Pore Structure Characteristics of MarineâContinental Transitional

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Pore structure characteristics of marine–continental transitional shale: A case study in the Qinshui Basin, China Zhaodong Xi, Shuheng Tang, Songhang Zhang, and Ke Sun Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b00911 • Publication Date (Web): 11 Jul 2017 Downloaded from http://pubs.acs.org on July 13, 2017

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Pore structure characteristics of marine–continental transitional shale: A case study in the Qinshui Basin, China Zhaodong, Xi 1, 2; Shuheng, Tang *1, 2; Songhang, Zhang 1, 2; Ke, Sun 1, 2 (1. MOE Key Lab of Marine Reservoir Evolution and Hydrocarbon Enrichment Mechanism, China University of Geosciences, Beijing 100083, China; 2. MOLR Key Lab of Shale Gas Resources Survey and Strategic Evaluation, China University of Geosciences, Beijing 100083, China)

* Corresponding author: Email, [email protected]; Phone, +86 10 8232 0601

Abstract: Organic shales deposited in a marine–continental transitional environment are well developed in the Qinshui Basin, northern China. However, previous researches concerning shales have predominantly focused on marine shales and barely on marine–continental transitional shales. In this study, geochemical and mineralogical analyses were performed on 23 marine–continental transitional shale samples obtained from four wells in a currently active shale gas play, Yushe-Wuxiang area in the Qinshui Basin. Furthermore, the complex pore structure of the transitional shales was well characterized by scanning electron microscopy (SEM), mercury intrusion, and low pressure gas physisorption. The results showed the abundance of organic matter (OM) with an average of 2.03% in the target shales. The dominant minerals in the shale were found to be clay and quartz, and the major clay minerals type is kaolinite and illite/smectite. SEM images clearly exhibited that the pores in the shale matrix are mainly associated with clay minerals and OM. Results of mercury intrusion and low pressure gas physisorption indicated the presence of pore volumes (PVs) and specific surface area (SSA) with different scales. The pore size distribution analysis indicated that mesopores were dominant in the shale from the study area. The PV was mainly attributed to the presence of mesopores and macropores and the SSA was mainly associated with the mesopores and micropores. Results of research on factors controlling pore structure development showed that it was principally controlled by clay mineral contents and total organic carbon content. The pore structure characteristics of the marine–continental transitional shale may have contributed to the preservation of shale gas in Yushe-Wuxiang area. This study provides important significance in gaining a comprehensive understanding of the transitional shale pore structure and the shale gas storage-seepage mechanism. Keywords: Coal-bearing shale; Mercury intrusion; Gas physisorption; Pore size distribution; Qinshui Basin

1. Introduction The exploration and development of shale gas in China have gone through two developmental stages since 2005, and recently high yield shale gas flow has been discovered successively in marine shales.1, 2 Up until the end of 2016, more than 800 wells were drilled into the Wufeng-Longmaxi Formation in the Sichuan Basin, of which > 200 wells had shale-gas flows after fracturing. An average output of 22.71 × 104 m3/d (70 wells) of Wufeng-Longmaxi Formation has been obtained.1 So far shale gas exploited in China mostly exists in marine shale gas reservoirs; however, there are several sets of marine–continental transitional shales from which shale gas has been rarely obtained. The transitional shale is mostly interlayered with coal beds, which usually features poor continuity, small thickness of high total organic carbon (TOC) content interval, poor to moderate brittleness index, complex reservoir space and wide change in gas content.1 Moreover, these shales also provide a possibility of co-existence and joint-production of shale gas, coalbed gas, and tight sand gas in the same formation.3 The huge geological reserve of shale gas in marine–continental transitional shale provides a significantly important opportunity for shale gas exploration and production in China. Shale gas may be stored as adsorbed gas on the surface of organic matter (OM) and clay minerals, as free gas in the matrix minerals-related fractures and larger pores, or as dissolved gas in oil and water.4 ACS Paragon Plus Environment

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Nanopores control the major storage space in shale gas reservoirs; therefore, identification of pore systems has a higher research priority because of the increase in the commercial value of shale gas.5–8 Shale gas exploration and development reveal that gas storage, release and flow are controlled by the nano-scale pore system such as the specific surface area (SSA) and geometry pore space (total pore volume (PV) and pore size distribution (PSD)).5 Nano-scale pores are widely recognized as an important component of the shale reservoirs in proven gas shale including the Barnett Shale,7 the Woodford shale9, 10and the Marcellus Formation.11 However, most studies focus only on marine shales9–13and neglect the marine–continental transitional shales. The geological resources of the marine–continental transitional shale in the Qinshui Basin are 0.49 × 1012 m3 and the recoverable resources are 0.11 × 1012 m3.3 Recently, several wells in Yushe-Wuxiang area of the Qinshui Basin were drilled to investigate the transitional shale gas potential in the Lower Permian Shanxi and Carboniferous Taiyuan Formations. The on-site gas content measurement in these wells revealed the presence of high gas content (0-2.81 m3, 1.02 m3 on average) and the complete coring of these two formations provided opportunities to obtain necessary information for evaluating the shale properties. Characterization of nano-scale pore system in shale reservoirs is a challenging task. The predominant presence of nano-scale pores in shale reservoir has been well recognized and considerable progress has been made in adapting different approaches to characterize the nano-scale pore system. Therefore in this study, three laboratory methods, namely, scanning electron microscopy (SEM), nitrogen (N2) and carbon dioxide (CO2) physisorption, and mercury intrusion, were used to characterize the pore structure of marine–continental transitional shale from the study area in the Qinshui Basin. The objective of this study was to present and discuss the features of OM, mineral compositions, pore morphology, PSD, SSA and PV based on the laboratory testing of shale samples, and the mode of influence of TOC and minerals contents on its porosity and development of different-scale pore structure were also discussed.

2. Geological setting The Yushe-Wuxiang area, a monocline striking NE, is located in the east-central Qinshui Basin in the southeastern Shanxi province, northern China (Figures 1a and b). The faults and folds are relatively developed in the study area (Figure 1c). The transitional source rocks were deposited in Taiyuan and Shanxi Formations, and these are the two main coal-bearing strata as presented in Figure 2. The thickness of the Taiyuan Formation varies from 70 to 120 m and conformably overlies the Benxi Formation. The Taiyuan Formation mainly consists of shale, fine-grained sandstones, limestone, and coal seams, which form a barrier coast and carbonate platform sedimentary system. The Shanxi Formation features river-delta marsh sediments, containing thin-bedded fine-grained sandstone and coal, and has spawned the development of three to five sets of dark gray–black shale with thickness in the range of 30–40 m. These characteristics reflect frequent changes in lithology (Figure 2) under the background of a transitional depositional environment.

