An artificial neural network visible mathematical model for predicting slug liquid holdup in low to high viscosity multiphase flow for horizontal to vertical pipes

Abstract Slug liquid holdup (SLH) is a critical requirement for accurate pressure drop prediction during multiphase pipe flows and by extension optimal gas lift design and production optimization in wellbores. Existing empirical correlations provide inaccurate predictions because they were developed...

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主要な著者:	Chibuzo Cosmas Nwanwe, Ugochukwu Ilozurike Duru, Charley Iyke C. Anyadiegwu, Azunna I. B. Ekejuba, Stanley I. Onwukwe, Angela N. Nwachukwu, Boniface U. Okonkwo
フォーマット:	Artigo
言語:	Inglês
出版事項:	SpringerOpen 2024-10-01
シリーズ:	Journal of Engineering and Applied Science
主題:	Artificial neural network Slug liquid holdup Visible mathematical model Black-box model Linear activation function Hyperbolic tangent activation function
オンライン･アクセス:	https://doi.org/10.1186/s44147-024-00530-7
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