Supercritical Methane Sorption on Organic-Rich Shales over a Wide

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Supercritical Methane Sorption on OrganicRich Shales over a Wide Temperature Range Feng Yang, Congjiao Xie, Shang Xu, Zhengfu Ning, and Bernhard M. Krooss Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b02628 • Publication Date (Web): 07 Nov 2017 Downloaded from http://pubs.acs.org on November 16, 2017

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Energy & Fuels

Supercritical Methane Sorption on Organic-Rich Shales over a Wide Temperature Range

Feng Yang,a,b,* Congjiao Xie,a Shang Xu,a Zhengfu Ning,b Bernhard M. Krooss c

a

Key Laboratory of Tectonics and Petroleum Resources, Ministry of Education, China University of

Geosciences, Wuhan 430074, PR China b

State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing),

#18, Fuxue Rd, Changping, Beijing 102249, PR China c

Energy and Mineral Resources Group (EMR), Institute of Geology and Geochemistry of Petroleum and

Coal, Lochnerstr. 4-20, RWTH Aachen University, 52056 Aachen, Germany * Corresponding Author: [email protected]

1

ACS Paragon Plus Environment

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ABSTRACT: Methane sorption on organic-rich shales over wide temperature and pressure ranges (30

2

to 120 °C, up to 25 MPa) is analyzed by the pore filling/potential theory. The supercritical

3

Dubinin-Astakhov (SDA) sorption model using a density term instead of the pseudo-saturation vapor

4

term is extended to methane sorption isotherms of shales with high accuracy. A modified adsorption

5

potential approach is suggested to analyze the temperature dependence of supercritical methane sorption

6

on shales. The temperature-invariant characteristic curves are obtained using the modified adsorption

7

potential approach. A characteristic curve equation derived from the SDA model is provided to predict

8

sorption isotherms at other temperatures using one isotherm. The physical meaning of the characteristic

9

curve has been discussed, and it comprehensively reflects the available pore space for methane sorption

10

and the affinity between methane molecules and organic matter. According to methane characteristic

11

curves of shales and clay minerals, shales in the gas window show higher affinity than shales in the oil

12

window and clay minerals, though the clay minerals may provide comparable adsorbed volume. The

13

adsorption characteristic energy shows a parabolic-like shape with a minimum approximately around Req

14

=1.1%, which are related with the evaluation of porosity of shales. This study advanced the fundamental

15

understanding about the dynamic process of methane sorption on shales.

16

KEYWORDS: shale gas; sorption isotherm; adsorption potential; characteristic curves

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Energy & Fuels

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Introduction

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Fine-grained sedimentary rocks, such as mudstones and shales, contain abundant nanometer- to

19

micrometer-sized pores. These narrow pores create intense fluid-rock interaction that may lead to complicated

20

fluid storage and transport process [1]. An important component of hydrocarbon storage in organic-rich shales is

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gas sorption on organic matter and clay minerals. Sorption is a general term, since sorption data measured on the

22

organic-rich materials may include a combination of adsorption onto the pore surface and absorption within the

23

organic matter [2]. Sorbed gas may significantly contribute to the original gas in place (OGIP) of unconventional

24

reservoirs. Remarkably, 50–80% of the total amount of natural gas in some of the largest shale gas plays in North

25

America is postulated to be trapped as adsorbed phase in the pores of the rocks [3].

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Concerns about the accurate evaluation of gas content and diffusion kinetics have led to many experimental

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studies about gas sorption on shales. Significant progress has been achieved in the controls on sorption capacity

28

of shales [4–12]. However, data on high-temperature high-pressure sorption isotherms of shales are still scare. In

29

particular, the burial depth of the Paleozoic shales in the Upper Yangtze region of China is mostly in a range of

30

2000–4000 m [13–16], which indicates that the temperature and pressure of shale reservoirs are in the range of

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60–120 °C and 20–40 MPa, assuming the hydrostatic pressure and normal geothermal gradients (0.01 MPa/m,

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0.03 °C/m). Experimental techniques employed in obtaining sorption data have to be optimized and at the same

33

time the measuring conditions have to be extended to in-situ conditions of deep shales while many published

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sorption data are limited to moderate pressures (< 15 MPa) and temperatures (< 60 °C) [4–7].

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The accurate modeling gas sorption behavior is important for OGIP estimation and production simulation.

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Methane sorption isotherms of shales, commonly IUPAC type I in shape, are often modeled by the Langmuir and

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less frequently the Dubinin-Astakhov (D-A) models [6–9, 17–21]. Recently, sophisticated theoretical models and

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molecular simulation techniques, which consider both the adsorbate-adsorbent interaction and pore structure

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characteristics of adsorbents, are also introduced to model gas sorption on shales [22–27]. Several investigators

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found that the D-A equation based on potential theory provides a better fit than Langmuir model on sorption data

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of coals [19–21]. The D-A model, originally developed for subcritical gas in microporous adsorbent, has been

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extend to supercritical gas sorption using the definition of pseudo-saturation vapor pressure (Ps, Table 1, [28–

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30]). Under the shale reservoir conditions, most gases (including CH4 and CO2) are supercritical and the

44

properties of the adsorbed fluid (e.g. density and volume) are not well defined due to the absence of a clear

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phase-transition. Though a series of approaches have been proposed to characterize the Ps and ρads (adsorbed

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phase density, Table 2, [31–32]), these schemes do not always work well in supercritical gas sorption at wide

