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Facilitated Diffusion of Methane in Pores with a Higher Aromaticity Yuanli Hu, Qiang Zhang, Mingrun Li, Xiulian Pan, Bin Fang, Wei Zhuang, Xiuwen Han, and Xinhe Bao J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.6b07500 • Publication Date (Web): 09 Aug 2016 Downloaded from http://pubs.acs.org on August 13, 2016

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Facilitated Diffusion of Methane in Pores with a Higher Aromaticity †‡

§





§

§

Yuanli Hu, , Qiang Zhang, Mingrun Li, Xiulian Pan, Bin Fang, Wei Zhuang, Xiuwen Han, and Xinhe Bao*, †





State Key Laboratory of Catalysis, Dalian Institute of Chemical Physics, Chinese Academy of

Sciences, 457 Zhongshan Road, Dalian 116023, China ‡

Graduate University of Chinese Academy of Sciences, Beijing 100049, China

§

State Key Lab of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese

Academy of Sciences, 457 Zhongshan Road, Dalsian 116023, China

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ABSTRACT: Shale gas, which is recently discovered with a large reserve, has invoked wide interest as an alternative energy resource of natural gas. However, little is known about the molecular properties of shale gas (mainly methane) confined in the nanopores of shale, such as their diffusivity, which is essential for its exploitation and utilization. We study here the diffusivity of methane using 1H pulsed field gradient (PFG) NMR and theoretical modelling. Following analysis of the physicochemical properties of shale, a well-ordered mesoporous silica material (SBA-15) modified with organic functional groups is employed to model the mesopores observed in the shale and to study the fundamental behavior of shale gas. The results demonstrates that methane moves faster in the pores modified with the aromatic phenyl groups than those with non-aromatic cyclohexyl groups, suggesting a higher diffusivity of methane with increasing maturity of shale.

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Introduction Shale gas, comprising mainly methane, attracts increasing attention as an important energy resource thanks to the breakthroughs of the horizontal drilling and the hydraulic fracturing techniques. This has invoked interest from a plethora of fields including fossil energy, chemical engineering and environmental science, etc.1-4 As a result, wide efforts have been carried out trying to gain knowledge about the diffusivity of shale gas in the nanopores.5 For example, tedious permeability tests through shales,6 and mathematical micro/nano-pore network analysis are frequently employed to capture dynamic fluid flow in various flow regimes.7 It was well accepted that the economically accessible shale gas is usually contained in the mature petroleum source rocks with rich organic matter in their natural fractures and pores. However, still little is known about the status and diffusivity of methane molecules confined within these nano-pores, which is essential for further exploitation and utilization. Generation of this information is complicated by the heterogeneous nature of chemical composition and pore networks in shale. 810

To establish a microscopic and quantitative understanding of this important but ambiguous issue, different factors affecting the methane sorption and diffusion in the nano-pores of shale need to be evaluated in a controllable manner. The extreme complexity of real shale has prompted researchers to turn to investigate the gas behavior with simplified model materials. For example, Guo et al. studied the gas flow through different sizes of commercial AAO nano ceramic membranes by experiment and numerical simulation.11 Zhai and Sharma et al. chose montmorillonite as the model to study adsorption and diffusion of shale gas using molecular dynamics simulations12, 13 Javadpour et al. adopt quartz nanopores with different sizes to study the flow behavior of liquid hydrocarbon.14 Therefore, we employed SBA-15, which is a silica

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material with a well-ordered pore structure, as a model since silica is the main inorganic chemical component in shale. Furthermore, to assess the influences of the organic environment inside the shale on the methane storage and diffusion, we modified the pores with typical functional groups of kerogen (the main organic matter found in shale), such as cyclohexyl and phenyl. These carefully engineered structures allow us to comprehend the effects of various physical factors on the confined methane diffusion in shale. Combining the pulsed field gradient (PFG) NMR technique with theoretical modelling, we explore the effects of the environmental aromaticity on methane diffusion. Aromaticity, which is defined as the fraction of aromatic carbon in the total carbon atoms, was reported to affect the storage of methane according to statistical studies over a range of shales.15, 16 However, its effect and the underlying mechanism has never been elaborated. We herein observed that methane moves faster in the phenyl-modified SBA-15 with higher maturity.

