Evaluation of nanoscale accessible pore structures for improved

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Evaluation of nanoscale accessible pore structures for improved prediction of gas production potential in Chinese marine shales Yang Wang, Yong Qin, Rui Zhang, Lilin He, Lawrence M. Anovitz, Markus Bleuel, David F.R. Mildner, Shimin Liu, and Yanming Zhu Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b03437 • Publication Date (Web): 28 Nov 2018 Downloaded from http://pubs.acs.org on December 1, 2018

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Evaluation of nanoscale accessible pore structures for improved prediction of gas production potential in Chinese marine shales

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Yang Wanga,b, Yong Qina,b*, Rui Zhangc,d **, Lilin Hed, Lawrence M. Anovitze, Markus Bleuelf,g, David F. R. Mildnerf, Shimin Liuc, Yanming Zhua,b aKey

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Laboratory of Coalbed Methane Resources and Reservoir Formation Process, China University of Mining and Technology, Xuzhou, Jiangsu 221008, China bSchool of Resources and Earth Science, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China cDepartment of Energy and Mineral Engineering, G3 Center and Energy Institute, The Pennsylvania State University, University Park, PA 16802, USA dNeutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA eChemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA fNIST Center for Neutron Research, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA gDepartment of Materials Science and Engineering, A. James Clark School of Engineering, University of Maryland, College Park, MD 20742, USA

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Corresponding authors: *Email: [email protected] ; **Email: [email protected]

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Abstract

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The Lower Cambrian Niutitang and Lower Silurian Longmaxi shales in the Upper Yangtze

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Platform (UYP) are the most promising strata for shale gas exploration in China. Knowledge of

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the nanoscale pore structure may improve the prediction of the gas production potential in Chinese

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marine shales. A systematic investigation of the pore accessibility and its impact on methane

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adsorption capacity has been conducted on shale samples using various techniques including

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geochemical and mineralogical analyses, field-emission scanning electron microscopy (FE-SEM),

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small-angle neutron scattering (SANS), helium porosimetry and methane adsorption. The results

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show that organic matter (OM) pores with various shapes dominate the pore systems of these

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shales. OM tended to mix with clay minerals and converted to organo-clay complexes, developing

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plentiful micro- and mesopores. A unified fit model with two pore structures, fractal pores and

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finite pores, was used to model the SANS data to characterize the pore structure of the shales. Both

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mass and surface fractals are identified for each pore structure. Total porosity estimated by the 1 ACS Paragon Plus Environment

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Porod method ranges between 2.35 % and 16.40 %, of which the porosity for finite pores ranges

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between 0.35 % and 6.36 %, and the porosity for the fractal pores ranges between 2.07 % and 8.51

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%. The fraction of open pores was evaluated by comparing the porosities estimated by He

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porosimetry and SANS. We find that the fraction of open pores is higher than 64 % for most of

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these shales. Correlation analyses suggest that clay and total organic carbon (TOC) have opposite

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effects on pore structure and methane adsorption capacity. Samples with higher clay contents have

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higher pore accessibility and lower total porosity, surface area and maximum methane adsorption,

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whereas samples with higher TOC content show the inverse relationships. The high percentage of

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open pores may reduce methane adsorption capacity in these shales, whereas low pore accessibility

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may reduce methane production at specific pressure differences. Thus, both TOC and pore

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accessibility may be essential controlling factors in methane production from shale gas reservoirs.

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Keywords

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Pore structure; pore accessibility; methane adsorption; Chinese marine shale; Upper Yangtze

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Platform

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1. Introduction

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In response to growing worldwide energy demands, shale gas is becoming an increasingly

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valuable energy resource. Following the shale gas revolution in North America and the

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development of the techniques of horizontal drilling and hydraulic fracturing, intensive efforts in

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shale gas explorations have been conducted in China [1-3]. Unlike conventional gas reservoirs,

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“shale gas reservoirs” are self-contained source reservoir systems that are generally characterized

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by high total organic carbon (TOC) contents compared to conventional gas reservoirs, complex

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mineral compositions, low porosities and low permeability matrices with extensive, heterogeneous,

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nanoscale pores [4-7]. This nanoscale pore structure is one of the key factors influencing the 2 ACS Paragon Plus Environment

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occurrence, storage capacity, and flow behavior of gas in these reservoirs [8-15]. Shale gases occur

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as both adsorbed and free gas and are thus directly affected by the nanoscale pore structures.

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Quantitative characterization of this nanoscale pore structure is, therefore, essential for evaluating

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gas production potential and providing clues to increasing gas extraction efficiency [9, 11, 16, 17].

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Due to the diversity, complexity and heterogeneity of shale pore structures, it is difficult to

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characterize pore structures using a single technique [11, 18-20]. A variety of techniques have,

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therefore, been used to characterize the pore structures of shales, in particular their porosity, pore

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volume and specific surface area. Direct imaging methods, including field emission-scanning

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electron microscopy (FE-SEM), transmission electron microscopy (TEM) and focused ion beam-

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scanning electron microscopy (FIB-SEM), have been successfully employed to observe the pore

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morphology and connectivity of pore networks [21-24]. However, these direct imaging techniques

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assess only limited areas of a sample at a given time, and thus their statistical reliability is limited.

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Indirect methods, including helium porosimetry, mercury intrusion porosimetry and low-pressure

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N2/CO2 adsorption, are also commonly used to quantitatively characterize the pore size distribution,

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pore volume and specific surface area of shales; however, these techniques typically interrogate

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larger sample volumes and can only characterize accessible pores and those with pore diameters

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larger than that of the probe molecule. Thus, adsorption techniques are unable to provide

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information about closed porosity [4, 19, 25-27]. In contrast, small-angle neutron scattering

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(SANS), a nondestructive physical technique, can be used to characterize both accessible and

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closed pores since it records the scattering intensity from all pores within the detectable size range

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[28-38]. Closed pores may play an essential role in gas shale production because they may contain

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methane, and thus the efficiency of gas recovery may depend on the extent to which they can be

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accessed. Given the apparent strengths and weaknesses of each of these approaches, therefore, a

3 ACS Paragon Plus Environment

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combination of different characterization techniques should lead to a more precise prediction of

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gas production potential.

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The marine shales in the Upper Yangtze Platform (UYP), the Lower Silurian Longmaxi

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Formation and the Lower Cambrian Niutitang Formation, are the primary targets for shale gas

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exploration and development in China because of their widespread occurrence, large thicknesses,

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organic richness, and favorable mineral compositions [1, 3, 13, 39]. Compared to the Longmaxi

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shales, the Niutitang shales has been more deeply buried and has higher thermal maturity [3,7]. In

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addition, high initial gas production rates of (10-50)×104 m3 per day have been reported for most

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pilot wells in the Jiaoshiba area of the Longmaxi shales [40, 41]. The breakthrough discovery of

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this shale gas field represents a significant milestone for shale gas exploration in China [3, 41].