3. Samples and methods 3.1. Samples In total 23 shale samples were collected from four wells in the study area of the Qinshui Basin at burial depths ranging from 600 to 1650 m (Table 1). Samples QS-1 to QS-9 were obtained from the ZK03-2 well, samples QS-10 to QS-16 were obtained from the ZK07-1 well, samples QS-17 to QS-18 were obtained from the ZK09-1 well, and samples QS-19 to QS-23 were obtained from the ZK10-1 well. 11 of the total samples ACS Paragon Plus Environment

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were obtained from the Shanxi Formation, and the remaining 12 samples were from the Taiyuan Formation. Table 1 lists the marine–continental transitional shale samples along with the measurements applied on each sample. All the 23 samples were tested for TOC content and mineral composition, and analyzed by SEM and N2 physisorption. The pore structure characteristics of 12 samples were analyzed by mercury injection and CO2 physisorption. Some samples, which have relatively integrated suite of test data, were selected for detailed analysis of the shale structure.

3.2. Experimental methods The mineralogical compositions and content of the samples were estimated by X-ray diffraction (XRD) using a Bruker D8 Advance X-ray diffractometer after crushing and sieving the samples powders into grains of size ranging from 200 to 300 mesh, the 2θ range of 4 to 75°. The measured data were analyzed via the basal reflections. The TOC content of the powdered samples was measured using a Leco CS230 carbon/sulfur analyzer. Firstly, samples were weighed and using hydrochloric acid to dissolve carbonates and then the samples were reweighed and combusted in the Leco CS230 at 60-80 degrees Celsius. Five samples were analyzed by vitrinite reflectance test using microscope photometer instruments under oil immersion, and at least 20 reading numbers of each sample obtained using this method. Some samples were further used for kerogen isolation, and the isolated kerogen was used to determine the maceral composition. The relative abundance of the primary maceral composition (i.e., liptinite, vitrinite, and inertinite), which was analyzed under reflected white and fluorescent light, was used to determine the types of OM (i.e., Type I, II1, II2, or III), based on type index (TI).14, 15 Morphology of the pores was characterized by SEM using a Tescan Vega 3 LM system with a maximum resolution of 3 nm. The accelerating voltage used was typically 30 kV, with varying spot size depending on the nature of the imaging being carried out. A Quantachrome Poremaster was used to measure the porosities and PSD in sizes ranging from 6 nm to 20 µm. The procedure involved the use of around 10-20 g of the sample with an approximate size of 20 × 20 mm sample, followed by drying it in an oven at 110 °C for at least 24 h under vacuum. The mercury injection pressure can range up to 3.13 × 104 Psi (215 Mpa), indicating that based on the Washburn equation, mercury can be injected into a pore as small as 6 nm.16 A low-temperature N2 physisorption test was performed using a Micromeritics ASAP 2020 surface area analyzer, which was primarily used to obtain PSD in the range of 1.7–300 nm. N2 adsorption/desorption isotherms were obtained for all samples under relative pressures ranging from 0.01 to 0.99 at 77.35 K, which is lower than the critical temperature of N2 (190.6 K). The Multi-point Brunauer–Emmett–Teller (BET) model17 was used to calculate the SSA, and the Barrett–Joyner–Halenda (BJH) model18 for PV and PSD of shale pores. The samples prepared for CO2 physisorption analysis were first outgassed at 353.1 K under high vacuum in the apparatus to remove air, free water and other gases. CO2 absorption data of 60–80 mesh samples were obtained at 273.0 K for at least 10 h. The tests were performed using a Micromeritics ASAP 2020 surface area analyzer. CO2 absorption data were analyzed by using the Density Functional Theory (DFT) model for SSA and PSD.19, 20

4. Results 4.1. Mineral composition and characteristics of organic matter Previous studies have demonstrated that shale composition, including minerals and OM, strongly influences the pore structure.7,10 The relative geochemical data and mineral percentages for the marine–continental transitional shale samples in this study are listed in Table 2. The dominant minerals in ACS Paragon Plus Environment

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the shale are quartz and clay, with average values of 36.6 and 50.46%, respectively. The quartz contents are between 19 and 57.9%; however, the clay contents range from 12.5 to 87.6%. The kaolinite is the major mineral in clays with an average of 49.38%, followed by illite/smectite (I/S) mixed layers with an average of 38.97%. The mineral compositions for the samples in this study area are similar to those of the transitional shale in the Huainan-Huaibei Coalfield in China;21, 22 however, different from those of Longmaxi black shale in Sichuan Basin23, 24and Chang 7 continental shales in Ordos Basin.25 The transitional shale contains less brittle minerals (such as feldspar and quartz) and more clay minerals than the marine shales, and contains sub-equal amounts of clay, quartz, pyrite and siderite with continental shales. Moreover, both continental shales and marine shales contain less kaolinite which is the major type in transitional shale. The TOC content for the 23 samples varied significantly ranging from 0.32 to 6.41%, with an average of 2.03%. The samples were dominated by Type III kerogen which was supported by the primarily negative values of the TI.26 The predominant Type III kerogen contains a larger range of terrigenous macerals (vitrinite and inertinite) which specifically characterize the marine–continental transitional shale.15 The vitrinite reflectance (Ro) values for available samples range from 1.95–2.24%, showing that the thermal maturity of OM in the study area is at the gas window.

