Seismic Data De-noising Based on Second Wavelet Transform

A main task of geophysical exploration is to remove random noises in seismic data processing to improve the signal-to-noise ratio. Recently wavelet theory is applied widely to remove random noises in seismic data processing. A commonly used de-noising method is represented by Donoho. On the basis of Donoho´s wavelet threshold de-noising processing method, the paper presents a de-noising method for seismic data based on second wavelet transform. The multi-scale wavelet transform is carried out for seismic data in the method, then second multi-scale wavelet transform is carried out again for wavelet coefficients in scale 1 mainly controlled by noises, zero is set for wavelet coefficient in scale 1 after second wavelet transform and reconstruction of wavelet coefficients in other scales is carried out, finally, the wavelet threshold de-noising processing is carried out for seismic section after above-mentioned processing. The results of theoretical model and practical data processing show that the method presented by the paper can effectively improve processing quality of seismic sections and S/N ratio of seismic data.