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In order to provide a more thorough assessment of the pore structures and gas production

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potential of the UYP, a series of pore structure characterization techniques were applied to

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characterize pore morphologies, porosities, pore volumes and specific surface areas of the marine

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shales from the Lower Cambrian Niutitang and Lower Silurian Longmaxi Formations. In this study,

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we have used a combination of FE-SEM, SANS, helium porosimetry and high-pressure methane

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adsorption to investigate pore accessibility and its effect on methane adsorption. Uniquely, the

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correlations between pore accessibility and methane adsorption properties indicating that pore

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accessibility could be an indicator for methane production from shale gas reservoirs. The results

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will be broadly applicable to shale gas exploration and development including reservoir

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assessment and evaluation, gas-in-place estimation, carbon sequestration and other characteristics

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of the UYP.


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2. Materials and methods 2.1 Sample collection

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The UYP is located in the western portion of the Yangtze Platform in southern China (Fig. 1).

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It includes the Chongqing city, northern Guizhou and Yunnan, western Hubei and Hunan, and

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eastern Sichuan province. Geological studies indicate that the Niutitang Formation and the

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Longmaxi Formation formed on a neritic shelf with a stagnant marine sedimentary environment

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[1, 3]. These marine shales are currently the most prominent exploration and production targets

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for shale gas in China.

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Fig. 1 Geographical map of UYP and sampling location

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A total of six shale samples were analyzed in this study. Four fresh Longmaxi Formation shale

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core samples were collected from the WX2 well, located in northeast Chongqing near the edge of

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the Sichuan Basin. Two fresh Niutitang Formation shale core samples were collected from the 5 ACS Paragon Plus Environment

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QD1 well located in northeast Yunnan near the southwestern edge of the UYP. Both of these shales

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are widely distributed around the UYP. Although both are thermally over-mature, the thermal

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maturity of the Niutitang shales is much greater than that of the Longmaxi shales, which indicates

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that the Niutitang experienced more severe compaction and underwent more complicated

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diagenesis than the Longmaxi [1].

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2.2 Geochemical and mineralogical tests

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Geochemical parameters and mineral compositions were characterized for all the shale samples

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measured in this study. Analysis of TOC content was performed using a LECO CS-230 carbon

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and sulfur analyzer. Due to the lack of vitrinite in the Lower Paleozoic shales, the reflectance of

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pyrobitumen was measured using a Leica MPV-SP microphotometer. The average pyrobitumen

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reflectance was then converted to an equivalent vitrinite reflectance (EqVRr) using the equation of

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Schoenherr et al. (2007), i.e., EqVRr =(BRr+0.2443)/1.0495, where BRr is the pyrobitumen

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reflectance [42]. The mineralogy of each sample was obtained using a RIGAKU D/Max-3B type

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X-ray diffractometer (XRD). Preparation, analysis and interpretation procedures were conducted

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following the Chinese Oil and Gas Industry Standard SY/T 5163-2010. Multicomponent

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quantifications were achieved by Rietveld refinement using the TOPAS software package. All

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analyses were carried out at the Experimental Research Center of East China Branch, SINOPEC.

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2.3 FE-SEM

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FE-SEM observations were performed using a Quanta 200F instrument at the China University

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of Petroleum, Beijing Campus (CUP). The FE-SEM images provide a spatial resolution of 1.2 nm,

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which is sufficient to characterize the nanoscale pore morphology. Before the experiment, the

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samples were pre-polished using an argon ion mill to create an artifact-free surface. Au was then

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coated onto the artifact-free surface to improve the image quality by enhancing the electrical 6 ACS Paragon Plus Environment

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conductivity. The experiment and subsequent analysis were carried out at a constant temperature

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of 24 °C and a constant humidity of 35 %. High-resolution images were obtained at an accelerating

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voltage of 10 kV to 15 kV with a working distance of 4 mm to 5 mm.

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2.4 SANS

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Of the six samples analyzed by SANS in this study, the first two (WX2-8 and WX2-33) were

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analyzed as powders and the other four (QD1-L3, QD1-L4, WX2-49 and WX2-54) as disks.

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Analysis of the powdered shales was conducted using the general-purpose small-angle neutron

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scattering diffractometer (GP-SANS) at the High Flux Isotope Reactor (HFIR) at Oak Ridge

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National Laboratory (ORNL) [43]. The samples had a non-uniform particle size of < 0.5 mm, and

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an overall sample thickness of 1.6 mm. These samples were measured under an ambient condition

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with sample-to-detector distances of 1.1 m, 8.8 m and 19.2 m. The neutron wavelength 𝜆 was set

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at 4.75 Å for the 1.1 m and 8.8 m measurements, and 12 Å for the 19.2 m measurements to extend

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the scattering vector 𝑄 range to values as small as possible (the largest sizes possible), where 𝑄 = 4

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𝜋sin 𝜃/𝜆 and 𝜃 is half of the neutron scattering angle. The overall 𝑄 range was between ~1.5×10-3

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Å-1 and ~0.8 Å-1, which corresponds to pore sizes between ~3 Å and ~1.6×103 Å using the

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empirical relation 𝑅 ≈ 2.5/𝑄 [44]. The absolute scattering intensities were obtained using

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measured sample transmission and thickness values as well as a standard scattering intensity

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measured on porous silica [45]. All the 1D scattering curves were obtained using the NCNR Igor

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macros package [46].

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In order to reduce multiple scattering, especially at low 𝑄 and long wavelengths [28, 47], the

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remaining samples were analyzed as thin disks with an arbitrary orientation, using the method

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outlined by Anovitz et al. [28]. These analyses were performed using the NG-7 30m small-angle

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neutron scattering diffractometer (NG7-SANS) at the NIST Center for Neutron Research (NCNR) 7 ACS Paragon Plus Environment

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at the National Institute of Standards and Technology (NIST) [48]. Four thin disk shale samples

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were commercially polished to a thickness of 0.1 mm and mounted on 1 mm thick quartz glass

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slides [28, 47]. These samples were analyzed with the normal to the incident beam and under

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ambient condition. Four SANS geometries were used: 1 m and 4 m sample-to-detector distances,

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and a 13 m distance with and without a set of biconcave MgF2 lenses. The neutron wavelength

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was set at 6 Å for SANS geometries of 1 m, 4 m and 13 m, and at 8.1 Å for the configuration with

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the lenses. These settings cover scattering vector 𝑄 range between ~1×10-3 Å-1 and ~0.6 Å-1, which

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corresponds to a pore size range between ~4 Å and ~2.5×103 Å.

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2.5 Porosity using helium porosimetry

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The total accessible porosity of the shale samples was determined at the Experimental Research

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Center of East China Branch, SINOPEC using a technique based on Boyle's Law, by measuring

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the grain volume under ambient conditions and bulk volume by Archimedes’ principle with helium

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porosimetry [47]. Samples were oven dried at 115 °C to a constant mass (±1 mg). Porosity was

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calculated from the difference between bulk volume and grain volume.

