Estimation of Local Equilibrium Model Parameters for Simulation of the Laboratory Foam-Enhanced Oil Recovery Process Using a Commercial Reservoir Simulator
Author(s) -
Lei Ding,
Leyu Cui,
Stéphane Jouenne,
Oussama Gharbi,
Mayur Pal,
Henri Bertin,
Mohammad Azizur Rahman,
Carolina Romero,
D. Guérillot
Publication year - 2020
Publication title -
acs omega
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.779
H-Index - 40
ISSN - 2470-1343
DOI - 10.1021/acsomega.0c03401
Subject(s) - enhanced oil recovery , porous medium , petroleum engineering , relative permeability , reservoir simulation , permeability (electromagnetism) , simulation modeling , porosity , materials science , simulation , process engineering , environmental science , computer science , chemistry , engineering , mathematics , composite material , biochemistry , membrane , mathematical economics
An accurate determination of the foam simulation parameters is crucial in modeling foam flow in porous media. In this paper, we present an integrated workflow to obtain the parameters in the local equilibrium foam model by history matching a series of laboratory experiments performed at reservoir conditions (131 F and 1500 psi) on Estaillades limestone using a commercial reservoir simulator. The gas-water and water-oil relative permeability curves were first validated after history matching with the unsteady-state flooding experiments. The modeling parameters for foam generation and foam dry-out effect were obtained by history matching with the gas/surfactant coinjection experiments at varying foam quality and injection rates. Moreover, the modeling parameters for the destabilizing effect of oil on foam and foam shear thinning effect were derived after history matching with the foam-enhanced oil recovery process and oil fractional flow experiments in the laboratory. In practice, the calculated results reproduce the experimental outputs reasonably well. Furthermore, sensitivity analysis of foam modeling parameters is investigated to determine the most dominating parameters for accurate simulation of foam-enhanced oil recovery process in porous media. In this work, an efficient parameter estimation approach is developed from reliable foam flooding experimental data, which may be further applied to field-scale simulation. Moreover, the simulation approach can also be utilized to facilitate our interpretation of complex lab foam flooding results.
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