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Mechanistic Modeling of Water-Alternating-Gas Injection and Foam-Assisted Chemical Flooding for Enhanced Oil Recovery
History-matching of core-flood experimental data through numerical modeling is a powerful tool to get insight into the relevant physical parameters and mechanisms that control fluid flow in enhanced oil recovery processes. We conducted a mechanistic numerical simulation study aiming at modeling prev...
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Published in: | Industrial & engineering chemistry research 2020-02, Vol.59 (8), p.3606-3616 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | History-matching of core-flood experimental data through numerical modeling is a powerful tool to get insight into the relevant physical parameters and mechanisms that control fluid flow in enhanced oil recovery processes. We conducted a mechanistic numerical simulation study aiming at modeling previously performed water-alternating-gas and foam-assisted chemical flooding core-flood experiments. For each experiment, a one-dimensional model was built. The obtained computed tomography scan data was used to assign varying porosity, and permeability, values to each grid block. The main goal of this study was to history-match measured phase saturation profiles along the core length, pressure drops, produced phase cuts, and the oil recovery history for each of the experiments conducted. The results show that, to obtain a good match for the water-alternating-gas experiment, gas relative permeability needs to be reduced as a function of injection time due to gas trapping. The surfactant phase behavior, for the aid of foam-assisted chemical flooding, was successfully simulated and its robustness was verified by effectively applying the same phase behavior model to the two different salinity conditions studied. It resulted in the oil mobilization, through the injection of a surfactant slug, being properly modeled. The mechanistic simulation of foam using the steady-state foam model built in UTCHEM proved inadequate for the mechanistic modeling of a foam drive in the presence of oil. An alternative heuristic approach was adopted to overcome this limitation. |
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ISSN: | 0888-5885 1520-5045 |
DOI: | 10.1021/acs.iecr.9b06356 |