Water flooding performance prediction in layered reservoirs using improved capacitance-resistive model

In this paper, we extend the available capacitance-resistive approach to estimate and optimize waterflooding performance in layered reservoir. For this approach well injection/production data and, likewise, Production Logging Tools (PLT) should be coupled with the basic equations of the CRM. This new approach is applied for a synthetic waterflooded layered reservoir in combination with a fractional-flow model. Genetic algorithm is used to solve the developed CRM. Results of this developed model show an appropriate agreement with those of a grid based commercial simulator. In comparison with commercial simulator results, the average relative error of 4.13% is obtained for estimation of oil production by the developed model. Also, the new approach is applied for a real layered reservoir and it is shown how the improvements in the model can improve the results.