Nanoscale pore structure heterogeneity and its quantitative characterization in Chang7 lacustrine shale of the southeastern Ordos Basin, China

Journal Pre-proof Nanoscale pore structure heterogeneity and its quantitative characterization in Chang7 lacustrine shale of the southeastern Ordos Basin, China Changan Shan, Weiwei Zhao, Fengqin Wang, Kun Zhang, Zhao Feng, Liulinbo Guo, Xueli Ma, Tian Liao PII:

S0920-4105(19)31173-8

DOI:

https://doi.org/10.1016/j.petrol.2019.106754

Reference:

PETROL 106754

To appear in:

Journal of Petroleum Science and Engineering

Received Date: 27 June 2019 Revised Date:

16 October 2019

Accepted Date: 28 November 2019

Please cite this article as: Shan, C., Zhao, W., Wang, F., Zhang, K., Feng, Z., Guo, L., Ma, X., Liao, T., Nanoscale pore structure heterogeneity and its quantitative characterization in Chang7 lacustrine shale of the southeastern Ordos Basin, China, Journal of Petroleum Science and Engineering (2019), doi: https://doi.org/10.1016/j.petrol.2019.106754. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier B.V.

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Nanoscale pore structure heterogeneity and its quantitative

2

characterization in Chang7 lacustrine shale of the southeastern

3

Ordos Basin, China

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Changan Shana,b,c*, Weiwei Zhaoa,c, Fengqin Wanga,c, Kun Zhangd, Zhao Fenga,

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Liulinbo Guoa, Xueli Maa, Tian Liaoa

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a

7

b

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of

8 9

School of Earth Sciences and Engineering, Xi’an Shiyou University, Xi’an 710065, China

Technology), Chengdu 610059, China c

Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi’an Shiyou University, Xi’an 710065,

10

China

11

d

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* Corresponding author. Tel.: +86 15829664235; E-mail address: [email protected] (C. Shan)

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Abstract

Shool of Geoscience and Technology, Southwest Petroleum University, Chengdu, 610500, China

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To gain a better understanding of nanoscale pore structure characteristics in

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Chang7 lacustrine shale, Ordos Basin, China, 33 shale samples from 15 wells are

16

examined and analyzed by total organic carbon (TOC), X-ray diffraction (XRD),

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mercury porosimetry, helium pycnometry, low-pressure N2 adsorption experiments

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and fractal method. The results show that Chang7 lacustrine shale pores diameter is

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mainly from 1.5 to 5 nm, and mesopores give the largest contribution to the total pore

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specific surface area (SBET) and volume (VBJH), and micropores have the second

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contribution to SBET but little contribution to VBJH, macropores have very little

22

contribution to SBET but make a good contribution to VBJH. According to the

23

occurrence and origin of shale pores, micro-pores can be divided into mineral

24

intragranular pore, minera intercrystalline pore and organic pore. Two fractal 1

25

dimensions (D1 and D2) are obtained from N2 adsorption isotherms analysis using

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FHH method. Relationships between fractal dimensions and shale compositions, pore

27

structure parameters are investigated, which show that both D1 and D2 have good

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positive relationships with SBET and VBJH, but obvious negative correlations with the

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average pore diameter. That is, the smaller the pore diameter, the more complex the

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pore structure is, resulting in the larger pore surface and volume. D1 and D2 are both

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positively correlated with total clay, illite, mixed-layer of illite-smectite, whereas no

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obvious relationships with chlorite, indicating that the layer and flocculent structure

33

increase the complexity of nanoscale pore structure. TOC content has positive

34

correlation with D1 but no obvious relationship with D2, indicating that the pores in

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organic matter are mostly micropores. Fractal dimensions are negatively correlated

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with total brittle mineral, quartz and feldspar content, that is because the surface of

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brittle minerals is smoother and more homogenous than that of clay minerals.

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Keywords

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Nanoscale pore structure heterogeneity; Quantitative characterization; Chang7

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lacustrine shale; Fractal characteristic.

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1. Introduction

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Shale gas has typical characteristics of self-generation, self-storage, and

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near-in-situ accumulation (Jarvie et al., 2007). Shale reservoir is characterized by

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coexistence of adsorption gas and free gas, ultra-low porosity and permeability, and

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serious heterogeneity (Bustin et al., 2008; Clarkson et al., 2012; Han et al., 2016). As an

46

important index to measure and evaluate shale gas reservoir, pore characteristics have

2

47

been widely studied by many researchers (Wang et al., 2014b; Lei et al., 2015; Jiang et al.,

48

2016; Sun et al., 2017). The pore size of shale reservoir is very small and the pore

49

structure is also complex, and it is difficult to observe the pore system through

50

traditional sample preparation methods(Yang et al., 2017a; Ke et al., 2018). Due to the

51

lack of research methods, the study of nanoscale pore structure and network

52

characteristics has become the research focus and difficulty of shale gas geology (Han

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et al., 2018; Li et al., 2018). Pore type, morphological characteristic, pore quantitative

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parameters, connectivity are the key factors affecting the accumulation, occurrence

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and migration of shale gas, and are also the basic contents of studying shale reservoir

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(Chalmers et al., 2012; Chen et al., 2014; Liu et al., 2017). Beyond that, shale reservoirs are

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also characterized by significant microscopic heterogeneity, which has control effect

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on shale gas productivity. Shale reservoir microscopic heterogeneity manifestations

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include: 1) the types and spatial distribution of mineral components are heterogeneous

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and controlled by sedimentation and diagenesis; 2) the occurrence characteristics of

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organic matter and the characteristics of organic matter itself have certain

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heterogeneity; 3) the type, morphology and distribution of micro-pores are

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significantly heterogeneous (Zhao et al., 2018). As we know, it is of great significance to

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study the nanoscale pore structure of shale gas reservoir for evaluating shale gas

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resources and understanding the reservoir forming mechanism, so the heterogeneity

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also needs to be further studied on the nanoscale pores in a more detailed and

67

quantitative way (Guo et al., 2015).

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Currently, previous researchers have carried out many studies on describing the

3

69

heterogeneity in shale pore structure, adsorption and so on (Yeh et al., 1986; Ross et al.,

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2009; Wang et al., 2016 c; Pang et al., 2018). However, due to the limitations of study scale

71

and quantification degree, the research on the characteristics of microscopic

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heterogeneity, especially the nanoscale pore structure heterogeneity is still in the

73

initial stage (Ross et al., 2009; Wang et al., 2016b). As for Chang7 lacustrine shale

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reservoir in Ordos Basin, China, the sedimentology and heterogeneity of lithology,

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geochemical parameters, micro-pore structure and physical parameters have been

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analyzed on the basis of core observation, thin section observation, pulse permeability

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test, organic carbon content test, gas composition analysis and logging interpretation

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results by many researchers(Qiu et al., 2015a;Yang et al., 2014a; Wang et al.,2016c;

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Yang et al., 2017b and c; Fan et al., 2018 . In addition, petrographic and geochemical

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characteristics, development mode, characteristics of silty laminae, pore characteristic,

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CH4 adsorption capacity Chang7 lacustrine shale gas reservoir have been studied by

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many previous researchers (Guo et al., 2014; Ji et al., 2014; Qiu et al., 2015b; Yang et al.,

83

2015; Lei et al., 2015; Wang et al., 2017;). However, there is still a lack of further in-depth

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study on the key evaluation parameters of nanoscale pore heterogeneity, evaluation

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methods of nanoscale pore heterogeneity, and the relationship between heterogeneity

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and shale gas geological parameters. Therefore, nanoscale pore structure

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heterogeneity, quantitative parameters characterization, and relationships between

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heterogeneity and geological parameters will be studied in this paper.

