Optimal rate allocation for production and injection wells in an oil and gas field for enhanced profitability

An oil and gas field requires careful operational planning and management via production optimization for increased recovery and long-term project profitability. This article addresses the challenge of production optimization in a field undergoing secondary recovery by water flooding. The field operates with limited processing capacity at the surface separators, pipeline pressure constraints, and water injection constraints; an economic indicator (net present value, NPV) is used as the objective function. The formulated optimization framework adequately integrates slow-paced subsurface dynamics using reservoir simulation, and fast-paced surface dynamics using sophisticated multiphase flow simulation in the upstream facilities. Optimization of this holistic long-term model is made possible by developing accurate second-order polynomial proxy models at each time step. The resulting formulation is solved as a nonlinear program using commercially available solvers. A comparative analysis is performed using MATLAB's fmincon solver and the IPOPT solver for their robustness, speed, and convergence stability in solving the proposed problem. By implementing two synthetic case studies, our mathematical programming approach determines the optimal production and injection rates of all wells and further demonstrates considerable improvement to the NPV obtained by simultaneously applying the tools of streamline, reservoir, and surface facility simulation for well rate allocation via systematic NLP optimization.