Modelling and model predictive control of oil wells with Electric Submersible Pumps

Pavlov, Alexey; Krishnamoorthy, Dinesh; Fjalestad, Kjetil; Aske, Elvira Marie B.; Fredriksen, Morten

doi:10.1109/cca.2014.6981403

Cited by 40 publications

(43 citation statements)

References 3 publications

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“…A similar model is also developed in [14], which is used for optimization in [11]. The simulator implemented in MATLAB is based on the model found in [13], and the model is repeated here for convenience. All model variables and parameters are given in SI units, and all well parameters, such as reservoir pressure p r and well productivity index PI, are considered known constants.…”

Section: B Third Order Modelmentioning

confidence: 99%

“…A simple, third order model of an ESP lifted well is developed by Statoil in [12], [13]. A similar model is also developed in [14], which is used for optimization in [11].…”

Section: B Third Order Modelmentioning

confidence: 99%

“…Whereas dynamic control is the focus in [13], the focus in the present paper is on the controller implementation aspects. Feasibility of embedded MPC is investigated for a production well incorporating an Electric Submersible Pump (ESP) for artificial lift.…”

Section: Introductionmentioning

confidence: 99%

“…Feasibility of embedded MPC is investigated for a production well incorporating an Electric Submersible Pump (ESP) for artificial lift. The considered system is described in Section II, together with a mathematical model of the system developed by Statoil in [12], [13], which is implemented as a simulator in MATLAB.…”

Section: Introductionmentioning

confidence: 99%

“…Also, perfect system knowledge is assumed. In [12], [13], a model of an ESP-lifted well is developed, the control challenges related to ESPs are discussed, and automatic control of an ESP installation is implemented and tested in a large-scale industrial test facility. The results motivate the use of MPC to provide optimal dynamic control.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller

Binder

Kufoalor

Pavlov

et al. 2014

2014 IEEE Conference on Control Applications (CCA)

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Abstract-Electric Submersible Pumps (ESP) can be installed in oil wells to create artificial lift, in order to increase recovery from the reservoir, and boost the production rate. A Model Predictive Controller (MPC) for an ESP, based on linearized models, is developed and designed using SEPTIC (Statoil's in-house software tool for MPC), and implemented on a Programmable Logic Controller (PLC). Automatic code generators have been utilized to generate an applicationspecific MPC controller in ANSI C code. Hardware-in-the-loop simulation results show that the control performance of the PLC implementation is comparable to the original SEPTIC controller.

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Section: B Third Order Modelmentioning

confidence: 99%

“…A simple, third order model of an ESP lifted well is developed by Statoil in [12], [13]. A similar model is also developed in [14], which is used for optimization in [11].…”

Section: B Third Order Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller

Binder

Kufoalor

Pavlov

et al. 2014

2014 IEEE Conference on Control Applications (CCA)

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Addressing the lack of measurements in the subsea environment by using a model scheduling Kalman filter coupled with a robust adaptive MPC

Delou

Souza

Secchi

2020

Braz. J. Chem. Eng.

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Electric submersible pumps (ESPs) are one of the most widespread oil artificial lifting technologies. In the operation of an ESP there are a large number of parameters that must be monitored and held within operational constraints in order to guarantee stable and optimal operation. Manual control is subject to sub-optimal production and constant violation of operational limits, that can cause either a reduction in ESP lifetime or premature failure. Therefore, a proper automation strategy must be applied to support operators in order to ensure the best production rate with less energy cost. Previous literature has proposed the use of linear MPC based on system identification, however all relevant system variable measurements were considered available. In this paper, the problem of losing measurements of the state variables due to the aggressive subsea environment is addressed. We show that a non-adaptive single linear model strategy lacks in quality for state estimation and, therefore, a robust MPC is not possible under this configuration. In this work, an adaptive constrained MPC coupled with a model scheduling Kalman filter (MSKF) is proposed. Two model scheduling strategies based on linear interpolation of a pre-set number of local models are proposed and compared to successive linearization at every sampling time, based on Taylor series expansion of the nonlinear model. All strategies guarantee model accuracy and model stability over the whole operational range. The proposed scheduling strategies presented similar performance compared to the successive linearization strategy, avoiding the need of obtaining a local linear model at each sampling time.

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An implementable zone-based NMPC with Echo State Networks applied to an ESP-lifted oil well for maximum oil production

de Abreu,

Ribeiro,

Foresti

et al. 2024

Computer Aided Chemical Engineering

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Modelling and model predictive control of oil wells with Electric Submersible Pumps

Cited by 40 publications

References 3 publications

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller

Addressing the lack of measurements in the subsea environment by using a model scheduling Kalman filter coupled with a robust adaptive MPC

An implementable zone-based NMPC with Echo State Networks applied to an ESP-lifted oil well for maximum oil production

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