On Generalized Reduced Gradient method with multi-start and self-optimizing control structure for gas lift allocation optimization

In most of the gas lifted oil fields, multiple oil wells share lift gas from a common gas distribution source. The lift gas should be distributed optimally among the wells to maximize total oil production. In this paper, a nonlinear dynamic model of the oil field is developed from first principles modeling. One of the objectives of this paper is to solve the optimal lift gas distribution problem using the Generalized Reduced Gradient (GRG) method. In addition, multi-start search routine is developed to ensure that the local optimal solution is closer to the global solution. Sensitivity of the optimal solution to changes in oil field parameters like reservoir pressure, Productivity Indices (PI), total lift gas supply (input disturbance) and separator pressure is studied. It is shown that the available lift gas is distributed among the wells according to the PI values of the wells and the optimal values are highly sensitive to the changes in PI values. A self-optimizing control structure using simple controllers is designed which is capable of keeping the oil field in optimal operating conditions without having to re-optimize the whole process when the input disturbance occur in the system. The simulation results show that the outcome of optimization is increased total oil production which leads to increased profit.