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2.6 High-pressure methane adsorption

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High-pressure methane adsorption isotherms were measured at a constant temperature of 40 °C

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and pressure up to 9 MPa using a volumetric sorption apparatus (IS-300 isothermal

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adsorption/desorption analyzer) manufactured by Terratek, USA. Before the adsorption

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measurement, samples were crushed to a particle size of less than 250 µm (60 mesh) and dried for

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24 h at 105 °C. The detailed methane adsorption measurement procedure is described by Ji et al.

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[49]. Methane sorption data were normalized to sample weight and parametrized using the

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Langmuir monolayer adsorption model [50].


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3. Results and discussion

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3.1 Geochemical and mineralogical parameters

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Detailed geochemical and mineralogical characteristics of the marine shale samples are listed

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in Table 1. Mass fraction is used for the chemical compositions. TOC contents range between 1.52

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wt.% and 6.33 wt.%. The marine shales in UYP have experienced strong thermal maturation and

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reached the post-mature stage with EqVRr values ranging from 2.06 % to 3.03 %.

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XRD analysis demonstrates that both Cambrian Niutitang shales and Silurian Longmaxi shales

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have complex mineralogy (Table 1 and Fig. 2). Quartz and clay are the major components with an

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average of 49.3 wt.% (38.0–56.6 wt.%) and 28.9 wt.% (22.0–41.0 wt.%), respectively. Fig. 2a

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shows that these shales also contain pyrite, calcite, dolomite, K-feldspar and plagioclase. Illite is

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the most abundant clay mineral ranging between 10.6 wt.% and 26.3 wt.% with a mean value of

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17.4 wt.%. Fig. 2b shows the other clay minerals including smectite, chlorite and illite/smectite

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mixed layer clays.


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Fig. 2 Chemical composition of the six Chinese marine shales: (a) Total mineral contents; (b) Clay mineral contents


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Table 1 Chemical composition of the six Chinese marine shales Formation

Niutitang (Є1)

Longmaxi (S1)

Sample ID

Quartz (wt.%)

K-feldspar (wt.%)

Plagioclase (wt.%)

Dolomite (wt.%)

Calcite (wt.%)

Pyrite (wt.%)

Clay (wt.%)

Illite (wt.%)

Smectite (wt.%)

Chlorite (wt.%)

Illite/Smectite mixed layer (wt.%)

TOC (wt.%)

EqVRr (wt.%)

QD1-L3

46.61

4.64

7.25

1.35

5.61

1.64

29.59

15.09

5.03

1.55

7.93

3.29

2.85

QD1-L4

54.15

1.44

3.64

/

6.98

2.39

27.08

19.61

1.15

0.77

5.55

4.32

3.03

WX2-8

37.42

1.48

14.28

/

2.17

2.76

40.38

25.90

/

5.12

9.36

1.52

2.06

WX2-33

46.33

/

9.60

2.94

13.71

3.82

21.54

10.38

/

2.55

8.62

2.05

2.12

WX2-49

49.41

1.15

5.27

/

3.26

9.10

27.58

16.09

1.53

3.35

6.61

4.25

2.26

WX2-54

50.77

3.09

8.43

1.12

3.28

5.99

20.98

13.58

1.12

2.15

4.12

6.33

2.32

196


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3.2 Qualitative pore morphology characteristics using FE-SEM

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Pore structure has an enormous impact on the occurrence of shale gas, the calculation of gas

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in place (GIP) and hydraulic fracturing. Qualitative analysis of pore morphology helps reveal the

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origin of nanoscale pores and the nature of microscopic pore structures. Based on detailed pore

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classifications proposed in previous studies [6, 9, 51-52], we have divided the pores observed in

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our marine shales into four categories: Interparticle (interP) pores, intraparticle (intraP) pores,

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organic matter (OM) pores and microfractures.

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FE-SEM observations (Fig. 3) suggest that OM pores dominate the pore system of the marine

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shales. Their diameters vary from several to hundreds of nanometers and they display various

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shapes such as spherical to ellipsoidal, schistose-like, irregular polygons and honeycombs (Figs.

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3a, b and c). OM pores are well-developed and often form pore networks with functional

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connectivity. Since these shales have reached the over-mature stage, it is likely that OM pores

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were formed gradually during thermal evolution. Furthermore, OM does not, necessarily, exist in

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isolation. OM is commonly intergrown with pyrite framboids (Figs. 3b and c), forming a large

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number of nanoscale pores (pore size in the nanometer range). OM also tends to partially mix with

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clay minerals (Fig. 3a), becoming converted to organo-clay complexes with a full range of micro-

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/mesopores sizes (pore size < 50 nm).

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IntraP pores are another major contributor to the porosity of these marine shales. This type of

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pore is mainly associated with pyrite framboids, clay aggregates and dissolution of unstable

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minerals such as plagioclase and calcite (Fig. 3f). Pyrite framboids were observed in these shales,

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and nanoscale pores were commonly observed between individual pyrite crystals. These were

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probably formed by incomplete cementation or dissolution of the pyrite grains (Figs. 3d and g).

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Fig. 3e shows an example of intraP pores within clay mineral aggregates displaying a “card house”


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structure [53]. This provides interconnected pores which may serve as essential pathways

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enhancing gas permeability.

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Fig. 3 FE-SEM images of the six Chinese marine shales: (a) OM pores and micro-/mesopores developed within

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organo-clay complexes (sample WX2-54); (b) OM is commonly intergrown with pyrite framboids (sample WX2-33);

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(c) Nanoscale pores within OM filled between pyrite framboids (sample WX2-33); (d) IntraP pores and interP pores

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developed between the contact areas of pyrite and clay minerals (sample WX2-49); (e) IntraP pores developed within

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clay mineral aggregates (sample QD1-L3); (f) Dissolution pores and fractures developed within calcite (sample WX2-

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8); (g) IntraP pores developed within pyrite framboids (sample QD1-L4); (h) Microfractures developed within clay

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minerals and OM (sample WX2-49); (i) Microfractures are commonly connected nanoscale pores (sample QD1-L4)


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In contrast to OM and intraP pores, interP pores are susceptible to mechanical compaction and

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difficult to preserve. InterP pores are usually developed at the points of contact between particles.

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They exist between the contact areas of OM and clay minerals and along the pyrite and quartz

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grains (Figs. 3d and i). The distribution of interP pores observed in these samples was quite

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heterogeneous with low connectivity.

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Various

kinds of microfractures were observed in the tested shales. Some microfractures were

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observed within unstable minerals and appeared to be formed as a result of dissolution (Fig. 3f).

