Local diffusion coefficient measurements in shale using dynamic micro-computed tomography
Diffusion is an important mass transport mechanism in ultra-low permeability shale matrix and thus, characterization of shale diffusivity is of practical necessity for shale gas developments. We present a novel method for measuring bulk and local diffusion coefficients of shale core-plugs using dyna...
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Veröffentlicht in: | Fuel (Guildford) 2017-11, Vol.207, p.312-322 |
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description | Diffusion is an important mass transport mechanism in ultra-low permeability shale matrix and thus, characterization of shale diffusivity is of practical necessity for shale gas developments. We present a novel method for measuring bulk and local diffusion coefficients of shale core-plugs using dynamic X-ray micro-computed tomography (micro-CT). Liquid diffusion experiments are conducted on a centimeter-scale shale core and a series of time-sequenced 3D micro-CT images are acquired through dynamic imaging. Local diffusion coefficients are measured numerically from the micro-CT data using a new mathematical method that allows us to evaluate the heterogeneity of shale diffusivity at the sub-core scale. The variation of local diffusion coefficients is quantified using the Dykstra Parsons method, which provides a means to quantify core-scale heterogeneity in shale samples. Although the micro-CT image data may be influenced by noise, the presented technique provides reasonable results and our validation studies provide fundamental design parameters for measuring diffusivity values from dynamic micro-CT experiments. In addition the presented method can be applied to other porous materials where diffusion occurs. |
doi_str_mv | 10.1016/j.fuel.2017.06.050 |
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We present a novel method for measuring bulk and local diffusion coefficients of shale core-plugs using dynamic X-ray micro-computed tomography (micro-CT). Liquid diffusion experiments are conducted on a centimeter-scale shale core and a series of time-sequenced 3D micro-CT images are acquired through dynamic imaging. Local diffusion coefficients are measured numerically from the micro-CT data using a new mathematical method that allows us to evaluate the heterogeneity of shale diffusivity at the sub-core scale. The variation of local diffusion coefficients is quantified using the Dykstra Parsons method, which provides a means to quantify core-scale heterogeneity in shale samples. Although the micro-CT image data may be influenced by noise, the presented technique provides reasonable results and our validation studies provide fundamental design parameters for measuring diffusivity values from dynamic micro-CT experiments. 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We present a novel method for measuring bulk and local diffusion coefficients of shale core-plugs using dynamic X-ray micro-computed tomography (micro-CT). Liquid diffusion experiments are conducted on a centimeter-scale shale core and a series of time-sequenced 3D micro-CT images are acquired through dynamic imaging. Local diffusion coefficients are measured numerically from the micro-CT data using a new mathematical method that allows us to evaluate the heterogeneity of shale diffusivity at the sub-core scale. The variation of local diffusion coefficients is quantified using the Dykstra Parsons method, which provides a means to quantify core-scale heterogeneity in shale samples. Although the micro-CT image data may be influenced by noise, the presented technique provides reasonable results and our validation studies provide fundamental design parameters for measuring diffusivity values from dynamic micro-CT experiments. In addition the presented method can be applied to other porous materials where diffusion occurs.