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Modelling and monitoring of geological carbon storage: A perspective on cross-validation

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  • Jiang, Xi
  • Akber Hassan, Wasim A.
  • Gluyas, Jon

Abstract

Effective monitoring and numerical simulations are essential to understanding the implications of long-term geological carbon storage; in particular, the predictions of CO2 plume flow under storage conditions, storage integrity of sites, and the design and operational aspects of the CO2 storage projects could be significantly supplemented. Site monitoring data can assure reliability and accuracy of the numerical simulation while numerical prediction results will provide more detailed information on the storage process. The cross-validation between numerical modelling results and monitoring data can play a major role in the development of carbon capture and storage technology. This paper briefly reviews the monitoring and modelling technologies associated with geological carbon storage. In addition, the spatial and temporal resolutions of the numerical simulations are highlighted, while estimations on the resolutions of some commonly used monitoring technologies are also presented. It is revealed that there are gaps in the correlations and cross-validation between the two technologies, where a possible option to reduce the gaps is to enforce more research efforts on multi-scale modelling and appropriate variable correlations.

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  • Jiang, Xi & Akber Hassan, Wasim A. & Gluyas, Jon, 2013. "Modelling and monitoring of geological carbon storage: A perspective on cross-validation," Applied Energy, Elsevier, vol. 112(C), pages 784-792.
  • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:784-792
    DOI: 10.1016/j.apenergy.2013.01.068
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    6. Zhong, Jinjin & Jiang, Xi, 2017. "A case study of using cosmic ray muons to monitor supercritical CO2 migration in geological formations," Applied Energy, Elsevier, vol. 185(P2), pages 1450-1458.
    7. Zhang, Shuwei & Bauer, Nico & Luderer, Gunnar & Kriegler, Elmar, 2014. "Role of technologies in energy-related CO2 mitigation in China within a climate-protection world: A scenarios analysis using REMIND," Applied Energy, Elsevier, vol. 115(C), pages 445-455.
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