Effects of Pore Structures of Different Maceral Compositions on Methane Adsorption and Diffusion in Anthracite

The pore structure of coal reservoirs is the main factor influencing the adsorption–diffusion rates of coalbed methane. Mercury intrusion porosimetry (MIP), low-pressure nitrogen adsorption (LP-NA), low-pressure carbon dioxide adsorption (LP-CA), and isothermal adsorption experiments with different macerals were performed to characterize the comprehensive pore distribution and methane adsorption–diffusion of coal. On the basis of the fractal theory, the pore structures determined through MIP and LP-NA can be combined at a pore diameter of 100 nm to achieve a comprehensive pore structural splicing of MIP, LP-NA, and LP-CA. Macro–mesopores and micro-transitional pores had average fractal dimensions of 2.48 and 2.18, respectively. The Langmuir volume (VL) and effective diffusion coefficients (De) varied from 31.55 to 38.63 cm3/g and from 1.42 to 2.88 × 10−5 s−1, respectively. The study results showed that for super-micropores, a higher vitrinite content led to a larger specific surface area (SSA) and stronger adsorption capacity but also to a weaker diffusion capacity. The larger the average pore diameter (APD) of micro-transitional pores, the stronger the diffusion capacity. The diffusion capacity may be controlled by the APD of micro-transitional pores.


Introduction
Coal reservoirs have complex pores and fractures. The pore characteristics of coal in these reservoirs, including porosity, pore structure, and specific surface area (SSA), can directly affect adsorption, desorption, diffusion, and seepage. Goaf caving, auxiliary ventilation equipment, and the drainage method also have a great influence on the productivity of methane [1]. These all can subsequently influence the commercial development of coalbed methane (CBM) [2]. The United States, Canada, and Australia have been successful in developing their CBM resources [3], and Poland has been working on it [4]. The production of CBM from coal in China is gradually increasing. CBM recoverable resources of anthracite in China account for approximately 25% of the country's total CBM micropore content [33,34]. Zhou et al. [35] proposed multi-scale fractal dimensions and calculated the contributions of different pores to porosity and permeability. They found that a negative correlation exists between the porosity contribution of different pores and the coalification degree.
In summary, previous studies have extensively examined the pore structure of anthracite. The comprehensive pore distribution of different macerals without the effects of anthracite geological structure and its effect on methane adsorption-diffusion, however, remain unclear. To determine them, anthracite samples from bright bands and dull bands of coal were obtained from No.3 coal seam, Hudi coal mine, in Qinshui Basin. For these samples, MIP, LP-NA, and LP-CA were used to characterize the comprehensive PSD, and isothermal adsorption tests were employed to describe the distinctive nature of the adsorption capacity.

Materials Collection and Preparation
Samples were collected from No. 3 coal seam of the Shanxi Formation in Hudi coal mines located in southern Qinshui Basin ( Figure 1). First, the coal sample lithotypes were determined. In the laboratory, the dull bands and bright bands of coal samples were manually chosen and thereafter crushed into 0.25-0.38 mm particles. Second, sufficient quantities of good-quality dull bands and bright bands were selected and named A1 and A5, respectively. Three samples, A2, A3, and A4, with different proportions of dull and bright bands were thereafter mixed according to the proportions 2:1, 1:1, and 1:2, respectively. A total of five samples were thus obtained (Table 1). Each prepared coal sample was divided into several parts, which were used for the preparation of briquettes, pore structure tests, and isothermal adsorption experiments.

