The influences of composition and pore structure on the adsorption behavior of CH₄ and CO₂ on shale

Abstract

CO₂ enhanced shale gas recovery (CO₂-ESGR) has attracted extensive attention as it can improve the shale gas recovery efficiency and sequestrate CO₂ simultaneously. In this study, the relationship between mineral composition, pore structure, CH₄ and CO₂ adsorption behavior as well as selective adsorption coefficient of CO₂ over CH₄ ({\alpha }_{{CO}_2/{CH}_4}) in marine and continental shales at different temperatures was investigated. The results illustrated that shale with higher total organic carbon (TOC), higher clay minerals and lower brittle mineral contents has a larger micropores and mesopores volume and specific surface area. TOC content was positively correlated with fractal dimension D_f. Both CH₄ and CO₂ adsorption capacity in shale have positive correlations with TOC and clay mineral content. CO₂ adsorption capacity of the all the tested shale samples were greater than CH₄, and the {\alpha }_{{CO}_2/{CH}_4} of shale were larger than 1.00, which indicated that using CO₂-ESGR technology to improve the gas recovery is feasible in these shale gas reservoirs. A higher TOC content and in shale corresponding to a lower {\alpha }_{{CO}_2/{CH}_4} due to the organic matters show stronger affinity on CH₄ than that on CO₂. Shale with a higher brittle mineral content corresponding to a higher {\alpha }_{{CO}_2/{CH}_4}, and no obvious correlation between {\alpha }_{{CO}_2/{CH}_4} and clay mineral content in shale was observed due to the complexity of the clay minerals. The {\alpha }_{{CO}_2/{CH}_4} of shale were decreased with increasing temperature for most cases, which indicated that a lower temperature is more favorable for the application of CO₂-ESGR technique.

Graphical abstract

Keywords

shale gas / carbon dioxide sequestration / pore structure / selective adsorption / fractal dimensions

1 Introduction

Shale gas, as a kind of unconventional natural gas, has attracted worldwide attention in recent years as a clean energy with huge reserves (Dayal, 2017; Shan et al., 2017; Cui et al., 2019; Jiao, 2019; Shcherba et al., 2019; Wang et al., 2019a; Zeng et al., 2019; Kuang et al., 2020; Pang et al., 2020; Zhang et al., 2020). The CO₂ enhanced shale gas recovery (CO₂-ESGR) is a promising technology as it can promote the shale gas recovery and simultaneously sequestrate CO₂ in shale gas reservoir (Li and Elsworth., 2015; Pei et al., 2016; Zhou et al., 2019a; Iddphonce et al., 2020). Generally, shale gas is stored in reservoirs in three states, including free gas, dissolved gas and adsorbed gas. Adsorbed gases account for 20%-85% of total gas in shale gas reservoirs (Charoensuppanimit et al., 2016; Wang et al., 2016). The mechanism of CO₂-ESGR in shale is the displacement of originally adsorbed CH₄ by the injected CO₂ due to the different adsorption potential in shale between CO₂ and CH₄ (Du et al., 2019; Klewiah et al., 2020; Zhou et al., 2020). Thus, understanding the adsorption behaviors of CH₄ and CO₂ on shale is essential to determining shale gas recovery efficiency and the geological CO₂ storage potential in shale.

The adsorption behavior of CH₄ and CO₂ in shale is mainly influenced by the factors of reservoir conditions and shale properties. Reservoir conditions include temperature, pressure, in-situ stress and water saturation, while shale properties include total organic carbon content, maturity, mineral type and content, and pore structures (Zhou et al., 2019b; Klewiah et al., 2020; Qin et al., 2020; Zhang et al., 2020). The adsorption capacity of CH₄ and CO₂ usually show positive correlations with organic matter content and pore specific surface area in shale, while the adsorption capacity of CH₄ and CO₂ show complex relationship with brittle minerals and clay minerals, depending on the specific mineral composition and content (Gasparik et al., 2014; Hellar and Zoback, 2014; Gu et al., 2017; Zhou et al., 2018; Zhou et al., 2019c; Klewiah et al., 2020). Generally, the adsorption capacity of CO₂ on shale is always larger than that of CH₄, however, the selective adsorption coefficient of CO₂ over CH₄ (α_CO2/CH4), which can be used as an important index to evaluate the competitive adsorption of CO₂ and CH₄, has shown a wide variation range in different shales (Duan et al., 2016; Zhou et al., 2017; Qi et al., 2018; Liu et al., 2019). The α_CO2/CH4 in shale is also relevant to the pore structure, organic matter type and mineral composition of shale (Gu et al., 2017; Liu and Hou, 2020). 