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2. Geological setting

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The Ordos Basin is located in the central part of China, which is a stable craton

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basin with complete stratigraphic development and weak deformation. Except for the 4

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marginal areas, the fault structure and local uplift are not very developed. According

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to the present tectonic pattern, the basin is divided into six structural units, namely,

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Yimeng uplift, Weibei uplift, Jinxi flexure belt, Yishan slope, and Tianhuan

95

depression and Western margin thrust belt (Fig. 1a)(Wang et al., 2016a). Of these

96

units, the Yishan slope is currently a major area of oil and gas production, which is a

97

west-dipping monocline with a 1 to 3 degree dip angle that has very few seismically

98

identifiable faults and local low-relief folds (Wang and Wang, 2013; Li et al., 2017).

99

The study area in this paper is located on the southern Yishan slope (Fig. 1b).

100

The Archean Eonothem and Paleoproterozoic basement of the Ordos Basin has

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undergone five evolutionary stages (Jiang et al., 2013b): 1) Mesoe Neoproterozoic

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aulacogen; 2) Early Paleozoic shallow marine platform; 3) Late Paleozoic strand plain;

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4) Mesozoic inland depression; 5) Cenozoic fault depression (Fig. 1c). Multi-cyclic

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fluvial and terrestrial clastic rocks were deposited in the Ordos Basin from the late

105

Triassic to the end of cretaceous, and the original sediments were as thick as

106

3000~4000m (Chen et al., 2006). The Triassic Yanchang Formation deposition were

107

experienced four stages of uplift and denudation: 1) Late Triassic, 2) Early Jurassic, 3)

108

Late Jurassic and 4) Late cretaceous, and the cumulative denudation thickness was

109

about 1800-2400m (Chen et al., 2006). The Yanchang Formation can be divided into

110

10 members, recording a complete cycle of lacustrine basin initiation, development

111

and cessation (Fig. 2). Chang7 sedimentation is the maximum expansion period of the

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lake basin, most areas of which belong to freshwater to brackish water environment,

113

indicating the semi-deep to deep lacustrine facies (Zhang et al., 2008; Qiu et al., 2014),

5

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and large numbers of aquatic organism and plankton multiply in the deep water(Wang

115

et al., 2008), forming the main source rock sedimentary strata in Ordos Basin. At the

116

bottom of the Chang7 member, the widespread and organic-rich source rock was

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deposited in the whole basin, the thickness of which is mainly between 30m and

118

100m (Jiang et al., 2013b). The lithology mainly consists of thick deep-gray,

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gray-black shale, carbonaceous shale, thin layer argillaceous siltstone, silty mudstone

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and siltstone. The organic matter of Chang7 lacustrine shale is mainly type I and II,

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and the peak of chloroform asphalt "A" is 0.10%~1.72%, the hydrogen index is

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generally 50~255 mg

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from 418°C to 474°C, Ro is between 0.7% and 1.3% (Wang et al., 2014a; Xu et al.,

124

2009; Liu et al., 2012; Guo et al., 2014; Yang et al., 2012).

125

3. Samples and methods

HC/g TOC,

S1 is 0.03~9.6 mg/g and S2 is 0.1~23.4mg/g, Tmax is

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33 shale samples of the Chang7 member from 15 wells in the southeastern Ordos

127

Basin, China (Fig. 1), and all samples are from depths of 517.39~1857.60 m. For our

128

studies of shale nanoscale pore structure and its heterogeneity, all 33 samples firstly

129

were examined using X-ray diffraction (XRD) analysis. Among these samples, 14

130

samples were tested for helium porosity and pulse permeability, 12 samples were

131

tested for total organic carbon (TOC) content, 4 samples for mercury injection, and 17

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samples for low-pressure N2 adsorption/desorption experiments.

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XRD analysis: Shale samples were first ground into powder with 200 mesh, then

134

dry for 5 hours under 50°C, and then XRD analysis was performed on a BRUKER D8

135

ADV ANCE X-ray diffractometer under 40 kV voltage and 30 mA operating current,

6

136

and the scan range is 3°~85°, 1mm of the slit with the scanning speed 4/min. The

137

TOC content, porosity and permeability were measured following the methods by

138

Yang et al. (2014). Mercury injection capillary pressure curves were tested according

139

to the China National standards (GB/T21650.1-2008), at emperature of 21°C,

140

humidity 38%, atmospheric pressure 1027 hPa. The low-pressure N2 adsorption/

141

desorption experiment method can be seen our previous study (Shan et al., 2018).

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4. Results

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4.1. Mineralogy and TOC

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XRD quantitative results of 33 Chang7 lacustrine shale core samples in the study

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area can be seen in Table 1, Fig. 3a,b and Fig.4a,b, which shows that the Chang7

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shale mainly consists of clay, quartz and feldspar. Total clay content ranges from 20%

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to 66% (averages at 45.67%), with mixed layers of illite-smectite being the most

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abundant (from 30% to 77%, averages at 48.55%), in which the content of smectite is

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low (15%~30%), followed by illite (from 11% to 48%, averages at 28.52%) and

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chlorite (from 6% to 48%, averages at 21.09%). Quartz abundance is between 18%

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and 40%, averages at 31.06%; feldspar is mainly composed of plagioclase (from 5%

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to 39%, averages at 14.69%) and potassium feldspar (from 2% to 10%, averages at

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4.52%). In addition, some samples contain small amount of kaolinite, pyrite and

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carbonate minerals such as calcite, dolomite, pyrite and siderite. High content of

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brittle minerals in shale is beneficial to produce natural and induced cracks under the

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action of external forces. The TOC and TS content Chang7 shale are both high, TOC

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ranges from 1.65% to 6.37% (averages at 3.37%). TS content is between 0.06% and

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0.92%, averages at 0.36% (Table 1). 7

159 160

4.2. Helium porosity and pulse permeability Porosity and permeability of 14 shale core samples were tested in this study by porosimeter

and

ULTRA-PERMTM200

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Ultrapore-200A helium

permeameter,

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respectively (Table 2). The porosity of all samples ranges from 0.2% to 1.7% and

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average at 0.94%. The permeability is from 0.0047 mD to 6.72 mD with an average of

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0.8106 mD. Cracks of five cylindrical samples were produced during the experiment

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process, increasing the permeability values. Exclude these five samples, the measured

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permeability ranges from 0.0047 mD to 0.0121 mD (averages at 0.0074 mD). These

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results show that the shale reservoir in the Chang7 Formation is characterized by

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ultra-low porosity and permeability. There is no obvious correlation between

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permeability and porosity of all samples (Fig. 5a), but permeability is positively

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correlated with porosity after excluding these five samples with cracks (R2=0.8957)

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(Fig. 5b). Thus, we can know that shale reservoir porosity has a good positive

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relationship with the original permeability, but do not increases with increasing

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permeability which acquired by late structural activity or human factors, such as

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hydraulic fracturing in shale reservoir.

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4.3. Physical characteristics by mercury intrusion method

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The morphology of mercury injection curves can reflect information of pores

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development and connectivity (Clarkson et al., 2013). On the capillary pressure

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cumulative intrusion curves, the lower the location of the flat section of the curve is,

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the larger the concentrated pore-throat is. And the longer the flat segment, the higher

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percentage of pore-throat concentration. The concentration range and percentage of

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pore-throat radius can reflect the degree of size and sorting. The larger the pore throat

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is, the better the sorting of pore structure is. Displacement pressure refers to the

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pressure when mercury starting to inject into the rock sample in the mercury injection

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experiment, in other words, it is the capillary pressure when the non-wetting phase

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begins to inject into the maximum connected pore throat of the rock sample. That is,

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the smaller the displacement pressure of the rock is, the more number macropore

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throat is.

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The capillary pressure cumulative intrusion curves on 4 samples can be seen in Fig.

