Development of a Neural Network for the Identification of Multiphase Flow Patterns

Inoue, Eduardo H.; Carvalho, R.D.M.; Estevam, Valdir; Bannwart, Antonio Carlos; Fileti, Ana Maria Frattini

doi:10.2316/p.2013.807-013

Cited by 4 publications

(6 citation statements)

References 16 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Authors such as Kouba [52], Thomas [53], Omebere-Iyari and Azzopardi [54], and Rosa et al [55] have proposed minor changes of the flow patterns aforementioned. Therefore, a grouping criteria similar to the reported by Inoue et al [49] is considered.…”

Section: Vertical Flow Patternsmentioning

confidence: 99%

“…Based on these considerations, the different flow patterns found in the literature can be grouped as (Tab. 2): Bubbly Flow, Intermittent Flow, and Annular Flow [49], graphically shown in Figures 1d-1f.…”

Section: Vertical Flow Patternsmentioning

confidence: 99%

“…For the wavy case, increasing the gas velocity destabilizes the interface and creates waves in the liquid surface [47,48]. This distinction, however, is not significant for the current work [49]. The flow patterns found in the literature can be grouped then as follows (Tab.…”

Section: Introductionmentioning

confidence: 96%

“…The flow patterns found in the literature can be grouped then as follows (Tab. 1): Segregated Flow, Intermittent Flow, and Bubbly Flow [49].…”

Section: Introductionmentioning

confidence: 99%

“…Flow pattern classification for horizontal pipes used in this work. Adapted from Inoue et al (2013)[49]Annular flow can be classified as segregated flow.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Probabilistic approach of a flow pattern map for horizontal, vertical, and inclined pipes

Amaya-Gómez

López

Pineda

et al. 2019

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

View full text Add to dashboard Cite

A way to predict two-phase liquid-gas flow patterns is presented for horizontal, vertical and inclined pipes. A set of experimental data (7702 points, distributed among 22 authors) and a set of synthetic data generated using OLGA Multiphase Toolkit v.7.3.3 (59 674 points) were gathered. A filtering process based on the experimental void fraction was proposed. Moreover, a classification of the pattern flows based on a supervised classification and a probabilistic flow pattern map is proposed based on a Bayesian approach using four pattern flows: Segregated Flow, Annular Flow, Intermittent Flow, and Bubble Flow. A new visualization technique for flow pattern maps is proposed to understand the transition zones among flow patterns and provide further information than the flow pattern map boundaries reported in the literature. Following the methodology proposed in this approach, probabilistic flow pattern maps are obtained for oil–water pipes. These maps were determined using an experimental dataset of 11 071 records distributed among 53 authors and a numerical filter with the water cut reported by OLGA Multiphase Toolkit v7.3.3.

show abstract

Section: Vertical Flow Patternsmentioning

confidence: 99%

Section: Vertical Flow Patternsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

“…The flow patterns found in the literature can be grouped then as follows (Tab. 1): Segregated Flow, Intermittent Flow, and Bubbly Flow [49].…”

Section: Introductionmentioning

confidence: 99%

“…Flow pattern classification for horizontal pipes used in this work. Adapted from Inoue et al (2013)[49]Annular flow can be classified as segregated flow.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Probabilistic approach of a flow pattern map for horizontal, vertical, and inclined pipes

Amaya-Gómez

López

Pineda

et al. 2019

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

View full text Add to dashboard Cite

show abstract

Dimensionality Reduction and Pattern Recognition of Flow Regime Using Acoustic Data

Vahabi

Selviah

2018

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

In this study we investigated the novel application of Principle Component Analysis (PCA) in order to reduce the dimensionality of acoustic data. The acoustic data are recorded by fibre optic distributed acoustic sensors which are attached along 4000 (m) pipe with frequency of 10 (kHz) and for a period of 24 hours. Data are collected from distributed acoustic sensors are very large and we need to identify the area that contains the most informative signals. The algorithm is applied to water, oil and gas dataset. We aimed to form the smaller dataset which preserves the pattern of original dataset but it is more efficient and less expensive for further analysis. The result of this study will lead to automation of multiphase flow pattern recognition for oil and gas industry application.

show abstract

The use of an ultrasonic technique and neural networks for identification of the flow pattern and measurement of the gas volume fraction in multiphase flows

Figueiredo

Gonçalves

Nakashima

et al. 2016

Experimental Thermal and Fluid Science

View full text Add to dashboard Cite

Development of a Neural Network for the Identification of Multiphase Flow Patterns

Cited by 4 publications

References 16 publications

Probabilistic approach of a flow pattern map for horizontal, vertical, and inclined pipes

Probabilistic approach of a flow pattern map for horizontal, vertical, and inclined pipes

Dimensionality Reduction and Pattern Recognition of Flow Regime Using Acoustic Data

The use of an ultrasonic technique and neural networks for identification of the flow pattern and measurement of the gas volume fraction in multiphase flows

Contact Info

Product

Resources

About