Abstract：Considering the defects of multiple model prediction by SRME, we propose in this paper an approach to reconstruct multiple model trace based on Curvelet transform. The directional characteristics of Curvelet transform allow Snell's law at the free surface to automatically construct the multiple contribution gathers(MCG) which obey Snell's law or exist in stationary zones. This strategy reduces the artifacts caused by the non-constructive multiple contributions. Moreover, based on multi-scale property of Curvelet transform, an anti-aliasing weighting filter is designed using the low frequency dataset without space aliasing to reduce the adverse influence to the multiple model when the input original dataset have space aliasing. In this way, the accuracy of multiple prediction models can be improved for the latter subtraction stage. Finally, tests on synthetic and field datasets have demonstrate the effectiveness of the proposed approach.
Lu Wenkai, Luo Yi, Zhao Bo. Adaptive multiple wave subtraction using independent component analysis. Chinese Journal of Geophysics, 2004, 47(5):886-891.
[5]
Douglas J Foster, Charles C Mosher. Suppression of multiple reflections using the Radon transform. Geophysics, 1992, 57(3):386-395.
[6]
Weglein A B, Gasparotto F A, Carvalho P M et al. An inverse-scattering series method for attenuating multiples in seismic reflection data. Geophysics, 1997, 62(6):1975-1989.
Dong Lieqian, Li Zhenchun, Yang Shaochun et al. Non-causal matching filter multiple elimination me-thod based correlation and iteration. Chinese Journal of Geophysics, 2013, 56(10):3542-3551.
Li Xuecong, Liu Yike, Chang Xu et al. The adaptive subtraction of multiple using the equipoise multichannel L1-norm matching, Chinese Journal of Geophy-sics, 2010, 53(4):963-973.
Dong Lieqian, Li Zhenchun, Yang Shaochun et al. An improved method of surface-related multiple elimination. Progress in Geophysics, 2013, 28(6):3148-3152.
[10]
Berkhout A J, Verschuur D J. Estimation of multiple scattering by iterative inversion, Part 1:Theoretical considerations.Geophysics, 1997, 62(5):1586-1595.
[11]
Candès E J, Donoho D L. Curvelet manuscript.http://www-stat.standford.edu/~Donoho/Reports/1999/curvelet/.pdf, 1999.
[12]
Candès E J, Donoho D L. New tight frames of curvelets and optimal representations of objects with C2 singularities. Comm. On Pure and Appl Math, 2004, 57(2):219~266.
[13]
Felix J, Herrmann, Deli Wang et al. Adaptive curvelet-domain primary-multiple separation. Geophysics, 2008, 73(3):A17-A21.
Bao Qianzong, Gao Jinghuai, Chen Wenchao. Wave field separation of vertical seismic profiling in curvelet domain. Journal of Xi'an Jiaotong University, 2007, 41(6):650-654.
Dong Lieqian, Li Zhenchun, Liu Lei et al. A method of Curvelet threshould denoising based on empirical mode decomposition. Journal of Jilin University(Earth Science Edition), 2012, 42(3):838-844.
[17]
Daniela Donno, Hervé Chauris and Mark Noble.Curvelet-based multiple prediction. Geophysics, 2010, 75(6):WB255-WB263.
