PittsburghV1, Main, Exploration, bibRecord, 004F14

Spatial Stochastic Modeling of Sedimentary Formations to Assess CO2 Storage Potential

Identifieur interne : 004F14 ( Main/Exploration ); précédent : 004F13; suivant : 004F15

Spatial Stochastic Modeling of Sedimentary Formations to Assess CO2 Storage Potential

Auteurs : Olga H. Popova [États-Unis] ; Mitchell J. Small [États-Unis] ; Sean T. Mccoy [États-Unis] ; A. C. Thomas [États-Unis] ; Stephen Rose [États-Unis] ; Bobak Karimi [États-Unis] ; Kristin Carter [États-Unis] ; Angela Goodman [États-Unis]

Source :

Environmental science & technology [ 0013-936X ] ; 2014.

RBID : Pascal:15-0025899

Descripteurs français

Pascal (Inist)
- Séquestration carbone, Séquestration CO2, Dioxyde de carbone, Engrais organique, Formation géologique, Modèle stochastique, Géostatistique, Bassin sédimentaire, Pennsylvanie, Gaz effet serre, Changement climatique, Mitigation, Développement durable, Analyse statistique, Géo-ingénierie, Aquifère salin, Réduction des émissions.
Wicri :
- topic : Engrais organique, Changement climatique, Développement durable.

English descriptors

KwdEn :
- CO2 sequestration, Carbon dioxide, Carbon sequestration, Emissions reduction, Geoengineering, Geological formation, Mitigation, Organic fertilizer, Pennsylvania, Saline aquifer, climate change, geostatistics, greenhouse gas, sedimentary basins, statistical analysis, stochastic models, sustainable development.

Abstract

Carbon capture and sequestration (CCS) is a technology that provides a near-term solution to reduce anthropogenic CO₂ emissions to the atmosphere and reduce our impact on the climate system. Assessments of carbon sequestration resources that have been made for North America using existing methodologies likely underestimate uncertainty and variability in the reservoir parameters. This paper describes a geostatistical model developed to estimate the CO₂ storage resource in sedimentary formations. The proposed stochastic model accounts for the spatial distribution of reservoir properties and is implemented in a case study of the Oriskany Formation of the Appalachian sedimentary basin. Results indicate that the CO₂ storage resource for the Pennsylvania part of the Oriskany Formation has substantial spatial variation due to heterogeneity of formation properties and basin geology leading to significant uncertainty in the storage assessment. The Oriskany Formation sequestration resource estimate in Pennsylvania calculated with the effective efficiency factor, E = 5%, ranges from 0.15 to 1.01 gigatonnes (Gt) with a mean value of 0.52 Gt of CO₂ (E = 5%). The methodology is generalizable to other sedimentary formations in which site-specific trend analyses and statistical models are developed to estimate the CO₂ sequestration storage capacity and its uncertainty. More precise CO₂ storage resource estimates will provide better recommendations for government and industry leaders and inform their decisions on which greenhouse gas mitigation measures are best fit for their regions.

Affiliations:

