Forecasting The Evolution of Chaotic Dynamics of Two-Phase Slug flow Regime
Published In
Journal of Petroleum Science and Engineering
Document Type
Citation
Publication Date
10-2021
Abstract
Presenting a predictive model through handling of the dynamical system is critical for modern technologies and industrial application. Here, Hankel-based dynamic mode decomposition is used to generate a predictive model for the slug flow regime. Flow dynamics are split into linear and nonlinear parts; the latter of which is responsible for intermittency phenomena. The proposed model shows the ability to predicts the time evolution of phase fraction. Forecasting of slug flow systems is achieved with no a priori knowledge of the equations of motion. The percentage of the variation between the actual states and predicted states is approximately 20%.
Rights
© 2021 Elsevier B.V. All rights reserved.
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DOI
10.1016/j.petrol.2021.108904
Persistent Identifier
https://archives.pdx.edu/ds/psu/36339
Citation Details
Naseem Ali, Bianca Viggiano, Murat Tutkun, Raúl Bayoán Cal, Forecasting the evolution of chaotic dynamics of two-phase slug flow regime, Journal of Petroleum Science and Engineering, Volume 205, 2021 https://doi.org/10.1016/j.petrol.2021.108904