189

6, the mercury injection curves of all samples are located in the upper-right area and

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lack the near-horizontal section, and the displacement pressure is 5.08~10.59 MPa

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with an average of 8.395 MPa (Table 2), which indicate that the distribution of

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pore-throat is narrow and the pore connectivity is very poor, making it difficult for

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mercury to access pores. Mercury injection experiment data show that the average

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diameter of shale pore throat is from 30 nm to 70 nm, with a low sorting coefficient of

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0.05~0.07 (Table 2). In addition, the mercury ejection curves show a sudden drop

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phenomenon

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(53.89%~67.81%, averages at 57.89%) (Fig. 6, Table 2). This phenomenon shows

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that mercury fails to completely discharge from the pores system, and approximately

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32.19%~46.11% of mercury is still trapped in the pore network, which indicates that a

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large number of “ink bottle” pores exist in shale samples leading to poor connectivity

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(Shan et al., 2015). This pore structure is beneficial to the accumulation of shale gas,

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but improves the difficulty of the migration of gas.

for all

samples,

showing

9

a inefficient

mercury withdrawal

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Histograms of pore size distribution in mercury injection of four samples are

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illustrated in Fig. 6. The pore size is widely distributed, but pores with diameter less

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than 100 nm account for 86.91%~90.62 % of the total pore volume. However, it

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should be noted that high pressure is destructive to pore structure, and mercury

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injection method is inaccurate for nanoscale pores. Therefore, N2 adsorption method

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is emphasized to explore the characteristics of nanoscale pores structure in this study.

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4.4. Low-pressure N2 adsorption/desorption

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4.4.1. Nanoscale pore geometry by N2 adsorption-desorption isotherms

211

The N2 adsorption isotherms and the relationship between adsorption and

212

desorption isotherms (hysteresis loops) of tight rocks can be used to analyze the pore

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shapes, pore size distribution and the surface properties (Shan et al., 2015). 17

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samples were selected from the 33 samples mentioned above and analyzed by

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low-pressure N2 adsorption-desorption experiment. The shapes of the adsorption

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isotherms and hysteresis loops of these shale samples are shown in Fig. 7. The N2

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adsorption curves of all samples are similar to “S” type. At the relative pressure range

218

0~0.9 P/Po, all adsorption curves of samples fit Henry’s law very well, and the latter

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part (P/Po>0.9) of the adsorption curves rise very more rapidly.

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Hysteresis loops can be divided into 4 types: Types D1, D2, D3 and D4, which

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can be seen in Fig. 8. The hysteresis loops of the LP177-2, LP177-5, X51-1 and

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W169-4 samples belong to the D1 type (Fig. 7). The adsorption and desorption curves

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are overlapped or the distance between them are very short, indicating that the

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semi-closed pores are develpped (Fig. 8). The D2 type shape are shown in DT005-1,

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LP123-1, LP176-1 and L106-5 samples (Fig. 7). The desorption curve shows a

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hysteresis pattern (>0.5 P/Po), then falls suddenly at 0.5 P/Po to overlap the adsorption

227

branch, having an obvious inflection point G, which shows “ink bottle” pores (Fig. 8),

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and the inflection point G corresponds to the bottle necks. The D3 type is represented

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by the DT005-3, LP177-4 and L106-4 samples (Fig. 7). The adsorption and

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desorption curves are separated at all the relative pressure region, reflecting that shale

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nanoscale pores are mainly opened pore (Fig. 8). The D4 type is represented by the

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DT018-1, DT018-2, LP127-1, L106-3, X39-1and W169-5 samples (Fig. 7). The

233

adsorption and desorption curves are separated at the >0.5 P/Po region, indicating that

234

shale nanoscale pores with larger pore size contain opened pores and may some

235

semi-closed pores (Mastalerz et al., 2012).

236

are overlapped, reflecting that smaller pores are mostly semi-closed pores (Fig. 8).

237

4.4.2. Nanoscale pore specific surface area, volume, and size distribution

At the <0.5 P/Po region, the two curves

238

Chang7 shale nanoscale pore quantitative analysis results by low-pressure N2

239

adsorption-desorption experiments can be seen in Table 3. The total specific surface

240

area (SBET) of 17 shale samples ranges from 0.682 m2/g to 3.881 m2/g (averages at

241

1.766 m2/g), and the total specific surface area (SBJH) is 1.048~5.897 m2/g with an

242

average of 2.531 m2/g, which is larger than SBET. The pore volume (VBJH) of all

243

samples ranges from 5×10-3 cm3/g to 13×10-3 cm3/g and averages at 7.9×10-3 cm3/g,

244

showing a good positive relationship with SBET and SBJH (Fig. 9). In addition, the

245

average pore size (dBJH) is from 12.8 nm to 28.1 nm. The N2 adsorption amount

246

ranges from 3.0961 cm3/g to 8.0516 cm3/g and averages at 4.9329 cm3/g of these

11

247

samples, and there are good positive relationships between N2 adsorption amount and

248

SBET, VBJH (Fig. 10).

249

4.5. Fractal dimensions from low-pressure N2 adsorption isotherms

250

Fractal theory has been widely used in many study areas after this concept was

251

proposed by Mandelbrot (1984). Fractal geometry is an important approach to

252

characterize and simulate complex Non-Euclidean shapes, especially the geometrical

253

properties and structural properties of solid surface(Avnir and Jaroniec, 1989). In

254

other words, fractal theory can be used to describe and evaluate irregular pore

255

structure heterogeneity of shale reservoir. Fractal characteristics is generally described

256

by fractal dimension (D), which is a parameter to describe solid surface roughness and

257

the irregularity of structure. D value is generally between 2 and 3, and affected by

258

geometric irregularity and surface roughness (Jaroniec, 1995). The maximum value of

259

3 corresponds to a completely irregular or rough surface, and the minimum value of 2

260

corresponds to a completely smooth surface (Liu et al., 2015). Many mathematical

261

models have been used to calculate D based on gas adsorption isotherms, such as

262

Langmuir model, Frenkele Halseye Hill (FHH) model, BET model and

263

thermodynamic method (Yao et al., 2008; Cai et al., 2013). Previous researches have

264

indicated that the FHH theory among these methods is the most effective (Tang et al.,

265

2016; Shan et al., 2018). The fractal dimension calculation using the FHH model can

266

be seen our previous paper (Shan et al., 2018).

267

The FHH plots of 17 samples are illustrated in Fig. 11. Based on the inflection

268

point of N2 desorption branches are usually 0.5 P/Po and different relative pressure

12

269

corresponds to different pore size, Region 1 (0~0.5 P/Po) and Region 2 (0.5~1 P/Po)

270

are divided and the linear regression equations and correlation coefficients (R2) are

271

shown in Fig. 11 and Table 4. Nearly all correlation coefficients (R12 and R22) of

272

samples are larger than 0.98 (just X51-1 sample: R12 =0.9727, R22 =0.9697),

273

indicating that both of them show good fits. The D1 and D2 values calculated

274

according to Eq. (2) and Eq. (3) are shown in Table 5. D1 and D2 values based on Eq.

275

(2) between 2 and 3, but are smaller than 2 based on Eq. (3), which shows that fractal

276

dimension should be calculated according to the Eq. (2). D1 values ranges from

277

2.1463 to 2.3952 with an average of 2.2916. D2 values is from 2.4765 to 2.6133,

278

averages at 2.5514 (Table 5), which is larger than D1.

279

5. Discussion

280

5.1 Pores genetic types

281 282

Lacustrine shale micro-pores can be divided into three types based on the occurrence and origin of them: mineral intragranular pore, minera intercrystalline pore and organic pore.

283

(1) Mineral intragranular pores

284

Intragranular pores refer to the pores developed in the interior of particles, most of them were

285

formed by transformation in the later stage of diagenesis. Intragranular pores are generally the

286

dissolution pores, which were generated in and on the surface of the quartz, feldspar and carbonate

287

particles by the dissolution of acidic fluid. Under the microscope, it was observed that the pores

288

were widely distributed on the surface of feldspar and pyrite crystals (Fig. 12a and b).

