Geologic CO2 sequestration monitoring design: A machine learning and uncertainty quantification based approach

•Filtering-based data assimilation method is developed to perform monitoring design.•Machine learning is used to reduce computational cost of data assimilation process.•Uncertainty reduction is chosen as the metric to quantify the VOI of monitoring data. Monitoring is a crucial aspect of geologic ca...

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Veröffentlicht in:	Applied energy 2018-09, Vol.225 (C), p.332-345
Hauptverfasser:	Chen, Bailian, Harp, Dylan R., Lin, Youzuo, Keating, Elizabeth H., Pawar, Rajesh J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Data assimilation Earth Sciences Geologic carbon sequestration Geologic carbon sequestration, monitoring design, machine learning, reduced order model, data assimilation, uncertainty reduction GEOSCIENCES Machine learning Monitoring design Reduced order model Uncertainty reduction
Online-Zugang:	Volltext
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