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pressure and temperature ranges, especially when the pressure is larger than the pseudo-saturation vapor pressure

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(P > Ps) [21]. The adsorption potential becomes negative at elevated pressures (> ~10 MPa) (Figure 1), which

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goes against Dubinin’s postulates in potential theory. It was recently proposed that the D-A equation can be

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applied to supercritical conditions by replacing the Ps term by the ρads and pressure by gas density [33–35]. The

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modified supercritical Dubinin-Astakhov (SDA) model has achieved good results in describing high-pressure

52

nitrogen and methane sorption on coals [33–35]. Furthermore, since gas sorption is temperature dependent, a

53

sorption model should be able to reliably predict the temperature dependence of supercritical gas sorption. The

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characteristic curve in Dubinin-Polanyi potential theory offers a method to investigate the temperature

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dependence of sorption. Though the SDA model was applied to describe supercritical methane sorption on shales,

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but the characteristic curve (another important issue associated with the potential theory) of methane on shales

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hasn’t been studied [20–23]. The classic characteristic curve method only works at low to moderate pressure

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range (P < Ps, Figure 1), and cannot be extended to high pressure sorption. The modified characteristic curve

59

described below can be applied to a much wider pressure and temperature ranges, and provides new insights into

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the dynamic process about methane sorption on shale systems.

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In this work, we examined the Dubinin-Polanyi potential theory on high pressure methane sorption on

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shales. New approach was proposed to extend the potential theory to supercritical gas sorption over wide

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temperature and pressure ranges. A set of high pressure sorption data for Paleozoic shales from Sichuan Basin

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has been measured at temperatures from 30 to 120 °C and pressure up to 25 MPa. Experimental data were

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parameterized by SDA-based excess sorption equations, and the validity of temperature dependence of

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supercritical methane sorption model has been tested. A modified adsorption potential method was proposed to

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calculate the characteristic curves for supercritical gas sorption, and then a rigorous function from the SDA

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equation was also developed to describe the modified characteristic curve, other than using an empirical

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polynomial equation. Furthermore, the physical meaning of characteristic curve has been elucidated by

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comparing characteristic curves of different kinds of shales and clay minerals. To the best of our knowledge, this

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is the first attempt to explain the interaction between adsorbent (shale) and adsorbate (methane) from the

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perspective of characteristic curve.

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2

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Experimental section 2.1

Samples

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Four Paleozoic shales were collected from the field standard stratigraphic section in Changning area in

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Southern Sichuan Basin (Table 3). The Sichuan Basin, a kind of cratonic basin in the western Yangtze platform,

77

has undergone multi-stage tectonic evolution [13]. The Upper Ordovician-Lower Silurian shales widely develop

78

in the Upper Yangtze region of southern China. The Upper Ordovician Wufeng Formation (O3w) formed in the

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deep-water continental shelf with water retention depositional environment, and was conformably overlain by

80

Lower Silurian Longmaxi Formation (S1l). The anoxic environment in Upper Ordovician caused by water

81

retention is favorable for the preservation of organic matter. In the Silurian, the anoxic environment was

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damaged because of a gradual sea level decline [14,15]. The transformation from anaerobic environment into

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normal oxygen deposition environment affects adversely the preservation of organic matter. Consequently, the

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TOC (total organic carbon) content of the studied stratigraphic section decreases from Upper Ordovician Wufeng

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Formation to Late Silurian Longmaxi Formation. Fresh shale samples were collected from outcrop profiles in

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Changning structure. The Changning stratigraphic section is frequently used as comparative study about marine

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shales in China [16]. The first shale gas well in China (Changxin1) was completed in this area in 2008. The

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Paleozoic shales in Sichuan Basin are currently considered as the key targets for shale gas exploration in China.

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Several national shale gas fields operated by PetroChina and Sinopec have been developed in this area. Total

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shale gas production from Weiyuan-Changning area was more than 2300 million m3 in 2016.

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Shale samples were first ground into powder with average particle size of 100 mesh and prepared for XRD

92

analysis, TOC, and adsorption measurements. Results from organic geochemistry and XRD measurements are

93

presented in Table 3. TOC content of the samples, based on LECO CS230 carbon/sulfur analyzer results, ranges

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from 0.89% to 4.83%. The equivalent vitrinite reflectance (Req), derived from the bitumen reflectance, is around

95

2.8%, which indicates that the samples are at the highly over-mature stage (Req > 2.0%).

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2.2

Pore structure characterization by nitrogen physisorption

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Low-pressure nitrogen adsorption measurements were conducted on Micromeritics Gemini VII 2390t to

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investigate the pore structure characteristics of shale samples. Powder samples were first degassed at 105°C in

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vacuum about 12 h to remove adsorbed moisture. Then degassed samples weighting 0.5–1.0 g were exposed to

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nitrogen at 77 K along a series of precisely controlled gas pressures. Nitrogen adsorption-desorption isotherms

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were obtained over the relative equilibrium pressures (P/P0) range of 0–0.995. The Brunauer-Emmett-Teller

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(BET) and t-plot methods were applied to estimate the total specific surface area and micropore surface area,

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respectively. Pore size distribution (PSD) was interpreted by using Barrett-Joyner-Halenda (BJH) approach.

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Energy & Fuels

2.3

High-temperature high-pressure methane sorption experiments

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High-temperature high-pressure (HTHP) sorption measurements were performed on a manometric setup.

