Model based Control and Analysis of Gas lifted Oil Field for Optimal Operation
Keywords:gas lifted oil wells, model predictive control, global sensitivity analysis, dynamic modeling and simulation, parametric uncertainty
AbstractThis paper describes mathematical modeling, optimization, and analysis of a gas lift oil ﬁeld with ﬁve wells. A global sensitivity analysis using the variance-based method is performed to classify the parameters, which are highly sensitive and uncertain simultaneously. An improved model is further used to design a model-based predictive controller to optimally distribute a limited supply of lift gas among the oil wells. Several simulation cases showed an increase in the total oil production, and all the constraints were fully satisﬁed when the deterministic NMPC was applied to the nominal model. The effect of parametric uncertainty is studied by applying the deterministic NMPC to the plant model containing the uncertain parameters. It has been shown that under the presence of uncertainty, robust constraint satisfaction is not guaranteed with some constraints not being satisﬁed, leading to unachievable and unrealistic lift gas distribution.
Andrea Capolei, Bjarne Foss, and John B. Jørgensen. Proﬁt and risk measures in oil production optimization. IFAC-PapersOnLine, 48(6):214–220, 2015. doi:10.1016/j.ifacol.2015.08.034.
Kristian G. Hanssen and Bjarne Foss. Production optimization under uncertainty - applied to petroleum production. IFAC-PapersOnLine, 48(8):217–222, 2015. doi:10.1016/j.ifacol.2015.08.184.
Kristian G. Hanssen, Andrés Codas, and Bjarne Foss. Closed-loop predictions in reservoir management under uncertainty. SPE Journal, 22(5):1585–1595, 2017. doi:10.2118/185956-PA.
Toshimitsu Homma and Andrea Saltelli. Importance measures in global sensitivity analysis of nonlinear models. Reliability Engineering & System Safety, 52(1):1–17, 1996. doi:10.1016/0951-8320(96)00002-6.
Dinesh Krishnamoorthy, Bjarne Foss, and Sigurd Skogestad. Real-time optimization under uncertainty applied to a gas lifted well network. Processes, 52(4), 2016. doi:10.3390/pr4040052.
Dinesh Krishnamoorthy, Sigurd Skogestad, and Johannes Jäschke. Multistage model predictive control with online scenario tree update using recursive bayesian weighting. 18th European Control Conference (ECC), pages 1443–1448, 2019. doi:10.23919/ECC.2019.8795839.
Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, and Stefano Tarantola. Global Sensitivity Analysis: The Primer. John Wiley & Sons, 2008. ISBN 978-0-470-72517-7.
Roshan Sharma, Kjetil Fjalestad, and Bjørn Glemmestad. Modeling and control of gas lifted oil ﬁeld with ﬁve oil wells. the 52nd International Conference of Scandinavian Simulation Society, pages 47–59, 2011.
Roshan Sharma, Kjetil Fjalestad, and Bjørn Glemmestad. Optimization of lift gas allocation in a gas lifted oil ﬁeld as non-linear optimization problem. Modeling, Identiﬁcation and Control, 33(1):13–25, 2012.
Ilya M. Sobol. Sensitivity analysis for non-linear mathematical models. Mathematical modelling and computational experiment, 1:407–414, 1993.
Copyright (c) 2022 Nima Janatian, Kushila Jayamanne, Roshan Sharma
This work is licensed under a Creative Commons Attribution 4.0 International License.