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    This study introduces a hardware-assisted distributed acoustic sensing (DAS) method. It significantly reduces data processing time and expands the dynamic measurement range for seismic wave observation.

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    Area of Science:

    • Geophysics
    • Optical Sensing Technologies

    Background:

    • Distributed acoustic sensing (DAS) offers dense seismic network capabilities but faces challenges with large data volumes and limited dynamic range.
    • Current DAS systems struggle with storage demands and demodulation speed due to extensive raw data.
    • The fixed strain sensitivity of conventional DAS restricts its ability to measure a wide range of seismic signal amplitudes.

    Purpose of the Study:

    • To develop a novel single-shot, multi-sensitivity distributed acoustic sensing (DAS) method.
    • To address the limitations of data volume and dynamic range in practical DAS applications.
    • To enhance the efficiency and applicability of DAS in complex environments and real-time detection scenarios.

    Main Methods:

    • Implemented a hardware filtering module to achieve lower sampling rates, reducing data acquisition and processing times.
    • Generated multiple sideband pulses with varying bandwidths (20, 40, and 80 MHz) for multi-sensitivity detection.
    • Utilized a single-shot approach to streamline the data acquisition and demodulation process.

    Main Results:

    • Reduced average processing time for single-sideband pulse detection by approximately 20 times (from 214.79 s to 9.83 s).
    • Enabled multi-sensitivity strain event detection through hardware-filtered, modulated pulses of different bandwidths.
    • Demonstrated the capability to recover seismic signals across different ranges of strain events.

    Conclusions:

    • The proposed hardware-assisted multi-sensitivity DAS method effectively mitigates data storage and processing speed challenges.
    • This innovative approach expands the dynamic measurement range of DAS systems.
    • The method presents a promising solution for real-time seismic monitoring in demanding environments.