Decoding Fluid Flow Characteristics Through Distributed Acoustic Sensing: A Novel Approach

Flow characteristic monitoring includes parameters such as flow regime, fluid characteristic frequency, and flow rate, which are crucial for optimizing production and ensuring the safety of oil and gas transportation systems. Existing fluid monitoring technologies, such as various flow meters, often face limitations in providing distributed and real-time monitoring data. In contrast, distributed acoustic sensing offers a spatial resolution of 1 m with high frequency sampling capability, allowing for long-term, multi-point dynamic monitoring of fluid migration characteristics. We developed an indoor physical simulation pipeline loop to assess the feasibility of using distributed acoustic sensing for monitoring flow migration characteristics. The experiment collected signal characteristics under different conditions, including background noise, single gas-phase flow, single liquid-phase flow, and gas-liquid two-phase flow. In the frequency-power spectral density analysis, single gas-phase flow signals are concentrated at lower frequencies, single liquid-phase flow displays noticeable spikes over a broader frequency range, and gas-liquid two-phase flow covers the widest frequency range with stronger amplitude signals. Autocorrelation analysis shows larger oscillations for gas-liquid two-phase flow, smoother signals for gas-phase flow, and more turbulent signals for liquid-phase flow. By examining root mean square energy changes, flow rates can be qualitatively estimated, revealing a positive correlation between energy and flow velocity. Finally, the study discussed the limitations of the experimental setup and proposed improvements and advanced research directions of distributed acoustic sensing in fluid monitoring.

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Publication Details

Journal
Sensors
Published
2025-03-23
DOI
https://doi.org/10.3390/s25072011
Citations
2
Primary Topic
Flow Measurement and Analysis
Type
article
Field-Weighted Citation Impact
1.73

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article

Decoding Fluid Flow Characteristics Through Distributed Acoustic Sensing: A Novel Approach

Kunpeng Zhang, Hailong Lu, Xiangge He, Haochu Ku et al.
2 citations
Sensors
Flow Measurement and Analysis
1.73
article

Decoding Fluid Flow Characteristics Through Distributed Acoustic Sensing: A Novel Approach

Kunpeng Zhang, Hailong Lu, Xiangge He, Haochu Ku, Min Zhang
article en
2 citations

Abstract

Flow characteristic monitoring includes parameters such as flow regime, fluid characteristic frequency, and flow rate, which are crucial for optimizing production and ensuring the safety of oil and gas transportation systems. Existing fluid monitoring technologies, such as various flow meters, often face limitations in providing distributed and real-time monitoring data. In contrast, distributed acoustic sensing offers a spatial resolution of 1 m with high frequency sampling capability, allowing for long-term, multi-point dynamic monitoring of fluid migration characteristics. We developed an indoor physical simulation pipeline loop to assess the feasibility of using distributed acoustic sensing for monitoring flow migration characteristics. The experiment collected signal characteristics under different conditions, including background noise, single gas-phase flow, single liquid-phase flow, and gas-liquid two-phase flow. In the frequency-power spectral density analysis, single gas-phase flow signals are concentrated at lower frequencies, single liquid-phase flow displays noticeable spikes over a broader frequency range, and gas-liquid two-phase flow covers the widest frequency range with stronger amplitude signals. Autocorrelation analysis shows larger oscillations for gas-liquid two-phase flow, smoother signals for gas-phase flow, and more turbulent signals for liquid-phase flow. By examining root mean square energy changes, flow rates can be qualitatively estimated, revealing a positive correlation between energy and flow velocity. Finally, the study discussed the limitations of the experimental setup and proposed improvements and advanced research directions of distributed acoustic sensing in fluid monitoring.

SensorsVol. 25(7)
Peking University (CN), China University of Petroleum, Beijing (CN), Institute of Optics and Electronics, Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, China Geological Survey
Openalex Percentile: Top 19%
Flow Measurement and Analysis
1.73
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