Experimental Methods
The maximum reflectivity of vitrinite (R o,max ) and coal macerals was determined via an optical microscope with an oil immersion reflection light following ASTM Standard D2798-05 and ISO 7404-3 (2009). The proximate analysis was completed in accordance with ASTM Standard D3172-13. The basic properties of the coal sample are summarized in Table 1.
The MIP measurements were conducted using a mercury porosimeter (Poremaster 60 GT, Quantachrome Instruments, Boynton Beach, FL, USA) at the Nanjing University of Technology. All coal samples were dehydrated for more than 24 h at a constant temperature of 110 • C before the MIP measurements. The maximum test pressure was approximately 274 MPa with a minimum test aperture of 5.4 nm.
The LP-NA tests were conducted at 77 K using V-Sorb 2800TP manufactured by the Gold APP Instrument Corporation (Beijing China). The evacuation time and temperature were 4 h and 150 • C, respectively. The instrument can accurately measure pores with sizes between 2 and 100 nm.
The LP-CA tests were performed at 273 K using Autosorb-IQ (Quantachrome Instruments, Boynton Beach, FL, USA). The evacuation time and temperature for each sample were 12 h and 105 • C, respectively. The PSD of coals was determined on the basis of the density functional theory (DFT). The measurable apertures were between 0.35 and 2 nm. High-pressure CH4 adsorption was performed on a gravimetric adsorption apparatus (ISOSORF-HP, Rubotherm, Bochum, Germany). The core component of the apparatus is a highprecision magnetically suspended balance with a 10 −6 g accuracy. The test process was conducted at a constant temperature of 30 °C, and the highest test pressure was set to 20 MPa. The absolute adsorption was estimated from the measured excess adsorption [37]. The simplified workflow generates the parameters pore structure, fractal dimension, and methane adsorption capacity ( Figure  2).  High-pressure CH 4 adsorption was performed on a gravimetric adsorption apparatus (ISOSORF-HP, Rubotherm, Bochum, Germany). The core component of the apparatus is a high-precision magnetically suspended balance with a 10 −6 g accuracy. The test process was conducted at a constant temperature of 30 • C, and the highest test pressure was set to 20 MPa. The absolute adsorption was estimated from the measured excess adsorption [37]. The simplified workflow generates the parameters pore structure, fractal dimension, and methane adsorption capacity (Figure 2

Fractal Theory
The fractal theory has been widely used to characterize rough and irregular systems in porous media [35,39]. Friesen and Mikula [40] calculated the fractal dimension based on MIP data. The function is as follows: where VP is the injected mercury volume (cm 3 /g) at pressure P; P is the experimental pressure (MPa); D is the fractal dimension. The fractal FHH (Frenkel-Halsey-Hill) model is simple and practical, and the fractal D can be obtained through LP-NA data. The FHH equation is as follows: where V is the adsorption volume (cm 3 /g) at pressure P; V0 is the monolayer volume (cm 3 /g); P is the test pressure (MPa); P0 is the saturation pressure (MPa); A is a constant.

Adsorption Kinetics
Previous researchers have shown that methane diffusion in coal can be represented by a unipore model [41,42] in which the constant surface concentration of the total amount of the diffusing substance that enters the sphere may be expressed as follows:  where Mt is the total diffusion mass (g) at time t; M∞ is the total diffusion gas uptake (g); rp is the diffusion channel length (10 −6 m); D is the diffusion coefficient (cm 2 /s); t is time (s).
For small time intervals (t < 600 s) and small diffusion masses (Mt/M∞ < 0.5), the effective diffusion coefficient (De) can be determined as follows [28,43]: where De is the effective diffusion coefficient (s −1 ).

Fractal Theory
The fractal theory has been widely used to characterize rough and irregular systems in porous media [35,39]. Friesen and Mikula [40] calculated the fractal dimension based on MIP data. The function is as follows: lg(dV p /dP) ∝ (D − 4)lgP (1) where V P is the injected mercury volume (cm 3 /g) at pressure P; P is the experimental pressure (MPa); D is the fractal dimension. The fractal FHH (Frenkel-Halsey-Hill) model is simple and practical, and the fractal D can be obtained through LP-NA data. The FHH equation is as follows: ln(V/V 0 ) = constant+A ln(ln(P 0 /P)) ( where V is the adsorption volume (cm 3 /g) at pressure P; V 0 is the monolayer volume (cm 3 /g); P is the test pressure (MPa); P 0 is the saturation pressure (MPa); A is a constant.

Adsorption Kinetics
Previous researchers have shown that methane diffusion in coal can be represented by a unipore model [41,42] in which the constant surface concentration of the total amount of the diffusing substance that enters the sphere may be expressed as follows: where M t is the total diffusion mass (g) at time t; M ∞ is the total diffusion gas uptake (g); r p is the diffusion channel length (10 −6 m); D is the diffusion coefficient (cm 2 /s); t is time (s). For small time intervals (t < 600 s) and small diffusion masses (M t /M ∞ < 0.5), the effective diffusion coefficient (D e ) can be determined as follows [28,43]: where D e is the effective diffusion coefficient (s −1 ).