4.2. Characterization of pore morphology by scanning electron microscopy According to the descriptive classification scheme proposed by Loucks et al.10, pores can be subdivided into interparticle (interP) pores (pores between minerals particles and crystals), intraparticle (intraP) pores (pore within particles), and OM pores, and all these three types of pores were clearly observed in this study as shown in Figure 3. By analyzing the types and morphological characteristics of pores in Longmaxi shale by focused ion beam (FIB)-SEM experiments, Yang et al.20pointed out that OM pores are dominant in the organic-rich marine shale while limited and isolated interP, intraP and OM pores are observed in organic-poor samples. The images obtained from the transitional shale indicated that the pores in the shale matrix are mainly associated with clay minerals and OM. (1) OM pores: Most pores are formed during the progressive thermal evolution of OM which vary from nearly spherical to irregular polygonal shape, with slightly irregular ellipsoids being the most common shape (Figures 3a–d). Hundreds of elliptical, round pores were observed in single OM particle and their pore size was less than 100 nm. However, Figures 3b and c exhibit limited and isolated OM pores, which are mainly polyhedral angular and elliptical with pore sizes within nm- and sub-µm range. OM pores are heterogeneously distributed in OM with different shapes and size. This may be attributed to the fact that different types of OM exhibit different levels of porosity through the same thermal maturity.9 (2) InterP pores: These pores are always developed between ductile materials such as clay and OM particles in diagenesis processes, and dispersed and distributed in the matrix. Figures 3e–g shows that the interP pores associated with OM and clay exhibit slit-like openings along the particle boundary. InterP pores in clay minerals are best developed, and these are mainly disordered lamellar slit and wedge-shaped pores. Many pores are linear in shape; however, some pores have triangular shapes, which are defined by the lattice of randomly oriented clay mineral platelets. (3) IntraP pores: These pores are always developed within carbonate and feldspar grains which are chemically unstable and may undergo dissolution. Figure 3h shows that these pores are comparatively larger in size range than other types of pores, from typically hundred nanometers to several microns in diameter. The shapes of the dissolution-related pores are usually irregular, polygonal, and alveolate. IntraP pores within pyrite framboids are not developed because most of them are filled with OM and/or clay minerals.

4.3. Mercury intrusion Figure 4 exhibits the plots of cumulative mercury volume versus pore width, clearly demonstrating the ACS Paragon Plus Environment

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development of three types of curves corresponding to the relationship between mercury injection and ejection. The first-type curves have wide hysteresis loops (Figure 4a). The injection curve increases in the initial stage, indicating the intrusion of significant amount of mercury into pores larger than 10 µm in size. However, the rate of mercury intrusion gradually decreases with a small amount of mercury being injected in the pores with size in the range of 50 nm–10 µm. Further, the mercury injection curves show a distinct increase in slope corresponding to mesopores, indicating that these samples require a very high pressure injection to invade the mesopores, demonstrating poor connectivity and/or difficult accessibility. Figure 4b shows that the second-type curves have narrow hysteresis loops. Significant amount of mercury invades the macropores larger than 10 µm, indicating more development of the microfracture. In the intermediate stage (pores with 50 nm–10 µm), almost no mercury passes into the samples, thus the injection curves become near-horizontal. However, a small slope remains toward the highest pressure of injections which demonstrate the existence of some small mesopores in these shales. Both these two types include a flat mercury ejection curve, indicating that a large amount of mercury is still trapped in the pore network. The third-type curves show that the volume of mercury injection increases with decreasing pore width and the mercury ejection curve decreases with increasing pore width (Figure 4c). These characteristics reflect preferable connectivity between pores and that the pores are mostly open at both ends and a mixture of slit-shaped and ink-bottle-shaped pores was obtained in these samples. According to the shape of mercury injection/ejection curves, the samples are divided into three categories; however, PSD of the shale samples only obtained from the mercury injection data, which is shown in Figure 5 using dV/d(logD) plots, and two types of curves are observed. Figure 5a shows that the dominant volume is mostly controlled by macropores larger than 10 µm, and the pores with size from 50 nm to 10 µm are not developed. The mesopore is not developed in most samples except in sample QS-4 with a peak at 10–30 nm. The second type (Figure 5b) demonstrates lower dV/d(logD) values than the first type. The curves show the presence of a small amount of mercury in the macropores; however, it is mostly intruded in the mesopores. Though, they all have a peak at approximately 10 µm, the macropores with size in the range of 50 to 100 nm of the second type are more developed than the first type. Furthermore, the mesopore-bimodal curves show that the peak varies among samples. Samples QS-1, QS-6, QS-11, and QS-13 have a peak at approximately 6–10 nm, and sample QS-2 exhibits a peak at 18 nm.

4.4. Nitrogen physisorption 4.4.1. Nitrogen adsorption–desorption isotherms and pore geometry Figure 6 shows that the adsorption branch of N2 adsorption–desorption isotherms can be divided into three stages27: The steep uptake (micropore filling) at the relative pressures less than 0.01, the adsorption branch, which steadily increases at medium relative pressures ranging from 0.4–0.8 (multilayer adsorption), and sharp uptake (even when P/Po approaches 1.0, the adsorption branch does not show a plateau), thus indicating that the samples possess a heterogeneous pore structure containing a broad range of pore sizes from micropores to macropores. The shape of hysteresis loops indicates the presence of two groups of adsorption–desorption curves. The first group samples are intermediate between types H3 and H2 according to IUPAC classification, which are mainly associated with slit- and wedge-shaped pores, and narrow neck pores.28 The second group samples are intermediate between types H3 and H4, indicating the presence of a large sheet grain matrix and the main types of pore geometry are plate, sheet crack, and mixed-pore. The actual pore shape may include a combination of different pore types which have been observed in the SEM images; therefore, the two methods should be integrated to analyze the pore shape.

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4.4.2. Pore size distribution The BJH models are one of the popular models used in N2 physisorption experiments for calculating the PSD in porous materials. Both the adsorption and desorption branches of the isotherm could be established by using the BJH models.6, 8, 29 Figure 7 demonstrates that all samples (a representative sample was selected as shown in Figure 7a) except QS-19 yield an apparent peak at approximately 4 nm in the PSD curves calculated by the BJH model using the desorption branch. However, the peak is missing in the PSD curves of adsorption branch, indicating that it is an artificial peak that may affect the accuracy of the PSD. Artificial peaks are mainly caused by tensile strength effects.30 The PSD curves calculated by the BJH model using the desorption branch for sample QS-19 display two peaks at approximately 4 and 80–100 nm, which are similar to the PSD curves of adsorption branch (Figure 7b). This characteristic indicates that the artificial peaks can be eliminated, and Li et al.31stated that the PSD data of the BJH model derived from the desorption branch can be corrected when the percentage of pores with sizes less than 10 nm is less than 10%. Clarkson et al.32 concluded that, for the tight sandstone, the PSD calculated from the adsorption branch was close to the USANS/SANS results. Owing to the existence of artificial peaks corresponding to desorption branch of most samples, herein the N2 adsorption branch data were used to investigate the PSD. The dV/dlog (D) versus D plot is widely used to display PSD which highlights the PV distribution.33 Figure 8a shows that all samples have bimodal curves and their peaks are at about 3 and 10–30 nm, and most samples exhibit a notable decrease between 2–3 nm. Figure 8b shows that pores with diameters of 2–10 nm provide the main volume and the PV decreases with the increasing pore size in the range of less than 10 nm. However, pores with diameters in the range of 10–100 nm are considerable and the curves have tailing phenomena, indicating the existence of a number of macropores within the samples. The dV/d(logD) values of the third type (Figure 8c) is significantly lower than the other two, indicating that all pores with diameters ranging from 1.7 to 300 nm are not developed.