The nanopore/micropore inner surfaces of organic and inorganic components in shale is the main adsorption site for CH₄ and CO₂, thus, the pore structure of shale has significant influence on the adsorption behaviors of shale. Shale pore structure has strong heterogeneity, and is also related to the mineral composition of shale as shale with higher TOC, higher quartz content and lower clay content tend to contain more heterogeneous micropores (Hou et al., 2018; Zhou et al., 2018; Li et al., 2020b). Fractal theory can be used as an efficient method to quantitatively characterize the pore structure (Zhang et al., 2016; Hou et al., 2018; Li et al., 2018; Zhou et al., 2018; Feng et al., 2019; Liu et al., 2020). Theoretically, fractal dimension is an effective parameter to reflect the complexity of pore structure (Zhou et al., 2018), thus it may be a useful index to describe the adsorption behavior of shale and establish the relationship between pore structure and adsorption capacity of CH₄ and CO₂ in shale.

As multiple factors such as mineral compositions and pore structure show different influences on the adsorption capacity and selective adsorption of CH₄ and CO₂ for different shales, so it is requisite to conduct specific research on the basis of specific cases. In addition, the mineral composition, pore structure and adsorption behaviors of shale are interrelated and influence each other. In this study, the relationship between shale mineral compositions, pore structure (including the amount of micropore/mesopore/macropore, fractal characteristics) and shale adsorption characteristics of CH₄ and CO₂ (including adsorption capacity and selective adsorption coefficient) for marine shale and continental shale in different regions was determined, aims to reveal the influence of shale properties on the CH₄ and CO₂ adsorption behaviors, then further provide the guidance for the evaluation of adaptability for the application of CO₂-ESGR technology in different shale gas reservoirs.

2 Materials and methods

2.1 Samples preparation

Six shale samples were used in this study, four marine shale samples were collected from the Silurian Longmaxi Formation (three samples, labeled as LMX1, LMX2 and LMX3) and the Ordovician Wufeng Formation (one sample, labeled as WF), two continental shale samples were collected from and the Triassic Yanchang Formation (two samples, labeled as YC1 and YC2). The WF sample was obtained from outcrop, and the LMX1, LMX2, LMX3, YC1 and YC2 samples were obtained from drilling cores at the depth of 660.0 m, 679.3 m, 629.8 m, 506.9 m and 660.1 m, respectively. The mineral composition, element content and pore structure of all the collected samples were characterized by X-ray fluorescence (XRF) spectrometry, X-ray diffraction (XRD) and low-temperature nitrogen adsorption, respectively, then the relationship between mineral compositions and pore structure was determined. Four samples (two marine shale samples LM1 and WF, and two continental shale samples YC1 and YC2) were selected for CH₄ and CO₂ adsorption measurements. As shown in Fig. 1, all shale samples were powdered and sieved according to the requirements of each test object. Samples were stored and transported in sealed bags filled with helium gas, which prevents the sample from interacting with gases in the air. The gases used in the adsorption experiments were pure CH₄ and CO₂.

2.2 Experimental section

2.2.1 Mineral compositions and geochemical parameters analysis

The element content and mineral compositions of the shale samples were determined by XRF and XRD, respectively. The XRF (RIGAKU ZSX Primus III plus) was conducted at 50 kV and 40 mA and the XRD (Rigaku D/Max-2500/PC) operated with Cu Kα radiation at 40 kV, 40 mA. Total Organic Carbon (TOC) content was obtained by Multi N/C 3100 TOC-TN analyzer (Analytik Jena, Germany). The organic maturity (R_o) was determined by Polarizing Microscope (DM 4500P, Leica, Germany).