Sample Characterization
The coal sample R o,max changed from 2.94 to 2.95% (mean 0.0298%). The coal samples consisted of high amounts of vitrinite and low amounts of inertinite in the ranges 80.10%-99.36% (mean 91.47%) and 0.32%-8.67% (mean 3.84%), respectively. The mineral matter content varied from 0.32% to 11.23%, with a mean value of 4.57%.

MIP Test Results
The TPV and SSA obtained from the MIP test varied in the ranges 0.0275-0.0338 cm 3 /g and 7.5-12.67 m 2 /g, with mean values of 0.03 cm 3 /g and 10.9 m 2 /g, respectively.
As shown in Figure 3A, the shapes of the mercury intrusion-extrusion curves were similar and could be divided into two distinct parts. When the pressure was small (corresponding to pore diameters in the range 50-10,000 nm), the mercury volume gradually increased; however, when the pressure was high (pore diameter of 6-50 nm), the volume increased rapidly. This indicates that the samples developed considerable micro-transitional pores. The mercury intrusion-extrusion curves were extremely narrow and practically parallel, indicating that the samples primarily developed semi-closed pores. These pores may remarkably affect pore connectivity, and thereafter prevent CBM output [44].        Figure 3. Curves of (A) cumulative mercury quantity and (B) incremental pore volume vs. pore diameter according to MIP data.

LP-NA and LP-CA Tests Results
The SSA and TPV determined by the LP-NA test varied in the ranges 0.913-1.559 m 2 /g and 0.0015-0.0025 cm 3 /g, with averages of 1.161 m 2 /g and 0.002 cm 3 /g, respectively ( Table 2). The average Appl. Sci. 2019, 9, 5130 7 of 16 pore diameter (APD) in the LP-NA test ranged between 6.47 and 9.66 nm. This indicates that the pores' sizes were mainly below 10 nm. Table 2. Characteristics of pore structure and methane adsorption.

Samples
MIP LP-NA LP-CA CH 4 Adsorption  The LP-NA adsorption-desorption isotherms can be adapted to identify the pore types [45]. According to their isotherm curves, the samples could be classified into two types [33]: Type A and Type B (Figure 4). The A3, A4, and A5 isotherms, which were parallel to the desorption isotherms (P/P 0 < 0.2), belonged to Type A. At this relative pressure range, the isotherms were reversible and corresponded to semi-closed pores. The isotherms exhibited moderate hysteresis loops when the relative pressure was higher, implying the existence of slit or cylindrical pores. On the contrary, the isotherms of Type B (A1 and A2) demonstrates a significant change in hysteresis loops (P/P 0 ≈ 0.5). This revealed the presence of spherical or ink-bottle pores.
This revealed the presence of spherical or ink-bottle pores.     The maximum adsorption volume of CO 2 was between 22.88 and 34.29 cm 3 /g (mean: 28.42 cm 3 /g). The super-micropore diameters were mainly distributed in the range 0.4-0.9 nm. Three peaks at pore diameters of 0.48, 0.55, and 0.82 nm are shown in Figure 5. The SSA and TPV of LP-CA tests varied in the ranges 241.67-357.96 m 2 /g and 0.074-0.106 cm 3 /g, with averages of 298.65 m 2 /g and 0.0898 cm 3 /g, respectively. These values are considerably greater than those of the MIP and LP-NA tests.

Comprehensive Characterization of Pore Fractals and Structures
Comprehensive Characterization of Pore Fractals The fractal dimension is generally from 2 to 3. On account of the fractal theory, there are evident positive correlations in the scatter plots of Figure 6 between lg(dV p /dP) and lgP. The slope, k, can be  Figure 6A shows and Table 3 summarizes the calculation process and results, respectively. The maximum adsorption volume of CO2 was between 22.88 and 34.29 cm 3 /g (mean: 28.42 cm 3 /g). The super-micropore diameters were mainly distributed in the range 0.4-0.9 nm. Three peaks at pore diameters of 0.48, 0.55, and 0.82 nm are shown in Figure 5. The SSA and TPV of LP-CA tests varied in the ranges 241.67-357.96 m 2 /g and 0.074-0.106 cm 3 /g, with averages of 298.65 m 2 /g and 0.0898 cm 3 /g, respectively. These values are considerably greater than those of the MIP and LP-NA tests.