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Microfractures within OM are usually related to hydrocarbon generation (Fig. 3h). Some

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microfractures were also developed within clay minerals (Fig. 3h). Typically, these are 20 nm to

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100 nm wide and about 3 μm long. Note that the origin of the microfractures in clay minerals

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remains uncertain which is likely formed due to clay shrinkage, either during diagenesis or perhaps

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secondarily as a result of core sample recovery and processing. Meanwhile, nanoscale pores and

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microfractures are also influenced by mechanical compaction since both Longmaxi and Niutitang

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Formations experienced multi-phase tectonic movements. Fig. 3i shows that microfractures

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connect micropores (pore size < 2 nm) and macropores (pore size > 50 nm), which can improve

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the connectivity of the pore networks. Therefore, microfractures not only provide space for free

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and adsorbed gas to accumulate but may serve an important role in shale gas migration.


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3.3 Quantitative pore structure characteristics using SANS

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3.3.1 Experimental scattering intensities

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Fig. 4 Comparison of background-subtracted experimental scattering intensities for the six Chinese marine shales: (a)

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log (𝐼(𝑄)) vs. log (𝑄); (b) log (𝑄4𝐼(𝑄)) vs. log (𝑄)

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Fig. 4 shows the background-subtracted 1D scattering profiles on logarithmic scales for the six

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Chinese marine shale samples tested. In each case, the log of the intensity decreases nearly linearly

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with increasing log (𝑄) over the entire measured 𝑄 region, although careful examination by

255

plotting log (𝑄4𝐼(𝑄)) as a function of log (𝑄) shows that this is not completely true, especially for

256

samples WX2-8 and WX2-33. This scattering profile is typical for shales in this 𝑄 range [10, 11,

257

34, 35, 37, 38, 54-60]. The scattering intensities measured for the two Niutitang samples and one

258

of the Longmaxi samples, QD1-L3, QD1-L4 and WX2-49 (all disk samples), were similar over the

259

measured 𝑄 range, indicating that the total pore volumes and pore volume distributions in this size

260

range (between ~4 Å and ~2.5×103 Å) among these samples are quite similar. The scattering

261

intensity of WX2-54 is the highest among the tested samples over the entire 𝑄 range and slope of

262

the scattering curve is shallower. This indicates that the total pore volume of WX2-54 is greater

263

than the other five samples over this specific size range, and that this difference is probably the

264

largest at smaller pore sizes. At the opposite extreme, the scattering intensity of WX2-8 is smaller 15 ACS Paragon Plus Environment

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Page 16 of 44

265

than that of other five samples at 𝑄 > ~0.01 Å-1, implying that this sample has a smaller total pore

266

volume over this pore range compared to the others. A hump is present at low 𝑄 for samples WX2-8

267

and WX2-33, and there is a broad hump in the data for WX2-54 around 0.03 Å-1 (~8 nm). A small

268

hump in the scattering profile was also observed for samples QD1-L4, WX2-8 and WX2-49 around

269

0.2 Å-1. Similar results have been seen in both SANS and SAXS data for shales [11], coals [10,

270

61, 62], and sandstones [29, 30]. Interestingly, a hump that is typically observed in the SAXS

271

profiles of coal samples is absent in the SANS profiles for the same samples [61]. Thus, these may

272

be caused by the interlayer spacing of clays in QD1-L4, WX2-8, WX2-49 and WX2-54.

273

3.3.2 Pore structure determination

274

In order to quantitatively characterize the nanopore structure of the tested shales we have

275

applied an empirical SANS model that combines Guinier and power-law equations to fit the

276

experimental SANS data. In this unified model the scattering intensity 𝐼(𝑄) is expressed as [63]:

{

𝑛 ∑𝑖 = 1

𝑄𝑅g

―

𝑄2𝑅g2 𝑖 3

[

( ( )) erf

6

𝑖

3

𝛼𝑖

]}

277

𝐼(𝑄) =

278

where 𝑄 is the scattering vector; 𝐺 is the Guinier coefficient, which is equal to the scattering

279

intensity at 𝑄 = 0; 𝑅g is a radius of gyration representing a domain size; 𝐵 is the power law

280

coefficient; 𝛼 is the power law exponent; 𝑖 is the number of the pore structure, as several

281

independent pore structures can be fitted with this model; 𝑛 is the total number of pore structures

282

considered; and 𝐵𝑘𝑔 is the scattering background. Based on the experimental scattering data

283

shown in Fig. 4, the presence of power-law scattering at low and medium 𝑄 implies the existence

284

of a fractal pore structure in the tested shales, with the exceptions of WX2-8 and WX2-33.

285

Furthermore, both the deviation in the scattering intensity from power-law scattering at high 𝑄 and

𝐺𝑖𝑒

+ 𝐵𝑖

𝑄

+𝐵𝑘𝑔

(1)


Page 17 of 44 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

Energy & Fuels

286

the “humps” may reflect additional fractal pore structures with finite size ranges. Thus, a model

287

with two pore structures based on Eq. 1 (with 𝑛 = 2) has been used to fit the data for the shale

288

samples. The first reflects the power-law scattering for a fractal pore structure (fractal pores); the

289

second is fitted with a combined Guinier and power-law model, and reflects a fractal pore structure

290

with a finite pore range (finite pores).

291

Fitting Eq. 1 to the scattering data for each shale sample was performed using the Irena

292

software package [64]. The results are shown in the supplementary Fig. S1 and detailed model

293

parameters are listed in the Supplementary Tables. Note that, because the thickness of the samples

294

led to excess multiple scattering at low 𝑄 for samples WX2-8 and WX2-33, the low 𝑄 cutoff of

295

model fitting was chosen at the linear range in the log (𝐼(𝑄)) ― log (𝑄) plot. The modeled

296

scattering intensity was then extrapolated to the experimental low 𝑄 limit for each sample as shown

297

in Figs. S1c and d. When the value of the fitted power law exponent 𝛼 is between 3 and 4 the data

298

may be interpreted as a surface fractal with dimensionality 𝐷s, given by 𝐷s = 6 ― 𝛼, so that 𝐷s lies

299

between 2 and 3. When the value of 𝛼 is smaller than 3 the correlation 𝐷m = 𝛼 was used to estimate

300

the mass fractal dimension 𝐷m [47, 65].

301

The estimated fractal dimensions for these shale samples are shown in Table 2. For the finite

302

pores the model yields mass fractal dimensions between 1.94 and 2.68 except for sample QD1-L4,

303

for which suggests a surface fractal dimension of 2.85. For the fractal pores, samples QD1-L4,

304

WX2-49 and WX2-54 have mass fractal dimensions 𝐷m between 2.84 and 2.93, whereas samples

305

QD1-L3, WX2-8 and WX2-33 generate surface fractal dimensions 𝐷s ranging between 2.42 and

306

2.78. The sample preparation procedure could be the reason for the existence of both mass and

307

surface fractals in the shales tested. The unified model suggests that the pore structure of the finite

308

pores has a maximum pore size ranging between ~3.8 nm and ~7.8 nm assuming spherical pore 17 ACS Paragon Plus Environment

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Page 18 of 44

309

shape, where 𝑅g = 3/5𝑅, as the radius of gyration 𝑅g ranges between ~3.0 nm and ~6.1 nm

310

(Tables S2-S7 in the supplementary). This represents the maximum domain size of this structure,

311

which is within the meso-/micropore size range. The results also indicate that the shale pores have

312

different fractal characteristics at different pore sizes.