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The setup was consisted by a low-temperature zone (< 40 °C) and a high-temperature zone (Figure 2). In order to

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protect the temperature-sensitive parts from high temperatures, the low-temperature zone was installed for the

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reference cell (the valves and pressure transducer) while the sample cell was placed in the high-temperature zone.

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A high-precision Keller pressure transducer with 30 MPa range (PAA-33X type, 0.01% precision of full scale

110

capacity guaranteed in 10–40°C) is used to monitor the pressure. The sample cell is sealed by metal face fitting

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(VCR®, Swagelok) with nickel gaskets having a 0.5 µm filter, which is used to prevent sample particles from

112

entering the valves. Temperature readings for both heating zones are taken from a Pt-100 resistance temperature

113

detector (RTD) with an estimated accuracy of 0.1 K. Volumes of the reference (VRC = 6.125 ± 0.005 cm3) and the

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sample cell (VSC = 51.26 ± 0.02 cm3) were determined by multiple helium expansions at a specified reference

115

temperature (TRC = TSC = 39 °C). Methane sorption measurements are performed on dry shale samples (~100

116

mesh), and the measuring procedure has been documented in previous studies [8,9,36]. Sufficient time was

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allowed for gas to reach “technically sorption equilibrium” in the RC and SC. Certainly, substantially long

118

equilibration times require a leak-tightness of the setup. An acceptable leakage rate is below 5 mbar/h, which is

119

determined prior to experiment using helium at a representative pressure.

120

The large void volume is one of the major sources of uncertainties in manometric method for excess

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sorption isotherm measurements [37]. Prior to each experiment, SC was packed with sample as much as possible.

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In this study, the typical used amount of the dry samples is 50–80g, which corresponds to Vvoid/VRC values of

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3.4–4.2 measured using helium expansions. Furthermore, blank methane expansion tests were performed on steel

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cylinders of different sizes placed in the SC at the target temperature. The blank methane sorption isotherms of

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stainless steel cylinders with different “void volumes” were interpolated to acquire the blank expansion value of

126

shale samples at an equivalent void volume. From the “raw” expansion data measured on a shale sample, the 7


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blank expansion values were subtracted to obtain the final corrected excess sorption isotherm. These blank

128

sorption tests were carried out to identify experimental artifacts, and have been used in previously international

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inter-laboratory comparison study to assess the reproducibility of sorption isotherms on shales [38]. The error in

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the excess sorption values determined from the experimental data can be estimated using the Gauss error

131

propagation theory. In this study, the calculated uncertainty of measured excess sorption increases with pressure

132

and is estimated to be 0.019 mmol/g at the high-end experimental pressure values.

133 134 135

The excess sorbed mass (mexc), also denoted “Gibbs surface excess”, is calculated through the following mass balance: = − (, )

(Eq. 1)

136

Here Vvoid is the pore space that is not occupied by the powered sample in SC and determined by helium

137

expansion; mtotal is the total mass of adsorbate (methane) transferred into the SC; ρgas(T, P) is free gas density

138

calculated using the GERG equation of state (EOS) provided by Kunz et al. [39].

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The mass balance calculations in the manometric method of sorption measurement rely on an EOS to

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calculate the gas density (or gas compressibility factor) at certain pressures and temperatures. There are

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numerous different EOSs available, however the most commonly used EOSs are the cubic equations of

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Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK), and the multi-parameter Setzmann and Wagner (Se-W,

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[40]) and Span and Wagner (Sp-W, [41]) EOSs. Currently, Se-W and Sp-W are the most accurate EOSs for CH4

144

and CO2 respectively, and have been used for instance in the National Institute of Standards and Technology

145

(NIST) Chemistry WebBook. More recently, Se-W and Sp-W EOSs are incorporated in the multi-component

146

EOS GERG 2004 and GERG 2008 by Kunz et al. [39]. The GERG EOS is used as International Organization for

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Standardization standard (ISO 20765–2: 2015) for natural gases. Figure 3 demonstrates calculated methane

148

density at 30 and 100 °C by PR, SRK, Se-W and GERG EOSs and density difference between those and Se-W

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EOS. Clearly, the methane density calculated by the cubic PR and SRK EOSs deviates significantly from that

150

based on the more accurate Se-W and GERG EOSs.

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Excess adsorbed mass was converted to excess adsorbed amount of substance (nexc, expressed in mmol/g or

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mol/kg) for consistency with earlier published data. The relationship between surface excess amount and the

153

absolute amount adsorbed is: = − = 1 −

154

(Eq. 2)

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Where nexc (mmol/g) is the Gibbs excess sorption; nabs (mmol/g) is the absolute adsorbed gas amount at pressure

156

P (MPa); ρgas and ρads is the bulk phase (free gas) and (average) adsorbed phase density, respectively; Vads is the

157

volume of the adsorbed phase, and can be calculated as = / .

158 159

2.4

Isotherm Models

2.4.1 Adsorbed phase density

160

Excess sorption can be converted into absolute sorption by determining either the adsorption volume or the

161

adsorbed phase density. However, both the ρads and Vads are not accessible to direct measurement. It’s common to

162

use approximate density values of the adsorbed phase or its volume. The transformation methods from the excess

163

sorption to absolute sorption using constant adsorbed phase density assumptions are summarized in Table 2. The

164

van der Waals (VDW) approximation assumed that the adsorbed phase consists of molecules having the VDW

165

constant, namely, the adsorbed phase density of methane is 0.373 g/cm3 [28]. This value is less than the liquid

166

density approximation (0.421 g/cm3 for methane) [31]. Ozawa et al. [32] regarded the supercritical fluid as

167

superheated liquid, and proposed a modified liquid method which corrected the thermal expansion of the

168

adsorbate. The adsorbed phase density can also be estimated under certain assumptions from excess sorption

169

isotherm which has a maximum in excess sorption (graphical method). In this work, we examined these

170

approximations above to describe our experimental data, and all the experimental isotherms recorded at different

9


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171

temperatures were fitted in the same regression.

