We have proposed a novel local bandlimited orthogonalization approach for removing highly non-stationary ground-roll noise, which can remove most ground-roll noise without harming the useful primary reflections. We orthogonalize the initial guess of primary reflections and ground-roll noise using local signal-and-noise orthogonalization. The initial guess of primary reflections and ground-roll noise are bandlimited data from a common bandpass filtering with a relatively high LBF such that all the ground-roll noise is removed during the initial guess. The proposed approach can solve the frequency-overlap problem when applying a simple bandpass filtering. The proposed approach can guarantee that the least amount of useful primary reflections is lost in the noise section. The procedure of the proposed approach is fairly convenient to implement because only a bandpass filtering and a regularized division between the initially denoised signal and initial noise are used. We have used an open-source field dataset to demonstrate the successful performance of the proposed approach in real data processing.
Ground-roll noise attenuation using a simple and effective approach based on local bandlimited orthogonalization
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