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Volume 32 Issue 4
Aug.  2021
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Zhiye Gao, Shuling Xiong. Methane Adsorption Capacity Reduction Process of Water-Bearing Shale Samples and Its Influencing Factors: One Example of Silurian Longmaxi Formation Shale from the Southern Sichuan Basin in China. Journal of Earth Science, 2021, 32(4): 946-959. doi: 10.1007/s12583-020-1120-5
Citation: Zhiye Gao, Shuling Xiong. Methane Adsorption Capacity Reduction Process of Water-Bearing Shale Samples and Its Influencing Factors: One Example of Silurian Longmaxi Formation Shale from the Southern Sichuan Basin in China. Journal of Earth Science, 2021, 32(4): 946-959. doi: 10.1007/s12583-020-1120-5

Methane Adsorption Capacity Reduction Process of Water-Bearing Shale Samples and Its Influencing Factors: One Example of Silurian Longmaxi Formation Shale from the Southern Sichuan Basin in China

doi: 10.1007/s12583-020-1120-5
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  • Due to the existence of water content in shale reservoir, it is quite meaningful to clarify the effect of water content on the methane adsorption capacity (MAC) of shale. However, the role of spatial configuration relationship between organic matter (OM) and clay minerals in the MAC reduction process is still unclear. The Silurian Longmaxi Formation shale samples from the Southern Sichuan Basin in China were prepared at five relative humidity (RH) conditions (0%, 16%, 41%, 76%, 99%) and the methane adsorption experiments were conducted on these water-bearing shale samples to clarify the MAC reduction process considering the spatial configuration relationship between clay minerals and OM and establish the empirical model to fit the stages. Total organic carbon (TOC) content and mineral compositions were analyzed and the pore structures of these shale samples were characterized by field-emission scanning electron microscopy (FE-SEM), N2 adsorption and high-pressure mercury intrusion porosimetry (HPMIP). The results showed that the MAC reduction of clay minerals in OM occurred at different RH conditions from that of clay minerals outside OM. Furthermore, the amount of MAC reduction of shale samples prepared at the same RH condition was negatively related with clay content, which indicated the protection role of clay minerals for the MAC of water-bearing shale samples. The MAC reduction process was generally divided into three stages for siliceous and clayey shale samples. And the MAC of OM started to decline during stage (1) for calcareous shale sample mainly because water could enter OM pores more smoothly through hydrophobic pathway provided by carbonate minerals than through hydrophilic clay mineral pores. Overall, this study will contribute to improving the evaluation method of shale gas reserve.
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Methane Adsorption Capacity Reduction Process of Water-Bearing Shale Samples and Its Influencing Factors: One Example of Silurian Longmaxi Formation Shale from the Southern Sichuan Basin in China

doi: 10.1007/s12583-020-1120-5

Abstract: Due to the existence of water content in shale reservoir, it is quite meaningful to clarify the effect of water content on the methane adsorption capacity (MAC) of shale. However, the role of spatial configuration relationship between organic matter (OM) and clay minerals in the MAC reduction process is still unclear. The Silurian Longmaxi Formation shale samples from the Southern Sichuan Basin in China were prepared at five relative humidity (RH) conditions (0%, 16%, 41%, 76%, 99%) and the methane adsorption experiments were conducted on these water-bearing shale samples to clarify the MAC reduction process considering the spatial configuration relationship between clay minerals and OM and establish the empirical model to fit the stages. Total organic carbon (TOC) content and mineral compositions were analyzed and the pore structures of these shale samples were characterized by field-emission scanning electron microscopy (FE-SEM), N2 adsorption and high-pressure mercury intrusion porosimetry (HPMIP). The results showed that the MAC reduction of clay minerals in OM occurred at different RH conditions from that of clay minerals outside OM. Furthermore, the amount of MAC reduction of shale samples prepared at the same RH condition was negatively related with clay content, which indicated the protection role of clay minerals for the MAC of water-bearing shale samples. The MAC reduction process was generally divided into three stages for siliceous and clayey shale samples. And the MAC of OM started to decline during stage (1) for calcareous shale sample mainly because water could enter OM pores more smoothly through hydrophobic pathway provided by carbonate minerals than through hydrophilic clay mineral pores. Overall, this study will contribute to improving the evaluation method of shale gas reserve.