172

2.4.2 Supercritical Dubinin-Astakhov model

173

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The classic Dubinin-Astakhov (D-A) equation, based on the mechanism of pore filling, is given by = " #$% &−

174

' (

)

(Eq. 3)

175

where n0 is the maximum (absolute) sorption capacity; A is the adsorption potential, and can be calculated as

176

A = RT-( /); R is the universal gas constant; T is the absolute temperature; Ps is the saturation vapor

177

pressure for the adsorbate; t is a structure heterogeneity parameter; E is the adsorption characteristic energy.

178

When t = 2, the D-A equation refers to D-R equation.

179

The D-A equation is usually used to describe the adsorption of subcritical vapors. Methane is in

180

supercritical state in shale gas reservoirs. Above critical temperature, gas cannot condense, and thus does not

181

exhibit a saturated vapor pressure. Several investigators proposed the concept of pseudo-saturation vapor

182

pressure [28–30]. However, these adaptations cannot well accommodate supercritical gas sorption at wide

183

pressure and temperature ranges, especially when the experimental pressure is larger than the pseudo-saturation

184

vapor pressure (P > Ps) [21]. Previous work on the meaning of the Dubinin’s isotherm has indicated that the term

185

Ps is not necessarily the saturation pressure, but is related to the energy required to compress the gas to the

186

sorbed phase density at the sorbent surface [42, 43]. If so, a form of Dubinin’s isotherm can be applied to a much

187

wider pressure and temperature ranges with gas density rather than pressure because density is more meaningful

188

at supercritical conditions [33–35]. The modified supercritical Dubinin-Astakhov (SDA) equation [33–35],

189

which substitutes the pressure term in D-A equation with a density term, can be applied to supercritical sorption

190

and is expressed as

191 192

= " #$% &− .- . / 0/1/ )

(Eq. 4)

The modified supercritical Dubinin-Astakhov (SDA) equation is applied to the excess sorption data as

10


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Energy & Fuels

(Eq. 5)

194

#$% &− .- . / 0/1/ )

234 = " 1 −

193

The above function can be written in the form of adsorption volume: 234 =

195

56 7

1 −

#$% &− .- .

/ 0/1/ )

(Eq. 6)

196

where W0 is the limiting adsorption volume and represents the total available adsorption space. W0 is a

197

property of adsorbent and assumed to be constant in order to be consistent with pore filling theory. Previous

198

investigation on supercritical fluids sorption on porous carbons has shown that adsorbed phase density is

199

likely temperature-dependent [44,45]. Eq. 6 contains four parameters, W0, E, t and ρads. They can be

200

obtained by simultaneously performing multi-variables nonlinear regression over the sorption data recorded

201

at different temperatures. During the process of fitting SDR equation against experimental data, W0, E, t are

202

regarded as characteristic parameters of adsorbent and ρads is temperature-dependent. The optimal fit is done

203

with Microsoft excel using a build-in program, solver, to minimize the square sum of residual (SSR):

204

SSR = ∑> ?@:

205 206

23;

3

(% ) − 4 (% )
~1.1 %) is larger than shales in the oil window

376

(Req < ~1.1 %) with the same TOC content (Figure 11). Organic matter-hosted pores develop during the thermal

377

maturation of organic matter. Under the same TOC content, shales in gas window always have more pores and

378

larger limiting adsorption volume than shales in oil window.

379

Clay minerals also contribute a lot to the limiting adsorption volume (Figure 11). There are abundant pores

380

in clay minerals, which provide adsorbed volume and sorption capacity for methane. The later stage of modified

381

characteristic curves (or the volume adsorbed) of sample CN_32 is comparable with CN_22, which is probably

382

related with its high TCM. The limiting adsorption volume of clay minerals decrease in the order:

383

montmorillonite > illite > chlorite > kaolinite, which is slightly different from the sequence of sorption capacity:

384

montmorillonite > kaolinite > illite > chlorite. This is caused by the difference in adsorbed phase density. The

385

fitted adsorbed phase density in kaolinite is about 404 kg/m3, while it is around 200 kg/m3 in illite. The limiting

386

adsorption volume of montmorillonite is 18.6 cm3/kg, which is larger than all the shale samples. The limiting

387

adsorption volume of illite is about 11.1 cm3/kg, which is comparable to matured shales with TOC content being

388

6%. The considerable limiting adsorption volume in clay minerals supports the argument that clay minerals

389

contribute a lot to methane sorption capacity of low-TOC and clay-rich dry shales [7,8].