289

The mineral composition of Chang7 shale is mainly clay mineral, and the content of rigid

290

grain mineral is low. The clay minerals with poor chemical stability are easily converted into the

13

291

mixed layer of illite/smectite or illite during the diagenesis process, during which a large number

292

of mineral pores are formed in the clay aggregate (Fig. 12c). The connectivity of these clay

293

mineral pores are the important storage space and migration channel for shale gas. Intragranular

294

pores of quartz grains are occasionally developed in continental shale reservoirs, with poor pore

295

connectivity, and little impact on the formation of shale gas (Fig. 12d).

296

(2) Mineral intercrystalline pore

297

Compared with Marine shale, the content of rigid particle minerals such as quartz and

298

feldspar is relatively less, while the content of clay minerals is relatively more. Rigid granular

299

minerals are often scattered embedded in clay minerals and organic matter. Intergranular pores are

300

poorly developed, mainly existing between brittle mineral particles and clay minerals (Fig. 12e).

301

Pyrite intercrystalline pores are widely developed in lacustrine shale (Fig. 12b and f). Pyrite

302

clumps are sometimes strongly dissolved and locally filled with organic matter, and organic matter

303

is associated with the inclusion of pyrite particles. The pores between the particles and organic

304

matter are widely developed, and the pore connectivity is good, which is conducive to the

305

formation and accumulation of shale gas.

306

(3) Organic pores

307

Besides maturity and organic carbon content, organic matter pore development is closely

308

related to organic matter type, the characteristics of organic pores between solid bitumen and

309

kerogen are quite different. Thus, the organic matter pores are further divided into kerogen pores

310

(Fig. 12g, h and i) and bitumen pores (Fig. 12j and k). Organic matter pores in kerogen were

311

relatively undeveloped in general, or no organic matter pores were visible to the naked eye, or a

312

small number of isolated organic matter pores were developed. Organic matter pores in a small

14

313

number of kerogen were relatively developed, and some fractures were also observed in some

314

kerogen (Fig. 12d). The organic pores in kerogen are mostly isolated, and some of them are

315

elliptic and elongated. In general, the organic pores in bitumen are relatively developed. The

316

bitumen pores are oval, round, irregular and polygonal, and most of them are honeycomb and

317

spongy in groups. Some adjacent organic matter pores are interconnected to form large pores with

318

complex

internal structure.

319 320

5.2. Contribution of micropores, mesopores, and macropores to SBJH and VBJH

321

The plots of SBJH and VBJH with respect to BJH pore diameter of shale are shown

322

in Fig. 13, which show that pores with diameter 1.5~5 nm make the major

323

contribution to the total pore surface area and pore volume. In other words, Chang7

324

lacustrine shale has the largest number of micropores and mesopores with size smaller

325

than 5 nm in all pores. A further discussion of the contribution of micropores (<2 nm),

326

mesopores (2~50 nm), and macropores (>50 nm) to the total SBJH and total VBJH is

327

conducted from N2 adsorption-desorption experiments, which can be seen in Table 6

328

and Fig. 14. The average SBJH values of three type pores in 17 shale samples are 0.474

329

m2/g (micropores, 0.003~0.900 m2/g), 2.024 m2/g (mesopores, 0.477~5.815 m2/g),

330

and 0.034 m2/g (macropores, 0.018~0.059 m2/g), respectively. The average

331

contribution of micropores, mesopores, and macropores to the total SBJH are 23.65%,

332

74.88% and 1.47%, respectively (Fig. 15a). In addition, the average VBJH values of

333

three type pores are 0.318×10-3cm3/g (micropores, 0.003×10-3~ 0.808×10-3cm3/g),

334

5.718×10-3 cm3/g (mesopores, 2.761×10-3~11.208×10-3 cm3/g), and 1.887×10-3 cm3/g

335

(macropores,

1.228×10-3~3.536×10-3

cm3/g),

15

respectively.

And

the

average

336

contribution of micropores, mesopores, and macropores to the total VBJH are 4.43%,

337

71.74% and 24.43%, respectively (Fig. 15b).

338

To sum up, the total pore specific surface area mainly depends on the number of

339

mesopores (74.88%), followed by the micropores (23.65 %). The average contribution

340

rate of the two types to total pore specific surface area can reach 98.53 %, which has

341

little relationship with macropores. The pore type with the largest contribution rate to

342

the total pore volume is also mesopores, with an average value of 71.4%. Macropores

343

give the 24.43% contribution rate to the total pore volume although the numbers of

344

which are low, and Chang7 shale has a number of micropores but contributes 4.43%

345

pore volume, that is because the pore volume of each micropore is very small but each

346

macropore is large.

347

5.3. Relationships between fractal dimensions and pore structure parameters

348

Relationships between fractal dimensions and pore specific surface, pore volume,

349

and pore size of marine and lacustrine shale in other areas have been discussed by

350

many researches (Yang et al., 2014b; Zhao et al., 2014; Wang et al., 2015; Liu et al.,

351

2015; Shao et al., 2017). All studies have shown that the fractal dimensions have the

352

positive correlation with the total specific surface area, but the conclusions about the

353

relationship between the fractal dimension and total pore volume are not consistent.

354

Wang et al. (2015) showed that there is a slight positive relationship between them of

355

Upper Cretaceous lacustrine shale from the Songliao Basin, NE China, but the

356

opposite conclusion of Longmaxi marine shale in Chongqing area obtained by Zhao et

357

al. (2014).

16

358

Based on different understandings, relationships between D1, D2 and SBET, VBJH,

359

dBJH of Chang7 lacustrine shale in the study area are discussed in this paper (Fig. 16

360

and Fig. 17). There are good correlations between D1, D2 and SBET (Fig. 16a and Fig.

361

17a), that is, shale with larger specific surface area always has larger fractal

362

dimensions. There is also an obvious positive relationship between D1, D2 and VBJH

363

of Chang7 shale samples, respectively (Fig. 16b and Fig. 17b), and both correlation

364

coefficient (R2) are similar and larger than 4, indicating that pore volume has the

365

obvious influence on fractal characteristics. In addition, both D1 and D2 increase with

366

the increasing of N2 adsorption amount, which can be seen in Fig. 16c and Fig. 17c.

367

There are good negative correlations between D1, D2 and pore diameter, which can

368

be seen in Fig. 16d and Fig. 17d, which is consistent with conclusions documented by

369

other researchers (Yang et al., 2014b; Wang et al., 2015).

370

Linear regression equations in Fig. 16 and Fig. 17 show that correlation

371

coefficients of D2 with SBET (R2=0.6353) and dBJH (R2=0.8705) are both higher than

372

that of D1 with SBET (R2=0.415) and dBJH (R2=0.5254), and the D2 increasing rate

373

with the increase of SBET and the D2 decreasing rate with the increase of dBJH are both

374

faster than D1, indicating that D2 may better represent the surface fractal dimension

375

and pore size.

376

5.4. Relationships between fractal dimensions and clay mineral compositions

377

The clay mineral is the highest composition in all shale samples, and the average

378

clay content reaches to 45.67 % (Table 1), therefore, the study of influences of clay

379

mineral compositions on pore structure is very important. Relationships between D1,

17

380

D2 and total clay minerals and all kinds of clay mineralogical compositions are

381

discussed in this paper, which are shown in Fig. 18 and Fig. 19. Both of D1 and D2

382

show the positive correlations with the total clay mineral content (Fig. 18a and Fig.

383

19a), that is, fractal dimensions increase with the increasing of clay mineral content.

