Influence of reservoir properties on the methane adsorption capacity and fractal features of coal and shale in the upper Permian coal measures of the South Sichuan coalfield,China

Abstract

Pore structure plays an essential role in the reservoir heterogeneity and methane adsorption capacity. Significant progress has been made in the pore structure classification of porous materials (such as coal and shale). Considering the pore structure characterization of the coal measures and the measuring range of high-pressure mercury intrusion porosimetry and low-pressure N₂/CO₂ gas adsorption, an integrated classification for coal and shale is provided. They are micropore (<2 nm), mesopore (2–100 nm), macropore A (100 nm–1 µm), macropore B (1–10 µm), and micro-fracture (>10 µm). For coal and shale samples from Guxu mining area, the micropores and mesopores largely control the gas adsorption while micro-fractures and macropore B are significant for the storage and flow of free gas. The fractal dimensions calculated from limited N₂ adsorption data are not suitable for the coal samples which are not developed in mesopore and macropore A; these samples are precisely corresponding to the N₂ adsorption/desorption isotherms of group B (reversible isotherm). Furthermore, the main factors influencing the methane adsorption capacity of coal and shale in the coal measures are micropore frequency, micro-fracture width, clay mineral composition, and total organic carbon content.

Keywords

Coal and shale pore structure methane adsorption coal measures South Sichuan coalfield

Introduction

Coalbed gas (also named coalbed methane) and shale gas, storing at the coal and shale reservoirs with low porosity and low permeability in the coal measures, belong to the gas types of unconventional natural gas (Li et al., 2019a; Tan et al., 2019; Wang et al., 2018). Both gases can be commingled and produced from a well by perforating the reservoirs at different depth. Gas commingling can improve the profitability of exploration and exploitation; it can also enhance the drainage efficiency and gas production output of a single well (Li et al., 2019b; Wang et al., 2018). The investigation of the pore structure characteristics of a mixed coal and shale reservoirs is one of the vital research areas in better evaluating the reservoir characteristics and gas content, to inform on the potential for commingling of both gases at the coal measures.

Previous research has proved that it is useful to study the pore structure of coal and shale with direct imaging techniques, radiation detection techniques, and fluid invasion methods. Direct imaging techniques contain focused ion beam scanning electron microscopy and field emission scanning electron microscopy/transmission electron microscopy (Zhou et al., 2019; Zhu et al., 2017). Radiation detection techniques contain small angle and ultra-small angle neutron scattering, small-angle X-ray scatting, and nuclear magnetic resonance (Cai et al., 2013; Liu et al., 2019; Zhao et al., 2019). Fluid invasion methods contain high-pressure mercury intrusion porosimetry (MIP), low-pressure N₂/CO₂ gas adsorption, and helium pycnometry (Ghanizadeh et al., 2015; Li et al., 2019c; Yang et al., 2016; Zhang et al., 2017, 2018a). In them, MIP data can analyze the pore diameter ranges from dozens of nanometers to hundreds of micrometers. The pore diameters of 2–100 nm and less than 2 nm can be obtained from low-pressure N₂ and CO₂ physisorption data, respectively.

As for the shale pore size classification, there is a unified classification, according to the International Union of Pure and Applied Chemistry (IUPAC). Shale pore structures can be divided into micropores (<2 nm), mesopores (2–50 nm), and macropores (>50 nm). Regarding the more complex porous materials, there is no unified classification for the coal. Generally, coal pore size can be divided into adsorption pores and seepage pores. The former refer to pore diameters less than 100 nm; the latter are pore diameters more than 100 nm (Shi and Durucan, 2005; Yao et al., 2006). Adsorption pores can be further divided into micropores (<10 nm in diameter) and mesopores (10–100 nm in diameter) (Yao et al., 2008). There is also another classification of the coal pore structure. It is a combined classification from IUPAC (1985) and Hodot(1996) for coal pore size: super micropores (<2 nm), micropores (2–10 nm), mesopores (10–100 nm), macropores (100 nm–1 µm), super macropores (1–10 µm), and micro-fractures (>10 µm) (Cai et al., 2013). It is well known that the coal and shale stratum are thoroughly developed alternately in the coal measures at the Taiyuan and Shanxi Formations of the North China and the Longtan Formation of South China (Tang et al., 2016a; Xao et al., 2018). To better understand the effects of coal and shale pore structures on both gas adsorption capacity and flow capability, an integrated classification for the pore structure characterization of coal-bearing stratum is provided in this work and is based on the analysis of MIP and low-pressure N₂/CO₂ gas adsorption testing results.

