Reconstruction of seismic data based on SFISTA and curvelet transform

Abstract

In seismic data processing, the reconstruction and interpolation of missing traces are essential tasks. To overcome the limitations of irregularly sampled seismic data, this paper proposes a seismic data interpolation method combining the smoothing fast iterative soft threshold algorithm (SFISTA) and the curvelet transform; this method uses the curvelet domain as the sparse domain. For comparison, the contourlet transform is used for different sparse domains, and the fast iterative shrinkage-thresholding algorithm (FISTA) is used for different optimization algorithms. Numerical modeling and real data show that the SFISTA method in the curvelet domain can give better reconstruction effects and higher reconstruction accuracy than those in the contourlet domain with the FISTA method; in addition, the SFISTA method in the curvelet domain can be used to reconstruct the missing traces of three-dimensional seismic data.