384

Clay minerals mainly include the mixed layers of illite–smectite (averages at

385

48.55 %), illite (averages at 28.52 %), and chlorite (averages at 21.09 %). In order to

386

understand the effect of every kind clay composition on fractal characteristics, all

387

correlations betweenD1, D2 and the mixed layers of illite–smectite, illite and chlorite

388

contents are further plotted in Fig. 18 and Fig. 19. D1 and D2 are positively correlated

389

with the mixed layers of illite–smectite and illite contents, but no obvious correlation

390

(Fig. 18b) or has a weakly negative relationship with chlorite (Fig. 19b). Compared

391

with illite content, the positive correlations between the mixed layers of illite–smectite

392

and D1, D2 are more obvious, which indicate that layer structure has higher

393

heterogeneity and specific surface area than flocculent structure. For the mixed layers

394

of illite–smectite, relationships between D1, D2 and the relative content of illite and

395

smectite were further discussed in Fig. 18e-f and Fig. 19e-f, which shows that illite

396

has better correlation with fractal dimensions than smectite, indicating that illite has

397

the the higher heterogeneity than smectite. No obvious relationship between D1 and

398

chlorite shows that chlorite minerals have very few micropores (Fig. 18b). However,

399

A weakly negative correlation between D2 and chlorite content is showing in Fig. 19b,

400

which can be predicted that chlorite minerals have some mesopores or macropores,

401

and the relatively smooth pores surface causes the fractal dimension (D2) to decrease

18

402

as the increasing of these pores number. Thus it can be seen that the order of pore

403

structure heterogeneity of four kinds clay minerals: the mixed layers of illite–

404

smectite> illite> smectite> chlorite.

405

5.5. Relationships between fractal dimensions and brittle mineral compositions

406

As shown in Fig. 20a and Fig. 21a, D1 and D2 decrease with the increase of total

407

brittle minerals, quartz and feldspar content, respectively. That is, the smooth surface

408

of quartz and feldspar suggests that brittle minerals in Chang7 lacustrine shale can

409

play a role on reducing the heterogeneity of pore structure. However, D2 has better

410

relationship with quartz than D1 (Fig. 20b and Fig. 21b), indicating that micropores

411

are not developed in quartz minerals. The correlation coefficients of D1and D2 with

412

the total feldspar content are similar and relatively high (Fig. 20c and Fig. 21c),

413

showing that feldspar minerals contain some micropores. That is because organic

414

matter in shale released a large amount of organic acids during thermal evolution,

415

feldspar is more likely to be dissolved and form secondary pores than quartz. In

416

addition, feldspar dissolves in contact with water and changes into clay mineral under

417

the condition of acidic medium, forming a lot of pores. Feldspar of Chang7 lacustrine

418

shale comprise plagioclase and potash feldspar, and relationships between fractal

419

dimensions (D1, D2) and plagioclase, potash feldspar are shown in Fig. 20d-e and Fig.

420

21d-e, showing that there are better correlations between fractal dimensions and

421

plagioclase than potash feldspar. Thus, it can be predicted that plagioclase can

422

produce more nanoscale pores than potash feldspar during the process of feldspar

423

changes into clay mineral.

19

424

5.6. Relationships between fractal dimensions and TOC content

425

Besides clay minerals and brittle minerals, a small amount of organic matter is

426

also an important component of shale. Loucks et al. (2009) indicated that Barnett

427

shale pores were mainly at the nano-level, and most of the nanoscale pores are related

428

to organic matter particles. In the process of thermal maturation and transformation of

429

convertible organic carbon, the decomposition of organic matter leads to the

430

generation of hydrocarbons, and the nanoscale pores were generated at the same time.

431

The improvement of thermal evolution degree promotes the continuous generation of

432

organic acids, CO2, H2S and other acidic fluids of organic matter to dissolve carbonate

433

rocks and feldspar, so as to improve the porosity of shale. Jarvie et al. (2007) reported

434

that 4.9% pores were increased when 35% organic carbon was consumed in the

435

process of hydrocarbon generation for shale sample with TOC of 7.0%. In addition,

436

Jarvie et al. (2007) indicated that shale with TOC of 6.41% can produce 4.3% pores

437

volume when it reaches the dry gas window. Behar and Vandenbroucke (1987) found

438

that shale pores with size of 5~50 nm depends on kerogen type.

439

TOC content is positively correlated with D1 (Fig. 22a) but has no apparent

440

relationship with D2 (Fig. 22b). This phenomenon is consistent with the result

441

documented by Yang et al. (2014), but is opposite with the study conclusions by Wang

442

et al. (2015) and Li et al. (2016). For the Upper Cretaceous lacustrine shale from the

443

Songliao Basin, NE China, Wang et al. (2015) showed that the relationship between

444

D1, D2 and TOC content is characterized by a U-shaped curve, with minimum D

445

values at 2.5%~3 % TOC content. Li et al. (2016) indicted that D1 and D2 are both

20

446

positively correlated with TOC values.40 It can be seen that the relationship between

447

the TOC content and fractal dimension of shale in different regions is not same. In this

448

study, Chang7 shale samples with higher TOC content always have the greater D1 but

449

D2 values, which can be predicated that the average pore size of organic pores in

450

organic matter is much smaller than that of inorganic matter. the dominant factor

451

influencing D1 may be the volume of micropores.

452

6. Conclusions

453

A lot of experiments (e.g. X-ray diffraction ,mercury porosimetry, helium

454

pycnometry total organic carbon and low-pressure N2 adsorption experiments) and

455

the fractal theory are carried on several Chang7 lacustrine shale core samples in

456

southestern Ordos Basin, China, to study nanoscale pore structure heterogeneity and

457

its quantitative characteristics. Two fractal dimensions (D1: 0

458

0.5

459

fractal Frenkele HalseyeHill (FHH) method. Furthermore, the relationships between

460

D1, D2 and pore structure parameters (pore specific surface area, volume, diameter),

461

clay minerals, brittle minerals and TOC content were discussed. The following

462

conclusions were obtained from the results.

463

(1) Chang7 lacustrine shale has the largest number of pores with diameter from

464

1.5 to 5 nm. Mesopores (2~50 nm) give the major contribution to the total pore

465

specific surface area (SBET) (74.88%) and volume (VBJH) (71.4%), micropores (<2 nm)

466

have the 23.65% contribution rate to SBET but only 4.43% contribution rate toVBJH,

467

and macropores (<50 nm) have the only 1.47% contribution rate to SBET but make a

21

468

good contribution only 24.43% contribution rate toVBJH.

469

(2) Fractal dimension D1 ranges from 2.1463 to 2.3952 with an average of

470

2.2916, and D2 is from 2.465 to 2.6133 with an average of 2.5514. The average value

471

of D2>D1 indicates that pores with diameter larger than 2.76 nm have higher pore

472

structure heterogeneity than smaller pores (<2.76 nm).

473

(3) Both D1 and D2 have good positive relationships with SBET and VBJH, and

474

obvious negative correlations with the average pore diameter. These findings suggest

475

that the smaller the pore diameter, the more complex the pore structure (the stronger

476

the heterogeneity), and the larger the pore surface and volume.

477

(4) D1 and D2 are both positively correlated with total clay, illite, mixed-layer of

478

illite and smectite, whereas no obvious relationship with the chlorite content. Both D1

479

and D2 are negatively correlated with the total brittle mineral, quartz and feldspar

480

content, indicating that the surface of brittle mineral grain is smoother and more

481

homogenous than organic matter and clay minerals

482

(5) TOC content has positive correlation with D1 but no apparent relationship

483

with D2, indicating that the pores in organic matter are mostly micropores, and the

484

higher TOC content is, the more complicated and heterogeneous micropore structure

485

would be.

486

Acknowledgements

487

This research was jointly supported by the Open Fund of State Key Laboratory

488

of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of

489

Technology) (Grant No. PLC20190503), Natural Science Basic Research Plan in

22

490

Shaanxi Province of China (Grant No. 2019JQ-100), Scientific Research Program

491

Funded by Shaanxi Provincial Education Department (Program No.18JK620), the

492

National science and technology major project (2017ZX05039001-002), the National

493

Natural Science Foundation of China (Grant No. 41702127, 41772150, 41372148 and

494

41804125).

