Agradecimentos: The authors would like to thank Petrobras, Statoil and FCMG. Also would like to thank CAPES Foundation for financial support under the process BEX 10004/14-9, University of Campinas – UNICAMP and the Center of Petroleum Studies – CEPETRO for permission to publish this article and provide the support to accomplish this work. We also would like to acknowledge CMG for the software support. We would like to thank ANP (“Compromisso de Investimentos com Pesquisa e Desenvolvimento”) Ver menos

Polymer flooding is a mature EOR technique implemented in many successful field projects. Understanding its mechanisms is very important to managing field operations. Generally, more oil is recovered when polymer solution is injected for a longer time. For a real project, optimization of field operations usually requires consideration of economic indicators, such as net present value (NPV) as objective function so polymer and other costs are included in the decision 3process. Several commercial and in-house simulators have the capability to model polymer flooding for the optimization purposes. In this paper, we present the numerical modeling of polymer retention and the reversibility, inaccessible pore volume, shape of the curve of viscosity vs. polymer concentration, salinity, permeability reduction, non-Newtonian behavior and degradation, etc. We first tested these models in simple benchmark cases, and then applied them to two synthetic field cases. The goal is to understand the impact of each polymer property on field performance indicators, especially NPV. The synthetic fields represent target Brazil oil fields which have high average permeability with heavy oil (~14° API). Retention of polymer, salinity, polymer rheology and degradation can decrease NPV by up to 25%. Permeability reduction, adsorption reversibility, inaccessible pore volume and selection of a correlation curve for the function of viscosity vs. concentration can influence NPV by less than 3%. Identification of the crucial polymer properties/simulation parameters helps with the decision for key laboratory tests and reducing uncertainties associated with each. This information also helps on the selection of simulation models and key sensitivity parameters where unimportant parameters can be neglected in simulation studies Ver menos