Zhiye Gao, Shuling Xiong. Methane Adsorption Capacity Reduction Process of Water-Bearing Shale Samples and Its Influencing Factors: One Example of Silurian Longmaxi Formation Shale from the Southern Sichuan Basin in China. Journal of Earth Science, 2021, 32(4): 946-959. doi: 10.1007/s12583-020-1120-5
Citation: Zhiye Gao, Shuling Xiong. Methane Adsorption Capacity Reduction Process of Water-Bearing Shale Samples and Its Influencing Factors: One Example of Silurian Longmaxi Formation Shale from the Southern Sichuan Basin in China. Journal of Earth Science, 2021, 32(4): 946-959. doi: 10.1007/s12583-020-1120-5
  • With the improvement of petroleum exploration theory and the development of horizontal drilling and hydraulic fracturing technologies, unconventional hydrocarbon resources have gradually become realistic and important energy supplies to support the economic development of the whole world. Since the successful exploitation of shale gas in North America in 1998, shale gas has become one of the unconventional petroleum research hotspots globally (Liu et al., 2019; Wood, 2019; Zhou et al., 2019; Li Y Z et al., 2016; Pan et al., 2015). Shale gas mainly exists in three types of occurrence states under geological conditions: dissolved gas, adsorbed gas and free gas. There is only a small amount of shale gas dissolved in kerogen, asphaltene or water while the majority of shale gas either is adsorbed on the surface of particles in shale (e.g., organic matter, clay minerals) or occupies shale pore spaces in free phase (Zhang et al., 2012; Ross and Bustin, 2007). And it was reported that the proportion of adsorbed gas in total gas content for shale reservoirs ranged from 20% to 85% (Curtis, 2002). Consequently, the methane adsorption capacity (MAC) of shale is an important factor affecting the reserve evaluation and development plan of shale gas reservoirs (Zou et al., 2019).

    Researchers usually use a manometric analytical method to measure the MAC. The methane adsorption amount measured in the experiment is the difference between the expanded volume and pore volume of the shale sample after absorbing methane, actually being the excess adsorption amount. In order to take the volume occupied by methane adsorption phase into account, excess adsorption amount should be converted to absolute adsorption amount (Merkel et al, 2016; Wang and Yu, 2016).

    The MAC of shale is mainly affected by external factors (e.g., temperature, pressure and water content) and internal factors (TOC, mineral composition, pore structure) (Wang and Yu, 2016; Liu et al., 2013; Ross and Bustin, 2007). Because methane adsorption is an exothermic process, the MAC of shale is inhibited with the increase of temperature (Guo, 2013). Pressure affects the distribution of methane in the pore structure by controlling the threshold pore width which determines the methane adsorption mechanism. The good positive correlation between the MAC and the total organic carbon (TOC) content has been reported extensively in the literature (Zhang H et al., 2013; Lu, 1995), which indicates the prominent role of organic matter in the methane adsorption of shale. As one of the main contributors of specific surface area and pore volume in organic-rich shale reservoirs (Tian et al., 2016), OM could provide a large number of adsorption sites for methane molecules. Comparing with the hydrophilic clay minerals, OM is hydrophobic which is much easier to adsorb methane molecules on its surface. As a result, the MAC of OM is significantly higher than that of clay minerals (Luo et al., 2019; Ji et al., 2012). Furthermore, The MAC of different maceral organic matters is also different. More specifically, the MAC of OM with more vitrinites is larger than that of OM with more inertinites (Bustin and Clarkson, 1998). It is reported that the MAC of type Ⅲ kerogen with more vitrinites and aromatics is higher than that of type Ⅰ and type Ⅱ kerogens due to the higher MAC of aromatic kerogen compared with that of aliphatic kerogen (Zhang et al., 2012).

    However, the MAC of clay minerals in shale should not be ignored due to the large specific surface areas of clay minerals and relatively high clay content in shale. Different types of clay minerals with different specific surface areas have different MACs and the MAC of different types of pure clay minerals is in the following order: montmorillonite > > illite montmorillonite mixture > kaolinite > chlorite > illite (Ji et al., 2012). Different types of clay minerals are always different in pore development and morphology. Smectite is mainly composed of micropores and mesopores, and the pore morphologies are mainly parallel plate-shaped, slits-shaped with openings on the four sides, ink-bottle pores. Kaolinite mainly develops mesopores and macropores. Chlorite mainly develops micropores and macropores. Illite mainly develops mesopores and macropores, and the pore morphologies of illite are also parallel plate-shaped and slit-shaped. And the major factor that affects the methane adsorption capacity of the clay minerals is the specific surface area (Ji et al., 2012).

    The MAC of shale is closely related to its pore structure. For example, the positive relationship between the MAC of shale and the specific surface area of shale is reported in the literature (Chen et al., 2019). As a result, it is of great significance to clarify the shale pore structure characteristics for determining the influencing factors of MAC of shale (Gao et al., 2018; Chalmers et al., 2012; Loucks et al., 2009).

    Considering the common existence of water content in shale reservoirs and the complicated effect of water content on the MAC of shale, it is of great significance to investigate the influence mechanism of water content on the MAC of shale for shale gas exploration and development. It is widely accepted that water content in shale has a negative effect on its MAC and the MAC of water-bearing shale could be reduced by about 40%–90% compared with its dry state (Gasparik et al., 2014). There is still no consistent understanding of the mechanism of MAC reduction in water-bearing shale and two mechanisms are proposed in the literature based on the water absorption characteristics of clay minerals. (1) When water enters shale pore spaces it will be preferentially absorbed by clay minerals due to their strong affinity to water (Luo et al., 2019). And the swelling of clay minerals after water absorption could block the pore system and reduce the accessibility of OM pores to methane. Also water molecules can occupy the adsorption sites on the surface of clay minerals and reduce the MAC of clay minerals. When water content in shale reaches a certain value, all the adsorption sites in clay minerals have already been occupied by water (Krooss et al., 2002) and the MAC of water-bearing shale will no longer decrease significantly with the increase of water content (Tan et al., 2014). (2) During the water absorption process in clay minerals, water molecules preferentially enter the small pores. With the increase of water vapor pressure in pore spaces, water molecules gradually occupy the large pores in clay minerals. And the water film formed on the surface of large pores changes the contact relationship between methane and pore surface from gas-solid contact to gas-liquid contact which reduces the MAC of clay minerals (Li J et al., 2016). Furthermore, it is reported that the pores less than 6 nm in clay minerals have been completely filled by condensed water molecules when the relative humidity reaches 98%, which leads to the decrease of pore connectivity and the effective specific pore surface area (Li J et al., 2017, 2016). Therefore, the mechanism of MAC reduction in the water-bearing shale needs further investigations.

