Application of suppressing random noise in seismic data based on Trivashrink and DTCWT
Wang, Hongye, Han, Liguo, Liu ., Chengming, Wei Wei, Yajie · 世界地质：英文版 · 2014
In process of seismic exploration,the noise of seismic signals produces serious interference. Conventional methods of wavelet threshold denoising cannot fully use the characteristics of seismic signals due to its limitations. There is always a certain degree of deviation between estimated value and actual value. In this study,a method of seismic data denoising is proposed,the authors use the current coefficients,the parent coefficients and the neighborhood coefficients based on dual-tree complex wavelet transform( DTCWT) and related sub-band denoising model( TrivaS hrink) to achieve the optimal estimation of shrinking factor and get the noise reduction of seismic records. It is found that the method is better than conventional methods of wavelet threshold denoising in removing random noise.