Quantification of organic content in shales via near-infrared imaging: Green River Formation
•Kerogen content of organic-rich shales is quantifiable from near-infrared images.•Spectral models are developed for the thermally immature Green River Formation.•Models are used to map organic content for an entire core at high resolution.•Performance is compared to a previously developed optical m...
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creator | Mehmani, Yashar Burnham, Alan K. Vanden Berg, Michael D. Tchelepi, Hamdi A. |
description | •Kerogen content of organic-rich shales is quantifiable from near-infrared images.•Spectral models are developed for the thermally immature Green River Formation.•Models are used to map organic content for an entire core at high resolution.•Performance is compared to a previously developed optical method.
We demonstrate the applicability of near-infrared (NIR) imaging for quantifying the spatial distribution of kerogen content in organic-rich shales with sub-millimeter resolution over cores that can span hundreds of feet in depth. We develop models that are validated for the thermally immature oil shale of the Mahogany zone in the Green River Formation. They utilize either all or part of the NIR reflectance spectrum thereby providing some flexibility in the choice of instrumentation and, thus, cost. The models accurately recover fine-scale (sub-millimeter) variabilities in kerogen content from calibrations to a few coarse-scale (centimeter to meter) measurements, a process known as downscaling. This obviates slow, costly, and discrete fine-scale measurements in favor of a rapid, inexpensive, and continuous mapping approach. It also has implications for mapping thermo-hydro-mechanical properties of organic-rich shales, given that they strongly depend on kerogen content. Since our models utilize kerogen-specific absorption bands, they may also find use in other hydrocarbon-bearing source rocks. |
doi_str_mv | 10.1016/j.fuel.2017.07.027 |
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We demonstrate the applicability of near-infrared (NIR) imaging for quantifying the spatial distribution of kerogen content in organic-rich shales with sub-millimeter resolution over cores that can span hundreds of feet in depth. We develop models that are validated for the thermally immature oil shale of the Mahogany zone in the Green River Formation. They utilize either all or part of the NIR reflectance spectrum thereby providing some flexibility in the choice of instrumentation and, thus, cost. The models accurately recover fine-scale (sub-millimeter) variabilities in kerogen content from calibrations to a few coarse-scale (centimeter to meter) measurements, a process known as downscaling. This obviates slow, costly, and discrete fine-scale measurements in favor of a rapid, inexpensive, and continuous mapping approach. It also has implications for mapping thermo-hydro-mechanical properties of organic-rich shales, given that they strongly depend on kerogen content. Since our models utilize kerogen-specific absorption bands, they may also find use in other hydrocarbon-bearing source rocks.</description><identifier>ISSN: 0016-2361</identifier><identifier>EISSN: 1873-7153</identifier><identifier>DOI: 10.1016/j.fuel.2017.07.027</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Absorption spectra ; Calibration ; Cores ; Green River Formation ; I.R. radiation ; Imaging spectroscopy ; Infrared imaging ; Infrared imaging systems ; Instrumentation ; Kerogen ; Mahogany ; Mapping ; Mechanical properties ; Near-infrared ; Oil shale ; Reflectance ; Rivers ; Shale ; Shales ; Spatial distribution</subject><ispartof>Fuel (Guildford), 2017-11, Vol.208, p.337-352</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Elsevier BV Nov 15, 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-36b522437798612cfaa14802388168b001a29ddd29a533cc3bd0bc392e75f57f3</citedby><cites>FETCH-LOGICAL-c328t-36b522437798612cfaa14802388168b001a29ddd29a533cc3bd0bc392e75f57f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0016236117308815$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27903,27904,65309</link.rule.ids></links><search><creatorcontrib>Mehmani, Yashar</creatorcontrib><creatorcontrib>Burnham, Alan K.</creatorcontrib><creatorcontrib>Vanden Berg, Michael D.</creatorcontrib><creatorcontrib>Tchelepi, Hamdi A.</creatorcontrib><title>Quantification of organic content in shales via near-infrared imaging: Green River Formation</title><title>Fuel (Guildford)</title><description>•Kerogen content of organic-rich shales is quantifiable from near-infrared images.•Spectral models are developed for the thermally immature Green River Formation.•Models are used to map organic content for an entire core at high resolution.•Performance is compared to a previously developed optical method.