313

Both the total porosity and the porosities of each pore structure were estimated using the Porod

314

invariant method. The Porod invariant 𝑄INV can be expressed as [66]:

315

𝑄INV = ∫𝑄max𝑄2𝐼(𝑄)𝑑𝑄 = 2𝜋2(𝜌s∗ ― 𝜌p∗ ) ∅(1 ― ∅)

316

where 𝜌s∗ and 𝜌p∗ are the scattering length densities (SLDs) of the solid matrix and pores,

317

respectively; 𝑄max and 𝑄min are the experimental maximum and minimum 𝑄 values, respectively;

318

and ∅ is the porosity. Here we assume that the SLD is the same for the fractal and finite pores for

319

porosity estimation. Nonetheless, if one were primarily OM filled, or one contrasted with a

320

different mineral than the other, the SLDs could be different, although probably not very different.

321

The value of ∅ estimated for each pore structure and the total porosity for all samples are shown

322

in Table 2. Note that the 𝑄 range for porosity estimation was confined between ~1.5×10-3 Å-1 (for

323

𝑄min) and ~0.5 Å-1 (for 𝑄max) for the reason noted above. Thus, the pore size range for total pores

324

is between ~0.5 nm and ~1.6×102 nm. For the divided two pore structures, fractal pores have the

325

same pore size range as the total pores. However, the pore size range of finite pores is sample

326

dependent. The lowest pore size limit is ~0.5 nm, while the highest pore size limit is between ~3.8

327

nm and ~7.8 nm for all the samples. The estimated total porosity ranged from 2.35 % to 16.40 %.

328

The porosity of finite pores ranged between 0.35 % and 6.36 %, and that of fractal pores between

329

2.07 % and 8.51 %. The reason why the total porosity is not the exact addition from the porosities

330

of fractal and finite pores is that the experimental scattering intensity is used to estimate ∅ total

331

while the modeled scattering intensity is used to estimate ∅ for each pore structure. Another reason

𝑄

2

min

(2)


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Energy & Fuels

332

could be the assumption of equal SLDs for the total, fractal and finite pores, which may be different.

333

With the exception of sample QD1-L3 the pore volume of the finite pores is generally smaller than

334

that of the fractal pores.

335

Table 2 Fractal dimension 𝐷 and porosity ∅ for the six Chinese marine shales

Formation

Niutitang (Є1)

Longmaxi (S1)

Sample ID

Finite pores

Fractal pores

∅ totala (%)

𝐷s

𝐷m

∅a (%)

𝐷s

𝐷m

∅a (%)

QD1-L3

/

2.64±0.05

3.70±0.02

2.78±0.01

/

2.10±0.01

5.81±0.03

QD1-L4

2.85±0.31

/

1.64±0.01

/

2.89±0.01

3.25±0.02

5.28±0.05

WX2-8

/

2.68±0.04

0.35±0.00

2.42±0.00

/

2.07±0.02

2.35±0.02

WX2-33

/

2.34±0.01

0.95±0.01

2.55±0.00

/

2.13±0.02

3.03±0.02

WX2-49

/

1.94±0.06

3.29±0.02

/

2.93±0.01

4.03±0.02

7.43±0.03

WX2-54

/

2.26±0.06

6.36±0.03

/

2.84±0.02

8.51±0.04

16.40±0.07

336 337 338 339

aThe

340

3.3.3 Pore structure affected by shale properties

𝑄 range for porosity estimation is between ~1.5×10-3 Å-1 and ~0.5 Å-1. ∅ total and each pore structure were estimated from total scattering intensity and scattering intensity of each pore structure, respectively. The experimental scattering intensity is used to estimate ∅ total while the modeled scattering intensity is used to estimate ∅ for each pore structure.

341

With the exception of sample WX2-49 there may be a U-shaped correlation between the fractal

342

dimension and TOC for the finite pores (Fig. 5b), while D increases and then becomes generally

343

constant with increasing TOC for the fractal pores (Fig. 5b). The maximum fractal dimension,

344

including both mass and surface fractals, occurs at ~27 % clay content and ~4.2 % TOC as shown

345

in Figs. 5a and b. This implies that the maximum complexity of shale fractal pore structure could

346

require at specific clay and carbon contents. In contrast, there is no obvious correlation between

347

the fractal dimension of the finite pores and clay content, and at best a weak decreasing or U-

348

shaped one for the fractal pores (Fig. 5a).

349

Figs. 5c and d show the total porosity and the porosities of the pore structures estimated by

350

both SANS and helium porosimetry as a function of clay and TOC contents. Negligible 19 ACS Paragon Plus Environment

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Page 20 of 44

351

correlations between the concentrations of other minerals and porosity were found; they do not

352

seem to be controlling factors for methane adsorption in these shales [27]. However, Figs. 5c and

353

d show that, in general, the SANS total porosity, the porosity of each pore structure, and the helium

354

porosity increase with increasing TOC. There is no obvious or weak correlation for clay content.

355

The results show a relatively strong correlation for TOC (R2 > 0.77) as a function of porosity,

356

indicating that TOC is a controlling factor in shale porosity. The weak correlation between clay

357

and porosity may reflect variations in the types of clay minerals present, as different clay minerals

358

may contribute to porosity differently.

359


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Energy & Fuels

360

Fig. 5 Correlation between pore structure and chemical compositions for the six Chinese marine shales: Fractal

361

dimensions vs. (a) clay and (b) TOC contents; Porosities vs. (c) clay and (d) TOC contents (Note: WX2-49 was treated

362

as an outlier in Fig. 5b)

363

3.4 Methane adsorption characteristics

364

3.4.1 Adsorption capacity determination

365

Fig. 6 shows the results of the methane adsorption isotherm measurements. Methane

366

adsorption exhibited a two-stage change with increasing pressure for all samples measured. At low

367

to moderate pressures (0 to 4 MPa), the adsorption capacity rapidly increased with increasing

368

pressure, as indicated by the slope of adsorption profile. When the adsorption pressure exceeded

369

4 MPa, however, the rate of sorption gradually decreased. However, although the overall sorption

370

patterns are similar, the methane adsorption capacity dramatically varies among the different

371

samples. In general, as shown in Fig. 7b, the maximum adsorption capacity for methane in these

372

shales increased as a function of TOC content.

