Abstract
In this article we apply an approach to identify the oil–gas–water three-phase flow patterns in vertical upwards 20 mm inner-diameter pipe based on the conductance fluctuating signals. We use the approach to analyse the signals with long-range correlations by decomposing the signal increment series into magnitude and sign series and extracting their scaling properties. We find that the magnitude series relates to nonlinear properties of the original time series, whereas the sign series relates to the linear properties. The research shows that the oil–gas–water three-phase flows (slug flow, churn flow, bubble flow) can be classified by a combination of scaling exponents of magnitude and sign series. This study provides a new way of characterising linear and nonlinear properties embedded in oil–gas–water three-phase flows.
Acknowledgments
This study was supported by National Natural Science Foundation of China (Grant Nos. 51527805, 41174109) and Key Laboratory of Green Chemical Process (Wuhan Institute of Technology), Ministry of Education of China (Grant No. GCP201407).
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