2.2.2 Pore Structure characterization

Pore structure of shale samples was analyzed by the low pressure nitrogen (N₂) adsorption measurements. The Micrometritics ASAP 2020 system was used to obtain low pressure nitrogen (N₂) adsorption/desorption isotherms. Based on low pressure nitrogen (N₂) adsorption/desorption isotherms and IUPAC pore size classification standard ((micropores (0‒2 nm), mesopores (2‒50 nm), and macropores (>50 nm)) (Sing, 1982), total specific surface area (SSA_total), micropore (SSA_mic), mesopore (SSA_mes) and macropore (SSA_mac)) specific surface area were calculated by Brunauer-Emmett-Teller (BET) model, and the total pore volume (PV_total), micropore (PV_mic), mesopore (PV_mes) and macropore (PV_mac)) pore volume and average pore diameter (PD_avg) were determined by Barret-Joyner-Halenda (BJH) model (Brunauer et al., 1938; Thommes et al., 2015).

2.2.3 CH₄ and CO₂ adsorption isotherms measurements

The adsorption isotherms of CH₄ and CO₂ of shale samples were determined by the volumetric method. All the adsorption measurements were accomplished in the PCTPro Full-automatic high-pressure gas adsorption/desorption instrument of Setaram (France) (Keshavarz et al., 2017), the physical picture of the system is shown in Fig. 2. The adsorption isotherm measurements were performed at different temperatures (298.15K, 318.15K, and 338.15K). To avoid the influence of residual moisture in shale on the adsorption isotherm test, all samples were dried at 105°C for 24 hours before the experiment.

3 Results and discussion

3.1 Mineral compositions and pore structure of shale samples

3.1.1 Mineral compositions

Table 1 shows the main element content of the tested shale samples, it can be concluded that the shale samples mainly composed of elements of Si, Al, Ca, Fe, K, Mg, S, etc. In addition, a small amount of elements such as Na, Ti, Ba, P, etc., with the contents less than 1.0% wt are also contained. Table 2 shows vitrinite reflectance (R_o), the total organic carbon (TOC) content and mineral compositions of the shale samples. The range of R_o in all the tested shale samples is between 0.93%‒2.76%, and the range of TOC is 1.89%‒3.53%. It was found that the average values of R_o and TOC in marine shales (2.98% and 2.28%, respectively) are larger than those in continental shales (2.14% and 0.99%, respectively), which is consistent with the results of others (Yang et al., 2017; Wang and Guo, 2020). The quartz, carbonate, feldspar and clay minerals were the main mineral components of the tested shale samples. Brittle mineral contents of quartz, carbonate and feldspar for the tested shale samples were 36.6%‒40.8%, 0.4%‒9.2%, 4.8%‒20.3%, respectively. The total content of brittle minerals is 43.9%‒57.3%, which shows good fracturability (Zou et al., 2010). Clay minerals, including kaolinite, montmorillonite, illite, and chlorite, which contribute micropore volume and provide adsorption sites for gas (Lu et al., 1995; Slatt and O’Brien, 2011), accounted for a high proportion of 40.1%‒54.9%.

3.1.2 Pore structure characterization

The low pressure N₂ adsorption isotherms of all the tested shale samples are shown in Fig. 3, it can be seen from that there is a significant hysteresis loop between the adsorption-desorption isotherms. The shape of hysteresis loop can reflect the micromorphology of shale pore structure. According to the IUPAC classification of hysteresis loops, the N₂ adsorption-desorption isotherms of marine shale samples belong to H2 and H3 types as the adsorption and desorption curves almost coincide in the low relative pressure area, which indicated the presence of slit-like and ink-bottle-shaped pores in shale. The N₂ adsorption-desorption isotherms of continental shale samples belong to H3 and H4 types, which are associated with slit-shaped pores and narrow slit-shaped pores (Thommes et al., 2015; Zhang et al., 2016).

