Model based Control and Analysis of Gas lifted Oil Field for Optimal Operation
DOI:
https://doi.org/10.3384/ecp21185241Keywords:
gas lifted oil wells, model predictive control, global sensitivity analysis, dynamic modeling and simulation, parametric uncertaintyAbstract
This 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.References
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Copyright (c) 2022 Nima Janatian, Kushila Jayamanne, Roshan Sharma
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