495

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Wang, X.J., Wang, Z.X., Liu, X.Y., Zeng, J.H., 2008. Restoring Palaeo-depth of the Ordos Basin by using uranium

response From GR logging. Natural Gas Industry, 28, 46-48. (In Chinese with English Abstract).

Wang, X.Z., Gao, S.L., Gao, C., 2014a. Geological features of Mesozonic continental shale gas in south of Ordos

28

622 623 624

Basin, NW China. Petroleum Exploration and Development, 41, 294-304.

Wang, X.Z., Zhang, L.X., Gao, C., 2016c. The heterogeneity of shale gas reservoir in the Yanchang Formation

Xiasiwan Ordos Basin area. Earth Science Frontiers, 23, 134-145.

625

Wang, X.Z., Zhang, L.X., Li, Z.T., Fu, H.J., 2016d. Pore type classification scheme for continental Yanchang shale

626

in Ordos Basin and its geological significance. Oil & Gas Geology, 37, 1-7. (In Chinese with English Abstract).

627

Wang, X.Z., Zhang, L.X., Lei, Y.H., Yu, Y.X., Jiang, C.F., Luo, X.R., Gao, C., Yin, J.T., Cheng, M., 2018.

628

Characteristics of migrated solid organic matters and organic pores in low maturity Lacustrine shale: a case

629

study of the shale in Chang7 oil - bearing formation of Yanchang Formation, southeastern Ordos Basin. Acta

630

Petrolei Sinica, 39, 141-150. (In Chinese with English Abstract).

631

Wang, Y., Zhu, Y.M., Chen, S.B., Li, W., 2014b. Characteristics of the Nanoscale Pore Structure in Northwestern

632

Hunan Shale Gas Reservoirs Using Field Emission Scanning Electron Microscopy, High-Pressure Mercury

633

Intrusion, and Gas Adsorption. Energy and Fuels, 28, 945−955.

634 635 636 637 638 639 640 641

Xu, S.L., Bao, S.J., 2009. Preliminary analysis of shale gas resource Potential and favourable areas in Ordos Basin.

Natural Gas Geoscience, 20, 460-465. (In Chinese with English Abstract).

Xu, S.Q., Zhou, Z.J., Yu, G.G., Wang, F.H., 2010. Effects of pyrolysis on the pore structure of four Chinese coals.

Energy and Fuels, 24, 1114–1123.

Yang, R.C., He, Z.L., Qiu, G.Q., Jin, Z.J., Sun, D.S., Jin, X.H., 2014a. A Late Triassic gravity flow depositional

system in the southern Ordos Basin. Petroleum Exploration and Development, 41, 724-733.

Yang, F., Ning, Z.F., Liu, H.Q., 2014b. Fractal characteristics of shales from a shale gas reservoir in the Sichuan

Basin, China. Fuel, 115, 378–384.

642

Yang, H., Fu, J.H., He, H.Q., Liu, X.Y., Zhang, Z.Y., Deng, X.Q., 2012. Formation and distribution of large low-

643

permeability lithologic oil regions in Huaqing, Ordos Basin. Petroleum Exploration and Development, 39,

29

644 645 646 647 648

683-691. (In Chinese with English Abstract).

Yang, J.J., 2002. Structural evolution and oil and gas distribution of Ordos Basin. Beijing, Petroleum Industry

Press, 20–245.

Yang, R., He, S., Hu, Q.H., Sun, M.D., Hu, D.F., Yi, J.Z., 2017a. Applying SANS technique to characterize

nano-scale pore structure of Longmaxi shale, Sichuan Basin (China). Fuel, 197, 91-99.

649

Yang, R.C., Jin, Z.J., Loon, T.V., Han, Z.Z., Fan, A.P., 2017b. Climatic and tectonic controls of lacustrine

650

hyperpycnite origination in the Late Triassic Ordos Basin, central China: Implications for unconventional

651

petroleum development. AAPG Bulletin, 101, 95-117.

652

Yang, Y.T., Liang, C., Zhang, J.C., Jiang, Z.X., Tang, X., 2015. A developmental model of lacustrine shale gas

653

genesis: A case from T3y7 shale in the Ordos Basin, China. Journal of Natural Gas Science and Engineering, 22,

654

395-405

655

Yao, Y.B., Liu, D.M., Tang, D.Z., Tang, S., Huang, W., 2008. Fractal characterization of adsorption-pores of coals

656

from North China: an investigation on CH4 adsorption capacity of coals. International Journal of Coal Geology,

657

73, 27-42.

658 659

Yeh, N.,

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Devonian shale and Austin Chalk reservoirs. Journal of Energy Resources Technology, 108, 120-130.

660

Zhao, D.F., Guo, Y.H., Xie, D.L., Su, C., Yang, Y.J., Yu, Y.F., 2014. Fractal characteristics of shale reservoir pores

661

based on nitrogen adsorption. Journal of Northeast Petroleum University, 38, 100-108. (In Chinese with

662

English Abstract).

663

Zhao, D.F., Guo, Y.H., Zhu, Y.M., Wang, G., Chong, X., Hu, X., 2018. Analysis of micro-scale heterogeneity

664

characteristics in marine shale gas Reservoir: Pore heterogeneity and its quantitative characterization. Journal of

665

China University of Mining & Technology, 47, 296-307. (In Chinese with English Abstract).

30

666 667

Fig. 1. (a)Tectonic map of the Ordos Basin, and the study area location; (b) Distribution of the

668

study wells and shale samples in the study area; (c) Stratigraphic column of the study area

669

(modified after Yang et al., 2015).

670

Fig. 2. Chart showing chrono- and litho-stratigraphy, lithology, sedimentary environments, and

671

occurrences of shales in the southern area of the Yishan slope of Ordos Basin, central China

672

(modified after Lei et al., 2015). Shale is mainly developed in the lower part of Chang7 (Chang73).

673 674

Fig.3. Mineral compositions bar chart of Chang7 lacustrine shale samples: (a) Total rock mineral

675

compositions bar charts ; (b) Clay mineral compositions bar charts .

676

Fig. 4. Triangular diagram of mineral compositions of Chang7 lacustrine shale samples: (a)

677

mineral compositions; (b) clay mineral compositions.

678 679

Fig. 5. The relationship between permeability and porosity of Chang7 shale reservoir: (a) The

680

relationship between permeability and porosity of 14 samples (Cracks were produced during the

681

experiment of 5 cylindrical samples); (b) The relationship between permeability and porosity of 8

682

samples (Exclude 5 samples with cracks produced during the experiment).

683

Fig. 6. Mercury injection-withdrawal capillary pressure curves and histograms of pore size

684

distribution in mercury injection of Chang7 lacustrine shale samples

685

Fig. 7..Low-pressure N2 adsorption–desorption isotherms of Chang7 lacustrine samples.

686

Fig. 8. Four types of hysteresis loops and types of pore geometry.

687

Fig. 9. (a) The relationship between the total BET specific surface area (SBET) and the total pore

688

volume (VBJH); (b) The relationship between the total BJH specific surface area (SBJH) and the total

689

pore volume (VBJH). 31

690

Fig.10. (a) The relationship between N2 adsorption amount and the total BET specific surface area

691

(SBET); (b) The relationship between N2 adsorption amount and the total BJH pore volume (VBJH).

692

Fig. 11. Plots of lnV vs ln[ln(Po/P)] reconstructed from the N2 gas adsorption isotherms of Chang7

693

lacustrine shale samples.

694

Fig. 12. Pore genetic types of Chang7 lacustrine shale (d quoted from Wang et al., 2016d; g, h, i, j,

695

k quoted from Wang et al., 2018; ).

