LAPSE:2023.30823
Published Article
LAPSE:2023.30823
Optimisation of a Gas-Lifted System with Nonlinear Model Predictive Control
April 17, 2023
Abstract
A gas-lifted system in a mature oil well can experience casing-heading instability, which reduces the mean oil production and it is not healthy for the downstream equipment. This instability was removed by implementing a terminal equality-constrained nonlinear model predictive control (NMPC) having input targets with control zones in the system. The input-dependent stability behaviour of the gas-lifted system was visualised through the bifurcation diagram and the step responses of the linearised model at various operating points. The controller was then presented. Then, the close-loop feasibility, as well as the convergence, were discussed. The controller stabilised the undisturbed gas-lifted system, improving production by 5.63% compared to the open-loop operation when the system was in casing-heading instability. For the two input case, the steady-state production, aided by the high-input target, reached 12.25 kg/s, which was far more than 9.57 kg/s for the one input case. This controller showed a 3.76% improvement over the PI controller for the same purpose.
Keywords
casing-heading instability, extended Kalman filter, gas lift, Model Predictive Control, optimisation
Suggested Citation
Adukwu O, Odloak D, Kassab F Jr. Optimisation of a Gas-Lifted System with Nonlinear Model Predictive Control. (2023). LAPSE:2023.30823
Author Affiliations
Adukwu O: Department of Telecommunications and Control, University of Sao Paulo, Sao Paulo 05508-010, Brazil; Department of Industrial and Production Engineering, Federal University of Technology Akure, Akure 340110, Nigeria [ORCID]
Odloak D: Department of Chemical Engineering, University of Sao Paulo, Sao Paulo 05508-010, Brazil [ORCID]
Kassab F Jr: Department of Telecommunications and Control, University of Sao Paulo, Sao Paulo 05508-010, Brazil [ORCID]
Journal Name
Energies
Volume
16
Issue
7
First Page
3082
Year
2023
Publication Date
2023-03-28
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16073082, Publication Type: Journal Article
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LAPSE:2023.30823
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https://doi.org/10.3390/en16073082
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