1. Introduction
Shale gas, as an unconventional natural gas resource, is characterized by abundant reserves, low carbon emissions, and high energy efficiency [
1]. It is recognized as a globally significant strategic energy reserve and a key alternative to conventional oil and gas resources [
2]. The United States leads the world in shale gas production. According to data from the U.S. NOVI platform, global shale gas production reached 805.8 billion cubic meters in 2021, with the U.S. accounting for approximately 94.7% of the total output. China, with over 36 trillion cubic meters of recoverable shale gas resources, ranks first globally, holding more than 20% of the world’s recoverable reserves. However, in the same year, China’s actual shale gas production was only 22.8 billion cubic meters, representing less than 3% of the global total [
3]. This stark contrast highlights the significant challenges China faces in shale gas exploration and development.
The primary component of shale gas is methane, which exists in shale primarily in adsorbed or free states, with the adsorbed state accounting for up to 85% of the total [
4]. Kerogen, the predominant carbonaceous material in shale, consists of over 90% carbon (C), hydrogen (H), and oxygen (O), along with trace amounts of nitrogen (N), phosphorus (P), and sulfur (S). Kerogen is typically classified into three types [
5]: Type I (Sapropelic kerogen): it contains abundant aliphatic chains, a small number of aromatic rings, and side-chain heteroatoms. The H/C ratio is typically greater than 1.5, and the O/C ratio is less than 0.1. Its pore structure is underdeveloped, consisting primarily of micropores with uneven distribution and low specific surface area. The density ranges between 0.8 g/cm
3 and 1.0 g/cm
3. Type II (Mixed kerogen): it contains fewer aliphatic components and a relatively high number of heteroatom functional groups, primarily lipid-based. The H/C and O/C ratios lie between those of Type I and Type III kerogen. The density typically ranges from 1.0 g/cm
3 to 1.2 g/cm
3. Type III (Humic kerogen): it consists mainly of aromatic rings and aliphatic chains, with a high proportion of aromatic rings. The O/C ratio ranges from 0.2 to 0.3, and the H/C ratio is less than 1. The density is usually greater than 1.1 g/cm
3, with well-developed and complex pore structures, including micropores, mesopores, and macropores.
The elemental composition, functional groups, and pore structure of kerogen significantly influence its methane adsorption behavior. Recent studies have increasingly focused on using realistic kerogen models to investigate methane adsorption characteristics. For instance, Tesson et al. [
6] conducted adsorption simulations on Type II-A kerogen using GCMC-MD methods, revealing that the diffusion coefficient of methane decreases by two orders of magnitude from the center of slit pores to the surface and organic matrix. They also proposed a potential coupling relationship between gas adsorption and kerogen matrix structural deformation. Huang et al. [
7] employed molecular dynamics and Monte Carlo simulations to construct kerogen models (primarily Type II) with varying pore sizes from the Longmaxi Formation. Their analysis indicated that methane preferentially adsorbs at the kerogen surface due to wall effects, with sulfur-containing groups serving as the primary adsorption sites. Lin et al. [
8] investigated methane adsorption in rough Type II kerogen nano-fractures, demonstrating that fracture roughness significantly affects methane adsorption behavior, with adsorption sites predominantly located in concave regions. Ho et al. [
9] used MD-GCMC methods to study methane adsorption in Type II-D kerogen models, showing that kerogen expansion increases with pressure, reaching a maximum of less than 5.4% at 300 K and 192 atm. Sui et al. [
10] studied Type II-A kerogen and found that the maximum methane-induced expansion was 4.45% at 340 K and 148 atm. Shi et al. [
11] investigated the adsorption and diffusion characteristics of Type II kerogen, demonstrating that the methane diffusion coefficient decreases with increasing burial depth. Li et al. [
12] simulated methane adsorption in Type II kerogen models, concluding that methane in small pores primarily exists in the adsorbed state, with almost no free state.