4.5. Carbon dioxide physisorption Adsorption isotherms of CO2 are type I curves as classified by IUPAC (Figure 9). The shales with relatively well developed micropores have more SSA and are more sensitive to the amount of CO2 absorbed than those with less micropores (Table 3). Rapid increase in absorption occurs at relatively low pressures; however, after a certain pressure is acquired further increase in absorption does not occur because of full charging in the micropores. Plots of micropore volume versus pore width from CO2 physisorption are displayed in Figure 10. Most samples have three peaks, respectively, in the range of 0.35–0.40 nm, 0.50–0.60 nm, and 0.70–0.85nm. Pores with a diameter less than 0.9 nm mainly contribute to the micropore volume. When the pore width is greater than 0.9 nm, all the samples have analogous curves. The increase in rate of micropore volume is very low and the distribution characteristic is similar among different samples.

5. Discussion 5.1. Characteristics of pore volume and specific surface area The pores in shale cover a significantly large range of PSD and no available methods can independently characterize the PSD, SSA, and PV of all the types of pores. Many previous studies have indicated that mercury intrusion is an appropriate method for investigating macropores, low-pressure N2 physisorption is reliable for mesopores, and CO2 physisorption is precise at the micropore level.25, 34, 35 For more comprehensive analysis of the PSD, integration of three fluid invasion methods is necessary. The SSA and ACS Paragon Plus Environment

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PV of micropore (50 nm) were obtained by using the Washburn equation via mercury intrusion (Table 3). Figure 11 exhibits the maximum contribution of the mesopore in most samples to SSA and PV. The average of PV and SSA percentage of mesopores is 56 and 77%, respectively. Owing to larger pore size of macropores, the PV percentage is typically between 22 and 53%, which corresponds to the moderate contribution to the PV; however, the contribution to SSA is negligible. The PV percentage of micropores is typically between 0.2 and 5%, but its SSA percentage is up to approximately 41%.

5.2. Analysis of factors controlling development of pores in shales Geological controls of pore structure, such as TOC content, thermal maturity and mineralogy, have been discussed in many previous studies.8–13, 20, 36 In this study, the values of PV and SSA of the mesopores obtained by N2 physisorption experiments could be considered as representative of the entire PV and SSA of samples to analyze the factors controlling shale pore development. There are two reasons as follows: (1) as mentioned above, mesopores correspond to the dominant pore size in the transitional shale with the largest SSA and PV. Moreover, Figure 12 shows a good positive correlation between total PV, SSA, and mesopore volume, and SSA with the correlation coefficient R2 of 0.83 and 0.95, respectively, and (2) N2 physisorption experimental analysis is an effective method for studying the mesopore. All the 23 samples were tested and the more the data, the more the accuracy. Jiang et al.25also considered the values of the mesopores to study the effect of geological factors on continental shale pore development. Thus, in this study, the pore development was analyzed based on controlling factors of the shale by determining factors associated with mesopore PV and SSA. 5.2.1. Relationships between mesopore specific surface area, pore volume, and average pore size Figure 13 shows the relationship between mesopore PV, SSA, and average pore diameter. A positive correlation is observed between SSA and PV (Figure 13a), and negative correlations are observed between the average pore diameter and PV and SSA (Figures 13b and c). These observations are in accordance with the research results of pore structure characteristics of the Upper Triassic Yanchang Formation of the Ordos Basin reported by Liu et al. and Jiang et al.25, 37. However, the correlation between PV and SSA is stronger than that in the Longmaxi Formation shales in Sichuan Basin38. These differences are related to variations in the pore structure. The Longmaxi Formation shales consist mainly of a large number of OM pores, and therefore have high SSA and relatively low PV. The marine–continental transitional shale consists not only of OM pores but also some large mineral-related pores, leading to a larger PV than the marine shale which indicates higher gas storage capacity for both free and adsorbed gas. 5.2.2. Effect of total organic carbon content on pore structure According to previous studies29, 33, 37, TOC content is the most important factors for determining the shale pore structure. The influences of TOC content on the SSA and PV are illustrated in Figure 14. Clearly, a positive relationship is observed among SSA, PV, and TOC values. However, notably, the relationship between SSA, PV, and TOC content is much weaker than the results obtained from the studies related to North America and South China shales.12, 29 These differences may be attributed to the type of kerogen. The marine shales (such as Longmaxi and Niutitang Formations) are dominated by Type II or Type I kerogen which exhibit higher SSA and PV than the transitional shale in high-postmature stage.13, 38–41 The slow rate of hydrocarbon generation is one of the characteristics for Type III kerogen which has a smaller volume loss associated with devolatilization during maturation than Type II or Type I kerogen. Pan et al.39 also suggested that the contribution of per gram OM to the porosity is only 0.29% for Permian marine–continental ACS Paragon Plus Environment