Pore structure parameters determined from low pressure N₂ adsorption isotherms are listed in Table 3. The total pore volume PV_total ranges from 9.70‒15.70×10⁻³ cm³/g, in which PV_mes is dominant which ranges from 5.61‒10.79×10⁻³ cm³/g), accounting for 70.51%‒89.23% of PV_total. The total specific surface area SSA_total ranges from 1.64‒16.67 m²/g, and SSA_mes is still dominant which accounting for more than 68.48% of the SSA_total. It is worth noting that the micropore and mesopore volume of shale samples account for 69.95%‒90.93% of the total pore volume, while the specific surface area of micropore and mesopore accounts for 89.74%‒99.45% of the SSA_total, indicating that micropores and mesopores contribute the majority specific surface area in shale, and provide the majority adsorption site for gas in shale.

The irregularity of pore surface morphology and structure in porous media can be characterized by fractal theory (Li et al., 2016; Li et al., 2019). The Frenkel–Halsey–Hill (FHH) model is widely used for calculating the fractal parameters of irregular pores in heterogeneous solids based on the data of N₂ adsorption (Pomonis and Tsaousi, 2009; Cai et al., 2013).

Using the FHH model, the fractal dimension (D_f) can be determined by:

(1)\ln V=A\ln \left[\ln \left(p_{\mathrm{0}}/p\right)\right]+\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t},

(2)D_{\mathrm{f}}=A+\mathrm{3}

where V denotes the volume of adsorbed gas molecules at the equilibrium pressure p (MPa), cm³/g; A represents a linear correlation coefficient; p₀ is saturated vapor pressure, MPa. The plots of lnV versus ln(ln(p₀/p)) and calculated D_f are shown in Fig. 4 and Table 4. There is a strong linear relationship for all the fitted curves as the fitting coefficients R² were greater than 0.97. Various D_f values reflect the difference in structural complexity of different shale samples. The D_f of the tested shale sample ranges from 2.3140‒2.8116, which is between 2 and 3, indicating that the pore structure of shale shows obvious fractal characteristics (Jaroniec, 1995). The D_f of the tested marine shales is larger than that of continental shales, revealing that the pore structure of the marine shale samples is more complex than that of continental shale samples.

3.1.3 Correlations between mineral composition and pore structure of shale

Shale includes minerals and organic matters, both of which have a strong influence on its pore structure. Figure 5 shows the relationship between R_o, TOC and the relevant pore structure parameters of shale. The correlation between R_o and total pore volume, total specific surface area in Fig. 5(a) is not obvious, which may be due to the fact that thermal evolution process has a complex influence on the pore structure. Ma and Guo (2020) observed that when the R_o values ranged in 0.93%‒2.76%, there is also no linear correlation between the R_o and the pore volume, which is similar to the tested shale samples in this study. There is a positive correlation between TOC and PV_mic (R²=0.8426), a weak positive correlation between TOC and PV_mec (R²=0.4242), and no obvious correlation between TOC and PV_mac (R²=0.2437) (Fig. 5(b)), which is due to that the organic matter contained abundant micropore in shale. Generally, organic matter in shale contained much nano-pores with the pore size less than 2 nm, so there is a good correlation between TOC and micropore. The positive correlation between SSA_mic, SSA_mes and TOC in Fig. 5(c) further indicates that organic matter contains abundant micropores and mesopores. It should be noted that TOC also has a good correlation with SSA_total (R²=0.8073), which further proves that the specific surface area of pores is mainly contributed by micropores and mesopores. Fig. 5(d) shows that TOC content was positively correlated with fractal dimension D_f (R²=0.7041). The shale with higher TOC content contained more developed organic matter pores, which leads to rougher pore surface and more irregular pore structure, as a higher D_f corresponding to more complex pore structure in shale, thus the D_f increased with the increase of TOC.

