Abstract
The present study simulated thermal enhanced oil recovery (steam and nanoparticles) for the first time using computational fluid dynamics. To better visualize fluid flow in the reservoir, a 2D micromodel generated by commercial grid generation tools was used as the porous medium. Four parameters that have a great impaction on the process were studied to determine the best combination of factors to attain maximum oil recovery. Type of nanoparticle, volume fraction of nanoparticles, diameter of nanoparticles and temperature of injected fluid were examined using the Taguchi method. All governing equations were solved in Fluent software based on finite volume. The numerical results were in a good agreement with the experimental results and the data shows that Al2O3 nanoparticles have the greatest potential for enhanced oil recovery in comparison with CuO and Fe3O4 nanoparticles. Decreasing the diameter of the nanoparticles and increasing their volume fraction in the base fluid and the temperature of the injected fluid improved oil recovery and a large amount of oil was produced from the porous medium. Injecting the nanofluid at an optimal level decreased the viscosity of the extra heavy oil from 35 to 25 Pa s.
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