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transitional shales with TOC content less than 12% in the Lower Yangtze region, which is significantly lower than that of the marine shale with dominated oil-prone kerogen (with a similar maturity). However, Bu et al.22 stated that though the data in the plot of TOC content versus SSA are relatively scattered, OM contributes significantly to the SSA in non-marine shales from the Huainan. In this study, a large number of OM pores could be observed by SEM and the correlation between TOC content and SSA is relatively well except in organic-poor samples (TOC < 1% in this study). Therefore, it was asserted that pores associated with OM and caused by hydrocarbon generation and expulsion are still a major shale pore component for marine–continental transitional shale. TOC content is one of the major factors controlling the pore structure of the organic-rich transitional shale. 5.2.3. Effect of clay minerals on pore structure A slightly positive correlation can be observed between PV, SSA, and the clay mineral content, as shown in Figure 15. Previous studies showed the existence of complicated relationships between clay minerals and pore development.42–44 On the one hand, the degree of development of pores is different in different types of clay minerals. On the other hand, some clay minerals can be transformed with evolution and many pores are developed or diminished. With the increase in the clay mineral content, the values of PV and SSA also gradually increase in this study. This relationship coincides with the results of the previous studies related to Chang-7 continental shale from the Upper Triassic Yanchang Formation, Ordos Basin,37, 45 Fort Simpson shales from northern British Columbia, western Canada,46 and Wufeng-Longmaxi shale in Sichuan Basin.30 Noteworthy, the data are scattered when the TOC content is less than 1% as shown in Figure 14a; however, this phenomenon disappears in the plot of SSA vs. total clays (Figure 15). This might indicate that when the TOC content was less than 1%, the clay minerals content was the dominant factor controlling the development of pore structure in organic-poor shale samples. Even though, the clay-rich marine O3w-S1l shales47, 48, with the comparable TOC content, still make a contribution of clay minerals to the pore system, which is consistent with this study. The kaolinite and I/S are the major clay mineral types in the shale samples. The positive linear correlations between kaolinite content and SSA (Figure 16a) reveal that the kaolinite possesses a significant quantity of nanopores and thus contributes substantially to the SSA of the transitional shales. However, I/S contents are negatively correlated with SSA (Figure 16b). Notably, previous studies have indicated that I/S possesses much more SSA than other clay mineral types,42, 49 therefore these negative correlations must be forcibly produced and driven by the negative correlation between I/S and kaolinite (Figure 16d). Moreover, no correlations were found between kaolinite, I/S, and PV in this study (Figure 16c). Kaolinite has a relatively high SSA because of its poor crystallization,50 and I/S is the dominant type clays with micropores and small mesopores in natural shales.51 New pores are developed due to layer collapse and mineral grain contraction during the dehydration and illitization, resulting in the growth of number of micro–mesopores.52, 53 Therefore, clay minerals mainly contribute to the SSA. 5.2.4. Relationships among shale organic matter, inorganic minerals and porosity The porosity (from mercury intrusion) of the 12 samples ranges between 1.66 and 9.36%, with an average of 4.53%. Except for sample QS-10, an obvious positive relationship was observed between the porosity and TOC content, with the intercept of 1.38 (Figure 17a). A porosity of 1.38% is obtained when the regression line is extrapolated to TOC = 0. We then assumed that this value is the porosity contributed by inorganic pores because the content of TOC is zero. Certainly, the validity of this assumption depends on our test data and the more data, the more the accuracy. Thus the pores contributed by the OM porosity are estimated in the range of 17–85.2% of the total porosity. Sample QS-10 has a porosity of up to 9.36%; however, its TOC value is only 1.81%, indicating the presence of more mineral matrix pores than other samples. However, sample QS-10 is also beyond the normal trends in the plot of porosity vs. clay minerals ACS Paragon Plus Environment

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(Figure 17b), indicating the contribution of other factors to the porosity. We assume that it is probably the quartz that contributes to this additional porosity because we found that the quartz content of sample QS-10 was the highest among all the samples. The high content of quartz has an important influence on pores preservation because it could have provided a rigid framework to preserve pores after they were formed. However, there is no relationship between quartz and the porosity (Figure 17c), and no obvious relationships are observed between quartz, SSA, and PV. The relationships among quartz content, porosity, and pore structure parameters are opposite to those mentioned in the previous studies on marine shales.8, 12, 20 Distinct correlations in different areas may relate to the origin of quartz, sedimentary environment, or diagenetic maturity. The marine–continental transitional shales in the study area were deposited in a typically transitional environment and the origin of quartz is mainly terrigenous;20, 40 however, the marine shale is deposited in a deep-water shelf sedimentary environment where the quartz is mainly of biogenic origin. Therefore, detailed investigations on the shapes and structures of terrigenous quartz should be carried out in the future study.

5.3. Effect of pore structure on gas preservation The evaluation of gas content, which was measured for samples obtained from the ZK03-2 well using canister desorption at the drilling site, showed that the measured gas contents for 57 samples varied between 0.09 and 2.41 m3/t with an average value of 0.85 m3/t. Though the marine–continental transitional shales from the study area are defined as poor to fair source rock compared to marine shale in the Sichuan Basin23, 24 , the on-site gas content measurement in the well revealed a high gas content which indicates that the gas in the shale is well-preserved. Moreover, burial-history curves further highlight the good preservation of shale gas in the Yushe-Wuxiang area (Figure 18). This reconstruction suggests the following four main stages: (1) an initial stage, encompassing relatively gentle subsidence in the Late Carboniferous-Permian; (2) a second stage of rapid subsidence and burial in the Triassic; (3) a third stage determined by encompassed relative gentle erosion and subsidence in the Jurassic–Early Cretaceous; and (4) a fourth stage determined by uplift and removal of overburden in the Early Cretaceous-Tertiary. According to this reconstruction, the target shale source beds included a primary phase of gas generation in the Early Triassic, and a secondary phase of gas generation in the Early–Middle Cretaceous. Though the majority of gas in the shale source beds experienced relatively simple thermal history in the study area, the shale still experienced subsequent folding and uplifting by the orogenesis. Even so, the gas in the shale could still be well-preserved probably due to the pore structure characteristics. On the one hand, the SEM images, combined with the mercury intrusion and low pressure gas physisorption results, have shown that the target shale mainly exhibited the development of nanoscale pores. Thus, the target shale may have a very high capillary pressure, making it difficult for the hydrocarbon to travel through the shale. On the other hand, Type III kerogen and clay minerals have a strong methane adsorption capacity which contributes to the preservation of shale gas.50, 51, 54

6. Conclusions (1) The marine–continental transitional shale samples contain abundant organic carbon, with TOC content in the range of 0.32 to 6.41%, and suitable maturity that ranges from 1.95 to 2.24%. The pores in the target shale are well developed and mainly associated with clay minerals and OM, showing potential for hydrocarbon generation for the marine–continental transitional shale from Yushe-Wuxiang area in the Qinshui Basin; (2) Mercury intrusion and N2 and CO2 physisorption analysis were utilized for the effective analysis of the all-scale PSD. According to the results, mesopores were dominant in the shale, and thus significantly ACS Paragon Plus Environment

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contributed to the PV and SSA. (3) The controlling factors for the pore structure of marine–continental transitional shale from Yushe-Wuxiang area were found to be TOC content and clay minerals. In contrast, the impact of the quartz content on shale pore structure was found to be relatively weak. The pore structure characteristics of the marine–continental transitional shale may have contributed to the preservation of shale gas in the study area. (4) Overall, the differences between marine shales and marine–continental transitional shales are as follows: (a) Type of OM: marine–continental transitional shales are typically enriched in vitrinite/inertinite macerals as opposed to liptinite-rich marine shales; (b) Mineral compositions: marine–continental transitional shales are typically enriched in clay minerals as opposed to silica mineral-rich marine shales. These two major differences of marine and transitional shales lead to different pore systems.

