) the reflectivity strength is affected by the bandwidth of the data.
Let us consider the case where the source and receiver wavefields coincide at the reflector depth and both have a similar frequency content. The best situation we could have is for their division to be a box function. This is unlikely to happen in a real case. Inside the data bandwidth the division is a constant value. But outside of the data bandwidth we may try to divide small numbers by small numbers, which has the potential to be unstable. In equation (
) we use a damping factor to avoid this source of instability but when we apply equation (
) we end up with values that were supposed to be zero contributing to the reflectivity strength.
A different implementation of equation (
), forcing hard zeros when
, reduces the impact of band-limited data in the reflectivity strength calculation as
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(94) |
There is another source of error for the band-limited.
The Fourier pair of the box function is a sinc function. In the extreme case of a infinite wide box the Fourier pair is a delta function centered at zero lag. As the box is getting narrower in the Fourier domain, the delta becomes a wider sinc function in the time domain. Therefore, the reflectivity strength
is a scaled version of his infinite bandwidth version.
We can compensate for the bandwidth of the data by computing the zero lag of the deconvolution as
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(95) |