696

Fig. 13. (a)The plots of SBJH with respect to BJH pore diameter of Chang7 lacustrine shale

697

samples; (b)The plots of VBJH with respect to BJH pore diameter of Chang7 lacustrine shale

698

samples.

699

Fig. 14. (a) The contribution of micropores, mesopores, and macropores to the total specific

700

surface area of 17 shale samples; (b) The contribution of micropore, mesopores, and macropores

701

to the total pore volume of 17 shale samples.

702

Fig. 15. (a) The average contribution of micropores, mesopores, and macropore to the total

703

specific surface area of 17 shale samples; (b) The average contribution of micropores, mesopores,

704

and macropores to the total pore volume of 17 shale samples.

705

Fig. 16. Relationships between total pore specific surface area, total pore volume, average pore

706

diameter, N2 adsorption amount and fractal dimension D1 of Chang7 lacustrine shale samples.

707

Fig. 17. Relationships between total pore specific surface area, total pore volume, average pore

708

diameter, N2 adsorption amount and fractal dimension D2 of Chang7 lacustrine shale samples.

709

Fig. 18. Relationships between clay mineral compositions and fractal dimension D1 of Chang7

710

lacustrine shale samples.

711

Fig. 19. Relationships between clay mineral compositions and fractal dimension D2 of Chang7

32

712

lacustrine shale samples.

713

Fig. 20. Relationships between brittle mineral compositions and fractal dimension D1 of Chang7

714

lacustrine shale samples.

715

Fig. 21. Relationships between brittle mineral compositions and fractal dimension D2 of Chang7

716

lacustrine shale samples.

717

Fig. 22. Relationships between TOC content and fractal dimensions (D1 and D2) of Chang7

718

lacustrine shale samples.

33

719

Table 1

720

Mineral composition based on XRD analysis of Chang7 lacustrine shale samples Sample

Depth

TOC

name

m

%

Mineral composition (%)

Total sulfur

Total

%

clay

Q

Po

Pl

Ca

Do

Clay composition (%) Py

Si

K

C

I

S

I/S

%S

DT005-1

672.4

6.37

0.92

34

32

8

26

29

22

49

25

DT005-2

685.8

2.41

0.14

56

30

3

11

35

22

43

20

DT005-3

691.7

4.38

0.34

46

23

9

22

33

20

47

20

DT006-1

610.3

58

29

4

7

26

23

51

30

DT018-1

517.4

57

31

3

9

28

15

57

25

DT018-2

531.4

43

37

3

17

48

14

38

25

LP123-1

1857.6

56

27

3

14

13

32

55

20

LP127-1

1651.2

43

31

5

21

23

35

42

20

LP171-1

1729.0

44

34

6

13

12

31

57

15

LP171-2

1730.0

40

34

5

21

9

27

64

15

LP171-3

1780.0

55

34

3

8

11

27

62

15

LP176-1

1657.5

43

27

2

22

13

34

53

15

LP177-1

1462.0

4.14

0.44

58

28

4

5

16

33

51

15

LP177-2

1473.4

3.76

0.22

51

34

4

11

13

25

62

15

LP177-3

1484.5

3.23

0.21

23

21

2

11

17

39

44

20

LP177-4

1486.2

1.65

0.06

50

29

6

11

15

38

47

20

2.92

0.19

2

1

2

6 2

29

3

5 4

34

9

C/S

%S

721

LP177-5

1494.7

66

23

3

6

18

38

44

15

L106-1

1446.5

29

37

6

25

18

48

34

15

L106-2

1447.5

40

36

5

14

18

47

35

15

L106-3

1518.0

30

30

7

15

5

13

41

46

15

L106-4

1518.5

56

18

3

10

13

25

31

44

15

L106-5

1522.0

51

29

7

8

5

22

46

32

15

XY12-1

907.45

49

27

4

18

22

30

48

20

X39-1

1122.2

53

28

5

10

4

13

28

59

15

X51-1

1435.0

20

34

5

39

2

42

28

30

20

Y261-1

696.0

50

40

2

7

28

17

55

25

Y261-2

697.0

51

36

2

6

20

13

36

25

Z061-1

535.14

53

24

4

19

31

37

32

25

W169-1

973.0

33

39

6

22

23

21

56

20

W169-2

973.5

43

36

2

17

2

7

8

18

67

20

W169-3

974.4

41

40

5

11

3

6

6

11

77

20

W169-4

976.7

2.29

0.45

31

34

10

22

3

17

35

13

35

20

W169-5

981.5

3.65

0.52

54

33

3

7

3

13

37

50

20

2.07

3.60

0.06

0.80

2 3 5 3

10

2

1 5

31

Q–quartz; Po–potassium feldspar; Pl–plagioclase; Ca–calcite; Do–dolomite; Py–pyrite; Si–siderite; K–kaolinite; A–ankerite; C–chlorite; I– illite; S–smectite.

35

722 723

Table 2 Physical property parameters of Chang7 lacustrine shale samples Cracks Sample

Depth

name

m

Bulk

Helium

Pulse

produced

Pore

density

porosity

permeability

during the

diameter

(g/cm3)

(%)

(md)

experiment

(nm)

Sorting coefficient

Displacement

Withdrawal

pressure

efficiency

(MPa)

(%)

Uniformity

Structural

coefficient

coefficient

(Yes or No) LP177-B1

1469.41

2.5

1.6

0.0121

No

LP177-B17

1478.24

2.35

1

0.2488

Yes

DT005-C10

678.12

2.6

1.5

0.0049

No

DT005-26

684.07

2.5

0.6

6.72

Yes

DT005-B12

689.43

2.42

0.8

0.0366

Yes

DT018-27

522.3

2.63

0.8

0.0091

No

DT018-B11

530.6

2.5

0.6

0.0085

No

DT018-C5

533.86

2.52

0.9

1.0035

Yes

G016-C8

867.06

2.59

1

2.47

Yes

W169-1

973

2.55

1.2

0.0094

No

W169-2

973.5

2.49

0.3

0.0047

No

W169-3

974.4

2.49

0.2

0.0049

No

W169-4

976.7

2.54

1.7

0.0057

No

724 725

36

0

0.05

5.08

53.89

0.39

0.01

30

0.07

10.41

67.81

0.47

0

30

0.06

10.59

55.17

0.43

0.03

40

0.07

7.5

54.68

0.43

0

726 727 728

Table 3 Results of shale nanoscale pores specific surface area, volume and pore size distribution by low-pressure N2 adsorption of Chang7 lacustrine shale samples Total specific surface area

N2 adsorption VBJH

dBJH

(×10-3cm3/g)

(nm)

(m2/g)

Sample

amount (cm3/g)

SBET

SBJH

DT005-1

1.793

2.421

9.14

19.8

5.7292

DT005-3

1.43

1.9

7.06

19.2

4.4347

DT018-1

1.296

1.763

5.9

17.5

3.6725

DT018-2

1.144

1.655

7.1

23.9

4.4239

LP123-1

3.19

5.897

8.7

15

5.3963

LP127-1

1.921

2.603

9

18.1

5.6316

LP176-1

3.881

4.883

13

12.8

8.0516

LP177-2

1.641

2.348

7.6

17.7

4.6942

LP177-4

1.401

2.038

7.23

19.9

4.4967

LP177-5

1.681

2.54

8.3

18.8

5.0962

L106-3

1.545

2.368

7.1

17.5

4.3581

L106-4

1.327

1.928

6.6

19.1

4.1042

L106-5

1.343

1.897

7.4

21.4

4.6341

X39-1

1.484

2.055

6.96

18.2

4.3598

X51-1

0.682

1.048

5

28.1

3.0961

W169-4

1.105

1.62

6.3

22.1

3.9436

W169-5

3.164

4.07

12.3

15.1

7.736

729

37

730

Table 4

731

Fractal dimension calculations based on the FHH model of Chang7 lacustrine shale samples Region1(P/Po:0-0.5) Sample

