Enhanced flow detection through a steel barrier using Doppler ultrasound: A numerical and experimental study

Uncontrolled leakages of hydrocarbons from oil and gas wells can have vast environmental consequences and lead to huge costs for the companies responsible. Thus, preventing and detecting potential leakages in wells is of great importance. In this work, Doppler ultrasound was used for the detection of flow behind steel to help assess the integrity of oil and gas wells. The main goal was to enhance flow detection with Doppler ultrasound through steel by improving the beamforming of the ultrasonic pulse. A naive beamforming approach assuming the medium to be homogeneous was compared to a ray tracing based beamforming algorithm, both in a numerical study and in an experimental setup. Simulations showed a 5 dB increase of the peak amplitude when taking refraction in the steel into account by applying the ray tracing based beamforming. In addition, the targeted focus was hit with a narrower, more precisely controlled beam on the far side of the steel layer. These two beamforming techniques were then employed and compared for flow detection behind steel in an experimental setup. Two cases were investigated, low velocity and high velocity, using three different transmit voltages for each velocity. Pulsed wave Doppler spectra were displayed, and the ratio between the flow signal power averaged over a range of frequencies was calculated. An increase of 3-4 dB was observed using the ray tracing technique, showing enhanced flow detection compared to the naive technique.

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Publication Details

Journal
Ultrasonics
Published
2025-12-27
DOI
https://doi.org/10.1016/j.ultras.2025.107922
Primary Topic
Flow Measurement and Analysis
Type
article
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article

Enhanced flow detection through a steel barrier using Doppler ultrasound: A numerical and experimental study

Svein‐Erik Måsøy, Jørgen Avdal, Andreas Sørbrøden Talberg, Cristiana Golfetto et al.
Ultrasonics
Flow Measurement and Analysis
article

Enhanced flow detection through a steel barrier using Doppler ultrasound: A numerical and experimental study

Svein‐Erik Måsøy, Jørgen Avdal, Andreas Sørbrøden Talberg, Cristiana Golfetto, Hefeng Dong, Ingvild Kinn Ekroll, Tonni Franke Johansen
article en

Abstract

Uncontrolled leakages of hydrocarbons from oil and gas wells can have vast environmental consequences and lead to huge costs for the companies responsible. Thus, preventing and detecting potential leakages in wells is of great importance. In this work, Doppler ultrasound was used for the detection of flow behind steel to help assess the integrity of oil and gas wells. The main goal was to enhance flow detection with Doppler ultrasound through steel by improving the beamforming of the ultrasonic pulse. A naive beamforming approach assuming the medium to be homogeneous was compared to a ray tracing based beamforming algorithm, both in a numerical study and in an experimental setup. Simulations showed a 5 dB increase of the peak amplitude when taking refraction in the steel into account by applying the ray tracing based beamforming. In addition, the targeted focus was hit with a narrower, more precisely controlled beam on the far side of the steel layer. These two beamforming techniques were then employed and compared for flow detection behind steel in an experimental setup. Two cases were investigated, low velocity and high velocity, using three different transmit voltages for each velocity. Pulsed wave Doppler spectra were displayed, and the ratio between the flow signal power averaged over a range of frequencies was calculated. An increase of 3-4 dB was observed using the ray tracing technique, showing enhanced flow detection compared to the naive technique.

UltrasonicsVol. 162
SINTEF (NO), Norwegian University of Science and Technology (NO)
Openalex Percentile: Top 42%
Flow Measurement and Analysis
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Enhanced flow detection through a steel barrier using Doppler ultrasound: A numerical and experimental study — Svein‐Erik Måsøy, Jørgen Avdal, et al. · Ultrasonics (2025) | TGRS Research Map | TGRS