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Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>CO2 sequestration</term>
<term>Carbon dioxide</term>
<term>Carbon sequestration</term>
<term>Emissions reduction</term>
<term>Geoengineering</term>
<term>Geological formation</term>
<term>Mitigation</term>
<term>Organic fertilizer</term>
<term>Pennsylvania</term>
<term>Saline aquifer</term>
<term>climate change</term>
<term>geostatistics</term>
<term>greenhouse gas</term>
<term>sedimentary basins</term>
<term>statistical analysis</term>
<term>stochastic models</term>
<term>sustainable development</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Séquestration carbone</term>
<term>Séquestration CO2</term>
<term>Dioxyde de carbone</term>
<term>Engrais organique</term>
<term>Formation géologique</term>
<term>Modèle stochastique</term>
<term>Géostatistique</term>
<term>Bassin sédimentaire</term>
<term>Pennsylvanie</term>
<term>Gaz effet serre</term>
<term>Changement climatique</term>
<term>Mitigation</term>
<term>Développement durable</term>
<term>Analyse statistique</term>
<term>Géo-ingénierie</term>
<term>Aquifère salin</term>
<term>Réduction des émissions</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Engrais organique</term>
<term>Changement climatique</term>
<term>Développement durable</term>
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<front><div type="abstract" xml:lang="en">Carbon capture and sequestration (CCS) is a technology that provides a near-term solution to reduce anthropogenic CO<sub>2</sub>
 emissions to the atmosphere and reduce our impact on the climate system. Assessments of carbon sequestration resources that have been made for North America using existing methodologies likely underestimate uncertainty and variability in the reservoir parameters. This paper describes a geostatistical model developed to estimate the CO<sub>2</sub>
 storage resource in sedimentary formations. The proposed stochastic model accounts for the spatial distribution of reservoir properties and is implemented in a case study of the Oriskany Formation of the Appalachian sedimentary basin. Results indicate that the CO<sub>2</sub>
 storage resource for the Pennsylvania part of the Oriskany Formation has substantial spatial variation due to heterogeneity of formation properties and basin geology leading to significant uncertainty in the storage assessment. The Oriskany Formation sequestration resource estimate in Pennsylvania calculated with the effective efficiency factor, E = 5%, ranges from 0.15 to 1.01 gigatonnes (Gt) with a mean value of 0.52 Gt of CO<sub>2</sub>
 (E = 5%). The methodology is generalizable to other sedimentary formations in which site-specific trend analyses and statistical models are developed to estimate the CO<sub>2</sub>
 sequestration storage capacity and its uncertainty. More precise CO<sub>2</sub>
 storage resource estimates will provide better recommendations for government and industry leaders and inform their decisions on which greenhouse gas mitigation measures are best fit for their regions.</div>
</front>
</TEI>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Pennsylvanie</li>
</region>
<settlement><li>Pittsburgh</li>
</settlement>
<orgName><li>Université Carnegie-Mellon</li>
<li>Université de Pittsburgh</li>
</orgName>
</list>
<tree><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Popova, Olga H" sort="Popova, Olga H" uniqKey="Popova O" first="Olga H." last="Popova">Olga H. Popova</name>
</region>
<name sortKey="Carter, Kristin" sort="Carter, Kristin" uniqKey="Carter K" first="Kristin" last="Carter">Kristin Carter</name>
<name sortKey="Goodman, Angela" sort="Goodman, Angela" uniqKey="Goodman A" first="Angela" last="Goodman">Angela Goodman</name>
<name sortKey="Karimi, Bobak" sort="Karimi, Bobak" uniqKey="Karimi B" first="Bobak" last="Karimi">Bobak Karimi</name>
<name sortKey="Mccoy, Sean T" sort="Mccoy, Sean T" uniqKey="Mccoy S" first="Sean T." last="Mccoy">Sean T. Mccoy</name>
<name sortKey="Rose, Stephen" sort="Rose, Stephen" uniqKey="Rose S" first="Stephen" last="Rose">Stephen Rose</name>
<name sortKey="Small, Mitchell J" sort="Small, Mitchell J" uniqKey="Small M" first="Mitchell J." last="Small">Mitchell J. Small</name>
<name sortKey="Small, Mitchell J" sort="Small, Mitchell J" uniqKey="Small M" first="Mitchell J." last="Small">Mitchell J. Small</name>
<name sortKey="Thomas, A C" sort="Thomas, A C" uniqKey="Thomas A" first="A. C." last="Thomas">A. C. Thomas</name>
</country>
</tree>
</affiliations>
</record>

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Spatial Stochastic Modeling of Sedimentary Formations to Assess CO2 Storage Potential

Spatial Stochastic Modeling of Sedimentary Formations to Assess CO2 Storage Potential

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