The current study collected eight coal and six shale samples from the upper Permian Longtan Formation in the upper Yangtze Plate of South China. The main aims of this work are to (i) determine a suitable classification of pore size for coal and shale samples in the coal measures; (ii) investigate the pore structure distribution characteristics of coal and shale samples in the coal measures; and (iii) discuss the relationships between methane adsorption capacity and matrix parameters, as well as pore structure (i.e. pore volume (PV), special surface area (SSA), and pore size distribution (PSD)).

Samples and experimental methods

Geological setting

The South Sichuan coalfield, located in the southeast Sichuan basin of the upper Yangtze Plate, contains the Nanguang, Junlian, Furong, and Guxu mining areas. The Guxu mining area, tectonically within the Gulin–Junlian fold belt, is the field of study. The EW brachy-axis complex fold is the primary fold type in the study area (Zhu et al., 2010). Figure 1 shows the geographic position and tectonic distribution of the south Sichuan coalfield. Sinian is the oldest stratum exposed in this area, and, except scattered Neogene, Cretaceous is the youngest stratum. Lacking strata are from Cambrian to Silurian and Carboniferous. Containing more than 10 coal seams, the lower Permian Longtan Formation is the leading coal-bearing stratum in the Guxu mining area. However, there are only five to eight coal seams with a stable distribution that are valuable for exploration. So, our samples are collected from these stable strata.

Figure 1.

Tectonic graph showing study area and sampling sites from the South Sichuan coalfield. Source: Modified from Zhu et al. (2010).

Samples

Six shales and eight coals are collected from drilling wells DC-4 and DC-5 at the Guxu mining area. The distance between the two wells is 4.8 km. Sampling site and depth are presented in Figures 1 and 2. A portion of gathered samples is packaged with silver paper and sealed into the closed bags for testing coal macerals, mineral composition, pore structure, and methane sorption capacity. Other partial samples are loaded into the CBM desorption canisters for measuring methane content (not part of the present study).

Figure 2.

Stratigraphic columns of wells DC-4 (a) and DC-5 (b) at the South Sichuan coalfield.

Experimental approaches

In order to study the geological properties of coal and shale samples in coal-bearing strata, the following are implemented: (i) mineral composition by X-ray diffraction (XRD); (ii) maturity and total organic carbon (TOC) by Rock-Eval pyrolysis analysis; (iii) microstructure and pore system by MIP, low-pressure N₂ and CO₂ physisorption; and (iv) methane sorption capability by methane isothermal adsorption. All the 14 samples are used for most experiments, except for four samples (two coals and two shales) for CO₂ physisorption.

MIP sample with particles of 5–20 mesh was dried at 100°C for 24 h in a vacuum oven to remove volatiles (Zeng et al., 2016). Mercury intrusion analysis is performed on vacuum dried samples using PoreMaster GT-60, according to the GB/T 21650.1-2008 standard (Xiong et al., 2015). The highest pressure of mercury intrusion is up to 29,000 psi (200 MPa), for primarily characterizing pores larger than 30 nm. Additional samples are crushed into grains of 60–80 mesh size for N₂ and CO₂ physisorption analysis using Micromeritics ASAP 2460 apparatus at the Beijing Center for Physical & Chemical Analysis. N₂ adsorption data are collected at temperature 77.4 K and saturation pressure less than 768.3 mmHg. CO₂ adsorption experiment is implemented at 273.0 K and saturation pressure at 26,142.0 mmHg. The crushed samples are dewatered at a temperature of 110°C for 5 h and then outgassed at a temperature of 110°C for 24 h. Multi-point Brunauer–Emmett–Teller (BET) and Barrett–Joyner–Halenda (BJH) models based on N₂ adsorption data and density functional theory (DFT), Dubinin–Radushkevich, and Dubinin–Astakhov models based on CO₂ adsorption data are used to calculate SSA, PV, and PSD, respectively (Javadzadeh et al., 2014; Song et al., 2017; Wang et al., 2015; Wei et al., 2016).

As supporting data for analyzing pore structure, the XRD and the TOC content are also examined. The XRD is performed with a Bruker D8 Advance diffractometer using Cu Kα radiation at a temperature of 24°C and humidity of 35%. The TOC data are measured with Rock-Eval-VI for pyrolysis analysis according to the GB/T 18602-2001 standard (Zhang et al., 2018b). The Rock-eval pyrolysis technique incorporates temperature-programmed heating of a small amount of sample in an inert atmosphere (helium) in order to determine the number of free hydrocarbons and hydrocarbon compounds present in the coal/shale (Mendhe et al., 2018). The TOC is actually a value that is calculated by adding the residual and pyrolyzed organic carbons. Furthermore, the methane isothermal adsorption experiment is carried out using a volumetric sorption apparatus (PCTPro Evo Setaram INC, Hillsborough, USA) on coal and by a gravimetric sorption apparatus (IsoSORP-HPII Static Rubotherm GmbH, Bochum, Germany) on shale. All experiments are performed at 30°C and conducted on an equilibrated moisture basis according to the GB/T 19560-2008 (Tang et al., 2016b). For each sample, 200 g of pulverized powder sample with particle size less than 60 mesh is used for the high-pressure methane sorption measurement. At each injection pressure, the excess adsorption amount can be estimated through the equation of state. Based on the excess experimental data, the absolute adsorption amounts are calculated according to the method of Sudibandriyo et al. (2003).