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390

4.5

Effect of thermal maturity on characteristic curves

391

The limiting adsorption volume of clay minerals is comparable to organic-rich shale. However, it does not

392

necessarily mean that the clay minerals play the same role in sorption process. It’s interesting to note that at the

393

initial stage (low pressure stage in gas sorption) of the characteristic curves, the adsorbed volume of clay

394

minerals is always less than shales under the same adsorption potential condition (Figure 12). Figure 12

395

illustrates the characteristic curves of representative shales at different thermal maturities. At the beginning of

396

methane sorption (low pressure stage), the adsorption potential of methane on shales and clay minerals decrease

397

in this order: shales in the gas window > shales in the oil window > clay minerals when the adsorbed volume is

398

equal (Figure 12b). This indicates that the heat for methane sorption on shales in the gas window is larger than

399

that on shales in the oil window and clay minerals. This also reflects the higher affinity of methane molecules for

400

sorption on organic matter than on clay minerals. Nonpolar gases like methane are preferentially attracted by

401

hydrophobic organic matter rather than by hydrophilic inorganic matter [57]. Furthermore, organic matter of

402

shales in the gas window is relatively rich in aromatic function groups, while the organic matter of shales in the

403

oil window is relatively rich in hydrophilic oxygen-containing functional groups and aliphatic function groups

404

[58]. The characteristic curves show that organic matter in shales in the gas window has stronger affinity for

405

methane than organic matter in shales in the oil window.

406

The adsorption characteristic energy E is a parameter to characterize the apparent heat of sorption system.

407

Figure 13 illustrates the effect of thermal maturity on adsorption characteristic energy of shales. Adsorption

408

characteristic energy shows a parabolic-like shape with a minimum approximately at the end of oil window (Req

409

≈1.1%), which is consistent with the evolution of porosity in New Albany shales with maturation. Mastalerz et

410

al. found that the porosity are high in immature shales (Req < ~ 0.5%), and decline with increasing maturity to

411

minima in the late mature samples (Req ≈ 1.1%, the end of oil window), and later increase towards the

412

postmature shale (Req > ~1.1%, gas window) [59]. The decline in porosity during the late mature stage is caused 20


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by the pore filling by oil or solid bitumen, which reduce the sorption sites and the sorption system release less

414

heat. Many pores in organic matter are generated by secondary cracking of oil and bitumen in postmature shales

415

(Req > ~1.1%). The interaction between methane and postmature shales enhances and the sorption system release

416

larger heat.

417

The parabolic-like trend between the characteristic energy and thermal maturity of shales is analogous to

418

but different from the previously reported parabolic shape in methane sorption on dry coals [60]. For dry coals,

419

sorption capacity shows a parabolic dependence on coal rank (thermal maturity). For dry shales, no obvious

420

relationship exists between sorption capacity and maturity. However, the characteristic energy instead of sorption

421

capacity shows a parabolic trend with thermal maturity in shales. This can be attributed to the difference in the

422

mineral compositions of coals and shales. In dry shales, the relationship between sorption capacity and thermal

423

maturity is covered by clay minerals because of low TOC content. Thus, total sorption capacity is a function of

424

not only TOC but also TCM in shales. Clay minerals contribute considerable adsorption volume (Figure 11), but

425

the sorption heat on clay minerals is less than organic matter (Figure 13). Adsorption characteristic energy is the

426

heat released by the sorption system-mainly the heat when methane sorption on high energetic sorption sites

427

(organic matter). The organic matter content of coals is high (commonly larger than 60%). Because methane

428

molecules preferentially adsorb on high energetic sorption sites, it can be inferred that probably both sorption

429

capacity and sorption heat of dry coals show a parabolic correlation with rank. Methane sorption characteristic

430

on coals and shales can be unified using parabolic trend from the point of sorption thermodynamic. Detailed

431

investigations about the thermodynamic property of methane sorption on shales will be discussed in future.

432

5

Conclusions

433

High-temperature high-pressure sorption data for methane on shales from Sichuan Basin have been

434

obtained at 30–120°C and pressures up to 25 MPa using a specially designed two-temperature-zone manometric

21


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

435

setup. The sorption isotherms over wide temperature ranges have been successfully described by the supercritical

436

Dubinin-Astakhov (SDA) sorption model. Methane characteristic curves were obtained using a new expression

437

of adsorption potential, and it is found that if the thermal expansion of adsorbed phase is considered, the

438

characteristic curves are temperature-invariant. A characteristic curve equation is provided and able to predict

439

methane sorption at other temperatures based on the easily tested sorption isotherm at room temperature. The

440

modified characteristic curves comprehensively characterize the available pore space for sorption and the affinity

441

of methane molecules. The later stage of the modified characteristic curves (limited adsorption volume) is

442

mainly controlled by the available pore space provided by organic matter and clay minerals. The initial stage of

443

the characteristic curves reflects the affinity of methane molecules for sorption on organic matter. According to

444

the characteristic curves, shales in the gas window show higher affinity than shale in the oil window and clay

445

minerals, though the clay minerals may provide comparable adsorption volume. The adsorption characteristic

446

energy shows a parabolic-like shape with a minimum approximately around Req =1.1%, which are related with

447

the evaluation of porosity of shales.

448

Acknowledgments

449 450 451

China (Grant No. 51604249, 41690134, 41572109), and State Key Laboratory of Petroleum Resources and

452

References

453 454 455 456 457 458 459 460 461 462 463

(1)

The authors would like to acknowledge the financial support of the National Natural Science Foundation of Prospecting Independent Research Subject (Grant No. PRP/open-1606).

Amann-Hildenbrand, A.; Ghanizadeh, A.; Krooss, B.M. Transport properties of unconventional gas systems. Mar. Petrol. Geol. 2012, 31, 90–99.

