The dynamic process of water depletion plays a critical role in both surface coalbed methane (CBM) development and underground gas extraction, reshaping water–rock interactions and inducing complex permeability responses. Addressing the limited understanding of the coupling mechanism between heterogeneous pore water evolution and permeability during dynamic processes, this study simulates reservoir transitions across four zones (prospective planning, production preparation, active production, and mining-affected zones) via centrifugal experiments. The results reveal a pronounced scale dependence in pore water distribution. During low-pressure stages (0–0.54 MPa), rapid drainage from fractures and seepage pores leads to a ~12% reduction in total water content. In contrast, high-pressure stages (0.54–3.83 MPa) promote water retention in adsorption pores, with their relative contribution rising to 95.8%, forming a dual-structure of macropore drainage and micropore retention. Multifractal analysis indicates a dual-mode evolution of movable pore space. Under low centrifugal pressure, D₋₁₀ and Δα decrease by approximately 34% and 36%, respectively, reflecting improved connectivity within large-pore networks. At high centrifugal pressure, an ~8% increase in D₀−D₂ suggests that pore-scale heterogeneity in adsorption pores inhibits further seepage. A quantitative coupling model establishes a quadratic relationship between fractal parameters and permeability, illustrating that permeability enhancement results from the combined effects of pore volume expansion and structural homogenization. As water saturation decreases from 1.0 to 0.64, permeability increases by more than 3.5 times. These findings offer theoretical insights into optimizing seepage pathways and improving gas recovery efficiency in dynamically evolving reservoirs.

Considerable variations in microscopic and industrial components (ash, moisture, volatile matter, etc.) have been reported within identical coal seams. These disparities in coal quality and pore structure within the same coal seam profoundly affect the drainage of deep coalbed methane (DCBM). This study focuses on 22 coal samples collected from two wells in the Benxi Formation of the central and eastern parts of the Ordos Basin. First, the coal facies were determined for all samples using submicroscopic components, and then, the adsorption pore and seepage pore structures were studied through CO₂/N₂ adsorption and mercury intrusive tests. Subsequently, the study delves into the correlation between coal rank, coal facies, and the distribution of the pore structures across various pore sizes, elucidating the primary controlling factors influenced by coal rank and coal phase. The results are as follows: (1) For a given coal seam, R_o, max exhibits minimal variation among the samples, which suggests R_o, max is not the primary factor affecting pore structure. Conversely, the ash content occupies the pore space, thereby revealing a negative correlation between the ash content and adsorption pore volume (PV). (2) On the basis of the texture preservation index (TPI) and gelatification index (GI), coal facies were classified into moist forest swamp facies (type A), moist herbaceous swamp facies (type B), and water-covered herbaceous swamp facies (type C). Type A is characterized by higher TPI, lower GI, and ash content, whereas type C exhibits lower TPI, higher GI, and ash content. (3) Type A samples, with the lowest ash content, display larger PV and specific surface area (SSA) compared with type B, while type C has the lowest values. Type C, with the highest vitrinite content, predominantly consists of semibright and bright coal, prone to microcracks, which results in a higher seepage PV compared with types A and B. (4) The coal facies represent variations in ash content and microscopic components, which significantly impacts both adsorption and seepage pores. Moist forest swamp facies samples are characterized by micropore development and the highest content of adsorbed gas. Herbaceous swamp facies samples display macropore development and the highest content of free gas.

Pore structure heterogeneity affects sandstone porosity and permeability and thus sandstone gas productivity. A total of 17 sandstone samples collected from the northwestern margin of the Junggar Basin in Xinjiang Province are investigated in this study. The pore-fracture system distribution of target sandstones is studied by high-pressure mercury injection tests. On this basis, single- and multi-fractal models are used to characterize pore structure heterogeneity, and the applicability of four models (Menger model, Sierpinski model, Thermodynamic model, multifractal model) to characterize pore and fracture distribution heterogeneity are discussed. Moreover, a correlation between fractal dimension, pore structure parameters, and variation coefficient of porosity-permeability is discussed based on overburden permeability test results. The results are as follows. (1) D _S (fractal dimension of Sierpinski model) shows a significant correlation with pore volume percentage, so the Sierpinski model could better characterize fracture distribution heterogeneity quantitatively. Multifractal dimensions are consistent with those of Sierpinski and Thermodynamic models, which indicates that the single- and multiple-fractal models are consistent. (2) The porosity and permeability decrease as a power function with higher confining pressure. The porosity and permeability behavior changes at a critical conversion pressure value. For a confining pressure lower than this critical value, the porosity and permeability decrease largely. For confining pressures higher than this critical value, the porosity and permeability vary less. In contrast, permeability has a larger variation rate and is more obviously affected by confining pressure. (3) Pore compression space is affected by the permeability variation coefficient. Compressibility, porosity, and permeability variation coefficient have no relationship with pore structure parameters since compressibility is affected by pore structure, mineral composition, and other factors in sandstone samples.

Pore and fracture structure heterogeneity is the basis for coalbed methane production capacity. In this paper, high-pressure mercury intrusion test curves of 16 coal samples from the Taiyuan Formation in the Linxing area are studied. Based on the fractal dimension values of mercury intrusion and retreat curves, the correlation between the two different fractal parameters is studied. Then, the permeability variation of different types of coal samples is studied using overlying pressure pore permeability tests. The correlation between the permeability variation of coal samples and dimension values is explored, and the results are as follows. (1) Based on porosity and mercury removal efficiency, all coal samples can be divided into three types, that is, types A, B, and C. Among them, Type A samples are characterized by lower total pore volume, with pore volume percentages ranging from 1000 to 10,000 nm not exceeding 15%. (2) During the mercury injection stage, both the M-model and S-model can reflect the heterogeneity of seepage pore distribution. In the mercury removal stage, the M-model cannot characterize the heterogeneity of pore size distribution in each stage, which is slightly different from the mercury injection stage. (3) The permeability of Type A samples is most sensitive to pressure, with a permeability loss rate of up to 96%. The original pore and fracture structure of this type of coal sample is relatively developed, resulting in a high initial permeability. (4) There is no significant relationship between compressibility and fractal dimension of mercury injection and mercury removal, which may be due to the comprehensive influence of pore structure on the compressibility of the sample.

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.