Results and analysis

Maturity, mineral composition, and TOC content

Previous research has demonstrated that maturity, mineral composition, and TOC content strongly affect the pore structure of the reservoir (Wang et al., 2014; Zhao et al., 2018). On the basis of XRD and Rock-Eval pyrolysis analysis, the mineral composition, maturity, and TOC content results are shown in Table 1. For the coal samples, the clay mineral composition is mainly mixed I/S. The principal clay mineral composition of shale samples is kaolinite. For the three coal samples from well DC-4, the maturity and TOC content means the content is 3.02% and 78.9 wt%. Brittle minerals mean content—including quartz and calcite—is 25.8 wt%. For the three shale samples from well DC-4, the mean contents of maturity, TOC, and brittle minerals are 2.91%, 8.3 wt%, and 50.9 wt%. For the five coal samples of well DC-5, the mean contents of maturity, TOC, and brittle minerals are 3.07%, 60.7 wt%, and 24.0 wt%. For the three shale samples of well DC-5, the mean contents of maturity, TOC, and brittle minerals are 3.09%, 4.6 wt%, and 34.5 wt%. Comparing the above results, it shows that the maturity of coal and shale samples in well DC-4 is lower than those of well DC-5; however, brittle minerals and TOC contents of coal and shale samples in well DC-4 are higher than those of well DC-5.

Table 1.

Basic properties and mineral composition of coal and shale samples in the Guxu mining area.

Sample ID	Depth (m)	Maturity (R_{o, max}; %)	TOC (wt %)	Mineral composition (wt%)
Sample ID	Depth (m)	Maturity (R_{o, max}; %)	TOC (wt %)	Mixed I/S	Illite	Kaolinite	Quartz	Calcite	Pyrite	Anatase
DC-4-C14-1	816.2	3.21	75.01	34.4	2.2	11	4.9	13.4	21.1	13.0
DC-4-C17-2	845.2	3.02	78.90	30.8	1.3	23	7.2	23.2	14.5	–
DC-4-C25-2	880.6	2.82	82.98	37.2	0.8	13.4	8.6	20.0	20.0	–
DC-4-Y2	814.9	2.93	4.19	8.7	2	43	11.5	33.5	–	1.3
DC-4-Y4	823.8	2.81	15.52	0.2	1.1	47	31.0	18.2	–	2.5
DC-4-Y9	875.5	3.00	5.21	18.2	2.8	20.3	35.1	23.6	–	–
DC-5-C14-1	726.9	2.96	44.21	62.1	4.4	8.2	4.9	3.0	8.0	9.4
DC-5-C17-2	747.8	3.16	73.56	31.2	0.7	18.2	3.2	32.2	10.4	4.1
DC-5-C23-1	758.3	2.92	53.12	41.2	3.6	14.4	4.9	24.6	11.3	–
DC-5-C24-1	763.7	3.22	53.05	37.5	1.2	14.6	8.3	20.2	18.2	–
DC-5-C25-1	775.7	3.08	79.46	53.1	5.2	9.1	1.0	7.8	3.1	0.7
DC-5-Y2	728.0	2.96	2.56	14.1	2.7	59.5	14.8	8.3	0.6	–
DC-5-Y4	744.6	3.05	2.69	31.9	2.4	43.2	11.3	7.4	2.7	1.1
DC-5-Y5	762.5	3.25	8.55	1.2	1.7	35.5	39.8	21.8	–	–

TOC: total organic carbon.

Pore structure characteristics and classification

According to the classification of IUPAC, porous materials are divided into micropore (<2 nm), mesopore (2–50 nm), macropore (>50 nm) by their pore diameters. According to the classification of Yao et al. (2008) and Cai et al. (2013), micropores of coal are divided into <10 and 2–10 nm in diameter. Mesopore of coal is divided uniformly into a pore diameter range of 10–100 nm. First, there is no unified classification standard of pore structure for the coal and shale. Second, the pore sizes of 2–100 nm are not developed in the coal and shale reservoirs. For clearly calculating the contribution of coal and shale samples on its PV, an integrated PSD is reset in Table 2. They are divided into micropore (<2 nm), mesopore (2–100 nm), macropore A (100 nm–1 µm), macropore B (1–10 µm), and micro-fracture (>10 µm). The nomenclature of macropore A and macropore B is for avoiding ambiguity with the general usage of macropore (>50 nm) and megapore (>7500 nm).

