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Bekara and van der Baan (2009) cleverly utilize this by-product of
EMD to attenuate coherent noise such as ground roll.
The detailed algorithmic steps of
EMD are given by Bekara and van der Baan (2009) as:
EMD can be used as an adaptive
filter. The cutoff wavenumber is adaptively defined and does not need any apriori knowledge about the seismic data in order to define the filter parameters. This adaptability makes
EMD very convenient to utilize in real applications. The frequency-slice-dependent adaptability also makes
EMD more precise than
predictive filtering, because all the filter parameters in
predictive filtering for each frequency slice are the same. Another advantage of
EMD over
predictive filtering is that the trace spacing does not need to be perfectly regular because no convolutional operator is used, a characteristic similar to local median and SVD filtering (Bekara and van der Baan, 2007,2009).
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sigimf
Figure 2. Demonstration of empirical mode decomposition on a synthetic signal. (a) The original signal, (b) first IMF, (c) second IMF, (d) third IMF, (e) residual. |
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