Acknowledgements This work was financially supported by the National Natural Science Foundation of China (Grant No. 41272176/D0208). The authors also greatly acknowledge the Shanxi Coal Geology survey and mapping institute for samples support and their permission to publish the results of this study.


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References: [1] Zou, C. N.; Dong, D. Z.; Wang, Y. M.; Li, X. J.; Huang, J. L.; Wang, S. F.; Guan, Q. Z.; Zhang, C. C.; Wang, H. Y.; Liu, H. L.; Bai, W.H.; Liang, F.; Lin, W.; Zhao, Q.; Liu, D. X.; Yang, Z.; Liang, P. P.; Sun, S. S.; Qiu, Z. Petro. Explor. Develop. 2015, 42(6), 753–767. [2] Zhao, W. Z.; Li, J. Z.; Yang, T.; Wang, S. F.; Huang, J. L. Petro. Explor. Develop. 2016, 43(5), 547–559. [3] Jiang, W. L. Shale Gas Resource Potential in North and Northeast China; Beijing: China University of Geosciences, 2012; P116-117. [4] Curtis, J. B.AAPG Bull. 2002, 86 (11), 1921–1938. [5] Yang, R.; He, S.; Hu, Q. H.; Sun, M. D.; Hu, D. F.; Yi, J. Z. Fuel. 2017, 197, 91–99. [6] Clarkson, C. R.; Freeman, M.; He, L.; Agamalian, M.; Melnichenko, Y. B.; Mastalerz, M.; Bustin, R. M.; Radlinski, A. P.; Blach, T. P. Fuel. 2012, 95(1), 371–385. [7] Loucks, R. G.; Reed, R. M.; Ruppel, S. C.; Jarvie, D. M. J. Sediment. Res. 2009, 79(12), 848–861. [8] Hu, J. G.; Tang, S. H.; Zhang, S. H. J. Nat. Gas. Sci. Eng. 2016, 28(6), 522–535. [9] Curtis, M. E.; Cardott, B. J.; Sondergeld, C. H.; Rai, C. S. Int. J. Coal Geol. 2012, 103(23), 26–31. [10] Loucks, R. G.; Reed, R. M.; Ruppel, S. C.; Hammes, U. AAPG Bull. 2012, 96(6), 1071–1098. [11] Milliken, K. L.;Rudnicki, M.; Awwiller, D. N.; Zhang, T. W. AAPG Bull. 2013, 97(2), 177–200. [12] Chalmers, G. R. L.; Bustin, R. M.; Power, I. M. AAPG Bull. 2012, 96(6), 1099–1119. [13] Hao, F.; Zou, H. Y.; Lu, Y. C. AAPG Bull. 2013, 97(8), 1325–1346. [14] Yang, W. L., Li, Y. K.; Gao, R. Q.; Guo, Q. F. Sci. China. 1981, 3(08), 1000–1008. [15] Dang, W.; Zhang, J. C.; Tang, X.; Chen, Q.; Han, S. B.; Li, Z. M.; Du, X. R.; Wei, X. L.; Zhang, M. Q.; Liu, J.; Peng, J. L.; Huang, Z. L. J. Nat. Gas. Sci. Eng., 2016, 28, 639–650. [16] Washburn, E. W. P. Natl. Acad. Sci. USA. 1921, 115–116. [17] Brunauer, S.; Emmett, P. H.; Teller, E. J. Am. Chem. Soc. 1938, 60(2), 309–319.


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[18] Barrett, E. P.; Joyner, L. G.; Halenda, P. P. J. Am. Chem. Soc. 1951, 73(1), 373–380. [19] Wei, M. M.; Zhang, L.; Xiong, Y. Q.; Li, J. H.; Peng, P. A. Micropor. Mesopor. Mat. 2016, 227, 88-94. [20] Yang, R.; He, S.; Yi, J. Z.; Hu, Q. H. Mar. Petrol. Geol. 2016, 70, 27–45. [21]Wang, G. C.; Ju, Y. W.; Yan, Z. F.; Li, Q. G. Mar. Petrol. Geol. 2015, 62 (1), 1–13. [22] Bu, H. L.; Ju, Y. W.; Tan, J. Q.; Wang, G. C.; LI, X. S. J. Nat. Gas. Sci. Eng. 2015, 24, 166–177. [23] Jiao, K.; Yao, S. P.; Liu, C.; Gao, Y. Q.; Wu, H.; Li, M. C.; Tang, Z. Y. Int. J. Coal Geol. 2014, 128(3), 1–11. [24] Chen, S. B.; Zhu, Y. M.; Qin, Y.; Wang, H. Y.; Liu, H. L.; Fang, J. H. Mar. Petrol. Geol. 2014, 57, 619–630. [25] Jiang, F. J.; Chen, D.; Wang, Z. F.; Xu, Z. Y.; Chen, J.; Liu, L.; Huang, Y. Y, Liu, Y. Mar. Petrol. Geol. 2016, 73, 554–571. [26] Cao, Q. Y. Petro. Explor. Develop. 1985, 5, 14–23. [27] Tang, H. M.; Wang, J. J.; Zhang, L. H.; Guo, J. J.; Chen, H. X.; Liu, J.; Pang, M. Feng, Y. T. J. Petro. Sci. Eng. 2016, 143, 1–7. [28] Sing, K. S.; Everett, D. H.; Haul, R. A. W.; Moscou, L.; Pierotti, R. A.; Rouquerol, J.; Siemieniewsha, T. Pure Appl. Chem. 1985, 57(2), 603–619. [29] Xiong, J.; Liu, X. J.; Liang, L. X. J. Nat. Gas. Sci. Eng. 2015, 22, 530–539. [30] Groen, J. C.; Peffer, L. A. A.; Pérez–Ramírez, J. Micropor. Mesopor. Mat. 2003, 60(1–3), 1–17. [31] Li, J. J.; Yin, J. X.; Zhang, Y. N.; Lu, S. F.; Wang, W. M.; Li, J. B.; Chen, F. W.; Meng, Y. L. Int. J. Coal Geol. 2015, 152, 39–49. [32] Clarkson, C. R.; Solano, N.; Bustin, R.; Bustin, A.; Chalmers, G.; He, L.; Melnichenko, Y. B.; Radlinski, A.; Blach, T. P. Fuel. 2013, 103(1), 606–616. [33] Tian, H.; Pan, L.; Xiao, X. M.; Wilkins, R. W. T.; Meng, Z.; Huang, Z. A. Mar. Petrol. Geol. 2013, 48, 8–19. [34] Mastalerz, M.; Schimmelmann, A.; Drobniak, A.; Chen, Y. Y. AAPG Bull. 2013, 97, 1621–1643. [35] Wang, Y.; Zhu, Y. M.; Chen, S. B.; Li, W. Energy & Fuels. 2014, 28, 945–955. [36] Bustin, R. M.; Bustin, A. M. M.; Cui, X.; Ross, D. J. K.; Murthy, P.V.S. SPE. 2008, 119892.


