Quantitative risk assessment in the early stages of a CO 2 geological storage project: implementation of a practical approach in an uncertain context
Methodologies for quantitative risk assessment regarding CO 2 storage operations are currently scarce, mostly because of the lack of experience in this field and the relatively significant degree of uncertainty regarding the subsurface intrinsic properties and the processes occurring after the injec...
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Veröffentlicht in: | Greenhouse gases: science and technology 2015-02, Vol.5 (1), p.50-63 |
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Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | Methodologies for quantitative risk assessment regarding CO
2
storage operations are currently scarce, mostly because of the lack of experience in this field and the relatively significant degree of uncertainty regarding the subsurface intrinsic properties and the processes occurring after the injection starts. This paper presents a practical approach designed to perform a quantitative risk assessment in an uncertain context. Our approach is illustrated by a realistic case study (Paris Basin, France), conceived to be representative of the level of information available in the early stages of a project. It follows the risk assessment principles from the international standards (ISO 31000:2009), which are adapted to account for the specificities and challenges of subsurface operations. After the establishment of the context of the specific case study, the main risks are identified and we analyze two different risk scenarios: risk of brine leakage from an abandoned well and risk of subsurface use conflict.These scenarios were selected to give a comprehensive overview of different types of analysis in terms of available data, modeling tools and uncertainty management methodologies. The main benefit of this paper is to propose an approach, based on existing risk assessment standards, best practices, and analysis tools, which allows an objective quantitative risk analysis taking into account the uncertainties, and therefore enabling fully informed decision‐making while evaluating risk acceptability. |
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ISSN: | 2152-3878 2152-3878 |
DOI: | 10.1002/ghg.1447 |