Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm
Velocity is an important parameter for fluid flow characteristics in profile logging. Particle tracking velocimetry (PTV) technology is often used to study the flow characteristics of oil wells with low flow velocity and high water cut, and the key to PTV technology is particle matching. The existin...
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doaj-923d6c50b3534dd8a9e0a3bdd5e8de122021-09-06T19:22:37ZengSciendoMeasurement Science Review1335-88712020-04-012029310310.2478/msr-2020-0012msr-2020-0012Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC AlgorithmHan Lianfu0Wang Haixia1Cong Yao2Liu Xingbin3Han Jian4Fu Changfeng5College of Electronics Science, Northeast Petroleum University, Fazhan road No.199, 163316, Daqing, China InstituteCollege of Electronics Science, Northeast Petroleum University, Fazhan road No.199, 163316, Daqing, China InstituteCollege of Electronics Science, Northeast Petroleum University, Fazhan road No.199, 163316, Daqing, China InstituteWorking Stations for Post Doctor, Daqing Oilfield Limited Corporation, XiBin Road, No.110, 163310, Daqing, ChinaCollege of Electronics Science, Northeast Petroleum University, Fazhan road No.199, 163316, Daqing, China InstituteCollege of Electronics Science, Northeast Petroleum University, Fazhan road No.199, 163316, Daqing, China InstituteVelocity is an important parameter for fluid flow characteristics in profile logging. Particle tracking velocimetry (PTV) technology is often used to study the flow characteristics of oil wells with low flow velocity and high water cut, and the key to PTV technology is particle matching. The existing particle matching algorithms of PTV technology do not meet the matching demands of oil drops in the oil phase velocity measurement of oil-water two-phase flow with low velocity and high water cut. To raise the particle matching precision, we improved the particle matching algorithm from the oriented FAST and the rotated BRIEF (ORB) feature description and the random sample consensus (RANSAC) algorithm. The simulation and experiment were carried out. Simulation results show that the improved algorithm not only increases the number of matching points but also reduces the computation. The experiment shows that the improved algorithm in this paper not only reduces the computation of the feature description process, reaching half of the computation amount of the original algorithm, but also increases the number of matching results, thus improving the measurement accuracy of oil phase velocity. Compared with the SIFT algorithm and the ORB algorithm, the improved algorithm has the largest number of matching point pairs. And the variation coefficient of this algorithm is 0.039, which indicates that the algorithm is stable. The mean error of oil phase velocity measurement of the improved algorithm is 1.20 %, and the maximum error is 6.16 %, which is much lower than the maximum error of PTV, which is 25.89 %. The improved algorithm overcomes the high computation cost of the SIFT algorithm and achieves the precision of the SIFT algorithm. Therefore, this study contributes to the improvement of the measurement accuracy of oil phase velocity and provides reliable production logging data for oilfield.https://doi.org/10.2478/msr-2020-0012orbransacoil-water two-phase flowptv |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Han Lianfu Wang Haixia Cong Yao Liu Xingbin Han Jian Fu Changfeng |
spellingShingle |
Han Lianfu Wang Haixia Cong Yao Liu Xingbin Han Jian Fu Changfeng Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm Measurement Science Review orb ransac oil-water two-phase flow ptv |
author_facet |
Han Lianfu Wang Haixia Cong Yao Liu Xingbin Han Jian Fu Changfeng |
author_sort |
Han Lianfu |
title |
Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm |
title_short |
Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm |
title_full |
Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm |
title_fullStr |
Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm |
title_full_unstemmed |
Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm |
title_sort |
oil phase velocity measurement of oil-water two-phase flow with low velocity and high water cut using the improved orb and ransac algorithm |
publisher |
Sciendo |
series |
Measurement Science Review |
issn |
1335-8871 |
publishDate |
2020-04-01 |
description |
Velocity is an important parameter for fluid flow characteristics in profile logging. Particle tracking velocimetry (PTV) technology is often used to study the flow characteristics of oil wells with low flow velocity and high water cut, and the key to PTV technology is particle matching. The existing particle matching algorithms of PTV technology do not meet the matching demands of oil drops in the oil phase velocity measurement of oil-water two-phase flow with low velocity and high water cut. To raise the particle matching precision, we improved the particle matching algorithm from the oriented FAST and the rotated BRIEF (ORB) feature description and the random sample consensus (RANSAC) algorithm. The simulation and experiment were carried out. Simulation results show that the improved algorithm not only increases the number of matching points but also reduces the computation. The experiment shows that the improved algorithm in this paper not only reduces the computation of the feature description process, reaching half of the computation amount of the original algorithm, but also increases the number of matching results, thus improving the measurement accuracy of oil phase velocity. Compared with the SIFT algorithm and the ORB algorithm, the improved algorithm has the largest number of matching point pairs. And the variation coefficient of this algorithm is 0.039, which indicates that the algorithm is stable. The mean error of oil phase velocity measurement of the improved algorithm is 1.20 %, and the maximum error is 6.16 %, which is much lower than the maximum error of PTV, which is 25.89 %. The improved algorithm overcomes the high computation cost of the SIFT algorithm and achieves the precision of the SIFT algorithm. Therefore, this study contributes to the improvement of the measurement accuracy of oil phase velocity and provides reliable production logging data for oilfield. |
topic |
orb ransac oil-water two-phase flow ptv |
url |
https://doi.org/10.2478/msr-2020-0012 |
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