Seismic data reconstruction combining discrete cosine transform and shearlet transform (ACER)
Yan, H.Y., Zhou, H., Liu, H.B., Xu, Z.H., Sun, Z.D., Liu, Z. and Zhang, M.K., 2023. Seismic data reconstruction combining discrete cosine transform and shearlet transform. Journal o Seismic Exploration, 32: 301-314. The irregularity of seismic data caused by field acquisition affects the imaging quality of subsequent seismic data processing. The reconstruction method based on compressed sensing theory can effectively restore seismic data. The aliasing caused by randomly missing seismic traces is distributed as white noise, and the effective signals are concentrated in the sparse domain. This paper transforms the seismic data reconstruction in the t-x domain into the random noise suppression problem in the discrete cosine transform (DCT) domain. The DCT is a global transform, which transforms the discontinuous t-x data into the continuous DCT data. We do multi-scale directional shearlet transform on the data in the DCT domain and eliminate the aliasing in the DCT domain through iterative inversion. The shearlet transform after the DCT can be used as a new sparse basis transform. The reconstruction experiments show that the reconstruction accuracy in the DCT+shearlet domain is higher than that in the shearlet domain.
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