivity is very poor, which indicates that it belongs to the small pore development type sample. (2) The single fractal model shows that, compared with other single fractal parameters, D₂ increases with the increase in the T_2 cut-off value, but the correlation is weak. Therefore, it is not feasible to predict the T_2 cut-off value using the single fractal dimension parameter. (3) The multifractal model shows that D₋₁₀–D₁₀ increases linearly with the increase in D₋₁₀–D₀, but there is no obvious linear correlation between D₀–D₁₀ and D₋₁₀–D₁₀, indicating that the low pore volume area in this kind of sample controls the overall heterogeneity of pore distribution. (4) The related parameters affecting the T_2 cut-off value include D₋₁₀–D₁₀, D₋₁₀/D₁₀, D₋₁₀–D₀, T_M and D₂. Therefore, based on the above five parameters, a T_2 cut-off value prediction model is constructed. The T_2 cut-off value calculated by the model is highly consistent with the experimental value, which proves the reliability of the model.

The relevant literature indicates that coal facies have a significant impact on the pore structure and adsorption properties of deep coal reservoirs. The content of submicroscopic components is used to calculate the parameters of coal facies. Based on traditional coal phase parameters and ash content, the coal phases of the coal samples in the study area were divided. Based on the adsorption potential theory, the differences in methane adsorption energy changes between different coal phases were compared. The results are as follows. The wet herbaceous swamp facies (type A) could be divided into two subtypes by using the ash yield: subtype A-1 (with an ash yield lower than 20% and a gel index (GI) lower than 5), and subtype A-2 (with an ash yield larger than 20% and a GI lower than 5). With the increase in micro-pore volume shown in A-1 samples, cumulative surface free energy increases linearly and the maximum rate of decline decreases linearly. Coal facies have an important effect on adsorption parameters: V_L increases and P_L decreases with higher structural preservation index (TPI). The effect of a low ash yield and different R_o,max on methane adsorption energy parameters is stronger.