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Open-Source Proxy Tool for CO2 Injection and Storage Modeling - Sustainable Utilization of the Norwegian Continental Shelf

CORDIS · observation · Publication date unknown

nsidered by considering the effect of GCGM parameters on CIS. The effect of GCGM parameters on such processes will be useful in CO2 leakage risk quantification, making the proxy model more realistic. Machine learning tools, such as PINN, ANN, SVR, and XGBoost, will be applied to the simulated data set to digitalize the CIS process efficiently. The developed proxy model will be validated with a synthetic truth model. Lastly, the novel proxy model will be added as a separate module to MRST - an open-access software. This integration offers researchers and industry professionals an openly accessible, fast & accurate proxy model to streamline the initial evaluation of CIS projects. Machine Learning, Proxy Modeling, Geological Carbon Sequestration, CO2 Storage, CO2 Enhanced Oil Recovery, Norwegian Continental Shelf

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recordType

award

status

TERMINATED

region

EU

value

226751.04

unit

EUR