Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6266
Title: Analysis of gas-liquid behavior in eccentric horizontal annuli with image processing and artificial intelligence techniques
Authors: Özbayoğlu, Ahmet Murat
Yüksel, H. Ertan
Keywords: two phase flow
multiphase flow
annulus flow
image processing
artificial intelligence
artificial neural networks
Issue Date: 2012
Publisher: Elsevier
Abstract: In drilling operations estimation of gas-liquid behavior such as flow patterns and liquid holdup is beneficial in terms of cost, time and efficient usage of resources for the well to be opened. There is a lack of research for hydraulic behavior of two phase fluids in annular geometries. One of the aims of this study is to observe the flow patterns experimentally in two phase eccentric annulus. The second aim is to detect the liquid holdup of these flows using digital image processing techniques instead of emprical correlations or mechanistic models. The last aim is to estimate the flow pattern and liquid holdup for two phase (air and water) flow in horizontal eccentric annulus. This is conducted by using artificial intelligence techniques rather than conventional mechanistic models. In this study, nearest neighbor algorithm, backpropagation neural networks, and decision trees are used as the artificial intelligence techniques. Flow is generalized by representing the flow patternsas superficial Reynolds numbers for both liquid and gas phase. The results showed that the back propagation neural network model provided the best results as an estimation model for flow pattern identification whereas regression decision tree had the best performance for liquid holdup determination. In air and water flow, 7 observed flow patterns are classified correctly with an accuracy of 90.38% and liquid holdup is estimated with an average absolute percent error of 17.06%. (C) 2011 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.petrol.2011.12.008
https://hdl.handle.net/20.500.11851/6266
ISSN: 0920-4105
1873-4715
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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