Details

Autor(en) / Beteiligte

• Zampieri, M. F.
• Ferreira, V. H. S.
• Quispe, C. C.
• Sanches, K. K. M.
• Moreno, R. B. Z. L.

Titel

History matching of experimental polymer flooding for enhanced viscous oil recovery

Ist Teil von

• Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2020-04, Vol.42 (4), Article 205

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2020

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Polymer flooding has been widely studied and applied for enhancing reservoir oil recovery. The key to evaluating the potential application of polymer injection is based on a clear understanding of the mechanisms involved in the recovery process. This work focuses on history matching of laboratory core flooding of heavy oil recovery by polymer flooding. We match the experiments through a small-scale simulation model and evaluate the challenges of representing the polymer behavior in porous media. The methodology we propose in this paper aims to model core-flooding experiments with laboratory-measured data. These data come from different experiments, including rheology, single- and two-phase core flooding and are separated into consolidated and uncertain data. Consolidated data include: core volume, permeability, porosity, oil viscosity and density, initial saturation conditions, test temperature and injection rate. The uncertain input parameters involve more complex variables, such as viscosity behavior against shear rate and concentration, residual resistance factor, adsorption, inaccessible pore volume and water–oil relative permeabilities. We compare the simulation output parameters with laboratory results and evaluate the quality of the match for four different two-phase core-flooding experiments. The output parameters include histories for differential pressure, recovery factor, water cut and cumulative produced water, oil and liquid. Our results show that the simulation models successfully matched the experimental data, for all the cases, using appropriate representation of the laboratory parameters. The contribution of this work relies on the proposed methodology, which allows integrating the laboratory data in the construction and validation of core scale simulation models appropriately.