Feedforward, Cascade and Model Predictive Control Algorithms for De-Oiling Hydrocyclones: Simulation Study

Abstract

Maintaining the efficiency of the produced-water treatment system is important for the oil and gas industry, especially taking into consideration the environmental impact caused of the produced-water. De-oiling hydrocyclones are one of the most common type of equipment used in the produced-water treatment system. The low residence time of this device makes it difficult for a control system to maintain efficiencies at different plant disturbances. In this paper, a control-oriented hydrocyclone model with a traditional pressure drop ratio (PDR) controller is analysed, and the inability of the PDR controller to maintain the efficiency when increasing the inlet concentration is shown experimentally as well as in simulation. Then, we propose three control schemes for dealing with this issue: a feed-forward, a feed-back/cascade and a model predictive controller. We show in simulation that all proposed schemes are able to improve and maintain the efficiency of hydrocyclones considering the upstream disturbances, such as variations in inlet oil concentrations and inflow rates. We also discuss the characteristics of the three methods and propose guidelines for choosing the appropriate scheme based on the available resources at the industrial site (such as measurements, hardware and software at hand).

Hammerstein–Wiener Model Identification for Oil-in-Water Separation Dynamics in a De-Oiling Hydrocyclone System

“…Discharge concentration: the discharge concentration denoted as C u is a natural choice of CV to comply with the discharge concentration limits, as studied in [6,8,18,19].…”

“…The authors approximated the separation efficiency for a fixed underflow valve opening degree as a second-order polynomial function of the overflow flow rate and derived mass balances to describe the separation dynamics. A PI controller was developed using the Skogestad internal model control (SIMC) tuning rules, and later, a sliding mode, feedback linearization, feedforward, cascade, and model predictive controller (MPC) were designed to track a constant discharge concentration reference in simulation [6,18,19]. These models have proven to be capable of representing the steady-state efficiency behavior of hydrocyclones, but the dynamic features have not been validated or have been insufficient to describe the data [4,6].…”

Modeling and Control of Offshore Produced Water Treatment Systems Using Online Oil-in-Water Monitors

“…• While the PDR control loop can control the flow split and respond to changes in Q i , it is unable to compensate for changes in inlet oil concentration C i or the droplet size distribution [44,45].…”

“…However, the separation efficiency ε oil changes dynamically, as the PWT system is subjected to disturbances and PDR and ε oil are uncorrelated in some operating conditions. As PDR can only detect changes in flow rate, a PDR-based control system can only respond to and mitigate flow rate disturbances but cannot handle changes in inlet concentration or droplet size distribution [44,45].…”