Despite these advancements, most studies have focused on modeling a single type of kerogen, particularly Type II, without considering the differences in adsorption performance among Type I, Type II, and Type III kerogen. Additionally, research on kerogen deformation induced by adsorption has primarily focused on volume expansion, neglecting changes in internal pore structures. Furthermore, most adsorption studies characterize adsorption behavior solely based on adsorption capacity, overlooking differences in adsorption heat. However, different types of kerogen exhibit distinct adsorption behaviors due to variations in thermal maturity, chemical composition, and pore characteristics. Investigating these behaviors can systematically reveal the nature of kerogen adsorption capacity and provide scientific insights into gas storage characteristics under different reservoir conditions. Adsorption-induced deformation directly affects stress distribution, pore structure changes, and permeability evolution in reservoirs. Adsorption heat, the energy difference between adsorbed and free states, determines the proportion of adsorbed and free gas and is one of the key factors contributing to the low permeability of shale gas reservoirs [
13]. Generally, higher adsorption heat makes shale gas easier to adsorb but harder to desorb.
Therefore, in this paper, we constructed microscopic cellular models of humic, mixed, and sapropelic types of kerogen, which differ from the traditional simplified structural models of graphene and the slit model of kerogen. Methane adsorption, adsorption energy, volume deformation effects, pore deformation effects, and diffusion coefficients were simulated. The results reveal the differences in adsorption characteristics among different kerogen types and compare them with previous studies. By integrating the actual conditions of typical shale formations in China, the adsorption behaviors of different kerogen types under varying reservoir pressures and temperatures are analyzed. This provides a more applicable theoretical foundation for shale gas development, particularly in optimizing gas reservoir development strategies for different kerogen types, offering significant practical implications.
2. Model Construction Method
2.1. Simulation of Kerogen Small Molecular Fragments
The presence of oxygen (O), nitrogen (N), and sulfur (S) elements in kerogen molecules significantly influences their adsorption behavior. To investigate these effects, a small number of benzene rings were extracted from a graphene molecular layer, and functional groups such as carboxyl and hydroxyl groups were constructed using O, N, and S elements to replace carbon (C) or hydrogen (H) atoms in the benzene rings. These modified fragments served as small molecular segments of kerogen, enabling the study of the impact of different elements on adsorption behavior. Molecular dynamics simulations were employed to optimize the small molecular fragments, and the Monte Carlo method was used to calculate the adsorption of a single methane molecule on the kerogen small molecular fragments (
Figure 1). The simulation results are summarized in
Table 1.
When the fragment contained only C and H elements, the methane molecule was positioned 3.536 Å away from the benzene ring. However, when C atoms in the benzene ring were replaced by O, N, or S elements to form new functional groups, the adsorption position and distance of methane exhibited notable changes. Among these elements, S caused the largest vertical displacement of methane, approximately 0.017 Å. When H atoms on the benzene ring were replaced by external functional groups, the C-S bond had the most significant influence on methane adsorption, resulting in a horizontal displacement of 0.861 Å. The C=O bond induced a horizontal displacement of approximately 0.603 Å, while the carboxyl and C-O bonds caused horizontal displacements of approximately 0.599 Å and 0.436 Å, respectively.
In terms of adsorption energy, the nitrogen (N) and oxygen (O) elements in the benzene ring of kerogen, as well as the oxygen (O) element in hydroxyl groups, exhibit a minor influence on adsorption energy. Notably, the oxygen (O) element in the benzene ring even slightly reduces the adsorption energy. In contrast, functional groups such as sulfur (S) in the benzene ring, C=O bonds, C-O bonds, C-S bonds, and carboxyl groups all contribute to an increase in adsorption energy. Among these, the C-S bond has a significantly greater effect on enhancing adsorption energy compared to other functional groups, being the only small fragment that elevates the adsorption energy above 10 kJ. These results demonstrate that different functional groups exert a notable impact on adsorption characteristics [
14]. Consequently, for different types of kerogen, the adsorption characteristics of methane vary significantly due to differences in elemental content and structural composition.