Table 2.

Pore structures classification from coal and shale samples in coal measures.

Name	Pore diameter	Application area	Source
Micropore	<2 nm	Shale	IUPAC (1985)
Mesopore	2–50 nm
Macropore	>50 nm
Super micropore	<2 nm	Coal	Cai et al. (2013)
Micropores	2–10 nm
Mesopore	10–100 nm
Macropore	100 nm–1 µm
Super macropore	1–10 µm
Micro-fracture	>10 µm
Micropore	<2 nm	Coal and shale inthe coal measures	This study
Mesopore	2–100 nm
Macropore A	100 nm–1 µm
Macropore B	1–10 µm
Micro-fracture	>10 µm

Quantitative analysis of the pore structure

In order to comprehensively describe the pore structure from micrometer scale to nanometer scale, MIP and low-pressure N₂ and CO₂ physisorption are carried out in this research. Macropore, mesopore, and micropore PV and specific surface area results are shown in Table 3.

Table 3.

Pore volume (PV) and specific surface area (SSA) based on IUPAC classification by MIP, N₂/CO₂ physisorption for coal and shale samples in the Guxu mining area.

Sample ID	Macropores A, B, and micro-fracture by MIP				Mesopores by N₂ adsorption			Micropores by CO₂ adsorption
	PV (cm³/100g)			SSA (m²/g)	BJH PV (cm³/100g)	BET SSA (m²/g)	PSD^a (nm)	DFT PV (cm³/100g)	D–R SSA (m²/g)
	>10 µm	1–10 µm	0.1–1 µm	>100 nm	2–100 nm			<2 nm
DC-4-C14-1	60.50	5.03	6.32	15.96	0.38	0.74	15.64	–	–
DC-4-C17-2	56.37	5.77	2.66	6.67	0.17	0.30	40.97	4.50	241.86
DC-4-C25-2	54.15	5.14	1.21	2.56	0.08	0.14	31.73	–	–
DC-4-Y2	22.08	14.43	5.07	3.25	2.57	14.76	7.44	–	–
DC-4-Y4	22.40	11.69	3.87	1.99	2.50	15.11	7.54	1.26	65.11
DC-4-Y9	16.89	9.04	3.81	1.02	2.63	15.61	7.23	–	–
DC-5-C14-1	42.94	6.22	5.89	4.63	4.07	27.37	8.09	–	–
DC-5-C17-2	61.24	3.28	2.48	6.66	0.13	0.32	18.15	–	–
DC-5-C23-1	41.42	9.05	4.03	3.59	1.11	5.50	7.02	3.28	161.10
DC-5-C24-1	62.05	1.77	1.57	4.38	0.23	1.18	9.18–9.65	–	–
DC-5-C25-1	32.15	9.07	6.27	4.31	1.50	4.67	9.76	–	–
DC-5-Y2	18.29	13.01	5.35	3.71	4.95	26.26	6.95	–	–
DC-5-Y4	12.45	15.53	6.69	3.49	4.45	25.23	6.46	–	–
DC-5-Y5	13.13	18.29	9.87	5.98	4.62	24.72	8.03	0.59	34.01

BET: Brunauer–Emmett–Teller; BJH: Barrett–Joyner–Halenda; DFT: density functional theory; D–R: Dubinin–Radushkevich; MIP: mercury intrusion porosimetry; PSD: pore size distribution.

^aPSD was the average pore diameter calculated from BJH desorption breath.

MIP results

MIP is capable and wildly used for calculating macropore pore characteristics of coals and shales (Okolo et al., 2015; Wang et al., 2016). The PSD and PV of coals and shales in the wells DC-4 and DC-5 are presented in Figures 3 and 4. They show an opposite PSD feature and a similar PV feature between coal and shale samples. The dominating PSDs of coal samples in wells C-4 and DC-5 range from 10 to 200 µm, followed with PSDs between 100 and 6000 nm, while PSDs in shale samples are dominated from 100 to 6000 nm, then from 6 to 200 µm (Figure 3). The PVs of coal samples in wells DC-4 and DC-5 are mainly contributed by micro-fracture (PSD with 10–100 µm). And shale PVs are provided primarily by macropore B and micro-fracture (PSD with 1–100 µm) (Figure 4).

Figure 3.

Mercury intrusion data showing the PSD of macropores of coal and shale samples from the Guxu mining area.

