Title

Forecasting The Evolution of Chaotic Dynamics of Two-Phase Slug flow Regime

Published In

Journal of Petroleum Science and Engineering

Document Type

Article

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.

DOI

10.1016/j.petrol.2021.108904

Persistent Identifier

https://archives.pdx.edu/ds/psu/36339

Share

COinS