Furthermore, it is observed that the adsorption energy of small kerogen fragments is relatively low. This phenomenon can be attributed to the limited number of molecules in the fragments and their predominantly planar structure. Compared to the complex, irregular pore structures of real kerogen unit cells, planar structures possess a lower specific surface area and fewer active sites, resulting in reduced adsorption energy. Therefore, to better understand the influence of different kerogen types on adsorption energy, a three-dimensional realistic molecular model of kerogen was subsequently constructed for further investigation.
2.2. Simulation of Kerogen Unit Cells
The properties of kerogen molecules vary significantly depending on their formation environment and source. Even when the molecular weight of the model exceeds 10,000, it remains insufficient to systematically and comprehensively describe kerogen. Therefore, when constructing models, it is neither practical nor necessary to account for every detail. Instead, average molecular structures are typically employed to represent the physicochemical properties and structural characteristics of kerogen. In this study, based on the relevant literature, average molecular structures of sapropelic (Type I) [
15], mixed (Type II) [
16], and humic (Type III) [
17] kerogen were constructed, as illustrated in
Figure 2. Among them, the sapropelic kerogen comes from the Longkou mine in Shandong, China, which is an immature shale, with plankton, lignin, and other fatty organic substances as its main constituents. The mixed kerogen comes from the Longmaxi Formation shale mines in Sichuan. The organic matter composition of the shale in this area is mainly dominated by Type II kerogen, formed by the mixed deposition of both aquatic organisms and terrestrial plants, influenced by tidal and river conditions. Humic kerogen is an immature organic matter shale typical of an Asian mine, deposited in a post-Jurassic deltaic environment, and its composition is dominated by organic matter-rich terrestrial vegetation, soils, and sediments, forming Type III kerogen.
The average molecular formulas for these kerogen types are
,
, and
. Elemental analysis and functional group data were obtained using X-ray photoelectron spectroscopy (XPS) or carbon nuclear magnetic resonance (CNMR). Based on the elemental ratios, the total number of carbon atoms (ranging from 150 to 250) and the number of aromatic carbon atoms were determined, followed by the allocation of hydrogen, oxygen, sulfur, and nitrogen atoms. These atoms were then assigned to their corresponding functional groups based on nearest-neighbor elemental analysis results. The gNMR 4.0 software was then used to continuously simulate and adjust the constructed average molecular model until the simulated NMR spectrum closely matched the experimental results. The model parameters are shown in
Table 2.
The average molecular models of the aforementioned kerogen types were structurally optimized using the Forcite module. The COMPASS II force field was selected, with electrostatic and van der Waals interactions calculated using the Ewald and atom-based methods, respectively. The simulation was run for 50,000 steps to achieve the lowest energy configuration. Subsequently, 10 optimized average molecular models of kerogen were selected, and unit cells were constructed using the Amorphous Cell module based on the Monte Carlo method with random distribution. The initial density of the unit cells was set to 0.5 g/cm3, the temperature was maintained at 298 K, and periodic boundary conditions were applied.
The constructed three-dimensional unit cell models were further optimized using the Forcite module to minimize energy. The final densities of the unit cells were determined using the Dynamics function in the Forcite module. The resulting densities were 0.997 g/cm
3 for Type I kerogen, 1.124 g/cm
3 for Type II kerogen, and 1.162 g/cm
3 for Type III kerogen, which align well with the actual density ranges of the corresponding kerogen types. The models were then subjected to relaxation and annealing using the Forcite module to obtain the final equilibrium structures, as illustrated in
Figure 3 (top). Unlike the simplified model of graphene, this model is constructed strictly based on the actual elemental ratio of kerogen and uses molecular dynamics optimization to ensure that the model’s density matches that of real kerogen molecules. Furthermore, the model fully retains the irregular pore distribution characteristics of kerogen, avoiding issues such as narrow-pore models with simplified pore shapes that lead to a single pore type and a density lower than the actual situation. Additionally, the kerogen unit cell model in this paper focuses on the tiny pores within the kerogen matrix rather than the intermolecular slit-like gaps, which better aligns with the research needs of shale gas occurrence mechanisms. All subsequent simulations in the paper are based on this model.
