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With the advances in smart well technology, substantially higher oil recovery can be achieved by intelligently managing the operations in a closed-loop optimization framework. The closed-loop optimization consists of two parts: geological model updating and production optimization. Both of these parts require gradient information to minimize or maximize an objective function: squared data mismatch or the net present value (or other quantities depending on financial goals), respectively. Alternatively, an ensemble-based method can acquire the gradient information through the correlations provided by the ensemble. Computation of the optimal controls in this way is nearly independent of the number of control variables, reservoir simulator, and simulation solver. In this paper, we propose an ensemble-based closed-loop optimization method that combines a novel ensemble-based optimization scheme (EnOpt …