摘要
一次波L1范数最小化的多次波自适应相减方法,简称L1方法,是基于匹配滤波器设计的多次波自适应相减算法中的一种常用方法。当一次波和多次波混杂在一起时,L1方法有时会伤害一次波,导致一次波同相轴的连续性变差。本文利用预测误差滤波器度量一次波同相轴的连续性,在L1方法的基础上,提出一种能够在压制多次波的同时,尽量保持一次波同相轴连续性的多次波自适应相减算法,简称连续性约束L1方法。利用Pluto模型数据进行多次波相减的结果表明,连续性约束L1方法能够在有效压制多次波的同时,更好地保护一次波。
The Lt-norm method is one of the widely used matching filters for adaptive multiple subtraction. When the primaries and multiples are mixed together, the L1-norm method might damage the primaries, leading to poor lateral continuity. In this paper, we propose a constrained L1-norm method for adaptive multiple subtraction by introducing the lateral continuity constraint for the estimated primaries. We measure the lateral continuity using prediction-error filters （PEF）. We illustrate our method with the synthetic Pluto dataset. The results show that the constrained L1-norm method can simultaneously attenuate the multiples and preserve the primaries.
基金
This work is sponsored by National Natural Science Foundation of China （No. 40874056）, Important National Science ＆ Technology Specific Projects 2008ZX05023-005-004, and the NCET Fund.Acknowledgements The authors are grateful to Liu Yang, and Zhu Sheng-wang for their constructive remarks on this manuscript.