Figure 6 shows the effect of clay mineral and brittle mineral contents on the pore structure of shale. The clay mineral content in shale is positively correlated with PV_total, PV_mes and PV_mac in different degrees (R² values were 0.8046, 0.8011 and 0.7557, respectively), while the correlation with PV_mic was not obvious (R²=0.2634) (Fig. 6(c)). And it is also positively correlated with SSA_total (R²=0.8161), while it is weakly negatively correlated with PD_ave (R²= 0.2790) (Fig. 6(d)). There are two groups of pores in clay minerals: micron-sized pores and nano-sized pores, in which montmorillonite mainly develops micropores, kaolinite mainly develops 20‒100 nm intergranular pores, illite and chlorite mainly develop micron-sized macropores (Ji et al., 2012a). The clay minerals in the tested shale samples mainly contain illite and chlorite, and a small amount of montmorillonite (Table 2), therefore, there is an obvious positive relationship between clay mineral content and PV_mes and PV_mac, while a weak relationship with PV_mic. However, clay minerals can fill the macropore space and suppress the development of macropores, thus, there is a negative correlation between the clay minerals content and PD_ave.

The content of brittle minerals is negatively correlated with PV_total (R²=0.7580), PV_mic (R²=0.8287) and PV_mes (R²=0.7357). There is also a good negative correlation between SSA_total and brittle mineral content (R²=0.9730), while the PD_ave is positively correlated with the content of brittle minerals (R²=0.6691). Wang et al. (2014) argued that per unit mass of organic matter in shale contributed the largest pore volume, followed by clay minerals, then finally is brittle minerals. Thus, with the increase of brittle minerals, the pore volume of shale was decreased. In addition, diagenesis is also an essential factor affecting pores development in brittle minerals, the majority of the brittle minerals contained in shale is quartz, the authigenic quartz can occupy part of the pore space in shale, resulting in decreases in the PV and SSA of shale. Nevertheless, there is no apparent correlation between the PV_mac and the content of brittle minerals. Overall, the thermal evolution degree, organic matters, clay minerals and brittle minerals content of shale all affect the pores development in shale, however, for different shale samples collected from different geological strata, the main control factor for the pore structure evolution is different, the comprehensive effects of these influencing factors on the pore structure are preferred to be considered.

3.2 Adsorption characteristic of CO₂ and CH₄

3.2.1 Adsorption isotherms of CH₄ and CO₂

The isothermal adsorption curves of CH₄ and CO₂ on shales at different temperatures are shown in Fig 7. At a certain temperature, the CH₄ and CO₂ adsorption capacity were increased with the increase of pressure. The increase rate of CH₄ and CO₂ adsorption volume at low pressure stage is larger than that at high pressure stage, and the increase rate gradually decreases with the increase of pressure. At the higher pressure stage, the CH₄ adsorption isotherm showed a steady upward trend tend to a saturation state, however, the CO₂ adsorption isotherm shown a sustained growth trend in the tested pressure range, which indicated that CO₂ adsorption in shale is far from its saturation adsorption state due to the maximum adsorption pressure is relative low in this study. The adsorption capacities of CH₄ and CO₂ on all the tested shale samples decreased with the increase of temperature. This is because of that the adsorption in shale is an exothermic process, thus at higher temperature is not conducive to gas adsorption, resulting in a lower adsorption of CH₄ and CO₂ at higher temperatures.

The adsorption data of CH₄ and CO₂ on shale were fitted to the commonly used Langmuir model (Langmuir, 1918):

(3)V={\displaystyle \frac{V_{L}P}{P+P_L}}\mathrm{.}

where, V is the adsorption amount at pressure P, mmol/g; V_L is Langmuir volume, which is corresponding to the maximum or total volume of gas that can be adsorbed in shale at infinite pressure, mmol/g; P_L is Langmuir pressure, which is corresponding to the pressure at which one half of the Langmuir volume can be adsorbed, MPa.

The fitting curves of CH₄ and CO₂ adsorption data for the Langmuir model are also shown in Fig. 7 with calculated parameters in Table 5. Langmuir model produce good fits for CH₄ and CO₂ adsorption isotherms in the tested pressure ranges with the fitting coefficient R² ranges of 0.9558‒0.9970. As shown in Table 5, at the same temperature, the V_L of CO₂ is always greater than that of CH₄ for all the tested shale samples, indicating that the adsorption capacity of CO₂ is greater than that of CH₄. The V_L of CH₄ and CO₂ decreased with the increase of temperature, which is consistent with the variation trend of CH₄ and CO₂ adsorption amount shown in Fig. 7. The P_L of CH₄ is higher than that of CO₂ at the same temperature, P_L reflect the affinity between the adsorbate and the adsorbent, a lower value of P_L imply a greater affinity of the adsorbate towards to the adsorbent (Gensterblum et al., 2013). P_L increased with the increase of temperature, indicating that the increase of temperature will weaken the affinity between gas molecules and shale. Shales from different regions and geological formations show different adsorption capacities of CH₄ and CO_2, thus, when adapting the CO₂-ESGR technology in different shale gas reservoirs, it is essential to study the CH₄ and CO₂ adsorption behavior on a case by case basis.