Comprehensive Characterization of Pore Fractals and Structures
Comprehensive Characterization of Pore Fractals The fractal dimension is generally from 2 to 3. On account of the fractal theory, there are evident positive correlations in the scatter plots of Figure 6 between lg(dVp/dP) and lgP. The slope, k, can be obtained by fitting the scatters and the fractal D = 4 + k. Figure 6A shows and Table 3 summarizes the calculation process and results, respectively.
The adsorption mechanism transforms with changes in P/P0. The van der Waals forces are dominant when P/P0 is less than 0.5; however, the adsorption mechanism transforms to capillary condensations when P/P0 is larger than 0.5. Ismail and Pfeifer used δ to discriminate the dominant adsorption mechanism. In general, if δ > 0, then the relationship between A and DS is as follows: if δ < 0, then it changes to: where Ds1 and Ds2 represent the fractal dimensions when P/P0 is in the 0-0.5 and 0.5-1.0 intervals, respectively. The calculation process and results are shown in Figure 6B and summarized in Table 3, respectively. The macro-mesopore fractal dimensions (D), pore surface fractal dimensions (Ds1), and pore structure fractal dimensions (Ds2) varied in the ranges 2.36-2.60, 1.69-2.43, and 2.10-2.37, with averages of 2.48, 1.96, and 2.18, respectively. The factor Ds1 is not discussed in subsequent sections of this paper because it has distinct anomalies.

Comprehensive Characterization of Pore Structures
To comprehensively describe the PSD characteristics of anthracite reservoirs, the results of MIP, LP-NA, and LP-CA tests were superimposed. The LP-NA and LP-CA tests caused inconsiderable destruction to the sample. The data of the two experiments did not overlap; hence, the direct superposition method was selected. The MIP and LP-NA, however, characterized the macromesopore and micro-transitional pore systems, respectively. The test data overlapped and therefore were cut and combined.
With regard to the coal matrix compressibility [46], a significant increase in mercury volume can be observed when the test pressure of MIP is higher than the critical value that can introduce errors to the fractal study of the pore structure. Relative to this, previous researchers have proposed a method for correcting MIP data based on the LP-NA test [47]. In this study, the fractal theory was used to analyze the compressibility of the coal matrix. By considering the fractal characteristics of MIP, it can be seen that fractal D distinctly changed at lgP = 1.16 (pore diameter = 100 nm in Figure  6A). It shows that when the mercury injection pressure was greater than 14.45 MPa, the coal matrix compressibility was considerable and would severely distort the pore volume test results. When the pressure was less than 14.45 MPa, however, the pore filling effect was dominant, and the mercury intrusion data were accurate. The MIP, LP-NA, and LP-CA data were therefore used to characterize macro-mesopores (larger than 100 nm), micro-transitional pores (2-100 nm), and super-micropores (less than 2 nm). The joint PSDs are listed in Table 4.  The adsorption mechanism transforms with changes in P/P 0 . The van der Waals forces are dominant when P/P 0 is less than 0.5; however, the adsorption mechanism transforms to capillary condensations when P/P 0 is larger than 0.5. Ismail and Pfeifer used δ to discriminate the dominant adsorption mechanism. In general, if δ > 0, then the relationship between A and D S is as follows: if δ < 0, then it changes to: Appl. Sci. 2019, 9, 5130 9 of 16 where Ds 1 and Ds 2 represent the fractal dimensions when P/P 0 is in the 0-0.5 and 0.5-1.0 intervals, respectively. The calculation process and results are shown in Figure 6B and summarized in Table 3, respectively. The macro-mesopore fractal dimensions (D), pore surface fractal dimensions (Ds 1 ), and pore structure fractal dimensions (Ds 2 ) varied in the ranges 2.36-2.60, 1.69-2.43, and 2.10-2.37, with averages of 2.48, 1.96, and 2.18, respectively. The factor Ds 1 is not discussed in subsequent sections of this paper because it has distinct anomalies.

