Optimization of petroleum reservoir waterflooding using receding horizon approach

In this paper, static and dynamic optimization of a reservoir waterflooding process for enhanced oil recovery was studied. The dynamic optimization was achieved using receding horizon (RH) algorithms. Two forms of RH which are moving-end and fixed-end RH were formulated and compared. MATLAB Reservoir Simulator (MRST) from SINTEF was used for reservoir simulation. The objective function to be maximized is net present value (NPV) of the venture while the control variable is water injection rate. Sequential quadratic programming (SQP) was applied for the optimization. It was found out that fixed-end RH gave the highest NPV with improvements of 0.81% and 1.49% over static and moving-end RH strategies respectively.