Model Synthetic Samples for Validation of NMR Signal Simulations
Simulations of nuclear magnetic resonance (NMR) signal from fluids contained in porous media (such as rock cores) need to account for both enhanced surface relaxation and the presence of internal magnetic field gradients due to magnetic susceptibility contrast between the rock matrix and the contain...
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Veröffentlicht in: | Transport in porous media 2022-04, Vol.142 (3), p.623-639 |
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description | Simulations of nuclear magnetic resonance (NMR) signal from fluids contained in porous media (such as rock cores) need to account for both enhanced surface relaxation and the presence of internal magnetic field gradients due to magnetic susceptibility contrast between the rock matrix and the contained fluid phase. Such simulations are typically focussed on the extraction of the NMR
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2
relaxation distribution which can be related to pore size and indirectly to system permeability. Discrepancies between such NMR signal simulations on digital rock cores and associated experimental measurements are however frequently reported; these are generally attributed to spatial variations in rock matric composition resulting in heterogeneously distributed NMR surface relaxivities (ρ) and internal magnetic field gradients. To this end, a range of synthetic sediments composed of variable mixtures of quartz and garnet sands were studied. These two constituents were selected for the following reasons: they have different densities allowing for ready phase differentiation in 3D μCT images of samples to use as simulation lattices and they have distinctly different ρ and magnetic susceptibility values which allow for a rigorous test of NMR simulations. Here these 3D simulations were used to calculate the distribution of internal magnetic field gradients in the range of samples, these data were then compared against corresponding NMR experimental measurements. Agreement was reasonably good with the largest discrepancy being the simulation predicting weak internal gradients (in the vicinity of the quartz sand for mixed samples) which were not detected experimentally. The suite of 3D μCT images and associated experimental NMR measurements are all publicly available for the development and validation of NMR simulation efforts.
Article Highlights
Model porous media samples (composed of quartz and garnet sands with distinctly different densities, magnetic susceptibilities and surface relaxivities) were used to systematically assess NMR signal modelling of saturating fluids.
Computation of 3D internal magnetic field map from digital rocks, followed by random walk simulations of the NMR signal of the saturating fluids.
Good agreement between the simulated and experimental internal magnetic field gradient probability distributions. |
doi_str_mv | 10.1007/s11242-022-01764-w |
format | Article |
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T
2
relaxation distribution which can be related to pore size and indirectly to system permeability. Discrepancies between such NMR signal simulations on digital rock cores and associated experimental measurements are however frequently reported; these are generally attributed to spatial variations in rock matric composition resulting in heterogeneously distributed NMR surface relaxivities (ρ) and internal magnetic field gradients. To this end, a range of synthetic sediments composed of variable mixtures of quartz and garnet sands were studied. These two constituents were selected for the following reasons: they have different densities allowing for ready phase differentiation in 3D μCT images of samples to use as simulation lattices and they have distinctly different ρ and magnetic susceptibility values which allow for a rigorous test of NMR simulations. Here these 3D simulations were used to calculate the distribution of internal magnetic field gradients in the range of samples, these data were then compared against corresponding NMR experimental measurements. Agreement was reasonably good with the largest discrepancy being the simulation predicting weak internal gradients (in the vicinity of the quartz sand for mixed samples) which were not detected experimentally. The suite of 3D μCT images and associated experimental NMR measurements are all publicly available for the development and validation of NMR simulation efforts.
Article Highlights
Model porous media samples (composed of quartz and garnet sands with distinctly different densities, magnetic susceptibilities and surface relaxivities) were used to systematically assess NMR signal modelling of saturating fluids.
Computation of 3D internal magnetic field map from digital rocks, followed by random walk simulations of the NMR signal of the saturating fluids.
