Common-Mode Noise Attenuation for Distributed Acoustic Sensing Data

초록

Distributed acoustic sensing (DAS) systems utilize optical fiber cables as seismic receivers by emitting light pulses and detecting the resulting minute deformations or vibrations along the fiber through an interrogator unit, thereby enabling the measurement of both strain magnitude and spatial location. While DAS exhibits high sensitivity and can capture even weak seismic signals, it often suffers from low signal-to-noise ratios due to various types of noise, including distinctive patterns not typically found in conventional seismic data. Therefore, target-oriented processing strategies are essential for effective noise suppression. In this study, we focus on common-mode noise, also referred to as horizontal stripe noise, which is caused by external factors such as mechanical vibrations acting on the interrogator. This noise appears as uniform horizontal patterns simultaneously recorded across all channels at specific times and must be removed prior to applying standard seismic processing workflows. Although conventional frequency-wavenumber domain filters can attenuate such noise, their performance often depends heavily on manually selected parameters and may result in unintended signal loss. To address these limitations, we propose a novel method that minimizes signal degradation while effectively isolating common-mode noise. Because common-mode noise exhibits spatial invariance across channels, randomly shuffling the traces disrupts coherent signal components while leaving the noise pattern unchanged. A time-frequency domain filter is then applied to the randomized data to suppress the now-randomized signals and extract the spatially coherent noise. The process is iteratively repeated to enhance robustness. The proposed method is validated on both synthetic and field DAS datasets obtained from a borehole installation, demonstrating effective suppression of common-mode noise with minimal impact on the underlying seismic signals.

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