Figure 3 (below) shows the pore distribution map of the kerogen unit cell. The pore parameters were measured using the molecular probe method. Since the diameter of methane is approximately 3.8 Å, it is commonly accepted that pore diameters larger than 4 Å are considered effective pore sizes, so the Connolly radius was selected to be 2 Å. The parameter values are shown in
Table 3. The results indicate that, from Type I to Type III kerogen, the pore size distribution exhibits a trend of transitioning from smaller to larger sizes, which is consistent with the geological evolution of kerogen and confirms the reliability of the model. The unit cell structure is reasonable, and therefore, all subsequent simulations were based on this optimized unit cell structure.
3. Simulation Process
3.1. Grand Canonical Monte Carlo Method
The simulation involved constructing models using molecular dynamics and performing adsorption simulations using the Grand Canonical Monte Carlo (GCMC) method [
12]. The Monte Carlo method, based on statistical mechanics, is widely employed to study and analyze distribution characteristics. Given the stochastic nature of shale gas adsorption in pores, this method is particularly suitable for adsorption research. The grand canonical ensemble is commonly used in conjunction with Monte Carlo adsorption simulations. In this ensemble, for each computational cycle, the temperature (
T), volume (
V), and chemical potential (
μ) remain constant, while the energy and number of molecules are continuously updated. Consequently, the partition function [
18] of this ensemble can be expressed as:
During the simulation process, methane gas is added, replaced, or removed with different probabilities. These operations are described as follows:
A molecule is randomly added, and the probability of acceptance is as follows:
A molecule is randomly replaced, and the probability of acceptance is as follows:
A molecule is randomly removed, and the probability of acceptance is as follows:
Here, is the volume of the model, m3; is the de Broglie wavelength of the particles in the model, m; is the Boltzmann constant, J/(mol·K); is the absolute temperature, K; are functions of and ; μ is the chemical potential of the particles, J/mol; is the total energy of the system, J/mol; is the total number of particles in the system; and s and s′ represent the configurations before and after the displacement, respectively. During the simulation, if the probability of any particle change exceeds a randomly generated number within the range [0, 1], the change is accepted, and a new configuration is generated to replace the original one.
3.2. Fugacity–Pressure Conversion
In Material Studio, the chemical potential is a function of fugacity, so the choice of pressure in simulations is mainly represented in terms of fugacity. Compared to pressure, fugacity provides a more comprehensive consideration of non-ideal adsorption behaviors, representing the escape ability and driving force of a gas in a given state. This is particularly significant under supercritical conditions, where the fugacity–adsorption amount correlation is more pronounced than that of pressure. The accuracy of fitting high-pressure adsorption isotherms is crucial. However, in practical experiments, due to experimental limitations, pressure parameters are usually used to characterize shale adsorption amounts, among other variables. To compare the simulation results with existing conclusions and verify the model’s accuracy, it is necessary to convert the simulated fugacity parameters into the corresponding pressure parameters. The fugacity–pressure conversion in this paper is based on the Peng–Robinson (PR) equation [
19]. Its complete form is as follows:
The equation can be rewritten in terms of the compressibility factor as follows:
where
By combining this with the thermodynamic relations, we ultimately obtain the following:
In the equation, P* is the pressure, MPa; R is the gas constant, 8.314 J (mol·K); T is the temperature, K; V is the molar volume, m3/mol; bi is volume parameter, m3/mol; Z is the compression factor; Ai and Bi are dimensionless parameter related to and ; is the temperature-dependent energy parameter, Pa·m6/mol2; and is the fugacity at , with units in MPa.
