Non-causal matching filter multiple elimination method based on correlation and iteration

作者：Dong Lie-Qian^*; Li Zhen-Chun; Yang Shao-Chun; Wang De-Ying; Wang Jiao

来源：Acta Geophysica Sinica, 2013, 56(10): 3542-3551.

DOI：10.6038/cjg20131029

• Multiple suppression
• Spatial convolution
• Data correlation
• Spatial aliasing
• Non-causal matching filter

In this paper, an improved method is proposed to overcome the shortcomings of conventional method of surface-related multiple elimination (SRME). Firstly, multiple model is predicted by data correlation and iterative update. The method can decrease the rigorous requirement of input data, however, which is needed in the method of SRME. Moreover, it can also improve the suitability of input data sets with near-offset deficiency or spatial aliasing. Secondly, a non-causal and non-stationary matching filter is designed, which can process an entire multiple model trace. In addition, even if the time of predictive multiple model is later than the actual multiple, the method still works well. Finally, applying the method to synthetical and field data sets indicates the superiority in multiple model prediction and matching subtraction.

• 出版日期2013-10
• 单位中国石油大学（北京）