Control Oriented Modeling of a De-oiling Hydrocyclone

Løhndorf, Petar Durdevic; Pedersen, Simon; Bram, Mads Valentin; Hansen, Dennis Severin; Hassan, Abdiladif Ahmed; Yang, Zhenyu

doi:10.1016/j.ifacol.2015.12.141

Cited by 21 publications

(10 citation statements)

References 5 publications

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“…The control aspects of hydrocyclones have been gaining more and more focus in recent years. A controloriented approach based on transfer functions models using experimental data from a test rig was developed by Durdevic et al (2015). Then, a grey box static model to calculate the separation efficiency of hydrocyclones based on flow resistance and droplet trajectory was developed by Bram et al (2018).…”

Section: Previous Workmentioning

confidence: 99%

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

Vallabhan¹,

Matias²,

Holden³

2021

MIC

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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).

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Section: Previous Workmentioning

confidence: 99%

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

Vallabhan¹,

Matias²,

Holden³

2021

MIC

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“…As V o has a small impact on the total output flow from the gravity separator, it is omitted. Under the assumption that the separator pressure, interface level and the pressure downstream of the valve are insignificant to affect the water level dynamic, the nonlinear model is linearised around an operating point of 0.15 m. Due to the complicated hydrodynamics of the hydrocyclone, a black-box model via system identification was proposed; refer to [38,39], where the model is designed from the PDR perspective, as this is the sole observable parameter in most of current the installations. The hydrocyclone model is described as a set of two identified models where the first model describes the input-output relationship from the overflow valve to the PDR and the second model describes the input-output relationship from the underflow valve to the PDR.…”

Section: Model Developmentmentioning

confidence: 99%

Application of H∞ Robust Control on a Scaled Offshore Oil and Gas De-Oiling Facility

Durdevic¹,

Yang²

2018

Energies

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Abstract:The offshore de-oiling process is a vital part of current oil recovery, as it separates the profitable oil from water and ensures that the discharged water contains as little of the polluting oil as possible. With the passage of time, there is an increase in the water fraction in reservoirs that adds to the strain put on these facilities, and thus larger quantities of oil are being discharged into the oceans, which has in many studies been linked to negative effects on marine life. In many cases, such installations are controlled using non-cooperative single objective controllers which are inefficient in handling fluctuating inflows or complicated operating conditions. This work introduces a model-based robust H ∞ control solution that handles the entire de-oiling system and improves the system's robustness towards fluctuating flow thereby improving the oil recovery and reducing the environmental impacts of the discharge. The robust H ∞ control solution was compared to a benchmark Proportional-Integral-Derivative (PID) control solution and evaluated through simulation and experiments performed on a pilot plant. This study found that the robust H ∞ control solution greatly improved the performance of the de-oiling process.

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“…In the field of industrial tomography, soft-field techniques such as electrical resistance [18,19], electrical capacitance [20,21], and electrical impedance tomography [22] have been applied in the study of the distribution of the phases and volumetric fractions of multiphase flows, and more sophisticated (hardfield) techniques such as MRI [23][24][25] and ultrasound [26,27] have been applied in the measurement of both the volumetric fraction and flow velocity. However, until recently, these techniques were still limited to slow processes or offline applications, and the realtime control of multiphase flows was limited to flow variables that are faster to measure, but are only indirectly connected to performance, such as pressure [28,29], density, or flow rate [30].…”

Section: Introductionmentioning

confidence: 99%

Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation

Garcia

Sattar

Atmani

et al. 2022

Sensors

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The performance of multiphase flow processes is often determined by the distribution of phases inside the equipment. However, controllers in the field are typically implemented based on flow variables, which are simpler to measure, but indirectly connected to performance (e.g., pressure). Tomography has been used in the study of the distribution of phases of multiphase flows for decades, but only recently, the temporal resolution of the technique was sufficient for real-time reconstructions of the flow. Due to the strong connection between the performance and distribution of phases, it is expected that the introduction of tomography to the real-time control of multiphase flows will lead to substantial improvements in the system performance in relation to the current controllers in the field. This paper uses a gas–liquid inline swirl separator to analyze the possibilities and limitations of tomography-based real-time control of multiphase flow processes. Experiments were performed in the separator using a wire-mesh sensor (WMS) and a high-speed camera to show that multiphase flows have two components in their dynamics: one intrinsic to its nonlinear physics, occurring independent of external process disturbances, and one due to process disturbances (e.g., changes in the flow rates of the installation). Moreover, it is shown that the intrinsic dynamics propagate from upstream to inside the separator and can be used in predictive and feedforward control strategies. In addition to the WMS experiments, a proportional–integral feedback controller based on electrical resistance tomography (ERT) was implemented in the separator, with successful results in relation to the control of the distribution of phases and impact on the performance of the process: the capture of gas was increased from 76% to 93% of the total gas with the tomography-based controller. The results obtained with the inline swirl separator are extended in the perspective of the tomography-based control of quasi-1D multiphase flows.

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Control Oriented Modeling of a De-oiling Hydrocyclone

Cited by 21 publications

References 5 publications

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

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

Application of H∞ Robust Control on a Scaled Offshore Oil and Gas De-Oiling Facility

Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation

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