We demonstrate the applicability of near-infrared (NIR) imaging for quantifying the spatial distribution of kerogen content in organic-rich shales with sub-millimeter resolution over cores that can span hundreds of feet in depth. We develop models that are validated for the thermally immature oil shale of the Mahogany zone in the Green River Formation. They utilize either all or part of the NIR reflectance spectrum thereby providing some flexibility in the choice of instrumentation and, thus, cost. The models accurately recover fine-scale (sub-millimeter) variabilities in kerogen content from calibrations to a few coarse-scale (centimeter to meter) measurements, a process known as downscaling. This obviates slow, costly, and discrete fine-scale measurements in favor of a rapid, inexpensive, and continuous mapping approach. It also has implications for mapping thermo-hydro-mechanical properties of organic-rich shales, given that they strongly depend on kerogen content. Since our models utilize kerogen-specific absorption bands, they may also find use in other hydrocarbon-bearing source rocks.</description><subject>Absorption spectra</subject><subject>Calibration</subject><subject>Cores</subject><subject>Green River Formation</subject><subject>I.R. radiation</subject><subject>Imaging spectroscopy</subject><subject>Infrared imaging</subject><subject>Infrared imaging systems</subject><subject>Instrumentation</subject><subject>Kerogen</subject><subject>Mahogany</subject><subject>Mapping</subject><subject>Mechanical properties</subject><subject>Near-infrared</subject><subject>Oil shale</subject><subject>Reflectance</subject><subject>Rivers</subject><subject>Shale</subject><subject>Shales</subject><subject>Spatial distribution</subject><issn>0016-2361</issn><issn>1873-7153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LAzEUxIMoWKtfwFPA89b82d1kxYuIrUJBFL0JIZt9qVnapCa7Bb-9qfUsDLzL_OYNg9AlJTNKaH3dz-wI6xkjVMxIFhNHaEKl4IWgFT9GE5JdBeM1PUVnKfWEECGrcoI-XkbtB2ed0YMLHgeLQ1xp7ww2wQ_gB-w8Tp96DQnvnMYedCyct1FH6LDb6JXzqxu8iAAev7odRDwPcfObdo5OrF4nuPi7U_Q-f3i7fyyWz4un-7tlYTiTQ8HrtmKs5EI0sqbMWK1pKQnjUtJatrm6Zk3XdazRFefG8LYjreENA1HZSlg-RVeH3G0MXyOkQfVhjD6_VLSpWCk4LVl2sYPLxJBSBKu2MfeP34oStV9R9Wq_otqvqEgWExm6PUCQ--8cRJWMA2-gcxHMoLrg_sN_AK7ger4</recordid><startdate>20171115</startdate><enddate>20171115</enddate><creator>Mehmani, Yashar</creator><creator>Burnham, Alan K.</creator><creator>Vanden Berg, Michael D.</creator><creator>Tchelepi, Hamdi A.</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>20171115</creationdate><title>Quantification of organic content in shales via near-infrared imaging: Green River Formation</title><author>Mehmani, Yashar ; Burnham, Alan K. ; Vanden Berg, Michael D. ; Tchelepi, Hamdi A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-36b522437798612cfaa14802388168b001a29ddd29a533cc3bd0bc392e75f57f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Absorption spectra</topic><topic>Calibration</topic><topic>Cores</topic><topic>Green River Formation</topic><topic>I.R. radiation</topic><topic>Imaging spectroscopy</topic><topic>Infrared imaging</topic><topic>Infrared imaging systems</topic><topic>Instrumentation</topic><topic>Kerogen</topic><topic>Mahogany</topic><topic>Mapping</topic><topic>Mechanical properties</topic><topic>Near-infrared</topic><topic>Oil shale</topic><topic>Reflectance</topic><topic>Rivers</topic><topic>Shale</topic><topic>Shales</topic><topic>Spatial distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mehmani, Yashar</creatorcontrib><creatorcontrib>Burnham, Alan K.</creatorcontrib><creatorcontrib>Vanden Berg, Michael D.</creatorcontrib><creatorcontrib>Tchelepi, Hamdi A.</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>Mehmani, Yashar</au><au>Burnham, Alan K.</au><au>Vanden Berg, Michael D.</au><au>Tchelepi, Hamdi A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantification of organic content in shales via near-infrared imaging: Green River Formation</atitle><jtitle>Fuel (Guildford)</jtitle><date>2017-11-15</date><risdate>2017</risdate><volume>208</volume><spage>337</spage><epage>352</epage><pages>337-352</pages><issn>0016-2361</issn><eissn>1873-7153</eissn><abstract>•Kerogen content of organic-rich shales is quantifiable from near-infrared images.•Spectral models are developed for the thermally immature Green River Formation.•Models are used to map organic content for an entire core at high resolution.•Performance is compared to a previously developed optical method.
We demonstrate the applicability of near-infrared (NIR) imaging for quantifying the spatial distribution of kerogen content in organic-rich shales with sub-millimeter resolution over cores that can span hundreds of feet in depth. We develop models that are validated for the thermally immature oil shale of the Mahogany zone in the Green River Formation. They utilize either all or part of the NIR reflectance spectrum thereby providing some flexibility in the choice of instrumentation and, thus, cost. The models accurately recover fine-scale (sub-millimeter) variabilities in kerogen content from calibrations to a few coarse-scale (centimeter to meter) measurements, a process known as downscaling. This obviates slow, costly, and discrete fine-scale measurements in favor of a rapid, inexpensive, and continuous mapping approach. It also has implications for mapping thermo-hydro-mechanical properties of organic-rich shales, given that they strongly depend on kerogen content. Since our models utilize kerogen-specific absorption bands, they may also find use in other hydrocarbon-bearing source rocks.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.fuel.2017.07.027</doi><tpages>16</tpages></addata></record> |
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subjects | Absorption spectra Calibration Cores Green River Formation I.R. radiation Imaging spectroscopy Infrared imaging Infrared imaging systems Instrumentation Kerogen Mahogany Mapping Mechanical properties Near-infrared Oil shale Reflectance Rivers Shale Shales Spatial distribution |
title | Quantification of organic content in shales via near-infrared imaging: Green River Formation |
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