(2) Montgomery, S.L.; Jarvie, D.M.; Bowker, K.A.; Pollastro, R.M. Mississippian Barnett Shale, Fort Worth basin, north-central Texas: Gas-shale play with multi-trillion cubic foot potential. AAPG Bull. 2005, 89, 155–175. (3) Curtis, J. B. Fractured shale-gas systems. AAPG Bull. 2002, 86, 1921−1938. (4) Chalmers, G.R.L.; Bustin, R.M. Lower Cretaceous gas shales in northeastern British Columbia, part 1: geological controls on methane sorption capacity. Bull. Can. Petrol. Geol. 2008, 56,1–21. (5) Ross, D.J.K.; Bustin, R.M. The importance of shale composition and pore structure upon gas storage potential of shale gas reservoirs. Mar. Petrol. Geol. 2009, 26, 916–927. (6) Zhang, T.W.; Ellis, G.S.; Ruppel, S.C.; Milliken, K.; Yang, R.S. Effect of organic-matter type and thermal 22


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maturity on methane adsorption in shale-gas systems. Org. Geochem. 2012, 47, 120–131. (7) Ji, L.M.; Zhang, T.W.; Milliken, K.; Qu, J.L.; Zhang, X.L. Experimental investigation of main controls to methane adsorption in clay-rich rocks. Appl. Geochem. 2012, 27, 2533–2545. (8) Gasparik, M.; Ghanizadeh, A.; Bertier, P.; Gensterblum, Y.; Bouw, S.; Krooss, B.M. High-pressure methane sorption isotherms of black shales from the Netherlands. Energy Fuels 2012, 26, 4995–5004. (9) Gasparik, M.; Bertier, P.; Gensterblum, Y.; Ghanizadeh, A.; Krooss, B.M.; Littke, R. Geological controls on the methane storage capacity in organic-rich shales. Int. J. Coal Geol. 2014, 123, 34–51. (10) Vandewijngaerde, W.; Piessens, K.; Dusar, M.; Bertier, P.; Krooss, B.M.; Littke, R.; et al. Investigations on the shale oil and gas potential of Westphalian mudstone successions in the Campine Basin, NE Belgium (well KB174): Palaeoenvironmental and palaeogeographical controls. Geol. Belg. 2016, 19, 1–11. (11) Yang, F.; Ning, Z.F.; Zhang, R.; Zhao, H.W.; Krooss, B.M. Investigations on the methane sorption capacity of marine shales from Sichuan Basin, China. Int. J. Coal Geol. 2015,146, 104–117. (12) Yang, F.; Ning, Z.F.; Wang, Q.; Zhang, R.; Krooss, B.M. Pore structure characteristics of lower Silurian shales in the southern Sichuan Basin, China: Insights to pore development and gas storage mechanism. Int. J. Coal Geol. 2016, 156, 12–24. (13) Zhou, Q.; Xiao, X.M.; Tian, H.; Pan, L. Modeling free gas content of the Lower Paleozoic shales in the Weiyuan area of the Sichuan Basin, China. Mar. Petrol. Geol. 2014, 56, 87–96. (14) Li, Y.F.; Zhang, T.W.; Ellis, G.S.; Zhao, D. Depositional environment and organic matter accumulation of Upper Ordovician-Lower Silurian marine shale in the Upper Yangtze Platform, South China. Palaeogeogr. Palaeocl. 2017, 466, 252–264. (15) Chen, C.; Mu, C.L.; Zhou, K.K.; Liang, W.; Ge, X.Y.; Wang, X.P.; et al. The geochemical characteristics and factors controlling the organic matter accumulation of the Late Ordovician-Early Silurian black shale in the Upper Yangtze Basin, South China. Mar. Petrol. Geol. 2016, 76, 159–175. (16) Dai, J.X.; Zou, C.N.; Liao, S.M.; Dong, D.Z.; Ni, Y.Y.; Huang, J.L.; et al. Geochemistry of the extremely high thermal maturity Longmaxi shale gas, southern Sichuan Basin. Org. Geochem. 2014, 74, 3–12. (17) Clarkson, C.R.; Haghshenas, B. Modeling of supercritical fluid adsorption on organic-rich shales and coal. SPE 164532 presented at the Unconventional Resource-USA in The Woodlands, Texas, USA, 10–12 April, 2013. (18) Rexer, T.F.T.; Benham, M.J.; Aplin, A.C.; Thomas, K.M. Methane adsorption on shale under simulated geological temperature and pressure conditions. Energy Fuels 2013, 27, 3099–3109. (19) Tian, H.; Li, T.F.; Zhang, T.W.; Xiao, X.M. Characterization of methane adsorption on overmature Lower Silurian-Upper Ordovician shales in Sichuan Basin, southwest China: Experimental results and geological implications. Int. J. Coal Geol. 2016, 156, 36–49. (20) Chen, L.; Jiang, Z.X.; Liu, K.Y.; Ji, W.M.; Wang, P.F.; Gao, F.L.; et al. Application of Langmuir and Dubinin-Radushkevich models to estimate methane sorption capacity on two shale samples from the Upper Triassic Chang 7 Member in the southeastern Ordos Basin, China. Energ. Explor. Exploit. 2017, 35, 122– 144. (21) Clarkson, C.R.; Bustin, R.M.; Levy, J.H. Application of the mono/multilayer and adsorption potential theories to coal methane adsorption isotherms at elevated temperature and pressure. Carbon 1997, 35, 1689–1705. (22) Chareonsuppanimit, P.; Mohammad, S.A.; Robinson Jr., R.L.; Gasem, K.A.M. High-pressure adsorption of gases on shales: Measurements and modeling. Int. J. Coal Geol. 2012, 95, 34–46. (23) Mohammad, S.A.; Arumugam,A.; Robinson Jr., R.L.; Gasem, K.A.M. High-pressure adsorption of pure gases on coals and activated carbon: Measurements and modeling. Energy Fuels 2012, 26, 536–548. (24) Mosher, K.; He, J.J.; Liu, Y.Y.; Rupp, E.; Wilcox, J. Molecular simulation of methane adsorption in micro23