    Previously considering organic matters as oil-wet and clay minerals as water-wet, many researchers divided the MAC reduction process of water-bearing shale into three stages. With the increase of water content, the MAC of water-bearing shale will experience rapid decline stage, moderate decrease stage and slow decrease stage (Yang et al., 2020; Wang et al., 2018). The moisture content thresholds that divide different reduction stages are mainly dominated by the competition between water and methane for adsorption sites on the surface of clay mineral pores (Fan et al., 2018). This is actually due to the difference between the affinity of water and methane to clay minerals and organic matter. However, there are organic matters existing as adsorption on the surface of clay minerals in the marine shale (Zhu et al., 2020), which complicates the methane adsorption process of these shale samples. Previous studies about the MAC of water-bearing shale usually treated the clay minerals as a whole part without considering the spatial configuration relationship between clay minerals and OM in these studies. Consequently, the MAC reduction process of the clay minerals in OM and outside OM is not clearly presented and needs to be investigated. In this study, the MACs of Longmaxi Formation shale samples from the Southern Sichuan Basin in China with different water contents were investigated. In addition, N2 adsorption, HPMIP, FE-SEM and Image Pro Plus (IPP) software were used complementarily to characterize shale pore structure. Finally, the MAC reduction process of water-bearing shale samples was clarified. And the role of spatial configuration relationship between organic matter and clay minerals in the MAC reduction process of water-bearing shale samples was also figured out.

  • The southern Sichuan Basin is located in the southwest of the Upper Yangtze Platform. The Lower Silurian Longmaxi Formation shale samples were collected from four different wells in Changning, Luzhou, Weiyuan and Yuxi blocks in southern Sichuan Basin (Fig. 1), and they are all located in the southern Sichuan Basin low steep structural belt which mainly develops some thrust fault block structures. The shale of Longmaxi Formation in Southern Sichuan Basin underwent four stages of tectonic evolution: the rapid burial stage in the Late Caledonian, the slow uplift stage in the Hercynian, fast burial stage from Indosinian to Early Yanshanian and the continuous uplift stage of Late Yanshanian to Himalayan. The paleoburial depth of the Lower Silurian Longmaxi Formation in the Sichuan Basin was generally deep (Liu S et al., 2016). And the thermal evolution degree of OM in Longmaxi Formation shale was high and generally entered the dry-gas window (Zhou et al., 2016). The TOC content of Longmaxi Formation shale in the Sichuan Basin was relatively high at the bottom (> 2 wt.%) and decreased with the depth going up due to the fall of the sea level (Zhang X et al., 2013). The classification method of shale lithofacies based on the TOC content and mineralogy of shale samples proposed by Tang et al. (2016) was followed in this study and four Longmaxi Formation shale samples with different lithofacies were selected to go through further analysis.

    Figure 1.  Well locations of Longmaxi Formation shale samples from the southern Sichuan Basin, China.

  • The shale samples were crushed into 40 mesh and the inorganic carbon in the shale samples was completely removed by using hydrochloric acid. And then the samples were burned to 600 ℃ and the TOC content of the shale samples was measured by a LECO CS230 carbon and sulfur analyzer. The X-ray diffractometer (XRD) (Ringaku Miniflexll) was used to obtain the mineral compositions of shale samples, which scanned shale samples from 5° to 90° with a scanning speed of 2°/min and a scanning step width of 0.02°. The incident light was Cu target and the working voltage and current of the X-ray tube were 30–45 kV and 20–100 mA respectively. The mineral compositions of shale samples were determined by analyzing their diffraction patterns and calculating the peak areas of different minerals in the patterns. The shale samples were pulverized to particle size less than 75 μm and ~10 g of shale sample was used for each XRD test.

  • FE-SEM images can directly reflect the morphological characteristics of shale pores with a relatively high resolution (< 10 nm) (Klaver et al., 2015). The optimal pore size characterization ranges of N2 adsorption experiment and HPMIP are mesopore (2–50 nm) and macropore (> 50 nm) respectively (Jiang et al., 2016). Consequently, these three methods were complementarily used in this study to characterize shale pore structure comprehensively.

    Shale samples were processed by argon-ion milling technology for FE-SEM observations (Loucks et al., 2009). ZEISS Merlin FE-SEM with working distances ranging from 2.3 to 10.8 mm was used to characterize shale pore structure. The FE-SEM images were statistically processed by image processing software Image-Pro Plus (IPP) to obtain the pore size distribution frequency of OM pores.

