Implementable MPC strategies for oilfield with electric submersible pump installations

Abstract

This work addresses the development of model predictive control (MPC) strategies applied to artificial lift systems based on electric submersible pumping (ESP), aiming to overcome challenges related to process stabilization in wide operating ranges, compliance with typical ESP constraints, and the pursuit of energy efficiency goals. Although the topic has been widely explored in the literature, the proposed solutions are mostly based on linear approaches that have degraded performance outside the nominal condition. Strategies based on nonlinear models and adaptive MPC have been suggested, but they face practical challenges, such as implementation in embedded systems and ensuring closed-loop stability, factors that are associated with the safety and reliability required by the industry. The main contribution of this thesis is the creation of MPC schemes that stabilize the process in a wide operating range, considering economic goals and operational constraints, in addition to allowing implementation in embedded systems with automatic generation of C/C++ code. This thesis proposes four MPC strategies to overcome the limitations of the approaches found in the literature: (i) an adaptive MPC control with successive linearization of the ESP model, ensuring the feasibility of the control law and operational stability over a wide range; (ii) a nonlinear MPC control coupled with an extended Kalman filter, which extends the operating range and estimates difficult-to-measure variables, such as the average flow rate; (iii) a robust extension of the infinite-horizon MPC, which considers operational uncertainties and constraints and ensures robust stabilization; and (iv) an improved version of the nonlinear MPC with an infinite prediction horizon to ensure nominal stability and computational feasibility in practical scenarios. Simulations and hardware-in-the-loop tests demonstrate the feasibility of these MPC solutions for real-time operation, highlighting the potential of nonlinear and robust approaches to optimize the operation of ESP systems in oil production fields.