</description><subject>Coefficient of variation</subject><subject>Computation</subject><subject>Computed tomography</subject><subject>Design parameters</subject><subject>Diffusion</subject><subject>Diffusion coefficient</subject><subject>Diffusivity</subject><subject>Dynamic imaging</subject><subject>Heterogeneity</subject><subject>Image acquisition</subject><subject>Local diffusion coefficients</subject><subject>Mass transit</subject><subject>Mass transport</subject><subject>Matrix methods</subject><subject>Micro-CT</subject><subject>Permeability</subject><subject>Plugs</subject><subject>Porous materials</subject><subject>Shale</subject><subject>Shale gas</subject><issn>0016-2361</issn><issn>1873-7153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LAzEQxYMoWKtfwFPA866TpJuk4EWK_6DgRQ-eQjY722bpbmqyK_Tbm1LPHoaZw3vzHj9CbhmUDJi878p2wl3JgakSZAkVnJEZ00oUilXinMwgqwouJLskVyl1AKB0tZiRr3Vwdkcb37ZT8mGgLmDbeudxGGmPNk0R-3wn6geatnaHNOuGDW0Og-29o3liKFzo99OIDR1DHzbR7reHa3LR2l3Cm789J5_PTx-r12L9_vK2elwXTnA9Fg1qqETVSquVxqbW1mqtpVxWtQDBoQG1ACUUX3KUoCxnrmZMMWZrxayUYk7uTn_3MXxPmEbThSkOOdKw5UJIzlkOmBN-UuW2KUVszT763saDYWCOCE1njgjNEaEBaTLCbHo4mTD3__EYTTqCcdj4iG40TfD_2X8BElN6Tw</recordid><startdate>20171101</startdate><enddate>20171101</enddate><creator>Zhang, Yulai</creator><creator>Mostaghimi, Peyman</creator><creator>Fogden, Andrew</creator><creator>Middleton, Jill</creator><creator>Sheppard, Adrian</creator><creator>Armstrong, Ryan T.</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope></search><sort><creationdate>20171101</creationdate><title>Local diffusion coefficient measurements in shale using dynamic micro-computed tomography</title><author>Zhang, Yulai ; Mostaghimi, Peyman ; Fogden, Andrew ; Middleton, Jill ; Sheppard, Adrian ; Armstrong, Ryan T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-de80535f6a878edb8aa8886695b30320d0740737292e607a21cb11711ab71a663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Coefficient of variation</topic><topic>Computation</topic><topic>Computed tomography</topic><topic>Design parameters</topic><topic>Diffusion</topic><topic>Diffusion coefficient</topic><topic>Diffusivity</topic><topic>Dynamic imaging</topic><topic>Heterogeneity</topic><topic>Image acquisition</topic><topic>Local diffusion coefficients</topic><topic>Mass transit</topic><topic>Mass transport</topic><topic>Matrix methods</topic><topic>Micro-CT</topic><topic>Permeability</topic><topic>Plugs</topic><topic>Porous materials</topic><topic>Shale</topic><topic>Shale gas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yulai</creatorcontrib><creatorcontrib>Mostaghimi, Peyman</creatorcontrib><creatorcontrib>Fogden, Andrew</creatorcontrib><creatorcontrib>Middleton, Jill</creatorcontrib><creatorcontrib>Sheppard, Adrian</creatorcontrib><creatorcontrib>Armstrong, Ryan T.</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Fuel (Guildford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yulai</au><au>Mostaghimi, Peyman</au><au>Fogden, Andrew</au><au>Middleton, Jill</au><au>Sheppard, Adrian</au><au>Armstrong, Ryan T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Local diffusion coefficient measurements in shale using dynamic micro-computed tomography</atitle><jtitle>Fuel (Guildford)</jtitle><date>2017-11-01</date><risdate>2017</risdate><volume>207</volume><spage>312</spage><epage>322</epage><pages>312-322</pages><issn>0016-2361</issn><eissn>1873-7153</eissn><abstract>Diffusion is an important mass transport mechanism in ultra-low permeability shale matrix and thus, characterization of shale diffusivity is of practical necessity for shale gas developments. We present a novel method for measuring bulk and local diffusion coefficients of shale core-plugs using dynamic X-ray micro-computed tomography (micro-CT). Liquid diffusion experiments are conducted on a centimeter-scale shale core and a series of time-sequenced 3D micro-CT images are acquired through dynamic imaging. Local diffusion coefficients are measured numerically from the micro-CT data using a new mathematical method that allows us to evaluate the heterogeneity of shale diffusivity at the sub-core scale. The variation of local diffusion coefficients is quantified using the Dykstra Parsons method, which provides a means to quantify core-scale heterogeneity in shale samples. Although the micro-CT image data may be influenced by noise, the presented technique provides reasonable results and our validation studies provide fundamental design parameters for measuring diffusivity values from dynamic micro-CT experiments. 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subjects | Coefficient of variation Computation Computed tomography Design parameters Diffusion Diffusion coefficient Diffusivity Dynamic imaging Heterogeneity Image acquisition Local diffusion coefficients Mass transit Mass transport Matrix methods Micro-CT Permeability Plugs Porous materials Shale Shale gas |
title | Local diffusion coefficient measurements in shale using dynamic micro-computed tomography |
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