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  • 标题:Evaluation of Lyapunov-based Adaptive Observer using Low-Order Lumped Model for Estimation of Production Index in Under-balanced Drilling
  • 本地全文:下载
  • 作者:Amirhossein Nikoofard ; Tor Arne Johansen ; Glenn-Ole Kaasa
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:8
  • 页码:69-75
  • DOI:10.1016/j.ifacol.2015.08.159
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractA distributed drift-flux model and a low-order lumped model describing a multiphase (gas-liquid) flow in the well during Under-Balanced Drilling (UBD) has been presented. This paper presents a novel nonlinear adaptive observer to estimate the total mass of gas and liquid in the annulus and production constant of gas and liquid from the reservoir into the well during UBD operations. Furthermore, it describes a joint unscented Kalman filter to estimate parameters and states for both the distributed drift-flux and lumped model by using real-time measurements of the choke and the bottom-hole pressures. The performance of the adaptive observers are evaluated for typical drilling scenarios. The results show that all adaptive observers are capable of identifying the production index, although the adaptive observers based on the low-order lumped model achieves better convergence rate than adaptive observer based on the drift-flux model. The results show that the LOL model is sufficient for the purpose of estimating the production parameters.
  • 关键词:KeywordsLow-order lumped modelEstimationSimplified drift-flux modelLyapunov stability and Unscented Kalman Filter
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