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Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site
Carbon dioxide (CO(2)) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO(2) emissions to the atmosphere. This study first simulates the leakage of CO(2) and brine from a storage reservoir through the caprock. Then, we estimate the resulting press...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5172198/ https://www.ncbi.nlm.nih.gov/pubmed/27996043 http://dx.doi.org/10.1038/srep39536 |
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author | Namhata, Argha Oladyshkin, Sergey Dilmore, Robert M. Zhang, Liwei Nakles, David V. |
author_facet | Namhata, Argha Oladyshkin, Sergey Dilmore, Robert M. Zhang, Liwei Nakles, David V. |
author_sort | Namhata, Argha |
collection | PubMed |
description | Carbon dioxide (CO(2)) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO(2) emissions to the atmosphere. This study first simulates the leakage of CO(2) and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites. |
format | Online Article Text |
id | pubmed-5172198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51721982016-12-28 Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site Namhata, Argha Oladyshkin, Sergey Dilmore, Robert M. Zhang, Liwei Nakles, David V. Sci Rep Article Carbon dioxide (CO(2)) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO(2) emissions to the atmosphere. This study first simulates the leakage of CO(2) and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites. Nature Publishing Group 2016-12-20 /pmc/articles/PMC5172198/ /pubmed/27996043 http://dx.doi.org/10.1038/srep39536 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Namhata, Argha Oladyshkin, Sergey Dilmore, Robert M. Zhang, Liwei Nakles, David V. Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site |
title | Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site |
title_full | Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site |
title_fullStr | Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site |
title_full_unstemmed | Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site |
title_short | Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site |
title_sort | probabilistic assessment of above zone pressure predictions at a geologic carbon storage site |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5172198/ https://www.ncbi.nlm.nih.gov/pubmed/27996043 http://dx.doi.org/10.1038/srep39536 |
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