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[37] Liu, X. J.; Xiong, J.; Liang, L. X. J. Nat. Gas. Sci. Eng. 2015, 22(7), 62–72. [38] Cao, T. T.; Song, Z. G.; Wang, S. B.; Xia, J. Sci. China Earth Sci. 2015, 58(4), 510–522. [39] Pan, L.; Xiao, X. M.; Tian, H.; Zhou, Q.; Chen, J.; Li, T. F.; Wei, Q. Int. J. Coal Geol. 2015, 146, 68–78. [40] Xi, Z. D.; Tang, S. H.; Li, J.; Li, L. Nat. Gas. Geosci. 2017, 28(3), 366–376. [41] Xi, Z. D.; Tian, Z. B.; Tang, S. H. Geol. Chin. 2016, 43(6), 2059–2069. [42] Ji, L. M.; Zhang, T. W.; Kitty, L. M.; Qu, J. L.; Zhang, X. L. Appl. Geochem. 2012, 27(12), 2533–2545. [43] Wu, J. G.; Liu, D. M.; Yao, Y. B. Oil Gas Geol. 2014, 35(4), 542–550. [44] Guo, X. S.; Li, Y. P.; Liu, R. B.; Wang, Q. B. Nat. Gas. Geosci. 2014, 33(2), 9–16. [45] Fu, H. J.; Wang X. Z.; Zhang, L. X.; Gao, R. M; Li, Z. T.; Xu, T.; Zhu, X. L.; Xu, W.; Li, Q. J. Nat. Gas. Sci. Eng. 2015, 26, 1422–1432. [46] Ross, D.J.K.; Bustin, R. M. Mar. Petrol. Geol. 2009, 26, 916–927. [47]Rexer, T. F.; Mathia, E. J.; Aplin, A. C.; Thomas, K. M. Energy & Fuels. 2014, 28, 2886–2901. [48]Zhang, X.; Liu C. L.; Zhu, Y. M.; Chen, S. B.; Wang, Y.; Fu, C. Q. J. Nat. Gas. Sci. Eng. 2015, 27, 321–335. [49]Kuila, U.; Prasad, M. Geophys. Prospect. 2013, 61, 341–361. [50] Tang, S. H.; Fan, E. P. J. China Coal Soc. 2014, 39(08), 1700–1706. [51] Fan, E. P.; Tang, S. H.; Zhang, C. L.; Guo, Q. L.; Sun, C. H. Energ. Explor. Exploit. 2014, 32(6), 927–942. [52] Zhao, X. Y. Acta Sedimentol. Sin. 1990, 2, 67–73. [53] Jarvie, D. M.; Hill, R. J.; Ruble, T. E.; Pollastro, R.M. AAPG Bull. 2007, 91(4), 475–499. [54] Zhang, T. W.; Ellis, G. S.; Ruppel, S. C.; Milliken, K., Yang, R. S. Org. Geochem. 2012, 47(6), 120–131.


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Figure 1 (a) Location of the Qinshui Basin in China; (b) The study area in the east-central Qinshui Basin; and (c) Geological structure of the study area and the locations of sampling wells.


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Figure 2 Stratigraphic column showing the black shales in Taiyuan and Shanxi Formations of the study area and their sedimentary environments


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Figure 3 SEM images of OM pores and inorganic mineral pores in the samples: (a) Sample QS-4; (b) and (c) Sample QS-7; (d) and (f) Sample QS-10; and (e), (g) and (h) Sample QS-20


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Figure 4 Three types (a–c) relationships between mercury injection and ejection and the pore diameter of the shale samples in the study area.


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Figure 5 Two types (a–b) of PSD using mercury intrusion of the shale samples


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Figure 6 Low-temperature N2 adsorption–desorption isotherms.


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Figure 7 PSD derived from N2 adsorption and desorption branches of isotherm using BJH model: (a) A representative sample QS-18 and (b) Sample QS-19


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Figure 8 Three types (a–c) of the PSD using N2 adsorption branch data of the shale samples in the study area.


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Figure 9 The absorption curves of the transitional shale samples measured by CO2 adsorption in the study area


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Figure 10 PSD derived from CO2 adsorption using DFT model.


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Figure 11 (a) The SSA percentages and (b) PV percentages for shale samples in the study area


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Figure 12 Relationships between the mesopores PV and SSA and total PV and SSA for the shale samples: (a) the correlation between mesopore PV and total PV and (b) the correlation between mesopore SSA and total SSA.


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Figure 13 Correlations between the PV, SSA and average pore diameter for shale samples: (a) Positive relationship between PV and SSA and (b) and (c) Negative relationships among average pore diameter, SSA and PV.


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Figure 14 Relationships between pore structure parameters and the TOC content: (a) Correlation between mesopore SSA and TOC content (the red points represent the samples with the TOC content less than 1%) and (b) Correlation between mesopore PV and TOC content.


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Figure 15 Relationships between pore structure parameters and the clay minerals: (a) SSA (the red points represent the samples with TOC content less than 1%) and (b) total PV


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Figure 16 Relationships between pore structure parameters, kaolinite and I/S contents: (a) Correlation between mesopore SSA and kaolinite content; (b) Correlation between mesopore SSA and I/S content; (c) Relationships between mesopore PV kaolinite and I/S contents; (d) Correlation between kaolinite and I/S contents


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Figure 17 Relationships between TOC content, clay minerals, quartz and porosity: (a) Correlation between TOC content and porosity, (b) Correlation between clay minerals content and porosity, and (c) Correlation between quartz content and porosity.


