A New Approach for Dynamic Optimization of Waterflooding Problems

Abstract

Abstract Technological advances have resulted in use of smart wells, which are typically equipped with remotely operated downhole chokes. We present an approach for controlling these chokes so that the water flooding is optimized. The optimization problem is done by maximizing either total cumulative oil production or net present value. The new methodology presented here avoids the limitations related to using optimal control as no adjoint equations are needed and the model equations are treated as a "black box". In the new approach the ensemble Kalman filter is used as an optimization routine, and the methodology is compared to the Partial Enumeration Method. We demonstrate the methodologies on a simple synthetic reservoir with five layers of different permeabilities. The conclusions from this work are that the ensemble Kalman filter approach is working robustly, and the results are in agreement with, or superior to, the results obtained with the Partial Enumeration Method and a reference solution.