Integrated static modeling and dynamic simulation framework for CO2 storage capacity in Upper Qishn Clastics, S1A reservoir, Yemen
Carbon dioxide (CO 2 ) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate large-scale anthropogenic CO 2 emissions into the atmosphere. In this context, CO 2 sequestration into depleted oil reservoirs is a practical approach, as it boosts the oil reco...
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creator | AlRassas, Ayman Mutahar Vo Thanh, Hung Ren, Shaoran Sun, Renyuan Le Nguyen Hai, Nam Lee, Kang-Kun |
description | Carbon dioxide (CO
2
) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate large-scale anthropogenic CO
2
emissions into the atmosphere. In this context, CO
2
sequestration into depleted oil reservoirs is a practical approach, as it boosts the oil recovery and facilitates the permanent storing of CO
2
into the candidate sites. However, the estimation of CO
2
storage capacity in the subsurface is a challenge to kick-start CCS worldwide. Thus, this paper proposes an integrated static and dynamic modeling framework to tackle the challenge of CO
2
storage capacity in the Upper Qishn Formation of the S1A reservoir in the Masila Basin, Yemen. To achieve this work's ultimate goal, the geostatistical modeling was integrated with open-source code (MRST-CO
2
lab) for reducing the uncertainty assessment of CO
2
storage capacity. Also, there is a significant difference between static and dynamic CO
2
storage capacity. The static CO
2
storage capacity varies from 4.54 to 81.98 million tons, while the dynamic CO
2
simulation is estimated from 4.95 to 17.92 million tons. Based on the geological uncertainty assessment of three ranked realizations (P10, P50, P90), our work found that the Upper Qishn sequence of the S1A reservoir could store 15.64 million tons without leakage. This finding demonstrates that the S1A reservoir has the potential for geological CO
2
storage. Ultimately, this study proposes a useful modeling framework that is easy to adapt for other reservoirs in the Masila Basin in Yemen.
Graphical abstract |
doi_str_mv | 10.1007/s40948-021-00305-x |
format | Article |
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2
) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate large-scale anthropogenic CO
2
emissions into the atmosphere. In this context, CO
2
sequestration into depleted oil reservoirs is a practical approach, as it boosts the oil recovery and facilitates the permanent storing of CO
2
into the candidate sites. However, the estimation of CO
2
storage capacity in the subsurface is a challenge to kick-start CCS worldwide. Thus, this paper proposes an integrated static and dynamic modeling framework to tackle the challenge of CO
2
storage capacity in the Upper Qishn Formation of the S1A reservoir in the Masila Basin, Yemen. To achieve this work's ultimate goal, the geostatistical modeling was integrated with open-source code (MRST-CO
2
lab) for reducing the uncertainty assessment of CO
2
storage capacity. Also, there is a significant difference between static and dynamic CO
2
storage capacity. The static CO
2
storage capacity varies from 4.54 to 81.98 million tons, while the dynamic CO
2
simulation is estimated from 4.95 to 17.92 million tons. Based on the geological uncertainty assessment of three ranked realizations (P10, P50, P90), our work found that the Upper Qishn sequence of the S1A reservoir could store 15.64 million tons without leakage. This finding demonstrates that the S1A reservoir has the potential for geological CO
2
storage. Ultimately, this study proposes a useful modeling framework that is easy to adapt for other reservoirs in the Masila Basin in Yemen.
