1. Just when you thought you were
More R-T noise attenuation
Just when you thought you were
Safe…
Henley

2. MORE coherent noise attenuation in the radial trace domain
(the saga continues)
David C. Henley
CREWES

3. Overview The R-T transform and its properties
Coherent noise attenuation methods
Modelling coherent noise in the R-T domain—single/multi-channel techniques
Noise cancellation techniques
R-T trajectory modifications
3D noise attenuation
Summary

4. R-T transform properties
R-T coordinate trajectories can be aligned with coherent noise wavefronts
R-T wavefield components separated by velocity, apparent frequency
Intrinsic R-T interpolation can discriminate between wavefield components

5. How to get radial traces
from an X-T panel of
seismic traces.
Numbered trajectories
correspond to radial
traces shown in adjacent
figure.
The R-T transform

6. Representative radial traces
created from the X-T seismic
trace gather in adjacent
figure.
The R-T transform

7. R-T transform interpolation methodsX1 X2 Rv a. b.
X-interpolation
V-interpolation
R-T transform interpolation methods

8. R-T noise attenuation methods
Attenuate noise directly in R-T based on velocity/frequency
‘Model’ noise in R-T based on velocity/frequency, subtract noise estimate in X-T domain

9. The two basic R-T coherent noise attenuation methods
R-T input
R-T input
X-T input
Hi-pass
Lo-pass
R-T noise
R-T signal
R-T-1
R-T-1
subtract
X-T noise
X-T signal
X-T signal 2 1
The two basic R-T coherent noise attenuation methods

10. Single-trace modelling operations (Based on frequency discrimination alone)
Low-pass Ormsby filter
Running mean (boxcar filter)
Running median

11. Raw Blackfoot shot gather with coherent noise
1.0
2.0
sec
-1370
1630
metres
Raw Blackfoot shot gather with coherent noise

12. R-T fan transform of Blackfoot shot gather
1.0
2.0
sec
-3300
3300
m/s
R-T fan transform of Blackfoot shot gather

13. Low-pass R-T transform of Blackfoot gather
1.0
2.0
sec
-3300
3300
m/s
Low-pass R-T transform of Blackfoot gather

14. X-T domain noise estimate
1.0
2.0
sec
-1370
1630
metres
X-T domain noise estimate

15. Blackfoot gather minus X-T noise estimate
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather minus X-T noise estimate

16. X-T noise estimate from 100 point running mean in R-T domain
1.0
2.0
sec
-1370
1630
metres
X-T noise estimate from 100 point running mean in R-T domain

17. Blackfoot gather minus 100 point noise estimate
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather minus 100 point noise estimate

18. Noise estimate from 50 point running mean in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Noise estimate from 50 point running mean in the R-T domain

19. Blackfoot gather minus 50 point noise estimate
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather minus 50 point noise estimate

20. Noise estimate from 25 point running mean in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Noise estimate from 25 point running mean in the R-T domain

21. Blackfoot gather minus 25 point noise estimate
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather minus 25 point noise estimate

22. Noise estimate from 100 point running median in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Noise estimate from 100 point running median in the R-T domain

23. Noise estimate from 50 point running median in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Noise estimate from 50 point running median in the R-T domain

24. Noise estimate from 300 point running median in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Noise estimate from 300 point running median in the R-T domain

25. Blackfoot shot minus 300 point running median noise estimate
1.0
2.0
sec
-1370
1630
metres
Blackfoot shot minus 300 point running median noise estimate

26. Multi-trace modelling operations (Based on frequency/velocity discrimination
K-F filter
Running mean/trace mix
Low-pass/weighted trace mix

27. Noise estimate from K-F filter in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Noise estimate from K-F filter in the R-T domain

28. Blackfoot gather minus K-F filter R-T domain noise estimate
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather minus K-F filter R-T domain noise estimate

29. Blackfoot gather K-F filtered directly in the R-T domain
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather K-F filtered directly in the R-T domain

30. Noise cancellation techniques
Simple subtraction
Scaled subtraction
Adaptive scaled subtraction
Iteration

31. Subtraction coefficient = 1.00
1.0
2.0
sec
-1370
1630
metres
Subtraction coefficient = 1.00

32. Subtraction coefficient = 1.25
1.0
2.0
sec
-1370
1630
metres
Subtraction coefficient = 1.25

33. Subtraction coefficient = 0.80
1.0
2.0
sec
-1370
1630
metres
Subtraction coefficient = 0.80

34. Noise estimate from second iteration of ‘model-and-subtract’
1.0
2.0
sec
-1370
1630
metres
Noise estimate from second iteration of ‘model-and-subtract’

35. Blackfoot gather minus first two noise estimates
1.0
2.0
sec
-1370
1630
metres
Blackfoot gather minus first two noise estimates

36. R-T trajectory modifications
Non-linearity can be used to make trajectories conform more/less closely to coherent noise wavefronts
More conformable trajectories lower apparent frequency of noise
Less conformable trajectories reduce spatial aliasing of noise

37. Conventional R-T transform with linear trajectories
1.0
2.0
sec
-3300
3300
m/s
Conventional R-T transform with linear trajectories

38. R-T transform with upward-curving trajectories
1.0
2.0
sec
-3300
3300
m/s
R-T transform with upward-curving trajectories

39. R-T transform with downward-curving trajectories
1.0
2.0
sec
-3300
3300
m/s
R-T transform with downward-curving trajectories

40. Noise attenuation in 3D
Data organisation is the key to noise attenuation
Organise 3D shot traces to maximise noise coherence
Receiver-line gathers usually have best spatial sampling, greatest coherent noise coherence

41. Receiver-line gathers from land 3D survey
0.0
1.0
2.0
3.0
Sec.
Receiver-line gathers from land 3D survey

42. 3D receiver line gathers after R-T domain filtering
0.0
1.0
2.0
3.0
Sec.
3D receiver line gathers after R-T domain filtering

43. Another application
R-T filtering used to remove ‘swell’ noise from marine data

44. Marine gathers with ‘swell’ noise
5.0
7.0
sec
9.0
11.0
Marine gathers with ‘swell’ noise

45. ‘Standard’ processing to remove ‘swell’ noise
5.0
7.0
sec
9.0
11.0
‘Standard’ processing to remove ‘swell’ noise

46. R-T filtering to reduce ‘swell’ noise
5.0
7.0
sec
9.0
11.0
R-T filtering to reduce ‘swell’ noise

47. Summary 1
Model-and-subtract most useful technique for R-T domain noise attenuation
Low-pass Ormsby filter best single-channel R-T modelling operation
K-F filter best multi-channel R-T domain modelling operation
Scaled subtraction best overall noise removal method

48. Summary 2 Iteration best enhancement for R-T domain noise attenuation
Non-linear R-T trajectories can optimise capture of some coherent noise
3D data can be filtered following proper trace organisation

49. The future
Optimised, data-adaptive subtraction techniques (e.g. least squares)
Auto-tracking R-T trajectories
New multi-channel modelling operation (combined R-T interpolation/modelling)

50. Acknowledgements CREWES sponsors for support
CREWES staff for discussion
EnCana for Blackfoot data use
Mike Hall and GX Technologies for 3D land and Marine data examples