Well placement optimization is often formulated as an integer-programming problem and is typically carried out assuming known well control settings. Similarly, finding optimal well controls is usually formulated and solved as a control problem in which the well locations are fixed. Solving each problem independently without accounting for the coupling between them leads to suboptimal solutions. We propose to solve the coupled well placement and control optimization problems for improved production performance. We present two alternative methods: i) sequential solution of the decoupled well placement and control subproblems where each subproblem is resolved after updating the decision variables of the other subporoblem from the previous step; ii) simultaneous solution by concurrently changing well locations and controls during the iterations using a generalized stochastic approximation simultaneous perturbations algorithm. The first approach allows for application of well-established methods in the literature to solve each subproblem individually while the second approach requires development of new methods to solve mix-integer optimization problems. We consider field development optimization under geologic uncertainty and discuss computationally efficient approximate solution techniques for robust optimization under ensemble model representations. Several numerical experiments with the PUNQ and a layer of the SPE10 benchmark models demonstrate the applicability of these methods.


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