Graphical abstract</description><identifier>ISSN: 2363-8419</identifier><identifier>EISSN: 2363-8427</identifier><identifier>DOI: 10.1007/s40948-021-00305-x</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Anthropogenic factors ; Atmospheric models ; Carbon dioxide ; Carbon dioxide fixation ; Carbon sequestration ; Clastics ; Dynamic models ; Energy ; Engineering ; Environmental Science and Engineering ; Foundations ; Frameworks ; Geoengineering ; Geology ; Geophysics/Geodesy ; Geotechnical Engineering & Applied Earth Sciences ; Hydraulics ; Modelling ; Oil recovery ; Oil reservoirs ; Original Article ; Reservoirs ; Simulation ; Source code ; Storage capacity ; Storage conditions ; Uncertainty ; Water storage</subject><ispartof>Geomechanics and geophysics for geo-energy and geo-resources., 2022-02, Vol.8 (1), Article 2</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-d74b4b5e46b4a991d0dca64da12a7a6e3a3aaabab3e08cd37088b77ac22a6e4d3</citedby><cites>FETCH-LOGICAL-c319t-d74b4b5e46b4a991d0dca64da12a7a6e3a3aaabab3e08cd37088b77ac22a6e4d3</cites><orcidid>0000-0002-7094-9380</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40948-021-00305-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40948-021-00305-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>AlRassas, Ayman Mutahar</creatorcontrib><creatorcontrib>Vo Thanh, Hung</creatorcontrib><creatorcontrib>Ren, Shaoran</creatorcontrib><creatorcontrib>Sun, Renyuan</creatorcontrib><creatorcontrib>Le Nguyen Hai, Nam</creatorcontrib><creatorcontrib>Lee, Kang-Kun</creatorcontrib><title>Integrated static modeling and dynamic simulation framework for CO2 storage capacity in Upper Qishn Clastics, S1A reservoir, Yemen</title><title>Geomechanics and geophysics for geo-energy and geo-resources.</title><addtitle>Geomech. Geophys. Geo-energ. Geo-resour</addtitle><description>Carbon dioxide (CO
2
) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate large-scale anthropogenic CO
2
emissions into the atmosphere. In this context, CO
2
sequestration into depleted oil reservoirs is a practical approach, as it boosts the oil recovery and facilitates the permanent storing of CO
2
into the candidate sites. However, the estimation of CO
2
storage capacity in the subsurface is a challenge to kick-start CCS worldwide. Thus, this paper proposes an integrated static and dynamic modeling framework to tackle the challenge of CO
2
storage capacity in the Upper Qishn Formation of the S1A reservoir in the Masila Basin, Yemen. To achieve this work's ultimate goal, the geostatistical modeling was integrated with open-source code (MRST-CO
2
lab) for reducing the uncertainty assessment of CO
2
storage capacity. Also, there is a significant difference between static and dynamic CO
2
storage capacity. The static CO
2
storage capacity varies from 4.54 to 81.98 million tons, while the dynamic CO
2
simulation is estimated from 4.95 to 17.92 million tons. Based on the geological uncertainty assessment of three ranked realizations (P10, P50, P90), our work found that the Upper Qishn sequence of the S1A reservoir could store 15.64 million tons without leakage. This finding demonstrates that the S1A reservoir has the potential for geological CO
2
storage. Ultimately, this study proposes a useful modeling framework that is easy to adapt for other reservoirs in the Masila Basin in Yemen.
Graphical abstract</description><subject>Anthropogenic factors</subject><subject>Atmospheric models</subject><subject>Carbon dioxide</subject><subject>Carbon dioxide fixation</subject><subject>Carbon sequestration</subject><subject>Clastics</subject><subject>Dynamic models</subject><subject>Energy</subject><subject>Engineering</subject><subject>Environmental Science and Engineering</subject><subject>Foundations</subject><subject>Frameworks</subject><subject>Geoengineering</subject><subject>Geology</subject><subject>Geophysics/Geodesy</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Hydraulics</subject><subject>Modelling</subject><subject>Oil recovery</subject><subject>Oil reservoirs</subject><subject>Original Article</subject><subject>Reservoirs</subject><subject>Simulation</subject><subject>Source code</subject><subject>Storage capacity</subject><subject>Storage conditions</subject><subject>Uncertainty</subject><subject>Water storage</subject><issn>2363-8419</issn><issn>2363-8427</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLAzEQxxdRsGi_gKeA167mta9jKT4KhSLag6cwu5nWaDdZk622Vz-50YrePM0w_8fAL0nOGL1glBaXQdJKlinlLKVU0CzdHiQDLnKRlpIXh787q46TYQimpoLxXEjGB8nH1Pa48tCjJqGH3jSkdRrXxq4IWE30zkIbj8G0m3WUnSVLDy2-O_9Cls6TyZzHoPOwQtJAB43pd8RYsug69OTOhCdLJmsIsTmMyD0bE48B_ZszfkQesUV7mhwtYR1w-DNPksX11cPkNp3Nb6aT8SxtBKv6VBeylnWGMq8lVBXTVDeQSw2MQwE5ChAAUEMtkJaNFgUty7oooOE8qlKLk-R839t597rB0Ktnt_E2vlQ8q7KsrEpRRBffuxrvQvC4VJ03LfidYlR94VZ73CriVt-41TaGxD4Uotmu0P9V_5P6BCzKhX0</recordid><startdate>20220201</startdate><enddate>20220201</enddate><creator>AlRassas, Ayman Mutahar</creator><creator>Vo