Curvelet-based Seismic Data Denoise
Sibing Liu · Jisuanji fangzhen · 2010
In the seismic exploration,random noise is a wide band disturbing wave,which is not ideal when denoised by conventional means. The basic principle and realization of curvelet transform,which has multi-scale and multi-direction characteristics,were introduced. And it was applied in the random noise decaying of seismic data by adopting lump threshold,and in the simulation and real data processing. The result proved that curvelet transform can relatively completely remove the noise while the edge of picture kept well and the detail part also kept at the same time. The result of noise decaying was good and better than wavelet and easy to realize,so that curvelet transform has the feasibility and prospect in the seismic data processing.