This paper deals with the design and implementation of a new wavelet frame for noise suppression based on the character of seismic data. In general, wavelet denoising methods widely used in image and acoustic processing use well-known conventional wavelets which, although versatile, are often not optimal for seismic data. The new approach, physical wavelet frame denoising uses a wavelet frame that takes into account the characteristics of seismic data both in time and space. Synthetic and real data tests show that the approach is effective even for seismic signals contaminated by strong noise which may be random or coherent, such as ground roll or air waves.

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