Good agreement between the simulated and experimental internal magnetic field gradient probability distributions.</description><identifier>ISSN: 0169-3913</identifier><identifier>EISSN: 1573-1634</identifier><identifier>DOI: 10.1007/s11242-022-01764-w</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Civil Engineering ; Classical and Continuum Physics ; Digital mapping ; Earth and Environmental Science ; Earth Sciences ; Garnets ; Geotechnical Engineering & Applied Earth Sciences ; Hydrogeology ; Hydrology/Water Resources ; Industrial Chemistry/Chemical Engineering ; Lattices ; Magnetic fields ; Magnetic permeability ; Mathematical analysis ; NMR ; Nuclear magnetic resonance ; Pore size distribution ; Porous media ; Quartz ; Random walk ; Sand ; Sediments ; Simulation</subject><ispartof>Transport in porous media, 2022-04, Vol.142 (3), p.623-639</ispartof><rights>The Author(s) 2022</rights><rights>The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c363t-fd114a6dfc01fa4bf1d7ab64d838356c449b46b24d9a8322b8744ab3680f05ed3</citedby><cites>FETCH-LOGICAL-c363t-fd114a6dfc01fa4bf1d7ab64d838356c449b46b24d9a8322b8744ab3680f05ed3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11242-022-01764-w$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11242-022-01764-w$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Ling, Nicholas N. A.</creatorcontrib><creatorcontrib>Hussaini, Syed Rizwanullah</creatorcontrib><creatorcontrib>Elsayed, Mahmoud</creatorcontrib><creatorcontrib>Connolly, Paul R. J.</creatorcontrib><creatorcontrib>El-Husseiny, Ammar</creatorcontrib><creatorcontrib>Mahmoud, Mohamed</creatorcontrib><creatorcontrib>May, Eric F.</creatorcontrib><creatorcontrib>Johns, Michael L.</creatorcontrib><title>Model Synthetic Samples for Validation of NMR Signal Simulations</title><title>Transport in porous media</title><addtitle>Transp Porous Med</addtitle><description>Simulations of nuclear magnetic resonance (NMR) signal from fluids contained in porous media (such as rock cores) need to account for both enhanced surface relaxation and the presence of internal magnetic field gradients due to magnetic susceptibility contrast between the rock matrix and the contained fluid phase. Such simulations are typically focussed on the extraction of the NMR
T
2
relaxation distribution which can be related to pore size and indirectly to system permeability. Discrepancies between such NMR signal simulations on digital rock cores and associated experimental measurements are however frequently reported; these are generally attributed to spatial variations in rock matric composition resulting in heterogeneously distributed NMR surface relaxivities (ρ) and internal magnetic field gradients. To this end, a range of synthetic sediments composed of variable mixtures of quartz and garnet sands were studied. These two constituents were selected for the following reasons: they have different densities allowing for ready phase differentiation in 3D μCT images of samples to use as simulation lattices and they have distinctly different ρ and magnetic susceptibility values which allow for a rigorous test of NMR simulations. Here these 3D simulations were used to calculate the distribution of internal magnetic field gradients in the range of samples, these data were then compared against corresponding NMR experimental measurements. Agreement was reasonably good with the largest discrepancy being the simulation predicting weak internal gradients (in the vicinity of the quartz sand for mixed samples) which were not detected experimentally. The suite of 3D μCT images and associated experimental NMR measurements are all publicly available for the development and validation of NMR simulation efforts.
Article Highlights
Model porous media samples (composed of quartz and garnet sands with distinctly different densities, magnetic susceptibilities and surface relaxivities) were used to systematically assess NMR signal modelling of saturating fluids.
Computation of 3D internal magnetic field map from digital rocks, followed by random walk simulations of the NMR signal of the saturating fluids.
Good agreement between the simulated and experimental internal magnetic field gradient probability distributions.</description><subject>Civil Engineering</subject><subject>Classical and Continuum Physics</subject><subject>Digital mapping</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Garnets</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Hydrogeology</subject><subject>Hydrology/Water Resources</subject><subject>Industrial Chemistry/Chemical Engineering</subject><subject>Lattices</subject><subject>Magnetic fields</subject><subject>Magnetic permeability</subject><subject>Mathematical analysis</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Pore size distribution</subject><subject>Porous media</subject><subject>Quartz</subject><subject>Random walk</subject><subject>Sand</subject><subject>Sediments</subject><subject>Simulation</subject><issn>0169-3913</issn><issn>1573-1634</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kE1LAzEQhoMoWKt_wFPAczQfs8nuTSlahVbBqteQ3SR1y3a3JltK_72xK3jzMMxhnvdleBC6ZPSaUapuImMcOKE8DVMSyO4IjVimBGFSwDEaUSYLIgomTtFZjCtKUyyHEbqdd9Y1eLFv-0_X1xVemPWmcRH7LuAP09TW9HXX4s7j5_krXtTL1iS8Xm-bwyGeoxNvmugufvcYvT_cv00eyexl-jS5m5FKSNETbxkDI62vKPMGSs-sMqUEm4tcZLICKEqQJQdbmFxwXuYKwJRC5tTTzFkxRldD7yZ0X1sXe73qtiE9EzWXCjIJUqhE8YGqQhdjcF5vQr02Ya8Z1T-m9GBKJ1P6YErvUkgMoZjgdunCX_U_qW-xq2s_</recordid><startdate>20220401</startdate><enddate>20220401</enddate><creator>Ling, Nicholas N. A.