Comprehensive Characterization of Pore Structures
To comprehensively describe the PSD characteristics of anthracite reservoirs, the results of MIP, LP-NA, and LP-CA tests were superimposed. The LP-NA and LP-CA tests caused inconsiderable destruction to the sample. The data of the two experiments did not overlap; hence, the direct superposition method was selected. The MIP and LP-NA, however, characterized the macro-mesopore and micro-transitional pore systems, respectively. The test data overlapped and therefore were cut and combined.
With regard to the coal matrix compressibility [46], a significant increase in mercury volume can be observed when the test pressure of MIP is higher than the critical value that can introduce errors to the fractal study of the pore structure. Relative to this, previous researchers have proposed a method for correcting MIP data based on the LP-NA test [47]. In this study, the fractal theory was used to analyze the compressibility of the coal matrix. By considering the fractal characteristics of MIP, it can be seen that fractal D distinctly changed at lgP = 1.16 (pore diameter = 100 nm in Figure 6A). It shows that when the mercury injection pressure was greater than 14.45 MPa, the coal matrix compressibility was considerable and would severely distort the pore volume test results. When the pressure was less than 14.45 MPa, however, the pore filling effect was dominant, and the mercury intrusion data were accurate. The MIP, LP-NA, and LP-CA data were therefore used to characterize macro-mesopores (larger than 100 nm), micro-transitional pores (2-100 nm), and super-micropores (less than 2 nm). The joint PSDs are listed in Table 4. Table 4. Combined results of MIP, LP-NA, and LP-CA.

Isothermal Adsorption and Its Kinetics
The Langmuir equation was used to describe the adsorption equilibrium of coal in this paper. The VL and PL changed from 31.55 to 38.63 cm 3 /g (mean 36.51 cm 3 /g) and from 0.70 to 1.29 MPa (mean 1.01 MPa), respectively. According to Figure 9A, the adsorption curves were typical isothermal adsorption curve of high-rank coal, which is characterized by larger VL and smaller PL values compared with semi-anthracites and low-and medium-rank coals [16,18,48].
The calculation method of De is shown in Figure 9B and given by Equation (4). The results are summarized in Table 3. The value of De in Hudi coal mine ranged from 1.42 to 2.88 × 10 −5 s −1 (mean 2.09 × 10 −5 s −1 ). These results conform with the report of Shen et al., whose research showed an average effective diffusion coefficient of 2.92 × 10 −5 s −1 [42].

Effects of PSD and Macerals on Adsorption Capacity and Adsorption Kinetics
The coal composition has a substantial influence on the adsorption capacity of methane. Methane is primarily present in the adsorbed state on the inner surface of coal. As the vitrinite content increases, VL distinctly increases. The effective diffusion coefficient, De, however, exhibits a negative correlation with the vitrinite content. The reason is that both the TPV and the SSA have significant linear correlations with the vitrinite content ( Figure 10G), and both correlation coefficients (R 2 ) are higher than 0.96. The higher the vitrinite content, the larger the adsorption surface area. Our results are in contrast to those obtained by Laxminarayana [49], whose research showed that the Langmuir volume decreased with the increase of vitrinite content in anthracite, but are consistent with the results of Guo [50] and Lamberson and Bustin [51]. The potential reason is that vitrinite is characterized by higher SSA and TPV of super-micropores [52], which supply more adsorption sites [53]. As shown in Figure 10B, VL is negatively associated with mineral matter contents (R 2 = 0.9031), indicating that the mineral matters may mainly develop macro-mesopores. It is therefore beneficial

Isothermal Adsorption and Its Kinetics
The Langmuir equation was used to describe the adsorption equilibrium of coal in this paper. The V L and P L changed from 31.55 to 38.63 cm 3 /g (mean 36.51 cm 3 /g) and from 0.70 to 1.29 MPa (mean 1.01 MPa), respectively. According to Figure 9A, the adsorption curves were typical isothermal adsorption curve of high-rank coal, which is characterized by larger V L and smaller P L values compared with semi-anthracites and low-and medium-rank coals [16,18,48].  Previous studies have shown a positive correlation between pore SSA and CH4 adsorption capacity [54,55]. As shown in Figure 10D, VL positively correlated with SSA in super-micropores (R 2  The calculation method of D e is shown in Figure 9B and given by Equation (4). The results are summarized in Table 3. The value of D e in Hudi coal mine ranged from 1.42 to 2.88 × 10 −5 s −1 (mean 2.09 × 10 −5 s −1 ). These results conform with the report of Shen et al., whose research showed an average effective diffusion coefficient of 2.92 × 10 −5 s −1 [42].