3.2.2 Effect of mineral compositions on the adsorption capacity of shale

Figure 8 shows the relationship between R_o, TOC and the V_L of CH₄ and CO₂ in shale. As shown in Figs. 8 (a) and 8(b), no direct correlation was observed between the adsorption capacity of CH₄ and CO₂ on shale and R_o (R² range is 0.2005-0.2989). Klewiah et al., (2020) argued that with the increase of thermal maturity (R_o), organic matter develops micropores as kerogen is thermally converted, and the increase of the amount of micropores improves the adsorption capacity of shale. Nonetheless, the prior analysis in this study illustrated the R_o of selected shale samples has no obvious relationship with the pore structure parameters, then R_o shows no direct correlation with the adsorption capacity of shale. There is a clear linear positive correlation between TOC content and V_L of CH₄ on shale (R² is 0.7800‒0.9075) (Fig. 8 (c)). Although V_L of CO₂ on shale also increases with the increase of TOC, but the linear relationship is not strong (R² is 0.2694‒0.6434) (Fig. 8 (d)), which indicated that adsorption of CH₄ in shale shown more significant relationship between TOC content than that of CO₂. Generally, a higher content of TOC corresponding to a more developed organic matter pores with more abundant adsorption sites in shale, thus the V_L of CH₄ and CO₂ were increased with the increase of TOC content, the results are consistent with the findings of Hong et al. (2016). In this study, the linear relationship between TOC and the maximum adsorption capacity of CH₄ is stronger than that of CO₂, indicating that the adsorption capacity of shale to CH₄ is more closely related to TOC. The reason may be due to that organic matter is more inclined to adsorb CH₄ (organic material) than CO₂ (inorganic material), while the inorganic material is more likely to adsorb CO₂ than CH₄ (Ross and Bustin, 2009).

The influence of mineral composition on the CH₄ and CO₂ adsorption capacity in shale are shown in Fig. 9. There is a weak positive correlation between the clay mineral content and the maximum adsorption capacity of CH₄ and CO₂ (Figs. 9 (a) and 9(b)). Clay mineral are commonly considered to contain abundant adsorption sites in shale. The influence of clay minerals on the adsorption capacity of shale has two main mechanisms. First, the increase of clay mineral content is conducive to the development of nano-scale pores, thereby improving the gas adsorption capacity of shale. In addition, the strong hydrophilicity of clay minerals makes the adsorption sites more easily occupied by water molecules, which inhibits the adsorption of gas in shale (Passey et al., 2010; Ji et al., 2012a). The samples used in this study are dried before the adsorption measurement, thus the first mechanism plays a dominant role, leading to the gas adsorption capacity increased with the increase of clay minerals content. In addition, many scholars have reported that the effect of clay minerals on the adsorption characteristics of shales is not obvious with high TOC shale, which may be another reason for the weak correlation in this study (Wang et al., 2013; Gasparik et al., 2014; Bi et al., 2016). It should be noted that adsorption capacity of CO₂ shown a more significant correlation with clay minerals than that of CH₄, which may be due to the aforementioned reason that inorganic minerals are more inclined to adsorb CO₂. The V_L of CH₄ and CO₂ in shale is negatively correlated with brittle minerals, which may be due to that the increase of brittle mineral content may lead to the decrease of micropores development, thus caused the decrease of gas adsorption capacity in shale. In addition, the increase of brittle mineral content may cause the decrease of TOC and clay mineral content in shale, thus further decrease the adsorption capacity of shale.

