SEISMIC EXAMPLES ARE INCLUDED IN THE PRESENTATION, A GEOPHYSICIST OR ANY OTHER DSP LEARNER CAN SEE THE PRESENTATION FOR QUICK REVIEW.

1. Presented By:
Abhilash Saini
GP 16
M.Tech. Applied Geophysics

2. Contents
 Introduction to Filtering
 Types of Filters
 F-K Filter
 Weiner Filters
 Case study using these filters
 Conclusions
 References

3. Filtering why and when?
 In signal processing, a filter is a device or process that
removes some unwanted components or features from
a signal. (e.g. Earth as low pass filter)

4. Types of filters
(1) FREQUENCY FILTERS
There are mainly four types of filters
employed in signal processing.
They are:
 Low pass (or high cut) filter
 High pass (or low cut) filter
 Band pass filter
 Band reject filter
BUT………………..we always need……….

5. (2) INVERSE FILTERS
 F-K Filter
 Weiner Filter
WHY?
Because after frequency filtering we still have noise in our seismic
signal, those are in same frequency range so we need a different
approach to do that,
There are many inverse filters designed according to the need but for
now we are going to discuss two of them :

6. F-K filter
Principle

7. F-K filter (cont.)
Along the spread direction, each individual sinusoidal component of the pulse
will have an apparent wavenumber ka related to its individual frequency f, where

8. F-K filter (cont.)
The effect of f–k filtering of a seismic section. (a) Stacked section showing steeply
dipping coherent noise events, especially below 4.5 s two-way reflection time. (b)
The same section after rejection of noise by f–k filtering (Courtesy Prakla-Seismos
GmbH).

9. F-K Filter Applications
 Removal of ground roll from shot gathers
 Which implies in better determination of stacking
velocities.
 Then its easy to remove the multiples too.
 F-K filtering can be done a section of seismic data
rather than doing it individually on each pulse, so easy
to remove diffraction pattern too.

10. Weiner Filter

11. Weiner Filter (cont.)

12. Weiner Filter (cont.)

13. Weiner Filter (cont.)

14. Weiner Filter (cont.)
The error in the above equation is minimized by differentiating w.r.t. a and b
respectively and setting equal to zero to provide us with the following
equations:

15. Weiner Filter (cont.)

16. Weiner Filter (cont.)

17. Weiner Filter (cont.)

18. Weiner Filter (cont.)

19. Weiner Filter (cont.)

20. Weiner Filter (cont.)
(a)
(b)
Removal of reverberations
by predictive deconvolution. (a) Seismic
record dominated by strong
reverberations. (b) Same section after
spiking deconvolution. (Courtesy
Prakla Seismos GmbH.)