Bubble mapping: three-dimensional visualisation of gas–liquid flow regimes using electrical tomography

Abstract

It is well known that electrical tomography is capable of 'seeing' through opaque pipe walls and flow media. However, due to the relatively low spatial resolution, electrical tomograms are ineffective on visualisation of small bubbles or sharp interfaces between large bubbles and the liquid. These limitations give rise to ambiguity in human and/or machine perception of flow dynamics from presenting bubble cluster and blurry boundaries of large bubbles in faint colour or grey. In this paper, a binary approach, called bubble mapping, is proposed to enhance the visibility of flow regime in gas-liquid pipeline flows. With the input gas concentration tomograms reconstructed by an electrical tomography, the method takes the major visual characteristics of typical flow regimes in common recognition as a prior knowledge and replaces the conventional colour mapping with a number of bubbles and their mergence with a thresholding value. With this approach, a stack of cross-sectional tomograms by electrical tomography is transformed and displayed as a collection of individual gas bubbles. The transformation is done with the help of a lookup table indexed by bubble size and an enhanced isosurface algorithm for vivid three-dimensional visualisation. This new approach has been applied to a gas-in-water flow rig and its performance is compared with photo images taken by a high-speed camera. Reasonable agreements have been obtained for common flow regimes including bubbly flow, stratified flow, plug flow, slug flow and annular flow in horizontal pipe and bubbly flow, slug flow and annular flow in vertical pipe. Results evidence the method can provide a photorealistic flow visualisation and therefore enhance the visibility of electrical tomograms for visual identification of flow regime, particularly for opaque media in industrial flows.

Perspectives of Flow Assurance Problems in Oil and Gas Production: A Mini-review

“…Terrain or riser slugging, ramp-up slugs, and sphering slugs are the most common flow assurance concerns caused by multiphase flow. 151,152 Moreover, in order to mitigate the multiphase flow assurance problems, it is necessary to measure the multiphase flow accurately. Multiphase flow meters could serve the purpose while measuring the mass flow rate of each phase by applying the interfacial approach (velocity and cross-sectional fraction measurements).…”

“…Four standard multiphase flow regimes can generally be observed depending on the superficial gas/liquid velocities: (i) stratified flow, wherein an uninterrupted flow of liquid stream at the bottom and gas stream at the top can be observed as presented in Figure (with the increase in gas velocity, the regime can be moved toward a stratified wavy flow); (ii) slug flow, or plug flow, which can be observed while increasing the liquid velocity toward turbulent flow; (ii) annular flow, wherein a thin film of liquid phase adheres to the pipeline wall and a gas stream in the middle along with liquid droplets (refer to Figure ); and (iv) bubble flow, wherein the gas phase is bubbling through the liquid phase. Terrain or riser slugging, ramp-up slugs, and sphering slugs are the most common flow assurance concerns caused by multiphase flow. , …”

Imaging of a distinctive large bubble in gas–water flow based on a size projection algorithm

“…Because the real velocity field is scarcely available from tomography-based methods, statistics-based methods, e.g. the cross-correlation method, are employed to derive the axial velocity as an approximate gas velocity [27]. Given a dualplane ERT system, whose two parallel-installed electrode planes have a fixed interval, axial gas velocity can be derived with a direct pixel-to-pixel cross-correlation method by…”

Size Projection Algorithm: Optimal Thresholding Value Selection for Image Segmentation of Electrical Impedance Tomography

“…Accuracy. In order to compare the accuracy of SPA and other methods, such as the empirical value method [7,10] and histogram-based method [15][16][17], relative image error (IE), as expressed by equation (7), is employed to evaluate the accuracy of these image segmentations:…”

“…Here, in EIT technique [1,6], the measured boundary data are electrical voltage signals, and the tomographic image is represented by conductivity difference in grey-value levels. In this paper, we focus on the tomographic reconstruction of single-material/tissue object, such as bubble/ oil/solid in water [7] and lung in human thorax [3,6,8]. e tomographic reconstructions, usually continuous greylevel or colour palette-based images, need be segmented for extracting quantitative information of objects, such as the object size or shape.…”