    For N2 adsorption tests, shale samples were crushed to 40–60 mesh and then were oven-dried at 60 ℃ for more than 48 h in order to completely remove moisture in pore spaces. Quantum Autosorb IQ instrument was used to conduct N2 adsorption tests. The N2 adsorption experiments were carried out under the condition of low temperature (77.3 K) generated by liquid nitrogen. The specific surface area, pore size distribution, pore volume of shale samples were derived from N2 adsorption data according to the BET (Bruner, Emmett and Teller), BJH (Barrot-Joyner-Halenda) and Density Functional Theory (DFT) respectively (Barrett et al., 1951; Brunauer et al., 1938).

    All the shale samples prepared for HPMIP tests were cut into 1 cm3 cubes and were oven-dried at 60 ℃ for at least 48 hours to remove moisture from the pore spaces before the HPMIP tests. Micromeritics Autopore IV9500 was used to record the volume of mercury intrusion at different intrusion pressures and the pore-throat radius corresponding to a specific mercury intrusion pressure could be calculated according to Washburn's equation (Washburn, 1921). The specific surface area of pores with different pore diameters was derived from HPMIP data according to Young-Dupré equation (Drummond and Israelachvili, 2002).

  • Previous scholars have always followed Greenspan's (1977) method to place shale samples in the chambers with different relative humidity controlled by different salt-saturated solutions to obtain shale samples with different initial saturations. However, this method is quite time-consuming (even after two weeks the weights of shale samples still change). Another method is to saturate shale samples with water under different pressures to obtain shale samples with different water contents (Wang et al., 2019). The water content is determined by the change of sample weight before and after water saturation and it is difficult to control the water content change precisely by using this method (Wang et al., 2018; Wang and Yu, 2016).

    In this study water vapor absorption experiments were conducted to obtain shale samples with different water contents. Shale samples were crushed into 20–40 mesh and were dried at 105 ℃ for 24 h before the water vapor absorption experiment. And then each shale sample was divided into 5 groups to go through water vapor absorption experiments with 5 different relative humidity (RH) (0% RH, 16% RH, 41% RH, 76% RH, 99% RH) separately. During the water vapor absorption experiment, the dried shale samples were placed in a vacuum sample cell and then a certain amount of distilled water was added to the sample cell. The amount of distilled water added was calculated by substituting the water-saturated vapor pressure at 35 ℃, standard atmospheric pressure and the relative humidity into the Clapeyron equation. The sample cell with crushed shale samples and distilled water was heated at 105 ℃ in an incubator for ~24 h to ensure the complete evaporation of distilled water and the achievement of vapor equilibrium environment in the sample cell. Finally the water-bearing shale samples with different water contents were obtained and the theoretical water content of each sample at different relative humidity was presented in Fig. 2. The detailed experimental procedures and apparatus as well as the validation of this method were provided by Fan et al. (2018). It could be seen that this water vapor absorption method was less time-consuming and was easy to control the water content in shale samples.

    Figure 2.  Theoretical water content of shale samples prepared at different relative humidity conditions.

  • Isothermal methane adsorption experiments of waterbearing shale samples were conducted at 35 ℃ and the applied pressure range was 0–20 MPa. During the experiment, the reference cell connected with the sample cell was installed to accurately control the pressure of the sample cell. The experimental apparatus was shown in Fig. 3 and the detailed experimental procedures were provided by Wang and Yu (2016). It should be noted that this methane adsorption experiment was carried out based on volumetric method and the pore volume in shale occupied by the adsorbed methane was ignored. Consequently, the methane adsorption measured was actually the excess methane adsorption, which should be converted into absolute methane adsorption according to Eq. (1) (Setzmann and Wagner, 1991).

    Figure 3.  Schematic of the methane adsorption experimental apparatus.

    where na is the absolute methane adsorption at experimental pressure (mmol/g); n'ais the excess methane adsorption at experimental pressure (mmol/g), the difference between the expanded volume and pore volume of the shale sample after absorbing methane; ρgis the density of methane at experimental pressure at 35 ℃ (g/mL); ρais the density of methane at one standard atmospheric pressure at 35 ℃ (g/mL), which is ρa=0.423 g/cm3.

  • The TOC contents and mineral compositions of the shale samples were presented in Table 1. The TOC content of four shale samples was between 1.21 wt.% and 3.24 wt.% with an average value of 2.24 wt.%. These shale samples mainly consisted of clay minerals, quartz and carbonates. More specifically, the clay content was 20.6 wt.%–64.3 wt.% with an average value of 39.2 wt.%, the quartz content was 12.6 wt.%–46.4 wt.% with an average value of 32.2 wt.% and the carbonates were 5.2 wt.%–63.4 wt.% with an average value of 22.8 wt.%. And the lithofacies of these shale samples classified according to Tang et al. (2016) based on TOC content and mineralogy was also presented in Table 1.

