Quantification of Simulation Model Grid Size Impact on Polymer Flooding Application in Heavy Oil Heterogeneous Reservoir

Abstract Polymer flooding can be a viable alternative to enhance oil recovery of heavy oil fields. The comparison of water and polymer flooding requires a reliable reservoir numerical model to safely ensure the decision analysis including uncertainties and involving a significant amount of simulation runs. Reservoir engineers usually work-around this problem using fast models to reduce computational time; however, it is important to maintain the reliability of heterogeneous reservoir models. Therefore, the proposed work demonstrates how the grid size impacts on accuracy of results and both the time and computational resources. In addition, it is performed an analysis to establish how the typical physical phenomena related to the polymer flooding impact the applicability of the proposed methodology. A highly heterogeneous heavy oil field is used in our proposed studies. The application is conducted to assist pilot test wells. Initially, the definition of the reference strategy (OTM) is presented. In this case study, the OTM strategy is based on the optimization of location and number of wells. Secondly, the effect of grid size on the process is evaluated through two procedures: (1) DA method: a selection of grid size defined by drainage area of the selected wells; and (2) UP method: upscaling is performed in the simulation model. Then, production parameters resulting from models of both procedures (DA and UP) are compared with OTM results. The definition of which procedure is better to represent the wells of interest is performed. Finally, the impact of three polymer flooding physical phenomena (degradation, adsorption and Non-Newtonian effect) on production results is presented, in order to verify the accuracy of the generated fast models in maintained considering these effects. The DA method present good accuracy for reservoir response compared to the reference OTM results. Differently, UP models are not as accurate as DA models for production results indicators. In conclusion, the application of the methodology allows choosing the DA over the UP technique to support our decision in the investigated recovery methods, showing a reliable and fast procedure. Finally, this procedure shows excellent applicability and robustness when a typical polymer flooding study is carried out: the evaluation of physical phenomena impact on production results based on wells of interest.