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Filtering of Seismic Data |
The interpretation of seismic data is made purely on the basis of what is observed in the final processed section. CMP processing greatly enhances the signal to noise ratio and allows coherent reflections to be visible. However, the data that goes into the CMP processing is often contaminated with "noise". The ground roll in the CSP gather shown previously is a good example. Also, the data might be contaminated with wind noise or instrument vibrations. These, and other types of noise, can be partially removed by using various filtering operations. Three Useful Filtering Operations
Wind, instrument, and cultural effects can generate unwanted noise at frequencies outside the seismic band. Often these are high frquency signals. Alternatively, ground roll and ship generated noise are low frequency. If this is the case then the seismic signal might lie in a frequency band that is distinct from the the noise. This is illustrated below. The unwanted noise can be removed using bandpass filtering in the frequency domain.
2. Deconvolution
A seismic wavelet is composed of the orginal wavelet plus a closely spaced reflection. This complicates the wavelet as shown in the figure below. A deghosting filter can remove the effect of the ghost so each reflection looks like a primary wavelet. b) Wavelet or Signature Deconvolution An "inverse filter" is designed so that the original source wavelet is contracted to a narrower and symmetric form. e.g.
This can enhance the vertical resolution, though not beyond the "theoretical" maximum which is controlled by wavelength. This type of processing can remove some multiples from a seismic section. Reverberation (multiples of the ocean-bottom reflection) in marine surveys is a common example of this type of problem. 3. Velocity or f-k filtering
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