An Optimization-Based Facility Network Solver for Well Allocation in Reservoir Simulation

Abstract

When coupling reservoir simulators to surface network solvers, an often used strategy is to perform a rule or priority-driven allocation based on individual well and group constraints, augmented by back-pressure constraints computed periodically by the network solver. The allocation algorithm uses an iteration that applies well-established heuristics in a sequential manner until all constraints are met. The rationale for this approach is simply to maximize performance and simulation throughput; one of its drawbacks is that the computed allocation may not be feasible with respect to the overall network balance, especially in cases where not all wells can be choked individually. In the work presented here, the authors integrate the well allocation process into the network flow solver, in the form of an optimization engine, to ensure that the solution conforms to the network rate and pressure balance equations. Results for three stand-alone test cases are discussed.