8 Feb
2016
8 Feb
'16
5:04 p.m.
Hi Francesco,
Le 08/02/2016 16:53, Francesco Civilini a écrit :
Hello all,
I would like to suggest an option in MSNoise to change the order of operations from
Bandpass -> 1Bit Norm -> Whitening to Bandpass -> Whitening -> 1 Bit Norm in
the s03_compute_cc.py routine.
I have observed that for datasets where there is significant correlation in the higher
frequencies by a cultural source (for example machinery near two stations), but the
frequencies of interest are lower, the resulting correlation will be completely dominated
by the high frequency signal if 1Bit Normalization occurs prior to whitening.
Could
you define "higher frequencies" ? In that specific case indeed,
that could be an issue, but on the other hand, if your data has a strong
earthquake, or even worse, a big glitch, it'll smash the FFT.
This could lead inexperienced users with noisy datasets to think that there are no low
frequency signals propagating across their array. By doing 1Bit normalization prior to
Whitening, it will no longer be possible to filter the cross correlations to further
narrow the target frequencies, which is not the case if Whitening occurs before 1 Bit.
Interesting. Could you provide some demo data to demonstrate the effect
? (the data, the parameters used, and some pictures? )
A workaround for the current version of MSNoise is to change the original bandpass to a
frequency range that excludes the problem frequencies, but this requires prior knowledge
of what the cross correlations will look like for a wide frequency band.
Welllll...
We usually assume poeple know what they have in hand... And
have at least done a spectrum or spectrogram of their data. But I agree,
it can be very tricky to identify before actually seeing the CCFs.
Cheers
Thomas
Does anyone have any personal examples for datasets that support or contrast these
observations?
Thanks,
-Francesco
Francesco Civilini, M.S.
Geophysics PhD Candidate
Victoria University of Wellington
Cotton Building Room 505
Wellington 6012, New Zealand
(027) 868-5939
Francesco.Civilini@vuw.ac.nz<mailto:Francesco.Civilini@vuw.ac.nz>
www.francescocivilini.com<mailto:Francesco.Civilini@vuw.ac.nz>
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