Nonlinear Model Predictive Control of Hydrocyclone Separation Efficiency

As oil fields mature, an increasing volume of water is produced alongside the oil and gas due to the injection of water to maintain reservoir pressure. The control of de-oiling hydrocyclones in produced water treatment on offshore oil and gas facilities is typically based on the pressure drop ratio (PDR). While PDR relates to the flow split in the hydrocyclone and affects the separation efficiency, it is only an indirect way to control the steady-state deoiling efficiency. When the separation facility is subjected to disturbances, e.g., changing inlet concentration or production volume, the separation efficiency changes dynamically. The PDR responds to changes in flow rate, but it cannot sense changes in inlet oil content. By deploying online oil-in-water monitors, the separation efficiency could, in principle, be measured and used for dynamic feedback. This work developed a plant model based on previously published models of PDR, separator water level, and hydrocyclone separation efficiency. A nonlinear model predictive controller is designed and placed in cascade with the existing PDR-based PI controller to optimize the hydrocyclone separation efficiency. The results indicate an increased separation efficiency and, thus, a potential reduction in discharged oil of approximately 12 percentage points.