373 374

Fig. 6 Isothermal methane adsorption profiles for the six Chinese marine shales


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Page 22 of 44

375

The Langmuir adsorption model was used to fit the experimental methane adsorption isotherms

376

[67]. The Langmuir equation is usually recommended for describing methane adsorption in shale

377

samples due to its practical advantages and simplicity, as it only contains two important adjustable

378

parameters 𝑉L and 𝑃L. The usual form of the Langmuir model is [50]:

379

𝑉 = 𝑃L + 𝑃

380

where 𝑃 is the experimental pressure, 𝑉 is the experimental adsorption capacity at each pressure,

381

𝑉L is the Langmuir volume showing the theoretical maximum adsorption capacity, and 𝑃L is the

382

Langmuir pressure representing the pressure at which half of theoretical maximum adsorption for

383

a given sample occurs. As can be seen in Fig. 6, this model fits the measured data (Table 3) quite

384

well. The Langmuir sorption capacity, 𝑉L, varies from 0.47 cm3/g to 3.62 cm3/g and the Langmuir

385

pressure, 𝑃L, ranges from 0.76 MPa to 3.30 MPa.

386

𝑉L𝑃

(3)

Table 3 The Langmuir volume and pressure for the six Chinese marine shales Formation Niutitang (Є1)

Longmaxi (S1)

387

Sample ID

𝑉L (cm3/g)

𝑃L (MPa)

R2

QD1-L3

1.55

2.62

0.974

QD1-L4

1.86

2.39

0.969

WX2-8

0.47

0.76

0.974

WX2-33

1.15

3.30

0.987

WX2-49

3.18

1.72

0.987

WX2-54

3.62

1.54

0.990

3.4.2 Adsorption capacity affected by shale properties and pore structure

388

Fig. 7 shows the correlations between the Langmuir constants and the clay and TOC contents

389

of the shales. While there is some scatter, the Langmuir volume generally decreases with

390

increasing clay content and increases with increasing TOC (Figs. 7a and b). This implies that clay

391

minerals have a smaller methane adsorption capacity than organic matter. The Langmuir pressure 22 ACS Paragon Plus Environment

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392

𝑃L, however, decreases with both increasing clay content and TOC (Figs. 7c and d). Note that

393

sample WX2-8 is an outlier in Fig. 7d, possibly because this sample has the lowest TOC content

394

(1.52 %), highest plagioclase (> 14 %) and clay mineral contents (> 40 %) the lowest total porosity

395

(2.35 %) of the shale samples. 𝑃L is the pressure at which half of the maximum adsorption volume

396

is achieved, describing the affinity of the adsorbed gas for the adsorbent [50, 68]. Thus, the results

397

indicate that the affinities of methane for clay and organic matter in shale may be similar, although

398

the correlations for clay are much poorer than those for TOC. Again, this could be due to variations

399

in adsorption capability among different clay minerals. Regardless, the strong correlations between

400

the Langmuir constants and TOC (R2 > 0.83) suggest TOC may be a controlling factor for methane

401

adsorption in shales.


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Page 24 of 44

402 403

Fig. 7 Correlation between Langmuir constants and chemical compositions for the six Chinese marine shales:

404

Langmuir volume vs. (a) clay and (b) TOC contents; Langmuir pressure vs. (c) clay and (d) TOC contents (Note:

405

WX2-8 was treated as an outlier in Fig. 7d)

406

In order to quantify the effects of pore structure on methane storage in shales, the correlations

407

between the Langmuir constants and the pore structure parameters derived from the SANS data

408

need to be investigated. Figs. 8a and c show that the correlations between fractal dimension and

409

the Langmuir constants for the pore structure of the finite pores are negligible. However, there

410

may be U-shaped correlations between fractal dimension and the Langmuir constants for the pore


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411

structure of the fractal pores when the Langmuir constants are treated as the independent variables,

412

with maximum values of about 2.5 ml/g for 𝑉L and 2 MPa for 𝑃L.

413

The correlations between the Langmuir parameters and porosity are, however, somewhat better.

414

The Langmuir volume, 𝑉L, the maximum adsorption capacity, increases with increasing porosity

415

(Fig. 8b). This is reasonable because both porosity (Fig. 5d) and 𝑉L (Fig. 7b) increase with

416

increasing TOC. However, the Langmuir pressure, 𝑃L, the affinity of methane molecules for the

417

shale, decreases with increasing porosities, with WX2-8 again being an outlier (Fig. 8d). This result

418

also seems reasonable as porosities (Fig. 5d) and 𝑃L (Fig. 7d) increase with increasing TOC. The

419

results indicate that shale porosity has the opposite effect on the 𝑉L and 𝑃L values for methane;

420

higher porosity yields higher 𝑉L but lower 𝑃L for shale.


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Page 26 of 44

421 422

Fig. 8 Correlation between Langmuir constants and pore structure for the six Chinese marine shales: Langmuir volume

423

vs. (a) fractal dimensions and (b) porosities; Langmuir pressure vs. (c) fractal dimensions and (d) porosities (Note:

424

WX2-8 was treated as an outlier in Fig. 8d)

425

3.5 Shale pore accessibility

426

The combination of helium porosimetry with the SANS data described above, was used to

427

investigate pore accessibility quantitatively. Table 4 shows the estimated fraction of accessible

428

pores, 𝜑 for each of the shale samples. The 𝜑 should be an approximate value since the pore range

429

for SANS is approximate between 0.5 nm and 167 nm, while the pore size range of open pores

430

measured by He porosimetry is larger than 0.2nm [47]. In most cases, the measured 𝜑 value is 26 ACS Paragon Plus Environment

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431

greater than 64 %. This indicates that the matrix pores of the tested shales are highly accessible.

432

The exception is sample WX2-33, which has the lowest total pore accessibility (𝜑=40.26 %) and

433

helium accessible porosity (1.22 %) as well as the second lowest total porosity (3.12 %). This may

434

be caused by the mineralogy of this sample. WX2-33 has the highest calcite content (13.71 %) of

435

all the samples investigated. Late calcite precipitation may have filled or sealed off many of the

436

pores. For the other samples, however, the pore accessibility results indicate that the transport

437

pathways for methane production and CO2 sequestration are, in fact, relatively open. This suggests

438

that, to the extent that these samples are representative of the two formations, after drilling and

439

hydraulic fracturing are completed a significant amount of natural gas should be extractable from

440

the Longmaxi and Niutitang formations, possibly making them essential Chinese shale gas

441

resources.

442

Table 4 Revisit clay and TOC contents, and pore accessibility 𝜑 obtained from SANS and helium porosities for the

443

six Chinese marine shales Formation Niutitang (Є1)

Longmaxi (S1)

444

aThe

Sample ID

Clay (wt.%)

TOC (wt.%)

SANS ∅ total (%)

Helium ∅ (%)

𝜑a (%)

QD1-L3

29.59

3.29

5.81

3.72

64.03

QD1-L4

27.08

4.32

5.28

3.61

68.37

WX2-8

40.38

1.52

2.35

2.01

85.53

WX2-33

21.54

2.05

3.03

1.22

40.26

WX2-49

27.58

4.25

7.43

4.83

65.01

WX2-54

20.98

6.33

16.40

10.76

65.61

𝜑 values were estimated based on SANS ∅ total and helium ∅.


