Leak Identification and Positioning Strategies for Downhole Tubing in Gas Wells

Accurate detection of downhole tubing leakage in gas wells is essential for planning effective repair operations and mitigating safety risks in annulus pressure buildup wells. Current localization methods employ autocorrelation analysis to exploit the time-delay features of acoustic signals traveling through the tubing–casing annulus. This allows non-invasive wellhead detection, avoiding costly tubing retrieval or production shutdowns. However, field data show that multiphase flow noise, overlapping reflected waves, and coupled multi-leakage points in the wellbore frequently introduce multi-peak interference in acoustic autocorrelation curves. Such interference severely compromises the accuracy of time parameter extraction. To resolve this issue, our study experimentally analyzes how leakage pressure differential, aperture size, depth, and multiplicity affect the autocorrelation coefficients of acoustic signals generated by leaks. It compares the effects of different noise reduction parameters on leakage localization accuracy and proposes a characteristic time selection principle for autocorrelation curves, providing a new solution for precise leakage localization under complex downhole conditions.

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Publication Details

Journal
Processes
Published
2025-05-29
DOI
https://doi.org/10.3390/pr13061708
Citations
1
Primary Topic
Drilling and Well Engineering
Type
article
Field-Weighted Citation Impact
1.15
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article

Leak Identification and Positioning Strategies for Downhole Tubing in Gas Wells

Guiqing Zou, Meng Niu, Jinyou Wang, Lianfang Zhang et al.
1 citations
Processes
Drilling and Well Engineering
1.15
article

Leak Identification and Positioning Strategies for Downhole Tubing in Gas Wells

Guiqing Zou, Meng Niu, Jinyou Wang, Lianfang Zhang, Maojiang Li, Yunpeng Yang, Jingfeng Yang, Xuliang Zhang, Guo-Hua Luan
article en
1 citations

Abstract

Accurate detection of downhole tubing leakage in gas wells is essential for planning effective repair operations and mitigating safety risks in annulus pressure buildup wells. Current localization methods employ autocorrelation analysis to exploit the time-delay features of acoustic signals traveling through the tubing–casing annulus. This allows non-invasive wellhead detection, avoiding costly tubing retrieval or production shutdowns. However, field data show that multiphase flow noise, overlapping reflected waves, and coupled multi-leakage points in the wellbore frequently introduce multi-peak interference in acoustic autocorrelation curves. Such interference severely compromises the accuracy of time parameter extraction. To resolve this issue, our study experimentally analyzes how leakage pressure differential, aperture size, depth, and multiplicity affect the autocorrelation coefficients of acoustic signals generated by leaks. It compares the effects of different noise reduction parameters on leakage localization accuracy and proposes a characteristic time selection principle for autocorrelation curves, providing a new solution for precise leakage localization under complex downhole conditions.

ProcessesVol. 13(6)
Tarim University (CN), China National Petroleum Corporation (China) (CN)
Openalex Percentile: Top 23%
Drilling and Well Engineering
1.15
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Leak Identification and Positioning Strategies for Downhole Tubing in Gas Wells — Guiqing Zou, Meng Niu, et al. · Processes (2025) | TGRS Research Map | TGRS