From variety of industry-oriented imaging solutions the electrical capacitance tomography applied to the two-phase gas-liquid mixtures visualization and the phase distribution calculation is getting popular especially when flow key parameters are required. Industry demands particularly include efficient non-invasive automatic phase fraction calculation and flow structure identification in the vertical and horizontal pipelines. This can be solved by using non-deterministic fuzzy-logic based techniques for analysis of volumetric images. This paper presents a preliminary study on automated two-phase gas-liquid flow pattern identification based on a fuzzy evaluation of series of reconstructed 3D ECT volumetric images. The set of volume data is obtained by using nonlinear electrical capacitance tomography reconstruction algorithms. Finally a set of fuzzy-based features is calculated for flow substructure classification. As a result of this analysis obtained features will be used to classify given volumetric image into one of known flow regime structures. (C) 2013 Elsevier Ltd. All rights reserved.