Experimental study of interaction between liquid droplets in oil-in-water emulsions using multivariate time series analysis

Oil-in-water emulsions is frequently encountered in the industry of oil exploitation. The complex dynamic behavior of oil droplets brings about a great challenge in understanding its underlying flow regime. In the present study, we attempt to characterize flow instability of oil-in-water emulsions through measuring the information transfer between oil droplets. An experiment of vertical upward oil-in-water emulsions is conducted in a flow loop facility with 20 mm pipe inner diameter (ID), and multivariate time series are acquired by sampling the signals of a distributed sixteen-channel conductance mono-sensor probe array. The collected multivariate time series are firstly processed with an algorithm designated as transfer entropy (TE), through which the interaction between oil droplets at pipe cross section are investigated. Moreover, with the aid of multivariate weighted multiscale permutation entropy (MWMPE) algorithm, we also explore the global flow instability of oil droplets. Research results indicate that with the increasing distance from pipe center, the interaction between oil droplets gradually weakens. Besides, the increase in mixture velocity or the decrease in water-cut will intensify the interaction between oil droplets and global flow instability. Multivariate time series analysis can be considered as an effective method for characterizing flow instability in oil-in-water emulsions.