Experimental section Samples The gas shale sample was obtained from Ordos Basin, provided by the Shaanxi Yanchang Petroleum (Group) Co. Ltd. Kerogen was extracted from shale according to a standard method reported by Chinese National Standard GB/T 19144-2010. Briefly, shales were crushed to powder and treated with 6 M HCl to remove carbonates. After washing with deionized water, 6 M HCl and 40% HF were added to remove silicates. The precipitation was recovered, followed by washing with 1 M HCl for three times. The decarbonating and desilicating processes were repeated and each time 1 M HCl was used to wash the precipitation for three times. Finally, the

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sample was washed with deionized water and heated at 333 K. No depyritization was conducted for the kerogens so we couldn’t avoid the influence of pyrite in NMR experiment. Mesoporous SBA-15 silica was purchased from Nanjing JCNANO Technology Co. Ltd, with an average pore size of 6.5 nm and a surface area of 800 m2/g. The cyclohexyltrimethoxysilane (97%) and phenyltrimethoxysilane (97%) were purchased from J&K Scientific Co. Ltd. The cyclohexyl and phenyl-modified SBA-15 samples have been prepared by adding 0.4 g SBA-15 powder to 0.33 mmol corresponding trimethoxy silane in 60 mL acetonitrile at 353 K for 24 h. The final solid products were filtered, washed with deionized water and dried at 333 K. The obtained samples were denoted as SBA-cyclohexyl and SBA-phenyl, respectively. For PFG NMR measurement, the different SBA-15 materials with 40~60 mesh and kerogen powder were activated under dynamic vacuum (= 2nD∆

(3)

where n represents the dimensionality of the diffusion process, for example n=3 indicates a three-dimensional diffusion feature. Theoretical calculation Molecular dynamics (MD) simulations were used to determine the dynamic properties of methane molecules in non-modified, phenyl-modified as well as cyclohexyl-modified SBA-15 pores at 293.15 K with Dreiding force field19 in the LAMMPS package.20 SBA-15 (Figure S1) contained 2103 H, 4442 O and 472 Si atoms, with the main pore about 6 nm, interconnected with micropore of about 1 nm. Cyclohexyl and phenyl groups were incorporated into pores by replacing the hydroxyl groups on the pore walls. The molar ratio of modifying groups to Si was set at 0.03:1. 105 methane molecules were added to SBA-15 corresponding to a molar ratio of CH4/Si = 0.05/1. Van der Waals interactions and electric interactions were calculated within a cutoff radius of 12 and 15 Å, respectively. Equation (3) was used to calculate the root-mean-square displacements and the self-diffusion coefficients of methane.

Results and discussion Characterization of the Pore Structure and Morphology of the Shale Sample

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In order to gain fundamental understanding of the methane status in the pores of the shale, we carried out characterization of a real shale sample, including the morphology and the pore texture. TEM and Energy Dispersive Analysis of X-rays analysis (EDXS) in Figure S2 revealed a heterogeneous texture and compositions at the nanoscale. Numerous inorganic phases scattered randomly. Detrital quartz and different alumimosilicates were clearly identified by EDXS. Iron existed throughout the clays with a content around 10 wt%. We had attempted to study methane sorption and diffusion behavior directly in this shale sample. However, such a high-content of paramagnetic iron species made it impossible for direct NMR characterization. In a typical TEM image (Figure 1), the organic matter was observed at the boundaries of different mineral grains. In some regions there was aggregation of organic matters forming larger monoblocks. Surprisingly, in addition to some typical large pores (>50 nm) in the shale,21 well-ordered mesopores were also clearly seen in the FIB sample (Figure 1b, c and e). The pore sizes were about 15 nm (Figure 1f). Although ordered mesopores were not reported in gas shale previously, formation of nanostructures in geochemical environment was studied, and the mass transport and geochemical reactions at nanoscales also attracted attention recently.22 With the help of underearth fluids such as water, rock alternation led to precipitation of tiny secondary mineral particles, subsequent aggregation of these mineral assemblages can create nanopores in the rock.23 The elemental analysis in Figure S2 indicated that this well-ordered mesoporous material mainly comprises aluminosilicate. Therefore, we employed a commercially available SBA-15, a silica material with well-ordered mesopores as a simplified model, in order to capture the fundamental behavior of the methane diffusion in shale. Methane diffusion in SBA-15