Effects of PSD and Macerals on Adsorption Capacity and Adsorption Kinetics
The coal composition has a substantial influence on the adsorption capacity of methane. Methane is primarily present in the adsorbed state on the inner surface of coal. As the vitrinite content increases, V L distinctly increases. The effective diffusion coefficient, D e , however, exhibits a negative correlation with the vitrinite content. The reason is that both the TPV and the SSA have significant linear correlations with the vitrinite content ( Figure 10G), and both correlation coefficients (R 2 ) are higher than 0.96. The higher the vitrinite content, the larger the adsorption surface area. Our results are in contrast to those obtained by Laxminarayana [49], whose research showed that the Langmuir volume decreased with the increase of vitrinite content in anthracite, but are consistent with the results of Guo [50] and Lamberson and Bustin [51]. The potential reason is that vitrinite is characterized by higher SSA and TPV of super-micropores [52], which supply more adsorption sites [53]. As shown in Figure 10B, V L is negatively associated with mineral matter contents (R 2 = 0.9031), indicating that the mineral matters may mainly develop macro-mesopores. It is therefore beneficial to diffusion ( Figure 10B). The correlation coefficient between mineral matter contents and D e was 0.8548.
The larger the APD, the shorter the length of the diffusion channel, which is more conducive to diffusion.
Previous studies have also shown that the larger the fractal dimension, the stronger the adsorption capacity. Fractal Ds2, however, showed a weak negative relationship to VL, and the relationship between fractal parameters and De was dispersed ( Figure 10F). This may be ascribed to differences in composition, measurement medium, measurement method, etc.

Conclusions
To investigate the pore structure of different maceral compositions in anthracite and its effect on methane adsorption-diffusion, maceral analysis, MIP, LP-NA, and LP-CA tests were performed, evaluating the maceral composition and PSDs of five samples. A high-pressure CH4 adsorption experiment was conducted to determine the adsorption properties.  Previous studies have shown a positive correlation between pore SSA and CH 4 adsorption capacity [54,55]. As shown in Figure 10D, V L positively correlated with SSA in super-micropores (R 2 = 0.7282), but there was a discrete relationship between V L and SSA in micro-transitional pores ( Figure 10C). By comparing the graphs in Figure 10A,D, it can be clearly observed that the controlling factors in materials with different compositions are the vitrinite content and the SSA of super-micropores.
Generally, the higher the vitrinite content, the larger the SSA of super-micropores, the stronger the adsorption capacity, the stronger the Knudsen diffusion, and the weaker the Fick diffusion. Research has shown that the Fick diffusion is considerably larger than the Knudsen diffusion [56]. The effective diffusion coefficient, therefore, negatively correlates with the SSA of super-micropores. Figure 10D shows that as the APD of micro-transitional pores increased, V L decreased, and D e increased. This indicates that D e is controlled by the APD of micro-transitional pores (R 2 = 0.6005). The larger the APD, the shorter the length of the diffusion channel, which is more conducive to diffusion.
Previous studies have also shown that the larger the fractal dimension, the stronger the adsorption capacity. Fractal Ds 2 , however, showed a weak negative relationship to V L , and the relationship between fractal parameters and D e was dispersed ( Figure 10F). This may be ascribed to differences in composition, measurement medium, measurement method, etc.

Conclusions
To investigate the pore structure of different maceral compositions in anthracite and its effect on methane adsorption-diffusion, maceral analysis, MIP, LP-NA, and LP-CA tests were performed, evaluating the maceral composition and PSDs of five samples. A high-pressure CH 4 adsorption experiment was conducted to determine the adsorption properties. The fractal and diffusion characteristics were separately described on the basis of the fractal theory and adsorption kinetics. The main conclusions drawn are as follows: According to the fractal theory and coal matrix compressibility, the pore structure data of MIP and LP-NA may be combined at a pore diameter of 100 nm, thereby realizing a comprehensive pore structure splicing. The results of comprehensive PSDs showed that super-micropores were abnormally developed (94.39-96.36%), followed by micropores, transitional pores, mesopores, and macropores. The super-micropore SSA was the most developed.
The LP-NA test results for different maceral compositions showed that the pore structure of durain is more complex than that of vitrain, and the former contains spherical or ink-bottle pores.
The MIP and LP-NA data were used to study the fractal D values of macro-mesopores and micro-transitional pores with averages of 2.48 and 2.18, respectively, thereby revealing that durain contains a more complex PSD than vitrain.
The results of different maceral compositions showed that the higher the vitrinite content, the larger the super-micropore SSA, the larger the V L , and the weaker the diffusion. The larger the APD of micro-transitional pores, the stronger the diffusion capacity.