Region2(P/Po:0.5-1)

Fractal fitting

Fitting

Fractal fitting

Fitting

equation

coefficient(R12)

equation

coefficient(R22)

DT005-1

Y=-0.6959X-0.4642

0.997

Y=-0.4765X-0.4014

DT005-3

Y=-0.6547X-0.71

0.9955

Y=-0.4534X-0.6184

DT018-1

Y=-0.6737X-0.7749

0.996

Y=-0.4353X-0.7149

0.9961

DT018-2

Y=-0.7237X-0.9293

0.9945

Y=-0.5062X-0.8523

0.999

LP123-1

Y=-0.6846X-0.2316

0.9883

Y=-0.3982X-0.144

0.9843

LP127-1

Y=-0.6632X-0.4407

0.9919

Y=-0.4468X-0.322

0.9961

LP176-1

Y=-0.6048X+0.3014

0.9965

Y=-0.3867X+0.382

0.9947

LP177-2

Y=-0.7106X-0.574

0.9829

Y=-0.4645X-0.6109

0.9927

LP177-4

Y=-0.7498X-0.707

0.9973

Y=-0.4552X-0.5708

0.9969

LP177-5

Y=-0.8108X-0.5295

0.9945

Y=-0.4265X-0.3748

0.996

L106-3

Y=-0.7586X-0.6543

0.9828

Y=-0.4317X-0.533

0.9961

L106-4

Y=-0.7251X-0.7725

0.9927

Y=-0.4303X-0.6649

0.9892

L106-5

Y=-0.7023X-0.8023

0.9888

Y=-0.4779X-0.7683

0.9963

X39-1

Y=-0.6443X-0.6496

0.9944

Y=-0.4427X-0.5802

0.9951

X51-1

Y=-0.8537X-1.5376

0.9727

Y=-0.5235X-1.6835

0.9697

W169-4

Y=-0.7635X-0.9745

0.9932

Y=-0.4663X-0.8851

0.999

W169-5

Y=-0.6231X+0.0788

0.9937

Y=-0.4041X+0.1473

0.9982

38

0.9987 0.9966

732 733

Table5

734

Fractal dimensions derived from the FHH model of Chang7 lacustrine shale samples Region1(P/Po:0-0.5)

Region2(P/Po:0.5-1)

Sample A1

D1=3+A1

D1=3+3A1

A2

D2=3+A2

D2=3+3A2

DT005-1

-0.6959

2.3041

0.9123

-0.4765

2.5235

1.5705

DT005-3

-0.6547

2.3453

1.0359

-0.4534

2.5466

1.6398

DT018-1

-0.6737

2.3263

0.9789

-0.4353

2.5647

1.6941

DT018-2

-0.7237

2.2763

0.8289

-0.5062

2.4938

1.4814

LP123-1

-0.6846

2.3154

0.9462

-0.3982

2.6018

1.8054

LP127-1

-0.6632

2.3368

1.0104

-0.4468

2.5532

1.6596

LP176-1

-0.6048

2.3952

1.1856

-0.3867

2.6133

1.8399

LP177-2

-0.7106

2.2894

0.8682

-0.4645

2.5355

1.6065

LP177-4

-0.7498

2.2502

0.7506

-0.4552

2.5448

1.6344

LP177-5

-0.8108

2.1892

0.5676

-0.4265

2.5735

1.7205

L106-3

-0.7586

2.2414

0.7242

-0.4317

2.5683

1.7049

L106-4

-0.7251

2.2749

0.8247

-0.4303

2.5697

1.7091

L106-5

-0.7023

2.2977

0.8931

-0.4779

2.5221

1.5663

X39-1

-0.6443

2.3557

1.0671

-0.4427

2.5573

1.6719

X51-1

-0.8537

2.1463

0.4389

-0.5235

2.4765

1.4295

W169-4

-0.7635

2.2365

0.7095

-0.4663

2.5337

1.6011

W169-5

-0.6231

2.3769

1.1307

-0.4041

2.5959

1.7877

735

39

736

Table 6

737

Contribution of micropore, mesopore, and macropore to the total pore specific surface area and pore volume of Chang7 lacustrine shale samples

Sample name

Total SBJH 2

(m /g)

Micropore

Mesopore

Macropore

(< 2nm)

(2-50 nm)

(>50 nm)

SBJH (m2/g)

Contri bution (%)

SBJH (m2/g)

Contri bution (%)

SBJH (m2/g)

Total VBJH

Contri

(×10-3

bution

cm3/g)

(%)

Micropore

Mesopore

Macropore

(< 2nm)

(2-50 nm)

(>50 nm)

VBJH (×10 3

-3

cm /g)

Contri bution

VBJH (×10

-3

(%)

3

cm /g)

Contri bution

VBJH (×10

-3

Contri bution

(%)

3

cm /g)

(%)

DT005-1

2.421

0.286

11.82

2.087

86.19

0.048

1.99

9.14

0.215

2.36

6.609

72.31

2.316

25.34

DT005-3

1.9

0.401

21.10

1.476

77.67

0.023

1.23

7.06

0.295

4.17

5.263

74.55

1.502

21.27

DT018-1

1.763

0.381

21.61

1.362

77.24

0.020

1.15

5.9

0.248

4.21

4.280

72.54

1.372

23.25

DT018-2

1.655

0.456

27.54

1.176

71.05

0.023

1.40

7.1

0.324

4.57

5.150

72.53

1.626

22.90

LP123-1

5.897

0.042

0.71

5.815

98.61

0.040

0.68

8.7

0.022

0.26

7.450

85.63

1.228

14.11

LP127-1

2.603

0.462

17.75

2.082

80.00

0.059

2.25

9

0.266

2.95

6.280

69.78

2.455

27.27

LP176-1

4.883

0.003

0.07

4.848

99.28

0.032

0.65

13

0.003

0.02

11.208

86.21

1.790

13.77

LP177-2

2.348

0.900

38.35

1.429

60.86

0.018

0.79

7.6

0.808

10.63

5.525

72.70

1.267

16.67

LP177-4

2.038

0.719

35.26

1.298

63.68

0.021

1.05

7.23

0.561

7.76

5.263

72.79

1.407

19.46

LP177-5

2.54

0.829

32.63

1.665

65.57

0.046

1.80

8.3

0.478

5.75

5.199

62.64

2.623

31.60

L106-3

2.368

0.459

19.37

1.879

79.37

0.030

1.26

7.1

0.254

3.57

5.316

74.87

1.530

21.56

L106-4

1.928

0.719

37.31

1.186

61.49

0.023

1.19

6.6

0.514

7.79

4.476

67.81

1.610

24.40

L106-5

1.897

0.175

9.22

1.688

89.01

0.034

1.77

7.4

0.118

1.59

5.346

72.24

1.937

26.17

X39-1

2.055

0.503

24.49

1.524

74.16

0.028

1.35

6.96

0.296

4.25

5.116

73.51

1.548

22.24

X51-1

1.048

0.545

51.98

0.477

45.56

0.026

2.47

5

0.358

7.16

2.761

55.22

1.881

37.62

W169-4

1.62

0.644

39.78

0.933

57.57

0.043

2.65

6.3

0.387

6.14

3.461

54.93

2.453

38.93

W169-5

4.07

0.529

13.00

3.484

85.60

0.057

1.40

12.3

0.261

2.12

8.503

69.13

3.536

28.75

738

40

Highlights


Chang7 lacustrine shale pores diameter is mainly from 1.5 to 5 nm.




The smaller the pore diameter, the more heterogeneity the pore structure is, and the larger the pore surface and volume is.




Fractal dimensions are both positively correlated with total clay mineral, and negatively correlated with total brittle mineral.