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We first studied the sorption and diffusion of methane in the SBA-15 pores without any modifications. The diffusion of methane under different pressures and temperatures were studied. Figure S3 displays the PFG NMR results at a pressure of 51 kPa and 300 K. Fitting the results with equation (1) did not give a satisfactory result. In contrast, by fitting with equation (2), we obtained two self-diffusion coefficients D1 and D2, with D1 = (1.39±0.03) ×10-5 m2/s and D2 = (2.26±0.12) ×10-6 m2/s, respectively. D1 was much larger than D2 and similar to that of free methane molecules in gas phase (in the order of 10-5 m2/s) (Figure S5a). Obviously there were two types of molecules with different diffusion kinetics in these nanopores. Molecular simulation results showed that statistically 90% methane molecules prefer to stay closer to the pore walls and only 10% are located in the pore center, with the boundary indicated by the red circle in Figure 2. Except for the adsorbed gas, in the actual sample, the molecules could also exist among the intercrystalline pores as free gas. Therefore, the D1 and D2 were likely ascribed to diffusivities of the methane molecules in the gas phase and those adsorbed on the pore wall of SBA-15, respectively. The molecules adsorbed on the pores usually suffered more from the diffusion resistance due to interaction with the pore wall. However, this diffusivity was much faster than that reported for methane in pure silica microporous CHA zeolites (in the order of 1011

m2/s at 301 K and 101.3 kPa), where intraparticle diffusion could be guaranteed.24 One of the

reason might lie in the much larger square roots of the mean square displacement (above 80 µm, obtained from equation (3)) than the length of pores in SBA-15. In addition, there were some defects along the SBA-15 channels25 and some methane molecules may slip away out of the channels or through these defects into the voids of the particles becoming free molecules. The frequent exchanges of molecules in the free and adsorption states may contributed to the

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diffusion of the two components. Nevertheless, the comparison of D1 and D2 under different pressures and temperatures in the pores of the same type of materials is still valid. We further studied the self-diffusion coefficients as a function of pressures and temperatures. The results in Figure 3a and b showed that both D1 and D2 decreased with methane pressure, while increased with the temperature. It was noteworthy that the parameter p (fraction of the molecules with the diffusivity D1 among the total number of molecules) decreased as the pressure increases (Figure S4), suggesting that more molecules become less mobile at a higher pressure. In another word, a higher pressure benefited the adsorption of methane in SBA-15. Methane molecules broke through the constraint of the pore wall and moved faster at a higher temperature. Methane diffusion in SBA-15 modified with organic groups It is known that kerogen is the main organic matter in shale. Therefore, we had attempted to extract the kerogen from shale intending to incorporate it directly into the SBA-15 pores. A widely employed method based on the elimination of the minerals from the shale sample by nonoxidant acid attacks was used for extraction.26 However, the obtained kerogen exhibited an extremely low surface area (about 24 m2/g), suggesting a very low porosity. The pore texture was likely destructed during extraction. The diffusion study showed that the molecules behaved like free gas (Figure S5). Therefore, we turned to introduce the typical structural units of kerogen into the pores of SBA-15, such as phenyl and cyclohexyl groups, creating the inorganic-organic interlaced pore environment in shale. The phenyl and cyclohexyl groups were loaded into the SBA-15 pores through the hydrolysis and condensation reaction of Si-OH and Si-OCH3, following a reported procedure.27

13

C-NMR

(Figure S6) confirm that these groups have been successfully incorporated into the pores of

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SBA-15 with the corresponding characteristic signals of the functional groups appearing in the spectra. TEM (Figure S7) and XRD (Figure S8) indicated that the pores retained the wellordered mesoporous morphology with the typical hexagonal symmetry. This suggested that the space of the nanopores was not affected significantly by these groups. The results in Figure 3c and 3d showed that the pressure exhibited a similar effect on the diffusivities as in the non-modified SBA-15 and diffusion slowed down at a higher pressure. D1 and D2 both reduced in the organic-modified pores but the modification exerted a stronger effect on D2. This again showed that D2 carried characteristic information of methane molecules interacting with the pores and the functional groups. Furthermore, the diffusivity in different pores followed the following trend: SBA-15 > SBA-phenyl > SBA-cyclohexyl. Organic modifications retarded the methane diffusion. Diffusion of the methane in SBA-cyclohexyl was always smaller than that in SBA-phenyl within the studied pressure range, suggesting that the cyclohexyl groups had a stronger effect suppressing the diffusion of methane. The aromaticity was reported to be linearly correlated with the maturity of the hydrocarbon source rocks.15 Therefore, our result that faster diffusivity within the pores with a higher aromaticity is meaningful and instructive for the shale gas utilization. Similar results had already been obtained in coal. It was believed that methane diffused faster in coal with a higher maturity under the identical temperature and pressure, although they analyzed the problem from the view of pore structure.28 The higher diffusivity in the SBA-phenyl pores was validated by theoretical calculation. Figure 4 compared the mean square displacements of methane in three different pores obtained from theoretical modelling. The average diffusion coefficients of methane in the pores calculated by Equation (3) were 2.26×10-7 m2/s, 1.64×10-7 m2/s and 1.15×10-7 m2/s. Although the actual