Using MATLAB R2020b software, the fugacity of methane was calculated, and the relationship curve between fugacity and pressure was obtained, as illustrated in
Figure 4. From the fitting results, it is evident that below 8 MPa, the fugacity of methane closely approximates the pressure. However, as the pressure increases, the fugacity becomes lower than the pressure. This is because, as pressure increases, the kinetic energy and interactions between gas molecules intensify, leading to a greater tendency for the gas to escape. However, since the methane used is not an ideal gas, the repulsive and attractive forces between molecules affect its behavior. Therefore, the increase in the escape tendency is smaller than the increase in pressure. When the temperature rises, the escape tendency also increases, as temperature enhances the kinetic energy and interactions of gas molecules. Especially for non-ideal gases, higher temperatures make it easier for the gas to overcome molecular interactions, leading to an increased tendency to escape into the external environment. This discrepancy between fugacity and pressure highlights the differences between Fick’s diffusion law and Darcy’s seepage law in describing the seepage characteristics in porous media. In this paper, microscopic diffusion properties are investigated, and it is more appropriate to use Fick’s law of diffusion to characterize percolation in porous media.
3.3. Model Validation and Adsorption Simulation
The accuracy of the constructed kerogen models directly determines the reliability of the simulation results. Ensuring the precision of the adsorption results is a fundamental prerequisite for the simulation. In this study, adsorption simulations were conducted using the Sorption module in Material Studio, with fugacity values selected in the range of 1 MPa to 20 MPa. By converting the fugacity parameters of the isothermal adsorption curve, calculated by the Sorption module, into pressure parameters and fitting them with other isothermal adsorption models, it is possible to verify the reasonableness of the adsorption simulation results. Given the non-uniform surface of the internal pores in kerogen, the Freundlich adsorption model was employed to fit the adsorption isotherms. The Freundlich formula is expressed as follows [
20]:
where
is the pressure in MPa, and
is the absolute adsorption amount in mmol/g.
and
are the equation coefficients, with
related to the specific surface area and adsorption temperature of the model, and
also related to the adsorption temperature. Since the adsorption amount in the adsorption isotherms plotted by the Sorption module is the specific number of methane molecules
adsorbed in a single unit cell, with the unit being average molecules/cell, it is necessary to convert the methane units to mmol/g before fitting. The conversion formula is as follows:
The parameters and in the Freundlich (11) model vary depending on the type of kerogen. Here, is the Freundlich adsorption constant, representing the adsorption capacity. Typically, the range of values is 0.3–0.7 for sapropelic kerogen (Type I), 0.5–1.0 for mixed kerogen (Type II), and 0.8–1.5 for humic kerogen (Type III). This increasing trend is directly related to the increase in the aromaticity and functional group content of the kerogen. The parameter represents surface heterogeneity, with values usually greater than 1. A larger value indicates greater surface non-uniformity of the kerogen.
A random value was selected as the initial value based on the corresponding distribution range of the Freundlich parameters for different types of kerogen, and iterative fitting was performed using Origin 2021 software. The best-fit results and corresponding parameter values were subsequently obtained. The results demonstrate that the adsorption behavior of the kerogen models constructed in this study adheres to the Freundlich adsorption law, as illustrated in
Figure 5. The relevant fitting parameters are summarized in
Table 4. The variations in parameters K and n are higher for high-type kerogen compared to low-type kerogen, which is consistent with the changes in parameters across different kerogen types. Furthermore, since the average molecular model used in the compositional model is correct, and the atomic composition aligns with the actual kerogen molecules, as well as the structural parameters, density, and porosity matching those of the kerogen molecules, it is concluded that the model is correctly constructed.
