On the sensitivity of distributed acoustic sensing

Area of Science:

• Photonics and Optical Sensing
• Signal Processing
• Fiber Optic Technology

Background:

• Distributed Acoustic Sensing (DAS) converts optical fibers into virtual microphone arrays.
• Current DAS methods rely on Rayleigh backscattering, leading to signal fading and fluctuating sensitivities.
• Existing sensitivity metrics for DAS are incomplete due to the random nature of signal fading.

Purpose of the Study:

• To statistically analyze the properties of DAS Signal-to-Noise Ratio (SNR) and sensitivity.
• To address the limitations of current DAS sensitivity characterization.
• To introduce a novel figure of merit for DAS system performance.

Main Methods:

• Statistical analysis of DAS SNR and sensitivity.
• Investigation of the relationship between dynamic DAS SNR and static backscatter profiles.
• Examination of the impact of interrogation pulse energy on DAS performance.

Main Results:

• The mean dynamic DAS SNR is directly proportional to the static backscatter SNR.
• Mean dynamic DAS SNR also scales with the energy of the interrogation pulse.
• A new metric, minimum input signal for a specified mean DAS SNR, is proposed.

Conclusions:

• Understanding the statistical nature of DAS sensitivity is crucial for accurate performance assessment.
• The proposed minimum input signal metric offers a robust way to characterize and compare DAS systems.
• This work provides a more complete framework for evaluating DAS sensitivity and performance.