Analysis of ultrasound Doppler flow pattern recognition method for drilling gas intrusion monitoring

High-pressure gas intrusion during drilling operations poses significant well control challenges, heightening blowout risks. To address this critical safety concern, this paper proposes a real-time monitoring framework by characterizing gas–liquid flow pattern transitions through ultrasonic Doppler detection and time–frequency analysis. The proposed methodology systematically integrates three innovative processes: (1) gas-phase channel enumeration for spatial quantification of gas distribution patterns, (2) Doppler frequency shift range analysis enabling dynamic flow characteristic resolution, and (3) flow pattern threshold calibration to establish robust classification criteria. The thresholds of various flow patterns are obtained by the number of gas-phase channels and Doppler frequency shift range to achieve the purpose of real-time monitoring of gas intrusion status. To validate the methodology, an experimental gas intrusion simulation system was developed, comprising a wellbore pipeline integrated with a drilling fluid circulation pool and an ultrasound Doppler detection array. This system replicates downhole flow pattern transitions by injecting controlled gas velocities (0.1–5 m/s) at multiple axial positions, enabling spatial–temporal analysis of gas–liquid phase redistribution under simulated drilling conditions. The results show that, our method effectively explain the dynamic evolution of two-phase flow under different flow regimes and achieved early detection of phase transitions. This method provide a non-invasive ultrasound-based pipeline, offering a high-responsiveness solution for gas kick monitoring in high-risk drilling.

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Publication Details

Journal
Scientific Reports
Published
2026-06-18
DOI
https://doi.org/10.1038/s41598-026-58432-y
Primary Topic
Drilling and Well Engineering
Type
article
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Analysis of ultrasound Doppler flow pattern recognition method for drilling gas intrusion monitoring

Guolang Shen, Minglei Men, Qing Liu, Lijun GENG et al.
Scientific Reports
Drilling and Well Engineering
article

Analysis of ultrasound Doppler flow pattern recognition method for drilling gas intrusion monitoring

Guolang Shen, Minglei Men, Qing Liu, Lijun GENG, Pengfei Li, Qingfeng Guo, Xiao Cai
article en

Abstract

High-pressure gas intrusion during drilling operations poses significant well control challenges, heightening blowout risks. To address this critical safety concern, this paper proposes a real-time monitoring framework by characterizing gas–liquid flow pattern transitions through ultrasonic Doppler detection and time–frequency analysis. The proposed methodology systematically integrates three innovative processes: (1) gas-phase channel enumeration for spatial quantification of gas distribution patterns, (2) Doppler frequency shift range analysis enabling dynamic flow characteristic resolution, and (3) flow pattern threshold calibration to establish robust classification criteria. The thresholds of various flow patterns are obtained by the number of gas-phase channels and Doppler frequency shift range to achieve the purpose of real-time monitoring of gas intrusion status. To validate the methodology, an experimental gas intrusion simulation system was developed, comprising a wellbore pipeline integrated with a drilling fluid circulation pool and an ultrasound Doppler detection array. This system replicates downhole flow pattern transitions by injecting controlled gas velocities (0.1–5 m/s) at multiple axial positions, enabling spatial–temporal analysis of gas–liquid phase redistribution under simulated drilling conditions. The results show that, our method effectively explain the dynamic evolution of two-phase flow under different flow regimes and achieved early detection of phase transitions. This method provide a non-invasive ultrasound-based pipeline, offering a high-responsiveness solution for gas kick monitoring in high-risk drilling.

Scientific Reports
Jingdezhen Ceramic Institute (CN), Tianjin Conservatory of Music (CN), China National Petroleum Corporation (China) (CN)
Openalex Percentile: Top 8%
Drilling and Well Engineering
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