Figure 4.

Relationship between PSD and PV determined from MIP method.

N₂ physisorption results

Both adsorption and desorption branches are usually recorded on the N₂ physisorption experiment (Figure 5). The hysteresis loop is also observed in all shales, and partial coals (i.e. DC-4-C14-1, DC-5-C23-1, DC-5-C24-1, and DC-5-C25-1) and possibly results from capillary condensation in mesopores. According to the classification of IUPAC, the hysteresis patterns of all shale samples and coal samples (except for DC-5-C17-2 and DC-5-C24-1) fall into type H3 loop, which was aggregated by plate-like particles and given rise to slit-shaped pores (IUPAC, 1985). The hysteresis patterns of DC-5-C17-2 and DC-5-C24-1 samples remain nearly horizontal and parallel over a wide range of relative pressure (P/P₀), indicating that the narrow slit-like pores are dominated types in these samples (IUPAC, 1985).

Figure 5.

N₂ adsorption–desorption isotherms of coal and shale samples in the Guxu mining area.

The BJH model is the most suitable and widely used method for analyzing the PSD of mesopore materials (Mastalerz et al., 2018), although there are some problems existing: cannot calculate the pores width less than 2 nm and the tensile strength effect (TSE) phenomenon appears at a pore diameter of 3.8 nm (Groen et al., 2003). The PSDs of the eight coal and six shale samples are calculated according to the N₂ adsorption branch and illustrated in Figure 6. In the dV(log(d)) plot which is (V_i+1−V_i)/(log(d_i+1)−log(d_i)), one peak of all samples is at about 10–100 nm in pore width, and the other peak of five samples (ID of DC-4-Y2, DC-4-Y4, DC-4-Y9, DC-5-C23-1, and DC-5-C25-1) is at about 2–4 nm in pore width. The peaks of DC-4-C14-1 and DC-5-Y2 samples appearing at 3.8 nm are caused by TSE phenomenon. It can also be found that the coal of DC-5-C14-1 has a height of less than 2 nm in width, explaining the reason for the largest of BET surface area in all 14 samples. The pores less than 10 nm in diameter are not developed in the coals of DC-4-C17-2, DC-4-C25-2, DC-5-C17-2, and DC-5-C24-1.

Figure 6.

PSD calculated by N₂ adsorption branch for coal and shale samples in the Guxu mining area.

CO₂ physisorption results

CO₂ physisorption has been approved to be an effective method for characterizing micropores between 0.3 and 1.1/1.5 nm (Wang et al., 2015). Two coals and two shales are chosen for the target to investigate the microporous feature in this study. Figure 7 shows the low-pressure CO₂ adsorption isotherms at 273 K for coal and shale samples. The CO₂ absorbed volumes of coals and shales range from 18.4 to 27.9 cm³/g and from 4.2 to 8.1 cm³/g, respectively. It can be found that the two coal samples have higher adsorption capacity than two shale samples, suggesting that the microporosity is prevailing in coal samples.

Figure 7.

Low-pressure CO₂ adsorption isotherms at 273 K for coal and shale samples.

The PSDs of micropore estimated by DFT model are presented in Figure 8. It can be found that the significant peak in the pore width ranges between 0.4 and 0.7 nm, and then is 0.7–0.9 nm. There is a sharp increase at more than 1.1 nm in pore width, implying a third peak appeared at pore width more than 1.1 nm after analyzed with N₂ adsorption results in Figure 6.

Figure 8.

PSDs obtained from the low-pressure CO₂ adsorption isotherm.

Methane isothermal adsorption

In a simple gas–solid adsorption system, the observed adsorption quantity (also called excess adsorption quantity or Gibbs excess adsorption uptake) is not equal to the actual adsorbed amount (Chattoraj and Birdi, 1984; Gibbs, 1878). The excess adsorption quantity is connected with the densities of the adsorbed phase (ρ_a) and the bulk gas phase (ρ_g). At a relatively low-pressure stage (P < 12 MPa), the value of the adsorbed phase density is much larger than that of the bulk gas phase density. The excess adsorption quantity can be approximately seen as the actual adsorption quantity (Tang et al., 2016b). That is why the Langmuir adsorption model, assuming an adsorbate behaves as an ideal gas at the isothermal condition, can be widely used to represent the adsorption behavior for coal and shale samples at the low pressure (Pan and Connell, 2007; Wang et al., 2016). However, the observed adsorption quantity reaches a maximum typically and then decreases at high pressure (P > 12 MPa; Tang et al., 2016b). It is necessary to concern the densities of the adsorbed phase (ρ_a) and the bulk gas phase (ρ_g) when illuminating the isothermal methane adsorption at high pressure.