Thanh, Hung</creator><creator>Ren, Shaoran</creator><creator>Sun, Renyuan</creator><creator>Le Nguyen Hai, Nam</creator><creator>Lee, Kang-Kun</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-7094-9380</orcidid></search><sort><creationdate>20220201</creationdate><title>Integrated static modeling and dynamic simulation framework for CO2 storage capacity in Upper Qishn Clastics, S1A reservoir, Yemen</title><author>AlRassas, Ayman Mutahar ; Vo Thanh, Hung ; Ren, Shaoran ; Sun, Renyuan ; Le Nguyen Hai, Nam ; Lee, Kang-Kun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-d74b4b5e46b4a991d0dca64da12a7a6e3a3aaabab3e08cd37088b77ac22a6e4d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Anthropogenic factors</topic><topic>Atmospheric models</topic><topic>Carbon dioxide</topic><topic>Carbon dioxide fixation</topic><topic>Carbon sequestration</topic><topic>Clastics</topic><topic>Dynamic models</topic><topic>Energy</topic><topic>Engineering</topic><topic>Environmental Science and Engineering</topic><topic>Foundations</topic><topic>Frameworks</topic><topic>Geoengineering</topic><topic>Geology</topic><topic>Geophysics/Geodesy</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Hydraulics</topic><topic>Modelling</topic><topic>Oil recovery</topic><topic>Oil reservoirs</topic><topic>Original Article</topic><topic>Reservoirs</topic><topic>Simulation</topic><topic>Source code</topic><topic>Storage capacity</topic><topic>Storage conditions</topic><topic>Uncertainty</topic><topic>Water storage</topic><toplevel>online_resources</toplevel><creatorcontrib>AlRassas, Ayman Mutahar</creatorcontrib><creatorcontrib>Vo Thanh, Hung</creatorcontrib><creatorcontrib>Ren, Shaoran</creatorcontrib><creatorcontrib>Sun, Renyuan</creatorcontrib><creatorcontrib>Le Nguyen Hai, Nam</creatorcontrib><creatorcontrib>Lee, Kang-Kun</creatorcontrib><collection>CrossRef</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Geomechanics and geophysics for geo-energy and geo-resources.</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>AlRassas, Ayman Mutahar</au><au>Vo Thanh, Hung</au><au>Ren, Shaoran</au><au>Sun, Renyuan</au><au>Le Nguyen Hai, Nam</au><au>Lee, Kang-Kun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrated static modeling and dynamic simulation framework for CO2 storage capacity in Upper Qishn Clastics, S1A reservoir, Yemen</atitle><jtitle>Geomechanics and geophysics for geo-energy and geo-resources.</jtitle><stitle>Geomech. Geophys. Geo-energ. Geo-resour</stitle><date>2022-02-01</date><risdate>2022</risdate><volume>8</volume><issue>1</issue><artnum>2</artnum><issn>2363-8419</issn><eissn>2363-8427</eissn><abstract>Carbon dioxide (CO
2
) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate large-scale anthropogenic CO
2
emissions into the atmosphere. In this context, CO
2
sequestration into depleted oil reservoirs is a practical approach, as it boosts the oil recovery and facilitates the permanent storing of CO
2
into the candidate sites. However, the estimation of CO
2
storage capacity in the subsurface is a challenge to kick-start CCS worldwide. Thus, this paper proposes an integrated static and dynamic modeling framework to tackle the challenge of CO
2
storage capacity in the Upper Qishn Formation of the S1A reservoir in the Masila Basin, Yemen. To achieve this work's ultimate goal, the geostatistical modeling was integrated with open-source code (MRST-CO
2
lab) for reducing the uncertainty assessment of CO
2
storage capacity. Also, there is a significant difference between static and dynamic CO
2
storage capacity. The static CO
2
storage capacity varies from 4.54 to 81.98 million tons, while the dynamic CO
2
simulation is estimated from 4.95 to 17.92 million tons. Based on the geological uncertainty assessment of three ranked realizations (P10, P50, P90), our work found that the Upper Qishn sequence of the S1A reservoir could store 15.64 million tons without leakage. This finding demonstrates that the S1A reservoir has the potential for geological CO
2
storage. Ultimately, this study proposes a useful modeling framework that is easy to adapt for other reservoirs in the Masila Basin in Yemen.
Graphical abstract</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s40948-021-00305-x</doi><orcidid>https://orcid.org/0000-0002-7094-9380</orcidid></addata></record> |
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subjects | Anthropogenic factors Atmospheric models Carbon dioxide Carbon dioxide fixation Carbon sequestration Clastics Dynamic models Energy Engineering Environmental Science and Engineering Foundations Frameworks Geoengineering Geology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Hydraulics Modelling Oil recovery Oil reservoirs Original Article Reservoirs Simulation Source code Storage capacity Storage conditions Uncertainty Water storage |
title | Integrated static modeling and dynamic simulation framework for CO2 storage capacity in Upper Qishn Clastics, S1A reservoir, Yemen |
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