    Sample Well No. Depth (m) TOC
    (wt.%)
    Quartz
    (wt.%)
    Feldspar
    (wt.%)
    Carbonates
    (wt.%)
    Clay minerals (wt.%) Pyrite (wt.%) Lithofacies
    B1 X1 3 393.2 1.21 28.5 1.4 5.2 64.3 0 Organic-moderate clayey shale
    B5 X4 4 064.0 1.98 41.1 5.5 10.5 39.3 3.6 Organic-moderate Siliceous shale
    B12 X3 2 323.5 2.54 12.6 1.2 63.4 20.6 2.2 Organic-rich calcareous shale
    B14 X2 3 607.8 3.24 46.4 4 12 32.5 5.1 Organic-rich siliceous shale

    Table 1.  TOC content and mineralogy of Longmaxi Formation shale samples used in this study

  • OM pores were the dominant pore type in B5, B12 and B14 samples and the OM-clay complexes were commonly observed in these three shale samples. There are clay minerals embedded in OM, and some clay minerals are located outside OM and directly connected with external space (Figs. 4a, 4c, 4e). The OM pores of these shale samples were well preserved due to the high contents of rigid minerals (e.g., quartz and pyrite) which had a strong ability to resist compaction (Figs. 4b, 4f). However, the shape, quantity and sizes of OM pores in these shale samples were quite different. As shown in Fig. 4b, the OM pores in sample B5 were mainly bubble pores probably related to the thermal evolution process of OMs while the primary OM pores with amorphous shapes formed by stacking of sedimentary OMs were eliminated a lot and less developed due to the strong compaction at this high thermal maturity stage. And about 53.0% of the total OM pores in sample B5 was less than 10 nm while OM pores larger than 50 nm only accounted for 1.1% and OM pores larger than 100 nm were almost not developed (Fig. 5). The area porosity of OMs in sample B5 was generally less than 5%. As shown in Fig. 5, few OM pores less than 5 nm were developed in samples B12 and B14, which accounted for 10.3% and 2.1% in samples B12 and B14 respectively. However, more OM pores larger than 50 nm were developed in samples B12 (7.6%) and B14 (12.2%) compared with sample B5 (1.1%) (Fig. 5). The amorphous primary OM pores and bubble pores with a large diameter were the main OM pore type developed in samples B12 (Fig. 4d) and B14 respectively (Fig. 4e). Furthermore, the area porosity of OMs in samples B12 and B14 was usually greater than 5%.

    Figure 4.  Pore development characteristics of organic matter in shale samples. (a) Clay minerals in OM (organic matter) and clay minerals outside OM in sample B5; (b) less distribution of amorphous primary OM pores, abundant existence of bubble pores within OM and existence of pyrite in sample B5; (c) clay minerals in OM and clay minerals outside OM in sample B12; (d) abundant existence of amorphous primary OM pores with a large diameter in sample B12; (e) clay minerals in OM, clay minerals outside OM and abundant existence of bubble pores with a large diameter in sample B14; (f) existence of pyrite and quartz in sample B14.

    Figure 5.  Organic pore size distribution obtained by IPP software using FE-SEM images.

  • All the N2 adsorption hysteresis loops of four shale samples shown in Fig. 6 belonged to H4 type according to the IUPAC classification standard (Sing, 1985), which indicated that the slit pores were mainly developed in these samples (Sing, 1985). The specific surface area distribution curves of the mesopores in these shale samples were shown in Fig. 7 and mesopores with diameter 2–6 nm made a great contribution to the total specific surface area of these shale samples. As shown in Table 2, the BET surface area of four shale samples ranged from 15.83 to 28.80 m2/g, which was comparable to the reported data in the literature (Wang et al., 2016). The HPMIP curves of shale samples were presented in Fig. 8 and sample B14 showed the highest mercury retraction efficiency (~60%) indicating its wellconnected pore system. The median pore-throat diameter corresponding to 50% mercury saturation of these shale samples was also presented in Table 2. Sample B5 had much larger median pore-throat diameter than sample B14. As OM pores in sample B5 had smaller pore sizes compared with OM pores in samples B14, it is appropriate to speculate that the inorganic pores in B5 had larger pore sizes than inorganic pores in B14.

    Figure 6.  N2 adsorption/desorption isotherms for Longmaxi Formation shale samples. TOC stands for total organic carbon; P stands for the equilibrium pressure; P0 stands for the saturated vapor pressure.

    Figure 7.  Specific surface area distribution of Longmaxi Formation shale samples.

    Sample BET surface area (m2/g) Volume of pores < 50 nm (V1) from N2 adsorption (mL/g) Volume of pores between50 nm and 1 μm (V2) from HPMIP (mL/g) Total pore volume combining HPMIP and N2adsorption (V1+V2)a (mL/g) N2 adsorption-HPMIP Porosity (ϕN2–HPMIP))b(%) Median pore-throat diameter fromHPMIP (nm)
    B1 19.09 0.016 2 0.002 70 0.018 9 4.97 13.7
    B5 17.57 0.010 3 0.001 32 0.011 6 3.12 43.8
    B12 15.83 0.010 8 0.001 65 0.012 4 3.24 46.2
    B14 28.80 0.017 2 0.001 45 0.018 6 4.81 14.6
    BET. Brunauer, Emmett, and Teller theory; HPMIP. high pressure mercury intrusion porosimetry. a The pores larger than 1 μm were not counted to eliminate the effect of microfractures. bϕN2–HPMIP=(V1+V2)/VHPMIPϕHPMIP, where VHPMIP is the total pore volume obtained from HPMIP, ϕHPMIP is the porosity obtained from HPMIP.