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moisture-equilibrated shales. Energy Fuels 2017,31,482–492. (58) Lis, G.P.; Mastalerz, M.; Schimmelmann, A.; Lewan, M.D.; Stankiewicz, B.A. FTIR absorption indices for thermal maturity in comparison with vitrinite reflectance Ro in type-II kerogens from Devonian black shales. Org. Geochem. 2005, 36, 1533–1552. (59) Mastalerz, M.; Schimmelmann,A.; Drobniak,A.; Chen, Y.Y. Porosity of Devonian and Mississippian New Albany shale across a maturation gradient: Insights from organic petrology, gas adsorption, and mercury intrusion. AAPG Bull. 2013, 97, 1621–1643. (60) Bush, A.; Gensterblum, Y. CBM and CO2-ECBM related sorption processes in coal: A review. Int. J. Coal Geol. 2011, 87, 49–71.

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590

591 592 593 594 595 596

597 598 599 600

601 602 603 604 605

Figures

Figure 1. The classic adsorption potential ( H = IJKL(MN /M) ) of methane calculated using pseudo-saturation vapor pressure based on Dubinin’s [28] and reduced Kirchhoff equations [29]. It should be noted that the classic adsorption potential becomes negative at elevated pressures (> ~10 MPa), which goes against Dubinin’s postulates in potential theory.

Figure 2. Schematic diagram of the high-temperature high-pressure (HTHP) sorption apparatus (modified after [9]).

Figure 3. Comparison of (a) methane density at 30 and 100 °C calculated using the PR, SRK, Se-W and GERG EOSs and (b) density difference between those and Se-W EOS.

26


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Energy & Fuels

606 607 608 609

610 611 612 613

Figure 4. (a) Low-pressure N2 adsorption-desorption isotherms for the shale samples; (b) Pore size distributions of the samples by using BJH method on the adsorption branch of the isotherms.

Figure 5. Methane excess sorption isotherms measured on dry shale samples at different temperatures. The error bars represent the estimated uncertainties in the amount of gas adsorbed according to the Gauss error propagation theory.

614 615 616 617

Figure 6. The extrapolated plot of methane excess sorption against gas density for sample CN_23. It should be noted that there is some uncertainty in the extrapolation beyond experimental pressure (gas density).

27


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

618 619 620

Figure 7. The modified characteristic curves for methane on sample CN_22 based on different adsorbed

621 622 623 624 625

The density of adsorbed phase was calculated using (a) VDW constant approximation [28]; (b) modified

626 627 628 629 630

gas density methods. The modified adsorption potential is calculated using H = IJKL:OPQN /ORPN < (Eq. 8). liquid density approximation [32]; (c) liquid density at boiling temperature and ambient pressure [31]. Characteristic curve data using the VDW constant and liquid density approximations for adsorbed phase density display larger dispersity than the modified liquid density method.

Figure 8. Modified characteristic curves for methane on shale samples. The modified adsorption potential is calculated using H = IJKL:OPQN /ORPN < (Eq. 8). The lines represent the fitted characteristic curves using Eq. (10), and the fitted correlation coefficient R2 are also labeled.

631 632 633

Figure 9. Measured and predicted methane excess sorption isotherms at 120 °C. Excess sorption isotherms at 120 °C are predicted by characteristic curve equations obtained from isotherms at 30–100 °C.

28


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Energy & Fuels

634

635 636 637 638 639 640 641

642 643 644 645 646 647

Figure 10. Effect of organic richness (TOC) and clay minerals (TCM) on modified methane characteristic curves of shales with thermal maturity level in the gas window. Semi log coordinate is used for comparison. The later stage (high pressure stage) of the modified characteristic curves is mainly controlled by the pore space provided by organic matter and clay minerals. The available pore volume for gas sorption on shales with high TOC and TCM are always large.

Figure 11. Comparison of the limiting adsorption volume as a function of TOC for shales at different thermal maturity levels (this study and Posidonia shales [9] and Barnett shales [6]) and clay minerals [7]). The limiting adsorption volume of shales in the gas window is larger than shales in the oil window with the same TOC content. The clay minerals also contribute to the limiting adsorption volume.

29


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

648 649 650 651 652 653 654 655 656 657 658

659 660 661 662 663

Figure 12. Effect of thermal maturity (Req) on modified methane characteristic curves of shales. The lines represent the fitted characteristic curves using Eq. (10). Generally, though the later stage of characteristic curves of the samples studied are controlled by TOC and clay mineral (Figure 10), the adsorbed volume at the initial stage of characteristic curves (gas sorption at low pressure) decrease in this order: shales in the gas window > shales in the oil window > clay minerals when the adsorption potential is equal, which indicates that shales at the gas window show higher affinity than shales at the oil window and clay minerals. It should be noted that the initial stage of characteristic curves of our four samples are almost the same because they are at the same thermal maturity level. Sample CN_22 represented this set of highly over-mature samples and was plotted.

