Stabilization of Artificial Gas Lift System Using Nonlinear Model Predictive Control with input Target and Control Zones

Gas lift, like every other artificial lift methods is used when the natural source of energy for lifting crude oil from the reservoir into the production platforms and then into the downstream facilities becomes insufficient. Interaction of the two-phase fluid in the tubing results in casing heading instability that is undesirable. We remove this instability and enhance crude oil recovery from gas-lifted oil well by use of advanced control system of nonlinear model predictive control (NMPC) with input target and control zones. The infinite Horizon NMPC is presented with the feasibility and convergence. Models of gas-lifted system which is a differential algebraic equation (DAE) system is presented. The oscillatory behavior of the system is shown. The developed NMPC is applied to the DAE gas lift system, where it is used in stabilizing the system and improving oil production rate by 3.4 percent compared to mean open loop production when both are operating at their maximum allowable inputs. The zone controller enables us to select state zones that favor instability removal while driving the input towards more economical value. The advantage of this approach is that instability can be removed or minimized while operating the system as close as possible to its optimal input from the optimization layer