    Table 2.  Pore structure information obtained from HPMIP and N2 adsorption for Longmaxi Formation shale samples

    Figure 8.  Mercury saturation (%) vs. pore-throat diameter (μm) obtained from HPMIP (high pressure mercury intrusion porosimetry) for Longmaxi Formation shale samples.

    The whole-aperture pore size distribution curves of four shale samples were obtained by combining mesopore information from N2 adsorption and macropore information from HPMIP (Fig. 9). It could be seen that the mesopore volume was significantly higher than macropore volume for all these four shale samples and there were several distribution peaks located in the pore diameter range of 3 to 6 nm. And the proportion of mesopore volume in total pore volume was 85.3%, 86.5%, 85.5% and 90.0% for samples B1, B5, B12, B14 respectively.

    Figure 9.  Whole-aperture pore size distribution obtained by combining N2 adsorption data and HPMIP (high pressure mercury intrusion porosimetry) data.

  • The absolute methane adsorption curves of shale samples

    with different water contents were shown in Fig. 10. For dry shale samples, the absolute methane adsorption capacities of four shale samples increased with increasing pressure and the absolute MACs were in the following order: B14 > B12 > B5 > B1. With the increase of water content in shale samples, the absolute MACs of all the samples gradually decreased. However, the absolute MACs of samples B1, B5, B14 no longer significantly decreased with the increase of water content when the relative humidity was higher than 76% while the absolute MAC of sample B12 continued to decrease significantly with the increase of water content when the relative humidity was higher than 76%.

    Figure 10.  Absolute methane adsorption capacity of water-bearing shale samples at 35 ℃.

  • As methane molecules are mainly adsorbed on the pore surface within shale samples, it is quite important to clarify the controlling factors of specific surface area of shale samples. As shown in Figs. 11a, 11b, there was no obvious relationship between BET surface area and TOC content or clay content. However, a good correlation with R2=0.95 was obtained between clay content-normalized BET surface area and TOC content (Fig. 11c) while TOC-normalized BET surface area showed a good correlation (R2=0.97) with clay content (Fig. 11d). It could be seen that the OMs and clay minerals jointly controlled the BET surface area of these shale samples, which was closely related to the common existence of OM-clay complexes in these samples. Furthermore, it seems that the coexistence of OMs and clay minerals in these Longmaxi shale samples improves the accessibility of both OM pores and clay mineral pores to the detecting fluid (N2), which leads to the higher BET surface area of shale samples with higher TOC content and clay content.

    Figure 11.  Relationship between BET specific surface area with TOC content (wt.%) and clay content (wt.%), clay content-normalized BET surface area with TOC content (wt.%), TOC-normalized BET surface area with clay content (wt.%).

  • As shown in Fig. 12, there was a good relationship with high correlation coefficient (R2 > 0.90) between absolute MAC and TOC content for dry samples, 16% RH samples, 41% RH samples and 76% RH samples. The relationship between absolute MAC and TOC content became weaker with R2=0.63 for 99% RH samples with the highest water content but still showed the significant impact of TOC content on methane adsorption. The controlling effect of TOC content on methane adsorption of these Longmaxi Formation shale samples was closely related with the hydrophobic property (or high affinity to methane molecules) of OM and the abundant existence of nanometer-sized pores within OM (Fig. 4).

    Figure 12.  The relationship between absolute methane adsorption of water-bearing shale samples and TOC content.

    The MAC of OM in these shale samples could be evaluated by the slopes of the trend lines shown in Fig. 12. The higher the slope is, the larger MAC per unit mass OM has. The slope increased a little from dry samples to 16% RH samples and the increase of water content did not weaken but even strengthened the MAC of per unit mass OM, which indicated water did not enter OM pores and the accessibility of OM pores to methane was improved at this stage. From 16% RH samples to 99% RH samples, the slope continuously decreased, indicating the decrease of MAC of per unit mass OM with the increase of water content. And the amount of methane adsorption decrease (with a slope decrease of 0.012 7) of per unit mass OM was maximized in the stage from 16% RH samples to 41% RH samples and then decreased (with a slope decrease of 0.004 2 from 41% RH samples to 76% RH samples and a slope decrease of 0.002 9 from 76% RH samples to 99% RH samples).

  • The contribution of inorganic minerals to methane adsorption of these shale samples could be evaluated by the intersection values to Y-axis of the trend lines shown in Fig. 12. For dry samples, the intersection value to Y-axis of the trend line was 0.028 5, which indicated inorganic minerals besides OM also made a contribution to methane adsorption of shale samples. Because clay minerals with higher BET surface area have much larger MAC than other inorganic minerals (e.g., quartz, feldspar, calcite) (Gao et al., 2020), clay minerals were thought to be the main methane adsorption contributors among the inorganic minerals. For 16% RH samples, the intersection value almost became zero, which indicated that the MAC of clay minerals almost fell to zero in 16% RH samples. Water was preferentially absorbed into the interlayer pore spaces of clay minerals to increase the interlayer spacing of clay minerals, which resulted in the decrease of surface adsorption energy (Johnston, 2010) and destroyed the MAC of clay minerals for 16% RH samples. However, water did not enter OM pores to hinder the methane adsorption of OM in 16% RH samples. The 'winner' (clay minerals) of water absorption competition between clay minerals and OM seemed to play a protection role of methane adsorption of OM in 16% RH samples. The swelling of clay minerals after absorbing water could generate microfractures (Liu X J et al., 2016), which could improve the accessibility of OM pores to methane and then lead to the increase of MAC of per unit mass OM in 16% RH samples.