Methane storage capacities of coal and shale samples are characterized by methane isothermal adsorption, and the results are shown in Figure 9. Coal methane isothermal adsorption curves are drawn according to the Langmuir adsorption model and shale methane isothermal adsorption curves are fitted based on adapted Langmuir function. Langmuir adsorption model is expressed as

V = P V_{L} / (P + P_{L})

where V (m³/t) is the gas sorption volume per unit weight of sample in equilibrium at a particular pressure, V_L (m³/t) describes the Langmuir volume (based on monolayer adsorption), P (MPa) is the gas pressure, and P_L (MPa) is the Langmuir pressure.

Figure 9.

Methane adsorption isotherms for (a) eight coal samples and (b) six shale samples in the Guxu mining area.

The adapted Langmuir function by Gensterblum et al. (2009) and Gasparik et al. (2012) is described as

V_{e} = V \times (1 - ρ_{g} / ρ_{a}) = P V_{L} / (P + P_{L}) \times (1 - ρ_{g} / ρ_{a})

where V_e is the excess adsorption capacity, ρ_g is the density of the gas phase, and ρ_a is the density of the adsorption phase.

The Langmuir volume (V_L) and Langmuir pressure (P_L) are calculated based on these two formulations, and the adsorbed phase density is also listed in Table 4. The Langmuir sorption capacities and Langmuir pressure for coal samples are from 11.39 to 25.06 m³/t and from 0.98 to 1.22 MPa, respectively. For shale sample, they are from 3.53 to 9.61 m³/t and from 1.04 to 3.24 MPa, respectively. The adsorbed phase density ranges from 0.29 to 0.48 g/ml.

Table 4.

Methane isothermal adsorption results for coal and shale samples.

Sample ID	V_L (m³/t)	P_L (MPa)	ρ_a (g/ml)
DC-4-C14-1	21.05	0.98	–
DC-4-C17-2	23.75	1.12	–
DC-4-C25-2	23.09	1.00	–
DC-5-C14-1	11.39	1.22	–
DC-5-C17-2	25.06	1.05	–
DC-5-C23-1	16.18	1.06	–
DC-5-C24-1	21.88	1.17	–
DC-5-C25-1	16.03	1.15	–
DC-4-Y2	4.35	1.71	0.48
DC-4-Y4	9.61	1.04	0.39
DC-4-Y9	3.53	2.21	0.36
DC-5-Y2	5.66	3.24	0.42
DC-5-Y4	4.96	3.03	0.29
DC-5-Y5	7.00	1.96	0.40

Fractal dimensions from low-pressure N₂ adsorption isotherms

Fractal dimension is a quantitative tool to characterize the complexity of pore surface and pore structure, which vary between 2 and 3 (Cai et al., 2013). Langmuir, n-BET, Frenkel–Halsey–Hill (FHH), fractal analogue of Dubinin–Astakhov equation, and the thermodynamic methods have been used to calculate the fractal dimensions based on the gas adsorption isotherms (Cai et al., 2013; Fripiat et al., 1986; Gauden et al., 2001; Xu et al., 1997; Yin, 1991). Among them, the fractal FHH model was believed to be an effective and reliable method for the analysis of gas adsorption data (Wang et al., 2016; Yao et al., 2008). On the plot of lnV versus ln(lnP₀/P) (Figure 10), two-line slopes (A₁ and A₂) were calculated according to the fractal FHH equation (Li et al., 2017). The fractal FHH equation is expressed as

ln (V / V_{o}) = A \times [ln (ln P_{0} / P)] + constant

where V expresses the volume of adsorbed gas molecules at the equilibrium pressure P, V₀ describes the volume of monolayer coverage, A is the power-law exponent that is dependent on D and the mechanism of adsorption, and P₀ is the saturation pressure of the gas.

Figure 10.

Plots of lnV versus ln(lnP₀/P) reconstructed from N₂ adsorption isotherms.

The fractal dimension values (D₁ and D₂) can be calculated at the relative pressure (P/P₀) range 0–0.5 and 0.5–1.0 according to the equations of D_n = 3A_n+3 and D_n = A_n+3 (n = 1, 2; Yao et al., 2008); however, the latter is used more widely than the former. The values of a fractal dimension ranging 2 and 3 are more conform to reality. Therefore, according to the equation of D_n = A_n+3, the fractal dimension values (D₁ and D₂) are calculated and shown in Table 5. The surface fractal dimension (D₁) of coals and shales range from 2.2536 to 2.7698 and from 2.7215 to 2.7540, respectively. The pore structure fractal dimensions (D₂) of coals and shales are 2.5493–2.9047 and 2.5822–2.6894, respectively. The fractal dimensions of some coal samples (i.e. DC-4-C14-1, DC-4-C17-2, DC-4-C25-2, and DC-5-C17-2) cannot be calculated based on FHH model, mainly because the nitrogen adsorption volumes in these samples are deficient and detected very difficult during relative pressure smaller than 0.9.

