Reservoir fluid production optimization to sustain net-present value (NPV) using gradient-based Quasi-Newton method

Abstract

Abstract After several years of production, the strong water drive reservoir can have high water cut. Unlike hydrocarbon, water has no commercial value, and tends to be disposed or separated. This leads to the decline in net present value (NPV) of reservoir. To sustain reservoir’s NPV for as long as possible, a gradient-based Quasi-Newton optimization in reservoir simulation is proposed. This mathematical method uses BFGS algorithm to find the minimum of the objective function of reservoir production. This method also assumes constant production and injection rate. Initially, the algorithm produces the base NPV (before optimized using Quasi-Newton method). After that, BFGS generates optimized NPV by iterating line search in the objective function until it meets the stopping criterion. This algorithm also shows the optimized oil and water production curve. These comparisons show how oil and water should be produced to sustain the NPV. The results show that the water cut value is decreased and NPV decline happens later than the non-optimized NPV. As a conclusion, to answer the sustainable energy needs, Quasi-Newton method using BFGS algorithm and its improvements are suitable to sustain the reservoir production in the long run.