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numbers were different, the trend in different pores was similar to those obtained from experiments. The much lower diffusion coefficients from theoretical calculation was likely related to the unavoidable defects in the samples, the distribution of pore size and finite length of the pores. The effective volumes of the phenyl and the cyclohexyl groups are 0.1032 nm3 and 0.1173 nm3, respectively, which are rather comparable. Therefore, the steric effect is negligible. These results demonstrated important role of the interaction of methane with the pore walls in methane diffusion. As the results above show, diffusion of methane is facilitated in SBA-phenyl pores. We anticipated that the presence of larger organic groups or matter may facilitate further the diffusion although the underlying mechanism requires further investigation.

Conclusion Diffusion of methane in shale has been studied using PFG-NMR employing SBA-15 with wellordered mesoporous pores, modified with typical structural groups of kerogen as model. The results reveal that the methane diffusivity increases within the pores with a higher aromaticity. Although the conditions of pressures and temperatures studied in this work are far away from the actual crust environment, the findings here provide fundamental understandings about the diffusion of methane in nanopores of shale.

ASSOCIATED CONTENT Supporting Information.

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Optimized structure of the SBA-15, STEM images of the shale, PFG NMR spin-echo attenuation curve, plot of p (the percentage) for SBA-15, plot of methane diffusion in kerogen. 13C CP MAS spectra, TEM and XRD results for the pure and organic-modified SBA-15 samples. This material is available free of charge via the Internet at http://pubs.acs.org. AUTHOR INFORMATION Corresponding Author *Email: [email protected], Tel: +86-411-8437-9969 Author Contributions Y. H. and Q. Z. contributed equally. Notes The authors declare no competing financial interest. ACKNOWLEDGMENT Shaanxi Yanchang Petroleum (Group) Co. Ltd is acknowledged for providing the shale sample. This work was supported by the “Strategic Priority Research Program” of the Chinese Academy of Sciences (grant XDB10020202, XDB10040304). REFERENCES (1)

Wang, Q.; Chen, X.; Jha, A. N.; Rogers, H. Natural Gas from Shale Formation – the

Evolution, Evidences and Challenges of Shale Gas Revolution in United States. Renewable Sustainable Energy Rev. 2014, 30, 1-28.

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B.; Carter, K.; Hakala, A.; Capo, R. An Approach for Assessing Engineering Risk from Shale Gas Wells in the United States. Int. J. Coal Geol. 2014, 126, 4-19. (3)

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Shale Gas by Integrating with Bioethanol Dehydration: Novel Process Design and SimulationBased Optimization. AIChE J. 2015, 61, 1209-1232. (4)

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Wastewater from Shale Gas Extraction by Hydraulic Fracturing. Fuel 2016, 182, 292-303. (5)

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Study and Modelling of Methane Adsorption and Diffusion in Shale. Fuel 2014, 117, 509-519. (6)

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Distribution of Nanometer-Scale Pores in Siliceous Mudstones of the Mississippian Barnett Shale. J. Sediment. Res. 2009, 79, 848-861.

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(10) Wang, J.; Wang, B. e.; Li, Y.; Yang, Z.; Gong, H.; Dong, M. Measurement of Dynamic Adsorption–Diffusion Process of Methane in Shale. Fuel 2016, 172, 37-48. (11) Guo, C.; Xu, J.; Wu, K.; Wei, M.; Liu, S. Study on Gas Flow through Nano Pores of Shale Gas Reservoirs. Fuel 2015, 143, 107-117. (12) Zhai, Z.; Wang, X.; Jin, X.; Sun, L.; Li, J.; Cao, D. Adsorption and Diffusion of Shale Gas Reservoirs in Modeled Clay Minerals at Different Geological Depths. Energy Fuels 2014, 28, 7467-7473. (13) Sharma, A.; Namsani, S.; Singh, J. K. Molecular Simulation of Shale Gas Adsorption and Diffusion in Inorganic Nanopores. Mol. Simul. 2014, 41, 414-422. (14) Wang, S.; Javadpour, F.; Feng, Q. Molecular Dynamics Simulations of Oil Transport through Inorganic Nanopores in Shale. Fuel 2016, 171, 74-86. (15) Werner-Zwanziger, U.; Lis, G.; Mastalerz, M.; Schimmelmann, A. Thermal Maturity of Type Ii Kerogen from the New Albany Shale Assessed by C-13 Cp/Mas Nmr. Solid State Nucl. Magn. Reson. 2005, 27, 140-148. (16) Gasparik, M.; Bertier, P.; Gensterblum, Y.; Ghanizadeh, A.; Krooss, B. M.; Littke, R. Geological Controls on the Methane Storage Capacity in Organic-Rich Shales. Int. J. Coal Geol. 2014, 123, 34-51. (17) Cotts, R. M.; Hoch, M. J. R.; Sun, T.; Markert, J. T. Pulsed Field Gradient Stimulated Echo Methods for Improved Nmr Diffusion Measurements in Heterogeneous Systems. J. Magn. Reson. (1969) 1989, 83, 252-266.

