Random noise attenuation by a selective hybrid approach using f-x empirical mode decomposition

Published as Journal of Geophysics and Engineering, 12, 12-25, (2015)

Random noise attenuation by a selective hybrid approach using f-x empirical mode decomposition

Yangkang Chen, Shuwei Gan, Tingting Liu, Jiang Yuan, Yizhuo Zhangand Zhaoyu Jin
Bureau of Economic Geology
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX 78713-8924

State Key Laboratory of Petroleum Resources and Prospecting
China University of Petroleum
Fuxue Road 18th
Beijing, China, 102200

Grant Institute, The King's Buildings, West Mains Road
University of Edinburgh
Edinburgh,UK, EH9 3JW

Abstract:

Empirical mode decomposition (EMD) becomes attractive recently for random noise attenuation because of its convenient implementation and ability in dealing with non-stationary seismic data. In this paper, we summarize the existing use of EMD in seismic data denoising and introduce a general hybrid scheme which combines $f-x$ EMD with a dipping-events retrieving operator. The novel hybrid scheme can achieve a better denoising performance compared with the conventional $f-x$ EMD and selected dipping event retriever. We demonstrate the strong horizontal-preservation capability of $f-x$ EMD that makes the EMD based hybrid approach attractive. When $f-x$ EMD is applied to a seismic profile, all the horizontal events will be preserved, while leaving few dipping events and random noise in the noise section, which can be dealt with easily by applying a dipping-events retrieving operator to a specific region for preserving the useful dipping signal. This type of incomplete hybrid approach is termed as selective hybrid approach. Two synthetic and one post-stack field data examples demonstrate a better performance of the proposed approach.

Random noise attenuation by a selective hybrid approach using f-x empirical mode decomposition