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Page 28 of 44

445 446

Fig. 9 Correlation between the fraction of accessible pores and chemical compositions for the six Chinese marine

447

shales: Fraction of accessible pores vs. (a) clay and (b) TOC contents (Note: WX2-33 was treated as an outlier)

448

Fig. 9 shows the correlations between the accessible pore fraction and the clay/TOC contents.

449

In contrast to the porosity correlations shown in Fig. 5, the fraction of accessible pores, 𝜑, increases

450

with increasing clay content (Fig. 9a), and decreases with increasing TOC (Fig. 9b). As noted

451

above, however, sample WX2-33 is an outlier with a 𝜑 value smaller than 41 %. These correlations

452

indicate that the fraction of accessible porosity in clay minerals is greater than that in organic

453

matter. Since the percentage of TOC (< 6.4 % for the tested shales) is small compared to the

454

mineral content, 𝜑 remains greater than 64 % for all these shale samples except WX2-33. Again,

455

the high calcite content of that sample (13.71 %) could be the cause of the low accessible porosity

456

(1.22 %) and pore accessibility (40.26 %) for this sample.

457

Fig. 10 shows the correlations between accessible porosity, 𝜑, and the fractal dimensions and

458

total, fractal and finite porosities. There are negligible correlations between the fractal dimensions

459

and the pore accessibility. However, 𝜑 seems to be anti-correlated with each of the porosity (again

460

with WX2-33 as an outlier). This may be because most of the inaccessible pores are in the organic

461

matter, so that samples with high TOC yield low 𝜑 (Fig. 9b) as well as high ∅ (Fig. 5d). These


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Energy & Fuels

462

results suggest TOC has a more complex structure than the mineral matrix, and that the gas

463

transport pathways are in the minerals rather than in the organic matter, which is where of the

464

methane formed.

465 466

Fig. 10 Correlation between pore accessibility and pore structure for the six Chinese marine shales: Pore accessibility

467

vs. (a) fractal dimensions and (b) porosities (Note: WX2-33 was treated as an outlier in Fig. 10b)

468

3.6 Possible micro-structural reasons for different gas prospectivity

469

The nanoscale accessible pore structure of marine shales is strongly influenced by regional

470

geological conditions. Slight changes in geochemical and mineralogical parameters may greatly

471

influence their nanoscale pore system [69]. In this study, the Lower Silurian Longmaxi Formation

472

and Lower Cambrian Niutitang Formation are lower Paleozoic, organic-rich shales that were

473

deposited in a similar sedimentary environment with similar complex mineral compositions. Both

474

formations have experienced a complex tectonic history involving significant burial, uplift, and

475

erosion, and both are primary targets for shale gas development in China [1].

476

There are, however, large differences in shale gas production between these two formations

477

[3, 7, 70]. Significant commercial gas production has been developed from the Longmaxi shales,

478

but no commercial gas has yet been obtained from the Niutitang shales. The main difference 29 ACS Paragon Plus Environment

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Page 30 of 44

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between the Niutitang and Longmaxi shales is paleo-burial depth. The Longmaxi shale was buried

480

to between 3000-7000 m in the study area, whereas the Niutitang was buried to greater than 6000

481

m. The thermal maturity of both shales reached the over-mature stage, but that of the Niutitang

482

shales was significantly higher than that of the Longmaxi. At this thermal maturity some of the

483

organic matter in the Niutitang shales has been carbonized. During carbonization, a subset of the

484

OM pores may have been destroyed or collapsed, resulting in a decrease of pore accessibility. In

485

addition, because it was buried deeper, the Niutitang Formation experienced more severe

486

compaction, which may have resulted in a decrease in pore size and a change in pore morphology.

487

These differences may partially explain why both 𝐷m and 𝐷s for the Niutitang shales are relatively

488

larger than those of Longmaxi shales (Table 2).

489 490

Fig. 11 Images of diverse graptolites in Longmaxi shales: (a) Abundant graptolites observed in core samples (sample

491

WX2-54); (b) Flattened carbonaceous graptolite fossil observed by SEM (sample WX2-54); (c) Interconnected pore

492

system within graptolite-derived OM (sample WX2-54)

493

An addition whereas all six samples examined in this study can be described as black

494

carbonaceous shales, abundant and diverse graptolite fauna are observed in Longmaxi shales but

495

not in Niutitang (Figs. 11a and b). Numerous nanoscale pores are well developed within the

496

graptolite-derived organic matter [24, 70], which could comprise a complex pore system which

497

may improve the pore accessibility of the Longmaxi shales (Fig. 11c). Despite all of these observed

498

and field-related differences, however, the results of this study (Table 4) show no obvious 30 ACS Paragon Plus Environment

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difference in pore accessibility between Longmaxi and Niutitang shales. This may simply be a

500

factor of the limited dataset in this study, but may also suggest that other factors, such as having

501

reached a minimum maturity level, are controlling, and that the observed differences in recovery

502

are related to larger-scale structures. Thus, a more comprehensive comparison study of the pore

503

structure of the two shale formations, and a correlation of the results with regional patterns of gas

504

production should be considered.

505

3.7 The implication of pore accessibility on methane production in shale

506

Fig. 12a and b show that both the Langmuir volume and pressure decrease with increasing

507

accessible pore fraction (with WX2-33 again an outlier). The higher the pore accessibility the lower

508

the maximum methane adsorption capacity (Fig. 12a). As noted above, 𝑉L increases with

509

increasing TOC (Fig. 7b), and the fraction of accessible pores deceases with increasing TOC and

510

increases with increasing clay content (Fig. 9). Thus, pore accessibility could be an indicator to

511

main chemical properties and methane storage in shale. It means that shale sample with higher

512

pore accessibility will have lower TOC, higher clay and lower methane sorption capacity, vice

513

versa. Since methane adsorption capacity is controlled by micropores, the results indirectly

514

confirm the conclusion that most of the micropores are in the organic matter, which tends to be

515

disconnected in shales. In contrast, higher pore accessibility correlates with lower maximum

516

methane adsorption pressure (Fig. 12b). Shales with a higher affinity for methane will have a lower

517

pressure at half of the maximum adsorption capacity. Thus, pore accessibility could be an indicator

518

to methane transport in shale. Shale sample with a higher pore accessibility tend to have lower 𝑃L

519

(higher methane affinity) - easier pathways for methane adsorption, vice versa, although our

520

sampling size is limited. As 𝑃L decreases with increasing TOC and clay content (Figs. 7c and d),


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

Page 32 of 44

521

the affinity of methane for organic matter, combined with the pore accessibility could dominate

522

the degree of difficulty for methane recovery from the shale nanopores.

