LAPSE:2023.36111
Published Article
LAPSE:2023.36111
Embedded MPC Strategies for ESP-Lifted Oil Wells: Hardware-in-the-Loop Performance Analysis of Nonlinear and Robust Techniques
June 13, 2023
This paper proposes embedded model predictive control strategies for oil-production processes equipped with electric submersible pump (ESP) installations. The novelty of this paper is the robustness and computational performance analysis of the Robust Infinite-Horizon Model Predictive Controller (RIHMPC) and Nonlinear Model Predictive Controller (NMPC) strategies, which have not yet been documented by the oil and gas exploration and production literature. The proposed method to embed the control laws is flexible with different hardware and is based on automatic code generation, which facilitates the project workflow. Hardware-in-the-loop simulation cases were used to compare the performance of both control strategies embedded in the Teensy 4.1 microcontroller, using key indices for real applications. The results showed that the RIHMPC strategy is a very promising alternative for real-time operation in ESP-lifted oil wells, with overall performance similar to the NMPC controller, even in noisy and plant−model mismatch scenarios, and using only linear models in its formulation.
Keywords
artificial lift, electrical submersible pump, embedded control, Nonlinear Model Predictive Control, robust model predictive control, zone control
Suggested Citation
Santana BA, Matos VS, Santana DD, Martins MAF. Embedded MPC Strategies for ESP-Lifted Oil Wells: Hardware-in-the-Loop Performance Analysis of Nonlinear and Robust Techniques. (2023). LAPSE:2023.36111
Author Affiliations
Santana BA: Mechatronics Program, Polytechnic School, Federal University of Bahia, Salvador 40170-110, Brazil; Department of Engineering and Computing, State University of Santa Cruz, Ilhéus 45662-900, Brazil [ORCID]
Matos VS: Mechatronics Program, Polytechnic School, Federal University of Bahia, Salvador 40170-110, Brazil [ORCID]
Santana DD: Department of Chemical Engineering, Polytechnic School, Federal University of Bahia, Salvador 40170-110, Brazil [ORCID]
Martins MAF: Mechatronics Program, Polytechnic School, Federal University of Bahia, Salvador 40170-110, Brazil; Department of Chemical Engineering, Polytechnic School, Federal University of Bahia, Salvador 40170-110, Brazil [ORCID]
Journal Name
Processes
Volume
11
Issue
5
First Page
1354
Year
2023
Publication Date
2023-04-28
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11051354, Publication Type: Journal Article
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Published Article

LAPSE:2023.36111
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doi:10.3390/pr11051354
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Jun 13, 2023
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CC BY 4.0
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[v1] (Original Submission)
Jun 13, 2023
 
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Jun 13, 2023
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https://psecommunity.org/LAPSE:2023.36111
 
Original Submitter
Calvin Tsay
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