Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session D36: Porous Media Flow: CO2 Sequestration and Other Geological Applications
2:30 PM–4:40 PM,
Sunday, November 18, 2018
Georgia World Congress Center
Room: B408
Chair: Marc Hesse, University of Texas, Austin
Abstract ID: BAPS.2018.DFD.D36.3
Abstract: D36.00003 : A machine learning approach to subsurface characterization in CO2-EOR operations
2:56 PM–3:09 PM
Presenter:
Mohammad Nomeli
(University of Maryland, California State University)
Author:
Mohammad Nomeli
(University of Maryland, California State University)
Sequestration of carbon dioxide (CO2) in deep, geologic formations is one of the most promising solutions to decrease CO2 concentration in the atmosphere. Depleted hydrocarbon reservoirs are one of the geologic targets considered for sequestration. Even though CO2 is currently being used in the Enhanced Oil Recovery (EOR) operations, characterization of hydrocarbon reservoirs through an integrated study that includes experiments and numerical simulations is required to evaluate the actual efficiency of the CO2-EOR operations. A novel Machine Learning algorithm is developed to dynamically characterize hydrocarbon reservoirs. The availability of hydrocarbon reservoirs properties contributes to the optimization of the project, both technically and economically. The results show a good agreement with other experimental literature data.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.D36.3
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