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

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 a selective hybrid approach. Two synthetic and one post-stack field data examples demonstrate a better performance of the proposed approach.