3.2.3 The influence of pore structure on the adsorption capacity of shale

Figures 10, 11(a) and 11(b) show that V_L of CH₄ and CO₂ in shale is positively correlated with both PV_total and SSA_total for a certain temperature, and the correlation between V_L and SSA_total is obviously stronger than that between V_L and PV_total. Generally, a larger SSA_total means more adsorption sites in shale, which is more conducive to gas adsorption in shale. Figure 11 shows that V_L of CH₄ is more significantly related to SSA_mic and SSA_mes than V_L of CO₂. CO₂ and CH₄ adsorption capacity in shale is influenced by comparative effects of organic matter pores and inorganic pores on the adsorption behaviors in shale (Hou et al., 2014). The previous analysis shown that organic matter has stronger affinity for CH₄, while clay minerals have stronger affinity for CO₂. As the micropores and mesopores in shale is mainly contributed by organic matter, thus V_L of CH₄ is more significantly correlated with SSA_mic and SSA_mes than that of CO₂ (Figs. 11(c) and 11(e)). Figure 11 also shown that the correlation between V_L of CO₂ and SSA_mes is the most significant compared with SSA_mac and SSA_mic, which shown a good consistent with the relationship between clay mineral content and mesopore volume shown in Fig.6(a). The results also indicated that CO₂ is preferred to be adsorbed on the mesopore contributed by clay mineral and further confirmed that the clay minerals are more likely to adsorb CO₂ than CH₄. It should be noted that the fitting coefficients of the correlation between V_L of CH₄ and CO₂ with SSA_total, SSA_mic, SSA_mes and SSA_mac were decreased with the increase of temperature, especially for the cases of CO₂ adsorption at the temperature condition of 338K, the correlation becomes very weak, which indicated that the influence of the temperature on the CO₂ adsorption characteristics is more significant than CH₄, and the adsorption behavior of shale is controlled by the combination effects of shale properties and reservoir conditions.

3.3 Selective adsorption of CO₂ and CH₄ on shale

3.3.1 Selective adsorption coefficient

The selective adsorption coefficient of CO₂ over CH₄ (α_CO2/CH4) on shale is an important parameter to evaluate the feasibility for CO₂-ESGR technique, which can be obtained as follows (Duan et al., 2016).

(4){\alpha }_{{\mathrm{C}\mathrm{O}}_2/{\mathrm{C}\mathrm{H}}_4}=\frac{V_{{L\mathrm{C}\mathrm{O}}_2}}{V_{{L\mathrm{C}\mathrm{H}}_4}}\cdot \frac{b_{{\mathrm{C}\mathrm{O}}_2}}{b_{{\mathrm{C}\mathrm{H}}_4}},

where, V_{{L\mathrm{C}\mathrm{O}}_2} and V_{{L\mathrm{C}\mathrm{H}}_4} are the Langmuir volume of CO₂ and CH₄, mmol/g, respectively, b_{{\mathrm{CO}}_2} and b_{{\mathrm{CH}}_{\mathrm{4}}} are respective fitting constants.

Table 6 shows the α_CO2/CH4 for all the tested samples, it can be observed that α_CO2/CH4 ranges of 2.85-7.83 at various temperatures, which indicated that the adsorption capacity of CO₂ in different types of shale is greater than that of CH₄, thus it is feasible for CO₂ injection to enhance shale gas recovery in these shale formations. At the same temperatures, the α_CO2/CH4 values of continental shale samples are higher than those of marine shale samples, which indicated that the CO₂-ESGR technique is likely more adaptable in continental shale. In addition, it can be seen from Table 6 that α_CO2/CH4 decreased with increasing temperature for most cases, which may due to that the interaction force of CO₂-shale decreased more significant than that of CH₄-shale with the increase of temperature. Therefore, a lower temperature is more favorable for the application of CO₂-ESGR technique.

