Integration of Prognostics and Control of an Oil/CO2 Subsea Separation System

The exploitation of reserves with a high CO2 content is challenging because of the need for its separation and the environmental impact associated with its generation. In this context, a suitable use for the generated CO2 is its reinjection into the reservoir, and subsea CO2 separation improves the efficiency of this process. The main objective of this work is to investigate the health-aware control of a subsea CO2 separation system. Previously identified linear models were used in a predictive controller with Kalman filter-based state estimation and online model update, and simulations were performed to evaluate the controller tuning. Regarding prognostics, a stochastic model of pump degradation, sensitive to its operating conditions, was proposed, and a particle filter was implemented to perform online degradation state estimation and remaining useful lifetime prediction. Finally, a health-aware controller was designed, which could extend the life of the process by four months when compared to operation with a conventional model predictive controller. Some difficulties in combining reference tracking and lifetime extension objectives were also investigated. The obtained results indicate that dealing with the control problem through the multiobjective optimization theory or addressing the lifetime extension in an optimization layer may improve its performance.