Figure 13. Effect of thermal maturity (Req) on adsorption characteristic energy of shales (this study and Posidonia shales [9] and Barnett shales [6] and clay minerals [7]). Thermal maturity of shales are approximately divided as: Immature: (Req < ~ 0.5%); Oil window: ~0.5% < Req < ~1.1%; Gas window: Req > ~1.1%.

30


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Energy & Fuels

Tables Table 1: Various methods for the estimation of pseudo-saturation vapor pressure Ps. Method

= (/4 )= 4

Dubinin’s equation Reduced Kirchhoff equation

= 4 #$% &

STEU SV

.

WX YV

]

Dubinin [28]

a

@ZSTEU /SV

ln = + _

Antoine equation a

Ref

Expression

/ 1 −

SV

)

S

Kapoor et al.[29]

b

Do [30]

c

S

Pc and Tc are the critical pressure and critical temperature of the adsorbate.

b

Tnbp is the temperature at the normal boiling point.

c

C and D are Antoine parameters.

Table 2: Various methods to estimate the adsorbed phase density. Method

Expression

Ref

= 8a4 /(04 )

VDW constant approximation

=

Liquid density approximation

a

Agarwal and Schwarz [31]

= #$%b−c × ( − )d

Modified Liquid density

Dubinin [28]

b c

Ozawa, et al. [32]

Graphical method

-

-

Optimization method

-

-

a b c

Pc and Tc are the critical pressure and the critical temperature of the adsorbate, and M is molar mass.

is the liquid density at boiling temperature and ambient pressure.

is the boiling temperature at ambient pressure and c is thermal expansion coefficient of the adsorbate.

Table 3: Geochemical characteristics, mineralogy composition, and pore structure of the shale samples. Sample

Age

TOC

Req

(wt %)

(%)

Quartz + feldspar (wt %)

Total

Carbonates (wt %)

clays (wt %)

SBET b

Vt c

Dd

Smicroe

Vmicrof

(m2/g)

(cm3/kg)

(nm)

(m2/g)

(cm3/kg)

CN_11

O3 w

4.83

2.8

74.0

0.0

26.0

28.75

43.0

6.0

11.8

4.7

CN_22

S1l

2.87

2.8

55.4

25.4

17.2

14.96

18.5

4.9

4.8

1.9

CN_23

S1l

2.92

2.8

57.4

27.4

36.2

14.19

19.7

5.6

6.0

2.5

CN_32 a

S1l

0.89

2.8

25.3

27.7

45.5

14.95

26.7

7.1

3.6

1.5

a

Pore structure parameters of CN_32 were provided based on the results on a copy sample from the sampling sites; b. Total

specific surface areas were determined by the BET method; c. Total pore volumes were evaluated from the adsorbed amount of N2 at the highest relative pressure point; d. average pore diameter; e. Micropore surface area interpreted by the t-plot method; f. t-plot micropore volume.

31


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Page 32 of 32

Table 4. Fitting parameters of SDA model for methane sorption on shales at different temperatures. Shales

TOC

Req

Thermal

W0

E

t

α

8869.6

1.56

0.0004

0.0089

6273.6

1.14

0.0028

0.0071

7747.8

1.32

0.0012

Gas window

0.0073

6559.8

1.37

0.0017

0.5

Oil window

0.0109

6687.5

1.41

0.0000

0.5

Oil window

0.0095

6572.2

1.44

0.0005

3

(wt %)

(%)

Maturity

(cm /g)

(J/mol)

CN_11

4.83

2.8

Gas window

0.0081

Sichuan

CN_23

2.92

2.8

Gas window

shale

CN_22

2.87

2.8

Gas window

CN_32

0.89

2.8

WIC_143

14.1

WIC_149

11.7

Posidonia shale a

Barnett shale b

a

Sample

HAR_038

9.3

0.9

Oil window

0.0089

4930.7

1.15

0.0011

HAD_103

6.7

1.5

Gas window

0.0091

7159.4

1.38

0.0010

HAD_115

7.7

1.5

Gas window

0.0095

7243.1

1.50

0.0009

HAD_119

7.7

1.5

Gas window

0.0142

5689.9

1.23

0.0016

HAD_123

10.5

1.5

Gas window

0.0117

7116.2

1.47

0.0010

Lee C-5-1

7.9

0.58

Oil window

0.0073

7806.4

1.95

0.0000

Tarrant A-3

7.05

0.81

Oil window

0.0071

7476.7

1.75

0.0000

Blakely #1

6.6

2.01

Gas window

0.0106

7414.3

1.42

0.0016

Smectite

0.0

-

-

0.0186

8881.5

1.99

0.0003

Clay

Illite

0.0

-

-

0.0111

4490.0

1.27

0.0038

mineral c

Kaolinite

0.0

-

-

0.0078

5639.6

1.43

0.0002

Chlorite

0.0

-

-

0.0079

5832.1

1.66

0.0024

Methane sorption data of the Posidonia shales were from Gasparik et al. [9]; b. Methane sorption data of Barnett

shales were from Zhang et al. [6]; c. Methane sorption data of the clay minerals were from Ji et al. [7].

32


Supercritical Methane Sorption on Organic-Rich Shales over a Wide

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