</creator><creator>Hussaini, Syed Rizwanullah</creator><creator>Elsayed, Mahmoud</creator><creator>Connolly, Paul R. J.</creator><creator>El-Husseiny, Ammar</creator><creator>Mahmoud, Mohamed</creator><creator>May, Eric F.</creator><creator>Johns, Michael L.</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20220401</creationdate><title>Model Synthetic Samples for Validation of NMR Signal Simulations</title><author>Ling, Nicholas N. A. ; Hussaini, Syed Rizwanullah ; Elsayed, Mahmoud ; Connolly, Paul R. J. ; El-Husseiny, Ammar ; Mahmoud, Mohamed ; May, Eric F. ; Johns, Michael L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c363t-fd114a6dfc01fa4bf1d7ab64d838356c449b46b24d9a8322b8744ab3680f05ed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Civil Engineering</topic><topic>Classical and Continuum Physics</topic><topic>Digital mapping</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Garnets</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Hydrogeology</topic><topic>Hydrology/Water Resources</topic><topic>Industrial Chemistry/Chemical Engineering</topic><topic>Lattices</topic><topic>Magnetic fields</topic><topic>Magnetic permeability</topic><topic>Mathematical analysis</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Pore size distribution</topic><topic>Porous media</topic><topic>Quartz</topic><topic>Random walk</topic><topic>Sand</topic><topic>Sediments</topic><topic>Simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ling, Nicholas N. A.</creatorcontrib><creatorcontrib>Hussaini, Syed Rizwanullah</creatorcontrib><creatorcontrib>Elsayed, Mahmoud</creatorcontrib><creatorcontrib>Connolly, Paul R. J.</creatorcontrib><creatorcontrib>El-Husseiny, Ammar</creatorcontrib><creatorcontrib>Mahmoud, Mohamed</creatorcontrib><creatorcontrib>May, Eric F.</creatorcontrib><creatorcontrib>Johns, Michael L.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Transport in porous media</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ling, Nicholas N. A.</au><au>Hussaini, Syed Rizwanullah</au><au>Elsayed, Mahmoud</au><au>Connolly, Paul R. J.</au><au>El-Husseiny, Ammar</au><au>Mahmoud, Mohamed</au><au>May, Eric F.</au><au>Johns, Michael L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Model Synthetic Samples for Validation of NMR Signal Simulations</atitle><jtitle>Transport in porous media</jtitle><stitle>Transp Porous Med</stitle><date>2022-04-01</date><risdate>2022</risdate><volume>142</volume><issue>3</issue><spage>623</spage><epage>639</epage><pages>623-639</pages><issn>0169-3913</issn><eissn>1573-1634</eissn><abstract>Simulations of nuclear magnetic resonance (NMR) signal from fluids contained in porous media (such as rock cores) need to account for both enhanced surface relaxation and the presence of internal magnetic field gradients due to magnetic susceptibility contrast between the rock matrix and the contained fluid phase. Such simulations are typically focussed on the extraction of the NMR
T
2
relaxation distribution which can be related to pore size and indirectly to system permeability. Discrepancies between such NMR signal simulations on digital rock cores and associated experimental measurements are however frequently reported; these are generally attributed to spatial variations in rock matric composition resulting in heterogeneously distributed NMR surface relaxivities (ρ) and internal magnetic field gradients. To this end, a range of synthetic sediments composed of variable mixtures of quartz and garnet sands were studied. These two constituents were selected for the following reasons: they have different densities allowing for ready phase differentiation in 3D μCT images of samples to use as simulation lattices and they have distinctly different ρ and magnetic susceptibility values which allow for a rigorous test of NMR simulations. Here these 3D simulations were used to calculate the distribution of internal magnetic field gradients in the range of samples, these data were then compared against corresponding NMR experimental measurements. Agreement was reasonably good with the largest discrepancy being the simulation predicting weak internal gradients (in the vicinity of the quartz sand for mixed samples) which were not detected experimentally. The suite of 3D μCT images and associated experimental NMR measurements are all publicly available for the development and validation of NMR simulation efforts.
Article Highlights
Model porous media samples (composed of quartz and garnet sands with distinctly different densities, magnetic susceptibilities and surface relaxivities) were used to systematically assess NMR signal modelling of saturating fluids.
Computation of 3D internal magnetic field map from digital rocks, followed by random walk simulations of the NMR signal of the saturating fluids.
Good agreement between the simulated and experimental internal magnetic field gradient probability distributions.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s11242-022-01764-w</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Civil Engineering Classical and Continuum Physics Digital mapping Earth and Environmental Science Earth Sciences Garnets Geotechnical Engineering & Applied Earth Sciences Hydrogeology Hydrology/Water Resources Industrial Chemistry/Chemical Engineering Lattices Magnetic fields Magnetic permeability Mathematical analysis NMR Nuclear magnetic resonance Pore size distribution Porous media Quartz Random walk Sand Sediments Simulation |
title | Model Synthetic Samples for Validation of NMR Signal Simulations |
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