1. Super-virtual interferometry
Fuqiang Chen
Ahmed Zidan

2. Data and acquisition parameters
Goal:
Detect Qadema fault
and subsurface geology.
Acquisition parameters:
Shot number=240.
Receiver
Shot interval=5m.
Receiver interval=5m.
Line length=1200m.

3. Problem Problems: Data are very noisy. Can’t pick first arrival.
Picking far offset is impossible.
Tomogram result is not good.
Courtesy(Aydar Zaripov,2015)

4. Theoretical Aspects of SVI
Super Virtual Interferometry and its implementation. Shuqian Dong, Jianming Sheng and Jerard T. Schuster

5. SVI: Numerical Tests
Spike test. 2 common receiver gathers (9 traces). Orange line represents
original signal and blue line represents enhanced signal using SVI.
Conclusion: For spike signal and refracted arrival of linear T-X curve,
SVI can perfectly recover it with amplification.

6. SVI: Numerical Tests
Original signal (upper) and noise signal (lower). The maximal amplitude of
signal is 0.4. The maximal amplitude of random noise is sources and
two common receiver gathers are used to enhance the virtual signal

7. SVI: Numerical Tests
The 1st common receiver gather with 80 times noise (upper) and
signal of S/N enhanced by SVI with lucky window. Original signal
is 3 points [….. * * * …..]. Lucky window is

8. SVI: Numerical Tests
The results of lucky window (upper) and (15 points) unlucky window (lower). 17th trace of true data(green), noise-adding data(red) and recovered data using SVI (blue).

9. SVI: Numerical Tests
Shot 21st before SVI (upper) and after SVI (lower)

10. SVI: Numerical Tests
Shot 57th before SVI (upper) and after SVI (lower)

11. proposed solutions Solutions: Process the data to enhance SNR.
Try SVI technique.

12. Processing Flow Karhunen-Loeve Filtering Amplitude Correction(Gain)
FX-Deconvolution
2D Weiner filter
FK Filter
1D median filter

13. Karhunen-Loeve Filtering
Why????????
50 m offset(right)
50 m offset(left)

14. Karhunen-Loeve Filtering
In Common Offset Domain.
Enhance Coherency.
Parameters:
Operator length=20, For left hand side.
Operator length=40, For right hand side.
Reference: M.D Sachi, SAIG, 2008

15. Karhunen-Loeve Filtering
50 m offset(right)
50 m offset(left)

16. Karhunen-Loeve Filtering
Shot # 120

17. Amplitude Correction Focus energy around the first arrival.
Parameters:
function: 𝑡 𝑎 × 𝑒 −𝑏𝑡 .
Reference: M.D Sachi, SAIG, 2008

18. Amplitude Correction
Shot # 120

19. FX-Deconvolution Remove the random noise.
Random noise bursts along the whole frequency spectrum. “Bandpass filter is ineffective ”.
Parameters:
Fmax=70Hz
Fmin=20Hz
Reference: M.D Sachi, SAIG, 2008

20. FX-Deconvolution Why FX-Deconvolution ????????
Why not Bandpass filter ??????

21. FX-Deconvolution
Shot # 120

22. 2D Adaptive Weiner Filter
Smooth the frequency spectrum.
Smooth the amplitude anomalies.
Parameters:
9 samples in time.
2 samples in space.

23. 2D Adaptive Weiner Filter
Shot # 120

24. FK Filter Removes Linear noise.
But, we kept linear events and remove every other events.
Parameters:
Path #1 remove events (Vmin=4000, Vmax=inf).
Path #2 remove events(Vmin=100, Vmax=400).
Reference: G.F. Margrave, CREWES, 1991.

25. FK Filter
Shot # 120

26. 1D median filter
Remove FK residuals.
Parameters:
8th order filter.

27. 1D median filter
Shot # 120

28. SVI SVI- Preconditioning Done on Right and Left hand-side separately.
Window around first arrival.
Shot # 160

29. SVI- Left hand side (mid offset)
Shot # 160

30. SVI- Left hand side (Far offset)
Shot # 160

31. SVI- right hand side (Far offset)
Shot # 160

32. Conclusion And Recommendation
Processing enhances the coherency of the data and enhance SNR.
SVI works well till mid offset (85m).
Recommendation:
Further data processing is required to enhance SNR for far offset.
Run SVI for far offset.
Perform reflection processing to estimate the NMO velocity.