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Figure18 Burial-history reconstruction for source rocks in the Yushe-Wuxiang area


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Table 1 The marine–continental transitional shale samples in the study area and applied measurements

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Experimental methods Sample ID

Well no.

Formation

Area

XRD

Ro

TOC

SEM

CO2

N2

Mercury

physisorption

physisorption

injection

QS–1

ZK03–2

Shanxi

Qinshui Basin

√

√

√

√

√

√

QS–2

ZK03–2

Shanxi

Qinshui Basin

√

√

√

√

√

√

QS–3

ZK03–2

Shanxi

Qinshui Basin

√

√

√

√

√

√

QS–4

ZK03–2

Shanxi

Qinshui Basin

√

√

√

√

√

√

QS–5

ZK03–2

Taiyuan

Qinshui Basin

√

√

√

QS–6

ZK03–2

Taiyuan

Qinshui Basin

√

√

√

√

QS–7

ZK03–2

Taiyuan

Qinshui Basin

√

√

√

√

√

√

QS–8

ZK03–2

Taiyuan

Qinshui Basin

√

√

√

√

√

√

√

QS–9

ZK03–2

Taiyuan

Qinshui Basin

√

√

√

√

√

√

QS–10

ZK07–1

Shanxi

Qinshui Basin

√

QS–11

ZK07–1

Shanxi

Qinshui Basin

√

QS–12

ZK07–1

Shanxi

Qinshui Basin

QS–13

ZK07–1

Shanxi

QS–14

ZK07–1

Shanxi

QS–15

ZK07–1

QS–16 QS–17

√

√ √

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

Qinshui Basin

√

√

√

√

√

√

Qinshui Basin

√

√

√

√

Shanxi

Qinshui Basin

√

√

√

√

ZK07–1

Shanxi

Qinshui Basin

√

ZK09–1

Taiyuan

Qinshui Basin

√

QS–18

ZK09–1

Taiyuan

Qinshui Basin

QS–19

ZK10–1

Taiyuan

QS–20

ZK10–1

Taiyuan

QS–21

ZK10–1

Taiyuan

QS–22

ZK10–1

QS–23

ZK10–1

√

√

√

√

√

√

√

√

√

√

√

Qinshui Basin

√

√

√

√

Qinshui Basin

√

√

√

√

Qinshui Basin

√

√

√

√

Taiyuan

Qinshui Basin

√

√

√

√

Taiyuan

Qinshui Basin

√

√

√

√

√

Note: XRD: X-ray diffraction; Ro: Vitrinite reflectance values


Page 33 of 34

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 Table 2 Geochemical data and mineralogical compositions of the shale samples.

Sample

Ro

ID

(%)

TOC

TI

Mineral composition (%)

Type

Qtz.

QS–1

0.72

–64

III

32.8

QS–2

0.32

–25

III

19

QS–3

Fel.

Cal.

Py. 1

Sd.

Clay

K

I/S

67.2

52.7

47.3

67.5

12.5

33.4

66.6

73

70

30

9.4

52.8

35.9

54.5

59

81.9

18.1

43.1

50.1

34.8

87.6

81.6

18.4

30.2

68.3

31.7

2.06

–74

III

25.6

QS–4

2.07

–39

III

37.8

QS–5

5.21

–54

III

41

1.81

–72

III

46.9

3.21

–77

III

12.4

3.38

–78

III

57.9

QS–9

0.87

–79

III

42

58

34.5

50.3

QS–10

1.81

–74

III

49.8

50.2

57.8

33.2

0.81

–78

III

42.3

57.7

31

51.8

QS–12

0.97

–44

III

48.5

QS–13

3.08

–47

III

38.1

QS–14

0.56

QS–15

1.58

QS–16

2.69

QS–6

2.05

(%)

OM

2.13

QS–7 QS–8

QS–11

QS–17

2.2

2.24

1.95

6.41

–52

III

1.2

1.9 2.6

51.5

37.4

56.9

61.9

53.2

46.8

2.4

42.7

45

37

0.3

31.1

1.7

40.7

2.3

4

7.6

5.8

39.8

43

44

27.8

3.4

2.2

20.3

8.4

38.5

37

43

3

1.3

1.3

3.6

63.4

74

12

–48

III

30

16.4

QS–18

2.07

1.4

48.4

33

32

QS–19

1.18

–74

III

43.5

36.5 1.3

4.3

5.1

32

49

32

QS–20

1.55

–68

III

40.8

3.6

7.9

1.6

51.1

39

39

QS–21

1.48

33.7

3

QS–22

0.62

37.5

3.6

QS–23

3.37

26.2

2.8

0.6

0.7 15.2

8.9

43.3

29

3.5

52.1

43

7.3

44.6

56

Note: TI = type index; Qtz.: Quartz.; Fel.: Feldspar; Cal.: Calcite; Py.: Pyrite; Sd.:Siderite; K= Kaolinite; and I/S=illite/smectite


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 34

Table 3 PV and SSA obtained by combining mercury intrusion with N2 and CO2 physisorption for marine–continental transitional shale in the Qinshui Basin, China Specific surface area (m2/g)

Sample ID

Pore volume(cm3/g)

Micropore

Mesopore

Macropore

Total

Micropore

Mesopore

Macropore

Total

(50nm)

SSA

(50nm)

PV

QS–1

5.17

9.1

0.122

14.39

0.0014

0.022

0.0067

QS–2

1.54

2.13

0.026

3.69

0.00054

0.007

0.0041

0.011

QS–3

5.79

13.24

0.086

19.12

0.00089

0.023

0.021

0.045

QS–4

2.17

9.45

0.204

11.83

0.0015

0.024

0.028

0.053

QS–6

0.88

9.58

0.209

10.67

0.0013

0.022

0.02

0.042

QS–7

8.86

17.17

0.464

26.49

0.00099

0.024

0.026

0.051

QS–8

1.28

5.51

0.037

6.82

0.0001

0.016

0.0083

0.025

0.03

QS–9

4.36

8.54

0.224

13.12

0.00039

0.021

0.014

0.036

QS–10

6.42

13.9

0.142

20.46

0.00016

0.026

0.031

0.058

QS–11

1.87

8.91

0.228

11

0.00034

0.024

0.027

0.052

QS–12

1.95

4.37

0.045

6.36

0.00021

0.016

0.0077

0.024

QS–13

2.19

7.87

0.088

10.14

0.00002

0.02

0.009

0.029


Pore Structure Characteristics of MarineâContinental Transitional

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