Quantitative assessment of monitoring strategies for conformance verification of CO2 storage projects
article
We propose a quantitative model-based workflow for conformance verification of CO2 storage projects. Bayesian inference is applied to update an ensemble of simulation models that capture prior uncertainty based on mis matches with measured data. Conformance assessments are derived by comparison of updated model predictions with storage permit requirements and confidence criteria. Two examples, one conceptual and one based on a real candidate storage site, are provided in which the quantitative workflow is applied to the a priori assessment of candidate monitoring strategies. The examples illustrate the limitations of pressure monitoring in the presence of realistic subsurface uncertainties, and the potential for cost saving by informed design of geophysical monitoring surveys. Approximate methods are discussed that could make the workflow also applicable for (quasi) real-time conformance monitoring.
Topics
TNO Identifier
967766
ISSN
17505836
Source
International Journal of Greenhouse Gas Control, 110, pp. 1-18.
Publisher
Elsevier Ltd
Article nr.
103403
Pages
1-18
Files
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