Experimental Study on Simulated Acoustic Characteristics of Downhole Tubing Leakage

In response to the limitations of experimental methods for detecting oil and gas well tubing leaks, this study developed a full-scale indoor simulation system for oil tubing leakage. The system consists of three components: a wellbore simulation device, a dynamic leakage simulation module, and a multi-parameter monitoring system. The wellbore simulator employs a jacketed structure to replicate real-world conditions, while the leakage module incorporates a precision flow control device to regulate leakage rates. The monitoring system integrates high-sensitivity acoustic sensors and pressure sensors. Through multi-condition experiments, the system simulated complex scenarios, including leakage apertures of 1–5 mm, different leakage positions relative to the annular liquid level, and multiple leakage point combinations. A comprehensive acoustic signal processing framework was established, incorporating time–domain features, frequency–domain characteristics, and time–frequency joint analysis. Experimental results indicate that when the leakage point is above the annular liquid level, the acoustic signals received at the wellhead exhibit high-frequency characteristics typical of gas turbulence. In contrast, leaks below the liquid level produce acoustic waves with distinct low-frequency fluid cavitation signatures, accompanied by noticeable medium-coupled attenuation during propagation. These differential features provide a foundation for accurately identifying leakage zones and confirm the feasibility of using acoustic detection technology to locate concealed leaks below the annular liquid level. The study offers experimental support for improving downhole leakage classification and early warning systems.

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Publication Details

Journal
Processes
Published
2025-05-20
DOI
https://doi.org/10.3390/pr13051586
Primary Topic
Drilling and Well Engineering
Type
article
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article

Experimental Study on Simulated Acoustic Characteristics of Downhole Tubing Leakage

Shengli Chu, Jinyou Wang, Yushan Zheng, Yinghua Jing et al.
Processes
Drilling and Well Engineering
article

Experimental Study on Simulated Acoustic Characteristics of Downhole Tubing Leakage

Shengli Chu, Jinyou Wang, Yushan Zheng, Yinghua Jing, Maojiang Li, Jingwei Zhang, Jianchun Fan, Yun-Peng Yang, Shuang Liang, Bingcai Sun
article en

Abstract

In response to the limitations of experimental methods for detecting oil and gas well tubing leaks, this study developed a full-scale indoor simulation system for oil tubing leakage. The system consists of three components: a wellbore simulation device, a dynamic leakage simulation module, and a multi-parameter monitoring system. The wellbore simulator employs a jacketed structure to replicate real-world conditions, while the leakage module incorporates a precision flow control device to regulate leakage rates. The monitoring system integrates high-sensitivity acoustic sensors and pressure sensors. Through multi-condition experiments, the system simulated complex scenarios, including leakage apertures of 1–5 mm, different leakage positions relative to the annular liquid level, and multiple leakage point combinations. A comprehensive acoustic signal processing framework was established, incorporating time–domain features, frequency–domain characteristics, and time–frequency joint analysis. Experimental results indicate that when the leakage point is above the annular liquid level, the acoustic signals received at the wellhead exhibit high-frequency characteristics typical of gas turbulence. In contrast, leaks below the liquid level produce acoustic waves with distinct low-frequency fluid cavitation signatures, accompanied by noticeable medium-coupled attenuation during propagation. These differential features provide a foundation for accurately identifying leakage zones and confirm the feasibility of using acoustic detection technology to locate concealed leaks below the annular liquid level. The study offers experimental support for improving downhole leakage classification and early warning systems.

ProcessesVol. 13(5)
Tarim University (CN), China National Petroleum Corporation (China) (CN)
Openalex Percentile: Top 86%
Drilling and Well Engineering
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