    For 41% RH samples, the intersection value to Y-axis was 0.008 9, which indicated the methane adsorption of clay minerals made a contribution again. However, these clay minerals were probably not the clay minerals directly accessible to methane (or water) providing methane adsorption in dry samples because their methane adsorption capacities were already lost due to the absorption of water in 16% RH samples. And the clay minerals offering methane adsorption sites in 41% RH samples were probably surrounded by OM (Fig. 4a) or clay minerals in OM. More specifically, these clay minerals in OM failed in the methane adsorption competition between these clay minerals in OM and their surrounding OM in dry samples. For 16% RH samples, these clay minerals in OM were 'protected' by their surrounding OM to avoid the water absorption but still failed in the methane adsorption competition. For 41% RH samples, more water molecules were adsorbed on the surface of clay minerals to form water film (Alansari et al., 2019; Johnston, 2010) and more clay mineral pores were filled with water due to capillary condensation (Wang et al., 2019), which caused the failure of clay minerals to play a good role in protecting the MAC of OM. As a result, OM pores started to adsorb water, which occupied the methane adsorption sites of OM and weakened the interactive force between OM and methane molecules. As a result, the MAC of per unit mass OM in 41% RH samples dramatically decreased 39% compared with 16% RH samples. Furthermore, the environment became favorable to clay minerals in OM in the methane adsorption competition between these clay minerals and their surrounding OM, which caused the increase of methane adsorption by clay minerals from 16% RH samples to 41% RH samples. From 41% RH samples to 99% RH samples, more inorganic pore spaces (including clay minerals in OM) were filled with water and more water were adsorbed by OM pores, which caused the continuous decrease of MAC of OM and clay minerals in OM.

    In order to clarify the effect of clay minerals on methane adsorption of water-bearing shale samples more clearly, the TOC-normalized absolute MAC was plotted versus clay content in Fig. 13 but no correlation was obtained considering the low R2 values (< 0.5), which indicated the limited MAC provided by clay minerals. However, the amount of methane adsorption decrease from dry samples to water-bearing samples at different RH conditions showed a good negative correlation with clay content for 41% RH samples, 76% RH samples and 99% RH samples as shown in Fig. 14, which indicated the positive meaning of clay minerals in protection of MAC of these shale samples (mainly OM) at these three RH conditions. As aforementioned for 16% RH samples, the methane adsorption decrease was mainly due to the methane adsorption decrease of clay minerals after absorbing water and the MAC of OM was protected. However for 16% RH samples, no positive relationship was observed as expected between the amount of methane adsorption decrease and clay content, which was possibly disturbed by sample B12 with 63.4% carbonates.

    Figure 13.  The relationship between TOC-normalized absolute methane adsorption capacity of water-bearing shale samples and clay content.

    Figure 14.  The relationship between the amount of methane adsorption capacity decrease in water-bearing shale samples and clay content.

    Consequently, the strong affinity of clay minerals to water makes them working as a protector of the MAC of OM in water-bearing samples. Without the protection of clay minerals, more water will enter OM pores and the MAC of OM is expected to decrease more seriously than it experienced in this study.

  • Generally, the methane adsorption reduction process of water-bearing shale samples can be divided into three stages from dry sample (or 0% RH sample) to 99% RH sample (Fig. 15).

    Figure 15.  Methane adsorption capacity reduction process of water-bearing shale samples.

    Stage (1): 0% RH–16% RH

    Water molecules preferentially enter the interlayer pores of clay minerals and almost no water is adsorbed by OM pores. The MAC of OM is not reduced and even could be enhanced due to the increased accessibility of OM to methane through microcracks caused by swelling of clay minerals. Consequently, the methane adsorption decrease of shale sample is attributed to the methane adsorption decrease of clay minerals.

    Stage (2): 16% RH–41% RH

    A large amount of water begins to enter OM pores leading to a significant decrease in MAC of OM, which dominantly contributes to the MAC decrease of shale sample. In addition, the clay minerals in OM begin to adsorb methane at this stage.

    Stage (3): 41% RH–99% RH

    More water is adsorbed by OM pores and clay minerals in OM. The MAC of OM continues to decrease but in a mild way compared with the rapid decrease in stage (2). Moreover, the MAC of clay minerals in OM is slightly decreased during this stage. The MAC decrease of OM mainly causes the MAC decrease of shale sample.

