Uncovering flow dynamic behaviors underlying oil–gas–water three phase flow using multivariate synchrosqueezing transform

Abstract

Oil-gas-water three-phase flow is distinguished by its intricate flow pattern. The analysis of experimental observations to reveal the oil-gas-water three phase flow’s dynamic behavior remains a challenging task. In this paper, firstly, a simulation investigation to compare the multivariate pseudo-winger distribution (MPWD) and multivariate synchrosqueezing transform (MSST) is presented. The cross term may be suppressed while maintaining high time-frequency concentration, according to our research on multivariate synchrosqueezing transform. The time-frequency analysis of various vertical oil–gas–water three phase flow patterns is then conducted utilizing MSST. The results from this study reveal that in various frequency bands, slug flow, bubble flow, and churn flow exhibit considerable temporal frequency variances. The MSST can effectively uncover the intrinsic connection between signal fluctuations and flow structure, and promote the understanding of various patterns of flow.