Signal Processing

Correlation Amplitude Levels

What kind of normalisation can be found on correlated vibroseis data

In frequency domain the correlation can be written as the multiplication of uncorrelated data \(D_u\) by the complex conjugate of the reference \(S\) : \[D_c(\nu)=‎ D_u(\nu).\bar{S}(\nu)\]

The resulting scaling amplitude of the result is obviously linked to the reference power (length, drive etc…). Several options for the scaling :

Normalize the correlation according to the total energy of the reference used :

\[D_c(\nu) = \frac{D_u(\nu).\bar{S(\nu)}}{\sum{S_n^2}}\]

In this case the gain of the obtained “Earth Response” is independent of the reference : all the signal is at the same level.

Normalize the correlation according to the signal-to-noise ratio :

\[D_c(\nu) = \frac{D_u(\nu).\bar{S(\nu)}}{\sqrt{\sum{S_n^2}}}\]

In this case the gain of the obtained “Earth Response” id scaled according to the reference and all the noise is at the same level.

Hybrid Sercel Unite/428 version :

\[D_c(\nu) = \frac{2.D_u(\nu).\bar{S(\nu)}}{N.\sum{S_n^2}}\]

Here the obtained “Earth Response” is scaled on the amplitude part of the reference but not on its length. The sweep length has no impact on the output gain.

SIGPROC
vibroseis signal processing correlation