Estimation and uncertainty analysis of the CO2 storage volume in the sleipner field via 4D reversible-jump markov-chain Monte Carlo SCIE SCOPUS
DC Field | Value | Language |
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dc.contributor.author | Cho, Yongchae | - |
dc.contributor.author | Jun, Hyunggu | - |
dc.date.accessioned | 2021-05-20T07:06:35Z | - |
dc.date.available | 2021-05-20T07:06:35Z | - |
dc.date.created | 2021-02-22 | - |
dc.date.issued | 2021-05 | - |
dc.identifier.issn | 0920-4105 | - |
dc.identifier.uri | https://sciwatch.kiost.ac.kr/handle/2020.kiost/41317 | - |
dc.description.abstract | Many scientists have developed technology to store CO2 in the subsurface and to monitor the storage conditions to comply with the requirements for zero detectable leakage and greenhouse gas control. The goal of this research is to propose a novel workflow to estimate the stored CO2 volume and to quantify the uncertainty of the injected volume. We implemented geophysical stochastic inversion using the time-lapse 3D seismic volumes as inputs, which provides an indirect estimation of the velocity changes and the migration path of the injected gas content. When performing the inversion, we employed the reversible-jump approach and used the Sleipner time-lapse 3D seismic volumes to demonstrate the proposed workflow. The inversion result was validated via forward modeling and pseudo well log interpretation. We then built a structural geology model and populated porosity logs by performing 500 realizations for volumetric analysis. In a comparison of the measured volume of the injected gas via volumetric analysis results, the predicted subsurface CO2 volume linearly increases in the same phase with the injection rate, and the volume estimation error is less than 17%. | - |
dc.description.uri | 1 | - |
dc.language | English | - |
dc.publisher | ELSEVIER | - |
dc.title | Estimation and uncertainty analysis of the CO2 storage volume in the sleipner field via 4D reversible-jump markov-chain Monte Carlo | - |
dc.type | Article | - |
dc.citation.title | JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING | - |
dc.citation.volume | 200 | - |
dc.contributor.alternativeName | 전형구 | - |
dc.identifier.bibliographicCitation | JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, v.200 | - |
dc.identifier.doi | 10.1016/j.petrol.2020.108333 | - |
dc.identifier.scopusid | 2-s2.0-85100663704 | - |
dc.identifier.wosid | 000628819200034 | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.subject.keywordPlus | Carbon dioxide | - |
dc.subject.keywordPlus | Greenhouse gases | - |
dc.subject.keywordPlus | Markov chains | - |
dc.subject.keywordPlus | Seismology | - |
dc.subject.keywordPlus | Stochastic systems | - |
dc.subject.keywordPlus | Structural geology | - |
dc.subject.keywordPlus | Volumetric analysis | - |
dc.subject.keywordPlus | Well logging | - |
dc.subject.keywordPlus | Forward modeling | - |
dc.subject.keywordPlus | Injection rates | - |
dc.subject.keywordPlus | Inversion results | - |
dc.subject.keywordPlus | Reversible jump | - |
dc.subject.keywordPlus | Reversible jump Markov chain Monte Carlo | - |
dc.subject.keywordPlus | Storage condition | - |
dc.subject.keywordPlus | Velocity changes | - |
dc.subject.keywordPlus | Volume estimations | - |
dc.subject.keywordPlus | Uncertainty analysis | - |
dc.subject.keywordAuthor | Carbon capture and sequestration | - |
dc.subject.keywordAuthor | Time-lapse monitoring | - |
dc.subject.keywordAuthor | Markov-chain Monte Carlo | - |
dc.subject.keywordAuthor | Uncertainty analysis | - |
dc.subject.keywordAuthor | Volume estimation | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Engineering, Petroleum | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalResearchArea | Engineering | - |