Abstract In this paper, we built upon the estimating primaries by sparse inversion (EPSI) method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and L1-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination (SRME) method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equation-based method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.
The research was financially supported by the National Science and Technology Major Project (No.2011ZX05023-005-008).
Cite this article:
FENG Fei,WANG De-Li,ZHU Heng et al. Estimating primaries by sparse inversion of the 3D Curvelet transform and the L1-norm constraint[J]. APPLIED GEOPHYSICS, 2013, 10(2): 201-209.
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