Vahabi, N;
Willman, E;
Baghsiahi, H;
Selviah, D;
(2020)
Fluid Flow Velocity Measurement in Active Wells Using Using Fiber Optic Distributed Acoustic Sensors.
IEEE Sensors Journal
10.1109/JSEN.2020.2996823.
(In press).
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Abstract
Real time monitoring of the behaviour of fluids along the whole length of fluid filled well pipes is important to the oil and gas industry as it enables well operators to maximize oil and gas production and optimize the quality of oil and gas produced, whilst reducing the cost. Flow speed measurement is one of the key approaches in fluid flow monitoring in wells. In this paper, three methods are designed, developed and demonstrated to estimate the speed and direction of flow at a range of depths in real world oil, gas and water wells using acoustic data set from distributed acoustic sensors that attached to the wells. The developed methods are based on a new combination of several techniques from signal processing, machine learning and physics. The Terabyte size acoustic dataset are recorded from each well as a two-dimensional function of both distance along the pipeline and time. The aim of the developed methods is estimating flow speed at each point along over 3000 meters pipelines and increasing the accurately and efficiently of the flow speed calculation compared to the existing method. The methods developed in this paper are computationally inexpensive, which make them suitable for real time well monitoring.
| Type: | Article |
|---|---|
| Title: | Fluid Flow Velocity Measurement in Active Wells Using Using Fiber Optic Distributed Acoustic Sensors |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/JSEN.2020.2996823 |
| Publisher version: | https://doi.org/10.1109/JSEN.2020.2996823 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Fluid characterization, fluid flow measurement, flow velocity, Hough transform, K-means clustering, optical sensors |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10098107 |
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