MODEL PREDICTIVE CONTROL FOR ROD PUMP SYSTEMS

Abstract

This paper enables to accelerate fluid recovery from oil and gas reservoirs by automatically controlling fluid height and bottomhole pressure in wells. Several studies in the literature show a significant increase in recoverable oil by determining a target bottomhole pressure, but rarely consider how to control this value. This work provides these advantages by maintaining bottomhole pressure or fluid elevation. Moving horizon estimation (MHE) determines uncertain well parameters using only conventional surface measurements. A model predictive controller (MPC) adjusts the stroke rate of the rod pump to maintain fluid height. Pump boundary conditions are modeled using mathematical programs with complementarity constraints (MPCC), and a nonlinear programming solver finds a solution in near real time. A combined rod string, well and reservoir model simulates dynamic conditions in the well and is formulated for simultaneous optimization by large-scale solvers. MPC increases cumulative oil production over conventional pump shut-in control by maintaining optimal fluid elevation.