3.3.2 Effect of mineral compositions on α_CO2/CH4 in shale

Figure 12 shows the relationship of R_o, TOC, clay mineral content, brittle mineral content and α_CO2/CH4 in shale. Figures. 12(a) and 12(b) show that α_CO2/CH4 is negatively correlated with R_o and TOC at the various temperatures. Although the relationship between R_o and the adsorption of CO₂ and CH₄ is not obvious, there is a weak negative correlation between R_o and α_CO2/CH4 (R² is 0.4189‒0.5222). Especially at the temperatures of 298.15K and 318.15K, α_CO2/CH4 and TOC shown more significant correlations (R² is 0.9662 and 0.9066, respectively), which is due to organic matter is more likely to adsorb CH₄, and this result is also consistent with the stronger correlation between TOC and CH₄ maximum adsorption capacity obtained above. The correlation between α_CO2/CH4 and TOC decreases significantly at 338.15K (R²=0.1751), indicating that the effect of temperature on the relationship between α_CO2/CH4 and TOC cannot be ignored. Figure. 12(c) shown that shale with a higher brittle mineral content corresponding to a higher α_CO2/CH4, which may be due to the more significant negative correlation between V_L of CH₄ and brittle minerals than that of CO₂. However, in Fig. 12(d), there is no obvious correlation between α_CO2/CH4 and clay mineral content in shale. The component of clay minerals in shale is complex, the α_CO2/CH4 of different pure component is varied widely. The adsorption capacity of illite and kaolinite for CO₂ is about 1.5 times and 4.0 times of that for CH₄, respectively (Heller and Zoback, 2014). Marine shale has higher content of illite and lower content of kaolinite than continental shale, which contributes to the higherα_CO2/CH4 in continental shale (Table 6).

3.3.3 Effect of pore structure on α_CO2/CH4 of shale

The correlations between α_CO2/CH4 and PV_total, PV_mic, SSA_total and SSA_mic are shown in Figs. 13(a)‒13(d), and the negative correlations were observed between α_CO2/CH4 and these parameters. The negative correlation between PV_total, SSA_total and α_CO2/CH4 is less pronounced (R²≤0.4568), while the relationship between PV_mic, SSA_mic and α_CO2/CH4 is more obvious (R² = 0.7054‒0.8758 and 0.4989‒0.6363 respectively). This is because the micropores associated with the organic components in the shale are favorable for the adsorption of CH₄, resulting in the decrease of α_CO2/CH4 with the increase of PV_mic and SSA_mic. The TOC value and micropore volume of marine shale are larger than those of continental shale, which leads to the α_CO2/CH4 of marine shale is smaller than that of continental shale at same temperature. Figure 13(e) shows α_CO2/CH4 is negative correlated with fractal dimension D_f of pore structure, as D_f can reflect the complexity and heterogeneity of pore structure, and is closely related to the organic matter and mineral content in shale, thus it can be used as a parameter to qualitatively characterize the α_CO2/CH4 of shale.

4 Conclusions

In this study, the adsorption behaviors of CH₄ and CO₂ were invested by using the marine shales of Wufeng-Longmaxi formation and the continental shales of Yanchang formation. The main conclusions are as follows.

1. Shale with higher TOC, higher content of clay minerals and lower content of brittle mineral has a larger micropores and mesopores volume and specific surface area, and shale with higher TOC content has larger fractal dimension D_f of pore structure.

2. The contents of TOC and clay minerals are positively correlated with the adsorption capacity of CH₄ and CO₂ in shale, and the correlation of the contents of clay minerals is weak. This is because the shale with higher TOC and clay mineral content corresponds to higher specific surface area, which can provide more adsorption sites for CH₄ and CO₂ in shale. The relationship between TOC and the maximum adsorption capacity of CH₄ is stronger than that of CO₂, while CO₂ adsorption capacity shown a more significant correlation with clay minerals than CH₄, which may be due to that organic matter is more inclined to adsorb CH₄ than CO₂, while the inorganic material such as clay mineral is more likely to adsorb CO₂ than CH₄.

3. All the α_CO2/CH4 of shale were larger than 1.00, which indicated the feasibility of application of CO₂-ESGR technology in these shale gas reservoirs. The shale with higher TOC content and brittle mineral content shows higher α_CO2/CH4 values, while there is no obvious correlation between α_CO2/CH4 and clay mineral content in shale. The α_CO2/CH4 of shale were decreased with increasing temperature for most cases, which indicated that a lower temperature is more favorable for the application of CO₂-ESGR technique.

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