Furthermore, since the model constructed in this study is a microscopic kerogen model at the molecular scale, with dimensions smaller than 4 nm, the pores in the model primarily exist as micropores. As a result, the adsorption results slightly differ from the macroscopic experimental adsorption quantities measured. As shown in
Figure 6, taking Type II kerogen as an example at 338 K and 20 MPa, the simulated adsorption quantity of Type II kerogen is 1.162 mmol/g, while the experimental adsorption quantity for Barnett shale, which is primarily composed of Type II kerogen, reaches 1.374 mmol/g. The adsorption quantity for kerogen with the same mass, simulated under high-pressure conditions, is slightly lower than the macroscopic adsorption quantity measured in the laboratory [
21]. However, at 3MPa, the simulated adsorption quantity is 0.714 mmol/g, while the experimental adsorption quantity is 0.632 mmol/g. This difference reflects the unique properties of micropore adsorption. The limitation in model size leads to the dominance of micropores during adsorption, resulting in slightly smaller simulated adsorption at high pressure compared to the macroscopic experimental results, while at low pressure, the simulated adsorption is slightly larger. This also serves as strong evidence to verify the rationality of the model.
Moreover, as pressure increases, the simulated adsorption quantity exhibits a trend nearly identical to the experimental adsorption quantity, which is highly consistent with previous works, especially the conclusions of Zhang [
22] and others, who found that methane adsorbs onto kerogen through surface adsorption and pore-filling adsorption, with pore filling being the dominant form of adsorption. At the same time, the maximum value of the simulated methane adsorption phase density reaches 0.385 g/cm
3, which is close to the commonly used experimental adsorption phase density value of 0.373 g/cm
3 (van der Waals density) and the previously measured adsorption phase density value of 0.377 g/cm
3, further validating the reliability of the model [
23,
24]. The slightly higher value is due to the micropores having a larger specific surface area, which leads to a cumulative adsorption effect and stronger adsorption capacity. These mutually corroborating pieces of evidence, from molecular structure to macroscopic properties, comprehensively demonstrate the correctness of the model construction and lay a solid theoretical foundation for the study of the microscopic adsorption mechanism of kerogen.
5. Conclusions
Based on the microscopic unit cell structures of the three types of kerogen, this study investigated the adsorption characteristics of methane in different types of kerogen using molecular dynamics and Monte Carlo methods. The following conclusions were drawn:
(1) Different elements in kerogen have a significant impact on methane adsorption energy and adsorption sites. The effect of sulfur (S) is the most pronounced, with the presence of C-S bonds causing a shift in the adsorption site by 0.861 Å and increasing the adsorption energy by 1.418 kJ. In contrast, nitrogen (N) has a minimal effect on methane adsorption. This finding clearly highlights the key role of sulfur-containing functional groups in kerogen adsorption, providing a theoretical basis for optimizing shale gas reservoir evaluation.
(2) The adsorption heats of the three types of kerogen follow the trend: Type I < Type II < Type III, with the limiting adsorption heats being 20.184 kJ/mol, 26.658 kJ/mol, and 28.436 kJ/mol, respectively, and the equivalent adsorption heats being 19.645 kJ/mol, 19.978 kJ/mol, and 24.135 kJ/mol, respectively. As the adsorption amount increases, the adsorption energy decreases. This indicates that the three types of kerogen have better gas storage potential. However, during extraction, due to their higher adsorption capacity, more efficient pressure-reduction and temperature-increase strategies need to be designed according to their characteristics.
(3) Kerogen adsorption leads to the expansion of both the total volume and pore volume as the adsorption amount increases, with expansion being type-dependent. Type I kerogen undergoes rapid expansion in the initial adsorption stage, while Type II and Type III kerogen enter the rapid expansion phase sequentially as the adsorption amount increases. The total volume expansion rate of kerogen is less than 3%, while the pore volume expansion rate can reach up to 57%. This provides a new approach for improving pore connectivity by utilizing the expansion effect.
(4) The diffusion coefficients of the three types of kerogen at 298 K and 21 MPa are 0.0464 Å2/Ps, 0.0187 Å2/Ps, and 0.0125 Å2/Ps, respectively. The diffusion coefficient of methane in the ultramicropores of kerogen measured in simulations is much smaller than the diffusion coefficient measured in macroscopic experiments, with the difference exceeding one order of magnitude. This difference in diffusion coefficients clarifies the relationship between the kerogen structure and gas storage at the molecular scale, providing new insights for shale gas micropore desorption and production capacity prediction.