523 524

Fig. 12 Correlation between Langmuir constants and pore accessibility for the six Chinese marine shales: (a) Langmuir

525

volume and (b) Langmuir pressure vs. pore accessibility; (c) A schematic of adsorption isotherm affected by the

526

percentage of pore accessibility for shale (Note: WX2-33 was treated as an outlier in Fig. 12a)

527

While it may be surprising to find a relationship between the percentage of accessible pores and

528

methane adsorption capacity in shale, and this relationship needs further testing, if verified it may

529

be useful as a guide to methane production in shale gas reservoirs. Fig. 12c schematically shows

530

the effect of shale pore accessibility on methane adsorption isotherms given the relationships

531

between pore accessibility and 𝑉L and 𝑃L described above. The inverse correlation between the

532

pore accessibility and maximum adsorption capacity suggests that when pore accessibility is low,

533

decreasing transport pathways, maximum methane adsorption 𝑉L, low increases due to a


Page 33 of 44 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

Energy & Fuels

534

simultaneous increase in adsorption sites. However, the data also suggest that under these

535

conditions the affinity of methane gas for the available sites in shale pores decreases. That is, the

536

pressure at half of the maximum adsorption capacity 𝑃L, low increases, so the amount of gas that

537

can be desorbed at a given pressure decreases. The methane adsorption capacity therefore increases

538

gradually with increasing adsorption pressure (Gray line in Fig. 12c). This has a negative effect on

539

shale gas production even with the high total methane adsorption capacity, because relatively little

540

gas is desorbed, and therefore releasable, at a given pressure.

541

Samples with high pore accessibility have a relatively small maximum adsorption, i.e., low

542

values of 𝑉L, high, but with steep adsorption profiles at low pressure and a plateau at high pressure,

543

i.e., low values of 𝑃L, high (Red line in Fig. 12c). That is, relatively more gas can be released at

544

lower pressures, but the maximum amount of gas storable is lower. Therefore, there may be an

545

optimum value for shale pore accessibility that will maximize production of methane in shale

546

reservoirs, and analysis of these values for target shales may help to direct drilling programs. In

547

the short-term, our data suggest that drilling in shale reservoirs with relatively high pore

548

accessibility will allow a significant amount of gas to be quickly produced at a relatively low

549

threshold pressures. In the longer-term, however, gradual production of larger total amounts of

550

methane with decreasing borehole pressures could be achieved for low pore accessibility shales.

551

Thus, the hydraulic fracturing plan may be tailored to control the percentage of accessible pores

552

in shale for the production time and amount during shale gas recovery.

553

4. Conclusions

554

In this study, we have combined FE-SEM, SANS, He porosimetry and volumetric high-

555

pressure adsorption techniques to characterize the geochemical and mineralogical compositions,


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

Page 34 of 44

556

pore structure and methane adsorption of six samples from two Chinese marine shale formations.

557

On the basis of these results, the following conclusions have been drawn:

558

(1) FE-SEM images show that OM pores are the most important pore type, dominating the pore

559

systems of these shales. Intra-particle pores, inter-particle pores and microfractures resulting

560

from sedimentary diagenesis occur between or within mineral grains. Meanwhile, nanoscale

561

pores and microfractures are also influenced by mechanical compaction since both Longmaxi

562

and Niutitang Formations experienced multi-phase tectonic movements.

563

(2) Application of the unified fit model with two pore structures (finite pores and fractal pores) to

564

the SANS data shows that both surface and mass fractals are present. Mass fractals with

565

dimensions ranging between 1.94 and 2.68 are identified for finite pores except for sample

566

QD1-L4 which has a surface fractal dimension of 2.85. For fractal pores, samples QD1-L4,

567

WX2-49 and WX2-54 have mass fractal dimensions ranging between 2.84 and 2.93, while

568

samples QD1-L3, WX2-8 and WX2-33 have a surface fractal dimension ranging between 2.42

569

and 2.78. Total porosity, estimated by the Porod Invariant method, ranges between 2.35 % and

570

16.40 %, while porosity of finite pores ranges between 0.35 % and 6.36 %, and porosity of

571

fractal pores ranges between 2.07 % and 8.51 %.

572

(3) Pore accessibility estimated based on combined helium porosimetry and SANS shows that the

573

fraction of accessible pores is greater than 64 % for most of the samples, except for sample

574

WX2-33 which has only 40.26 % accessible pores, possibly as a result of carbonate

575

precipitation during diagenesis.

576

(4) Clay and TOC have opposite effects on the pore structure. Samples with higher clay contents

577

have higher pore accessibilities, and lower porosities and total methane adsorption capacities.

578

Increasing TOC has the opposite effect. This suggests that, in shales, gas is stored in the organic


Page 35 of 44 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

Energy & Fuels

579

matter, but the transport conduits are through the inorganic matrix, especially through the clay.

580

Thus, the organic matter is the controlling factor for methane storage in shale gas reservoirs,

581

but the inorganic matrix controls gas release.

582

(5) In comparing the two shale formations, both the mass and surface fractal dimensions for

583

Niutitang shales are relatively greater than those of the Longmaxi shales. This may be a result

584

of the relative depths to which the two formations were buried (the depths from which the

585

Niutitang shales were recovered are greater than those of Longmaxi shales).

586

(6) Both Langmuir adsorption capacity and Langmuir pressure decrease with increasing shale pore

587

accessibility. This suggests that, in shales, high pore accessibility may reduce methane

588

adsorption capacity, while low pore accessibility may reduce methane desorption. Pore

589

accessibility could, therefore, become an essential factor in understanding and controlling

590

methane production in shale gas reservoirs.

591

Acknowledgements

592

The authors would like to acknowledge the financial support of the National Natural Science

593

Foundation of China (41802183), the National Postdoctoral Program for Innovative Talents

594

(BX201700282) and the China Postdoctoral Science Foundation (2017M621870). Work by LMA

595

was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy

596

Sciences, Chemical Sciences, Geosciences, and Biosciences Division. This research used

597

resources at the High Flux Isotope Reactor, a DOE Office of Science User Facility operated by the

598

Oak Ridge National Laboratory. Access to NG7 SANS was provided by the Center for High-

599

Resolution Neutron Scattering, a partnership between the National Institute of Standards and

600

Technology and the National Science Foundation under Agreement No. DMR-1508249. The

601

authors declare no competing financial interest. 35 ACS Paragon Plus Environment

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Page 36 of 44

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Disclaimer

603

Certain commercial equipment, instruments, or materials are identified in this paper to foster

604

understanding. Such identification does not imply recommendation or endorsement by the

605

National Institute of Standards and Technology, nor does it imply that the materials or equipment

606

identified are necessarily the best available for the purpose.

607

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