We introduce a nondiagonal seismic denoising method based on the continuous wavelet transform with hybrid block thresholding (BT). Parameters for the BT step are adaptively adjusted to the inferred signal property by minimizing the unbiased risk estimate of Stein (1980). The efficiency of the denoising for seismic data has been improved by adapting the wavelet thresholding and adding a preprocessing step based on a higher-order statistical analysis and a postprocessing step based on Wiener filtering. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising and improving the signal-to-noise ratio of local microseismic, regional, and ocean bottom seismic data.
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