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(18) Ray, M. S. Diffusion in Zeolites and Other Microporous Solids. Wiley & Sons: New York 1992. (19) Mayo, S. L.; Olafson, B. D.; Goddard, W. A. Dreiding - a Generic Force-Field for Molecular Simulations. J. Phys. Chem. 1990, 94, 8897-8909. (20) Plimpton, S. Fast Parallel Algorithms for Short-Range Molecular-Dynamics. J. Comput. Phys. 1995, 117, 1-19. (21) Loucks, R. G.; Reed, R. M.; Ruppel, S. C.; Hammes, U. Spectrum of Pore Types and Networks in Mudrocks and a Descriptive Classification for Matrix-Related Mudrock Pores. AAPG Bull. 2012, 96, 1071-1098. (22) Wang, Y. Nanogeochemistry: Nanostructures, Emergent Properties and Their Control on Geochemical Reactions and Mass Transfers. Chem. Geol. 2014, 378-379, 1-23. (23) Simonyan, A. V.; Dultz, S.; Behrens, H. Diffusive Transport of Water in Porous Fresh to Altered Mid-Ocean Ridge Basalts. Chem. Geol. 2012, 306–307, 63-77. (24) Hedin, N.; DeMartin, G. J.; Roth, W. J.; Strohmaier, K. G.; Reyes, S. C. Pfg Nmr SelfDiffusion of Small Hydrocarbons in High Silica Ddr, Cha and Lta Structures. Microporous Mesoporous Mater. 2008, 109, 327-334. (25) Menjoge, A. R.; Huang, Q.; Nohair, B.; Eic, M.; Shen, W.; Che, R.; Kaliaguine, S.; Vasenkov, S. Combined Application of Tracer Zero Length Column Technique and Pulsed Field Gradient Nuclear Magnetic Resonance for Studies of Diffusion of Small Sorbate Molecules in Mesoporous Silica Sba-15. J. Phys. Chem. C 2010, 114, 16298-16308.

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(26) Vandenbroucke, M. Kerogen: From Types to Models of Chemical Structure. Oil Gas Sci. Technol. 2003, 58, 243-269. (27) Huang, H.; Yang, C.; Zhang, H.; Liu, M. Preparation and Characterization of Octyl and Octadecyl-Modified Mesoporous Sba-15 Silica Molecular Sieves for Adsorption of Dimethyl Phthalate and Diethyl Phthalate. Microporous Mesoporous Mater. 2008, 111, 254-259. (28) Xu, H.; Tang, D.; Zhao, J.; Li, S.; Tao, S. A New Laboratory Method for Accurate Measurement of the Methane Diffusion Coefficient and Its Influencing Factors in the Coal Matrix. Fuel 2015, 158, 239-247.

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Figure 1. STEM image of the FIB section of a piece of shale sample (a) overview with the marked regions enlarged in (b, c and d); (e) and (f) show the larger view of the mesopores in (c) and the corresponding fast Fourier transform pattern.

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Figure 2. The adsorption sites of methane molecules in the pore of the pure SBA-15 obtained from molecular dynamics simulation.

Figure 3. The pressure dependence of self-diffusion coefficients D1 and D2 at different temperatures for the pure SBA-15 mesoporous silica (a, b) and for the SBA-phenyl and SBAcyclohexyl (c, d). The error bars are based on the standard error.

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Figure 4. Mean square displacement (MSD) of methane in the pores of SBA-15, and those modified by phenyl and cyclohexyl groups, obtained by MD simulation.

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