Numerical study on CO2 leakage detection using electrical streaming potential data

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Title:Main Title: Numerical study on CO2 leakage detection using electrical streaming potential data
Description:Abstract: We study the feasibility of detecting carbon dioxide (CO2) movement in the overburden of a storage reservoir due to CO2 leakage through an abandoned well by self-potential (SP) measurements at the surface. This is achieved with three-dimensional numerical (SP) modeling of two-phase fluid flow and electrokinetic coupling between flow and streaming potential. We find that, in typical leakage scenarios, for leaky and/or injection wells with conductive metal casing, self-potential signals originating from injection can be identified at the surface. As the injection signal is also observed at the leaky well with metal casing, SP monitoring can be applied for detecting abandoned wells. However, leakage signals are much smaller than the injection signal and thus masked by the latter. We present three alternatives to overcome this problem: (i) simulate the streaming potential of the nonleaky scenario and subtract the result from the measured streaming potential data; (ii) exploit the symmetry of the injection signal by analyzing the potential difference of dipoles with the dipole center at the injection well; or (iii) measure SP during periods where the injection is interrupted. In our judgement, the most promising approach for detecting a real-world CO2 leakage is by combining methods (i) and (ii), because this would give the highest signal from the leakage and omit signals originating from the injection well. Consequently, we recommend SP as monitoring method for subsurface CO2 storage, especially because a leakage can be detected shortly after the injection started even before CO2 arrives at the leaky well.
Identifier:10.1002/2016WR019803 (DOI)
Citation Advice:Busing, H., C. Vogt, A. Ebigbo, and N. Klitzsch (2017), Numerical study on CO2 leakage detection using electrical streaming potential data, Water Resour. Res., 53, doi:10.1002/2016WR019803.
Responsible Party
Creators:Henrik B├╝sing (Author), Christian Vogt (Author), Anozie Ebigbo (Author), Norbert Klitzsch (Author)
Contributor:Johanna Ochs (Contact Person)
Publisher:AGU PUBLICATIONS, Washington DC, USA
Publication Year:2017
TR32 Topic:Other
Related Subproject:B8
Subjects:Keywords: CO2 Flux, Modelling
GEMET Thesaurus entry: carbon dioxide
Geogr. Information Topic:Environment
File Details
Data Type:Text - Article
File Size:1.4 MB
Date:Accepted: 17.12.2016
Mime Type:application/pdf
Data Format:PDF (PDF-1.7)
Download Permission:Only Project Members
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Licence:[TR32DB] Data policy agreement
Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Water Resources Research
Number of Pages:15 (455 - 469)
Metadata Details
Metadata Creator:Johanna Ochs
Metadata Created:21.05.2017
Metadata Last Updated:21.05.2017
Funding Phase:3
Metadata Language:English
Metadata Version:V50
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