Seismic data reconstruction with Shearlet transform based on compressed sensing technology
Zhang Liang1, Han Liguo1, Xu Dexin2, Li Yu1, Li Hui1
1. College of Geo-exploration Sciences and Technology, Jilin University, Changchun, Jilin 130026, China;
2. Northeastern Investigation, Design & Research Co., Ltd, China Water, Changchun, Jilin 130021, China
Abstract：Seismic data reconstruction based on the prediction filtering usually has huge error; seismic data reconstruction based on the wave equation needs large calculation time; and seismic data reconstruction based on some transform methods suffers low accuracy.Therefore,we propose seismic data reconstruction with Shearlet transform based on compressed sensing.Based on the signal sparsity,the sampling matrix is designed according to seismic data loss,and seismic data get sparse with Shearlet transform.Then,the orthogonal matching pursuit algorithm is used to reconstruct the sparsity coefficients in the Shearlet domain.Finally,seismic data reconstruction is realized by inverse Shearlet transform.Experimental results show that the Shearlet transform based on compressed sensing can well reconstruct seismic data.Moreover,the proposed approach has higher reconstruction accuracy than the Fourier transform,discrete cosine transform,Wavelet transform,and Curvelet transform.
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