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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Fuel (Guildford) 2017-11, Vol.207, p.312-322
Hauptverfasser: Zhang, Yulai, Mostaghimi, Peyman, Fogden, Andrew, Middleton, Jill, Sheppard, Adrian, Armstrong, Ryan T.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 322
container_issue
container_start_page 312
container_title Fuel (Guildford)
container_volume 207
creator Zhang, Yulai
Mostaghimi, Peyman
Fogden, Andrew
Middleton, Jill
Sheppard, Adrian
Armstrong, Ryan T.
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
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1943622105</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0016236117307585</els_id><sourcerecordid>1943622105</sourcerecordid><originalsourceid>FETCH-LOGICAL-c328t-de80535f6a878edb8aa8886695b30320d0740737292e607a21cb11711ab71a663</originalsourceid><addsrcrecordid>eNp9kE9LAzEQxYMoWKtfwFPA866TpJuk4EWK_6DgRQ-eQjY722bpbmqyK_Tbm1LPHoaZw3vzHj9CbhmUDJi878p2wl3JgakSZAkVnJEZ00oUilXinMwgqwouJLskVyl1AKB0tZiRr3Vwdkcb37ZT8mGgLmDbeudxGGmPNk0R-3wn6geatnaHNOuGDW0Og-29o3liKFzo99OIDR1DHzbR7reHa3LR2l3Cm789J5_PTx-r12L9_vK2elwXTnA9Fg1qqETVSquVxqbW1mqtpVxWtQDBoQG1ACUUX3KUoCxnrmZMMWZrxayUYk7uTn_3MXxPmEbThSkOOdKw5UJIzlkOmBN-UuW2KUVszT763saDYWCOCE1njgjNEaEBaTLCbHo4mTD3__EYTTqCcdj4iG40TfD_2X8BElN6Tw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1943622105</pqid></control><display><type>article</type><title>Local diffusion coefficient measurements in shale using dynamic micro-computed tomography</title><source>Elsevier ScienceDirect Journals</source><creator>Zhang, Yulai ; Mostaghimi, Peyman ; Fogden, Andrew ; Middleton, Jill ; Sheppard, Adrian ; Armstrong, Ryan T.</creator><creatorcontrib>Zhang, Yulai ; Mostaghimi, Peyman ; Fogden, Andrew ; Middleton, Jill ; Sheppard, Adrian ; Armstrong, Ryan T.</creatorcontrib><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.</description><identifier>ISSN: 0016-2361</identifier><identifier>EISSN: 1873-7153</identifier><identifier>DOI: 10.1016/j.fuel.2017.06.050</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>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</subject><ispartof>Fuel (Guildford), 2017-11, Vol.207, p.312-322</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Elsevier BV Nov 1, 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-de80535f6a878edb8aa8886695b30320d0740737292e607a21cb11711ab71a663</citedby><cites>FETCH-LOGICAL-c328t-de80535f6a878edb8aa8886695b30320d0740737292e607a21cb11711ab71a663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.fuel.2017.06.050$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,45974</link.rule.ids></links><search><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><title>Local diffusion coefficient measurements in shale using dynamic micro-computed tomography</title><title>Fuel (Guildford)</title><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.</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 &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical &amp; 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 &amp; 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. In addition the presented method can be applied to other porous materials where diffusion occurs.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.fuel.2017.06.050</doi><tpages>11</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0016-2361
ispartof Fuel (Guildford), 2017-11, Vol.207, p.312-322
issn 0016-2361
1873-7153
language eng
recordid cdi_proquest_journals_1943622105
source Elsevier ScienceDirect Journals
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
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T16%3A56%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Local%20diffusion%20coefficient%20measurements%20in%20shale%20using%20dynamic%20micro-computed%20tomography&rft.jtitle=Fuel%20(Guildford)&rft.au=Zhang,%20Yulai&rft.date=2017-11-01&rft.volume=207&rft.spage=312&rft.epage=322&rft.pages=312-322&rft.issn=0016-2361&rft.eissn=1873-7153&rft_id=info:doi/10.1016/j.fuel.2017.06.050&rft_dat=%3Cproquest_cross%3E1943622105%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1943622105&rft_id=info:pmid/&rft_els_id=S0016236117307585&rfr_iscdi=true