Joint noise attenuation technique based on curvelet transform and total variation minimization

In order to take advantage of curvelet transform in seismic data denosing and overcome its inherent shortcomings, we applied the joint random noise attenuation technique based on curvelet transform and total variation minimization on seismic data. This technique uses the nonlinear-thresholding approach to realize the curvelet transform and adopts total variation minimization for small coefficients. Theoretical model and real data processing results show that this technique can greatly attenuate random noise, effectively overcome aliased curves when merely using curvelet transform, and preserve the significant signal in seismic data as well.