Table 5.

Fractal dimensions derived from fractal FHH model.

Sample ID	P/P₀ = 0–0.5			P/P₀ = 0.5–1.0			Adsorption/desorption isotherms^a
Sample ID	A ₁	D ₁	Coefficient (R²)	A ₂	D ₂	Coefficient (R²)	Adsorption/desorption isotherms^a
DC-4-C14-1	−0.7464	2.2536	0.9876	–	–	–	Group A
DC-4-C17-2	–	–	–	–	–	–	Group B
DC-4-C25-2	–	–	–	–	–	–	Group B
DC-4-Y2	−0.2703	2.7297	0.9977	−0.3454	2.6546	0.9955	Group A
DC-4-Y4	−0.2611	2.7389	0.9973	−0.3390	2.6610	0.9912	Group A
DC-4-Y9	−0.2683	2.7317	0.9944	−0.3106	2.6894	0.9955	Group A
DC-5-C14-1	−0.2302	2.7698	0.9963	−0.3597	2.6403	0.9912	Group A
DC-5-C17-2	–	–	–	–	–	–	Group B
DC-5-C23-1	−0.2807	2.7193	0.9793	−0.4038	2.5962	0.9973	Group A
DC-5-C24-1	−0.4310	2.5690	0.9817	−0.0953	2.9047	0.6843	Group A
DC-5-C25-1	−0.3826	2.6174	0.9936	−0.4507	2.5493	0.9996	Group A
DC-5-Y2	−0.2739	2.7261	0.9891	−0.4036	2.5964	0.9982	Group A
DC-5-Y4	−0.2460	2.7540	0.9888	−0.4178	2.5822	0.9991	Group A
DC-5-Y5	−0.2785	2.7215	0.9948	−0.3883	2.6117	0.9959	Group A

FHH: Frenkel–Halsey–Hill.

^aGroup A (exist hysteresis loop) and group B (reversible isotherm) are divided from N₂ adsorption/desorption isotherms.

According to the N₂ adsorption/desorption isotherms, all shale samples are divided into group A, which show the hysteresis loops in Figure 5. Coal samples are divided into groups A and B.

Three coal samples of group B are not found hysteresis loops in their N₂ adsorption/desorption isotherms, suggesting mesopores and macropore A (100 nm–1 µm) are not developed in these coal samples. The adsorption and desorption phenomena are also inconspicuous at a low-pressure stage in these three coal samples. Therefore, it can be stated that the fractal dimensions calculated from limited N₂ adsorption data are not suitable for the coal samples which are not developed in mesopore and macropore A. Maybe group B includes samples whose fractural dimensions could not be estimated in this paper; this statement needs to be verified by more samples. However, the previous study has also proved that the pore structure of coal or shale samples in group A is more complicated than that of group B (Liu et al., 2015).

Discussions

Comparison of pore structure from coal and shale

In this study, the pore structure was analyzed by mercury intrusion for the PSD of macropores A, B and micro-fractures (Figures 3 and 4), N₂ physisorption for the PSD of mesopores (Figure 6), and CO₂ physisorption for the PSD of micropore (Figure 8). In terms of mercury intrusion, N₂ physisorption, and CO₂ physisorption results, the specific surface area of coal and shale samples from Guxu mining area is primarily contributed from micropores, followed by mesopores (Figure 11(a)). The PV is main from micro-fracture and macropore B (Figure 11(b)). Therefore, micropores and mesopores will mainly control the gas adsorption while micro-fractures and macropore B are significant for free gas storage and flow. Micropores primarily contribute to the specific surface area of coal, while both micropores and mesopores are essential contributors to the specific surface area of shale. Also, the total PV of coal is mainly contributed by micro-fracture, while for shale samples, besides micro-fracture, macropore B has the same importance for the total PV.

Figure 11.

Percentages of (a) the specific surface area under the IUPAC classification and (b) the total PV under this study classification of coal and shale samples.

Effect factors on the methane adsorption capacity

Previous researchers have proved that there were many factors, such as the mineral composition, organic matter type and maturity, moisture, and pore structure (PSD, SSA, and PV), influencing the gas storage state and adsorption capacity (Wang et al., 2014, 2015; Zhang et al., 2018a). In this study, we focus on the following factors, such as pore structure (PV and SSA), TOC, and clay mineral content.

