Abstract

Polymer flooding can be a viable alternative to improve recovery of heavy oil reservoirs. The comparison of water and polymer flooding demands a detailed simulation results. The analysis of relevant data including uncertainties seeks to improve the decision process and requires a high number of simulation runs. Reservoir engineers usually bypass this problem using fast models to reduce computational time; however, it is important to maintain the reliability of heterogeneous reservoir models. This work presents an evaluation of fast models considering precision of results and simulation time in specific wells of interest. The fast model is required in this case because the simulation time of the entire reservoir would demand excessive computation effort for probabilistic approaches used in the decision analysis. Therefore, the main objective of the proposed work is to establish an innovative approach to evaluate and quantify how the grid size impacts the accuracy of results and both the time and computational resources. Based on the well location, three procedures are compared: (1) original grid size model (OTM), (2) selection of grid size based on streamlines to set a limited region defined by drainage area of wells of interest and a reliable results production index (DA), and (3) upscaling of the simulation model (UP). These two fast models are compared with the OTM model by evaluating water and polymer flooding production indicators. The results show an average simulation time reduction of 65% for the DA method and 34% for the UP method in comparison with OTM model (considering DA and UP cases with acceptable results). The DA method shows better accuracy than the UP method. In conclusion, the DA method offers a good alternative yielding a faster and reliable tool. This work presents a methodology used to build a fast model which can evaluate the impact of fast models in decision analysis comparing water and polymer flooding, especially when using EOR strategies and/or complex reservoirs.

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