Data-driven prediction of in situ CO2 foam strength for enhanced oil recovery and carbon sequestration

Author:

Iskandarov Javad12ORCID,Fanourgakis George S.34ORCID,Ahmed Shehzad5,Alameri Waleed5,Froudakis George E.3ORCID,Karanikolos Georgios N.1267ORCID

Affiliation:

1. Department of Chemical Engineering, Khalifa University, P. O. Box 127788, Abu Dhabi, UAE

2. Research and Innovation Center on CO2 and H2 (RICH), Khalifa University, P. O. Box 127788, Abu Dhabi, UAE

3. Department of Chemistry, University of Crete, Voutes Campus, Heraklion, GR-70013, Crete, Greece

4. Laboratory of Quantum and Computational Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

5. Department of Petroleum Engineering, Khalifa University, P. O. Box 127788, Abu Dhabi, UAE

6. Center for Catalysis and Separations (CeCaS), Khalifa University, P. O. Box 127788, Abu Dhabi, UAE

7. Department of Chemical Engineering, University of Patras, 26504 Patras, Greece

Abstract

Data-driven approaches for foams can be a time- and data-efficient alternative method to experimental and conventional modeling techniques.

Funder

Khalifa University of Science, Technology and Research

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

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