Random Noise Suppression of Multicomponent Seismic Data Using Discrete Orthogonal Quaternion Wavelet Transform

Abstract The literature on seismic data processing offers numerous methods for denoising single-component seismic data. However, more random noise attenuation methods explicitly for multicomponent seismic data remain underexplored. This study introduces a vector thresholding method based on the discrete orthogonal quaternion wavelet transform (DOQWT) for multicomponent seismic random noise attenuation. To address the accurate estimation of threshold value, we derive a new threshold estimation formula suitable for three-component data denoising. Furthermore, we analyze the influence of some key factors on the DOQWT vector threshold denoising performance, including threshold function, threshold value, and noise correlation. Tests on both synthetic and field ocean bottom seismometer (OBS) seismic data demonstrate that the proposed DOQWT vector threshold method outperforms the conventional scalar wavelet thresholding method and concatenated vector thresholding method in terms of signal-to-noise ratio, preservation of polarization characteristics, and recovery of weak signals.