Model predictive automatic control of sucker rod pump system with simulation case study

Abstract

This work enables accelerated fluid recovery in oil and gas reservoirs by automatically controlling fluid height and bottomhole pressure in wells. Several literature studies show significant increase in recovered oil by determining a target bottomhole pressure but rarely consider how to control to that value. This work enables those benefits by maintaining bottomhole pressure or fluid height. Moving Horizon Estimation (MHE) determines uncertain well parameters using only common surface measurements. A Model Predictive Controller (MPC) adjusts the stroking speed of a sucker rod pump to maintain fluid height. Pump boundary conditions are simulated with Mathematical Programs with Complementarity Constraints (MPCCs) and a nonlinear programming solver finds a solution in near real-time. A combined rod string, well, and reservoir model simulate dynamic well conditions, and are formulated for simultaneous optimization by large-scale solvers. MPC increases cumulative oil production vs. conventional pump off control by maintaining an optimal fluid level height.