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

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

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

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

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

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

R-T transform interpolation methods X1 X2 Rv a. b. X-interpolation V-interpolation R-T transform interpolation methods

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Noise cancellation techniques Simple subtraction Scaled subtraction Adaptive scaled subtraction Iteration

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

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

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

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’

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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