    It should be noted that clayey shale sample B1 and siliceous shale samples B5 and B14 were grossly following these three stages. However, calcareous shale sample B12 showed quite different process (Fig. 16). The wettability of carbonate minerals could be altered from hydrophilic to hydrophobic by the interaction between carbonate minerals and organic fluids produced during the thermal evolution of OM (Legens et al., 1998). The abundant existence of hydrophobic carbonate minerals in sample 12 helped water enter OM pores more smoothly during all the three stages. And sample 12 had the lowest clay content, which provided the weakest protection for MAC of OM in water-bearing shale samples. Consequently, the MAC of OM began to decrease during stage (1) and the MAC decrease of OM dominantly controlled stages (2) and (3). As shown in Fig. 12, the MAC decrease of sample B12 from 16% RH to 99% RH was evenly distributed in the three RH intervals with an average value of 0.017 mmol/g, which was mainly caused by the MAC decrease of OM. If the MAC decrease of 0.017 mmol/g related to OM was assumed to occur during the stage (1), the MAC decrease related to clay minerals was modified to 0.013 mmol/g and a positive relationship between MAC decrease and clay content for stage (1) was finally obtained as shown in Fig. 14.

    Figure 16.  Methane adsorption capacity reduction process of water-bearing calcareous shale sample.

    Samples B1, B5 and B14 showed a little difference, which was related to their compositions and pore structures. Sample B1 with the highest clay content contained much more clay minerals in OM, which caused a much smaller MAC decrease (0.005 mmol/g) in stage (2) compared with the MAC decrease of sample B5 (0.02 mmol/g) and B14 (0.034 mmol/g) at this stage even considering the difference of their TOC content (Fig. 17). For siliceous shale samples B5 and B14, a little difference occurred during stage (3). The inorganic pores in B5 had larger pore sizes than inorganic pores in B14. With the increase of RH, larger clay mineral pores will be filled with water due to capillary condensation (Li et al., 2017). Consequently, more clay mineral pores with smaller pore size were filled with water to block methane entering OM pores from 41% RH to 76% RH for sample B14 compared with sample 5, which caused the larger MAC decrease (0.014 mmol/g) of sample B14 from 41% RH to 76% RH compared with sample B5 (0.006 mmol/g) even considering the difference of their TOC content. While at a higher RH range from 76% RH to 99% RH, more clay mineral pores with larger pore size in sample B5 were filled with water and reduced the MAC of OM, which caused a larger MAC decrease (0.005 1 mmol/g) of sample B5 compared with sample B14 (0.004 8 mmol/g) and this effect was more obvious if TOC content was taken into consideration.

    Figure 17.  Methane adsorption capacity reduction process of water-bearing clayey shale sample.

  • The actual water content is very complicated in shale reservoirs, while hydraulic fracturing actually leaves a tremendous amount of water into shale reservoirs (Makhanov et al., 2014). It is difficult to predict the maximum absolute methane adsorption under in-situ conditions. Accurate evaluation of maximum absolute methane adsorption (MAXAMD) is very beneficial for evaluating the exploitation value of shale reservoir.

    Therefore, based on the three stages of MAC reduction, empirical model is established to predict the maximum absolute methane adsorption of shale reservoirs under different RH conditions.

    Stage (1): 0≤RH < 0.16

    Stage (2): 0.16≤RH≤0.41

    Stage (3): 0.41 < RH≤0.99

    where MAXAMD is the maximum absolute methane adsorption (mmol/g); w(TOC) is the content of OM (wt.%); w(clay) is the content of clay minerals (wt.%); RH is the relative humidity.

    As shown in Fig. 18, the ratio of actual MAXAMD and predicted MAXAMD is basically near the reference baseline. It should be noted that the empirical model can be used to predict the maximum absolute methane adsorption at 35 ℃.

    Figure 18.  The ratio of actual MAXAMD and predicted MAXAMD.

  • (1) This study investigated the controlling factors of the MAC reduction process of water-bearing Longmaxi Formation shale samples. The OM-clay complexes were commonly observed in these Longmaxi Formation shale samples, which significantly affected the MAC reduction process of water-bearing shale samples. Both the contribution of clay minerals to the MAC of dry samples and the MAC protection role of clay minerals in water-bearing shale samples were confirmed in this study. Furthermore, the clay minerals outside OM and clay minerals in OM worked differently in the established MAC reduction model, which was the main finding of this work.

    (2) The MAC reduction model of these water-bearing shale samples was generally divided into three stages. During Stage (1), water was preferentially absorbed into the interlayer spaces of clay minerals outside OM, which destroyed the MAC of these clay minerals. With the increase of moisture in stage (2), the MAC of clay minerals in OM, which was negligible in stage (1) compared with clay minerals directly accessible to methane without passing through OM pores, seemed to be activated in Stage (2) in the methane adsorption competition with its surrounding OM which had adsorbed water on its pore surface. Consequently, it is not appropriate to treat the clay minerals as a homogenous part in the MAC reduction process of water-bearing shale samples as most researchers did. And the role of spatial configuration relationship between OM and clay minerals in the MAC reduction process should be paid much more attention in future studies.

    (3) The MAC reduction model established in this study and the empirical prediction model is of great significance for estimating the shale gas content in different geological periods. The empirical prediction model is put forward to explain the application value of the three MAC reduction stages. It should be noted that the model could be improved in the future when more data are available.

    It should be noted that the lithofacies of shale samples used in this study are quite limited and more investigations should be conducted in the future to establish the MAC reduction model for different shale lithofacies. Also the effect of OM-clay complexes on MAC reduction process of water-bearing shale samples and its relationship with thermal maturity, clay mineral type as well as kerogen type should be further investigated experimentally and theoretically.

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