The amount of gas adsorbed on the coal surface depends on the adsorption potential energy, which lies with the adsorbents and the pore size (Wang et al., 2014). As shown in Figure 12(a) and (b), the pore size notably influences the methane adsorption capacity. Especially micropores (<2 nm) and micro-fractures (>10 µm) have a positive contribution to the PV and the methane adsorption capacity, while mesopores (2–100 nm) and macropore B (1–10 µm) negatively contribute to the PV and the methane adsorption capacity (Figure 12(a) and (b)). Combining with the above analysis of PV and SSA percentage in different PSD, micropores contribute to the SSA and micro-fractures contribute to the PV of coal and shale samples. Adsorbed methane was mainly adsorbed on the surface of the matrix, which is closely related to the SSA concentration. Therefore, pore size strongly affects the methane adsorption capacity and the ratio of free to adsorbed gas. That is because the methane filling happens in micropores mainly in an adsorbed state, in micro-fracture in a free stage, and mesopores and macropore B in adsorbed and free stages. Micro-fracture frequency has no relationship with the methane adsorption capacity; it mainly depends on the width of micro-fracture.

Figure 12.

The relationship between methane adsorption capacity and cumulative PV (a, b), as well as specific surface area (c, d), clay mineral compositions (e, f, and g), and TOC content (h) for coal and shale samples. TOC: total organic carbon.

A positive relationship presented between micropores SSA and the methane adsorption capacity and a negative relationship appeared between mesopores SSA and the methane adsorption capacity of the coal and shale samples (Figure 12(c)). The methane adsorption capacity is negatively correlated with the mixed I/S and illite concentrations and positively correlated with the kaolinite concentration of the coal and shale samples (Figure 12(e) to (g)). TOC content is also positively correlated with the methane adsorption capacity (Figure 12(h)). Therefore, pore structure, clay mineral composition, and TOC content have a close relationship with the methane adsorption capacity. In them, the PV and SSA of micropores, micro-fracture PV, kaolinite concentration, and TOC content are positively correlated with the methane adsorption capacity.

Conclusions

The methane adsorption capacity is closely related to the pore size and pore structure, especially to the micropore SSA and micro-fracture PV. In order to better understand the effects of coal and shale pore structure in the coal-bearing stratum on the methane adsorption capacity, an integrated classification is provided based on the test range of MIP and low-pressure N₂/CO₂ gas adsorption. They are micropore (<2 nm), mesopore (2–100 nm), macropore A (100 nm–1 µm), macropore B (1–10 µm), and micro-fracture (>10 µm). Micropores have a positive contribution to the pore structure and the methane adsorption capacity, while mesopores and macropore B negatively contribute to the pore structure and the methane adsorption capacity. Micro-fracture frequency has no contribution to the methane adsorption capacity. However, micro-fracture width is closely related to the methane adsorption, storage, and transport.

Coal samples are divided into groups A and B, and all shale samples are divided into group A. The pore structure of coal or shale samples in group A is more complicated than that of group B, and the fractal dimensions calculated from N₂ adsorption data are not suitable for the coal samples which are not developed in mesopore and macropore.

The main factors influencing the methane adsorption capacity of coal and shale in the coal measures are the micropore concentration and micro-fracture width in the pore structure, clay mineral composition, and TOC content. The contributions of micropore PV, micro-fracture PV, micropore SSA, brittle minerals, and TOC content in well DC-4 are higher than that in well DC-5 based on the mentioned experimental data analysis in this article.

Footnotes

Acknowledgements

We especially appreciate the assistance of Dongqiang Wang and Hu Liu for collecting the samples.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The following institutes supported this work: The National Natural Science Foundation of China (Grant Nos. 41530315, 41502156, 41372213), Sichuan Science and Technology Support Plan Project (Grant No. 2016JZ0037), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA05030100), and Excellent Yong Technology Foundation by Xi’an University of Science and Technology (Grant No. 2018YQ2-08).

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Influence of reservoir properties on the methane adsorption capacity and fractal features of coal and shale in the upper Permian coal measures of the South Sichuan coalfield,China

Abstract

Keywords

Introduction

Samples and experimental methods

Geological setting

Samples

Experimental approaches

Results and analysis

Maturity, mineral composition, and TOC content

Pore structure characteristics and classification

Quantitative analysis of the pore structure

MIP results

N2 physisorption results

CO2 physisorption results

Methane isothermal adsorption

Fractal dimensions from low-pressure N2 adsorption isotherms

Discussions

Comparison of pore structure from coal and shale

Effect factors on the methane adsorption capacity

Conclusions

Footnotes

Acknowledgements

Declaration of conflicting interests

Funding

References

N₂ physisorption results

CO₂ physisorption results

Fractal dimensions from low-pressure N₂ adsorption isotherms