surface wave elimination by interferometry and adaptive subtraction yanwei xue university of utah
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SURFACE WAVE ELIMINATION BY INTERFEROMETRY AND ADAPTIVE SUBTRACTION
YANWEI XUEYANWEI XUE
University of UtahUniversity of Utah
OutlineOutline
• Surface Wave Problem & RemedySurface Wave Problem & Remedy• Theory of Interferometric FilteringTheory of Interferometric Filtering• 2D Field Data Results2D Field Data Results• 3D Field Data Results3D Field Data Results• ConclusionsConclusions
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A seismogram with surface waves and reflectionsA seismogram with surface waves and reflections
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Problem: Surface waves blur the Problem: Surface waves blur the
seismograms.seismograms.
dd surfsurf
Surface Surface waveswaves
== ++ dd refref
Reflection Reflection
waveswaves
Solution: Filter the surface waves by Non-Solution: Filter the surface waves by Non-Linear Filter (NLF) and interferometric Linear Filter (NLF) and interferometric methodmethod
OutlineOutline
• Surface Wave Problem & RemedySurface Wave Problem & Remedy• Theory of Interferometric PredictionTheory of Interferometric Prediction• 2D Field Data Results2D Field Data Results• 3D Field Data Results3D Field Data Results• ConclusionsConclusions
Prediction of Surface WavesPrediction of Surface WavesNear-OffsetNear-OffsetSurf. WaveSurf. Wave
A B
Mid-OffsetMid-OffsetSurf. Wave Surf. Wave
A B
Near-OffsetNear-OffsetSurf. Wave Surf. Wave
A B
A BA B A B
A B
Basic StrategyBasic Strategy
Surface waves are Surface waves are removed completely?removed completely?NoNo
Input data Input data dd
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Output Output data data
YesYes
rr
Interferometric predictionInterferometric prediction
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ss ddLeast squares Least squares subtractionsubtraction
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Nonlinear Local FilterNonlinear Local Filter
OutlineOutline
• Surface Wave Problem & RemedySurface Wave Problem & Remedy• Theory of Interferometric FilteringTheory of Interferometric Filtering• 2D Field Data Results2D Field Data Results• 3D Field Data Results3D Field Data Results• ConclusionsConclusions
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Raw DataRaw Data
Remove Surface Waves by NLF Remove Surface Waves by NLF
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Remove Surface Waves by Int.+NLFRemove Surface Waves by Int.+NLF
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Raw DataRaw Data
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Remove Surface Waves by F-KRemove Surface Waves by F-K
Remove Surface Waves by Int.+NLFRemove Surface Waves by Int.+NLF
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Surface Waves Predicted by F-KSurface Waves Predicted by F-K
Surface Waves Predicted by Int.+NLFSurface Waves Predicted by Int.+NLF
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OutlineOutline
• Surface Wave Problem & RemedySurface Wave Problem & Remedy• Theory of Interferometric FilteringTheory of Interferometric Filtering• 2D Field Data Results2D Field Data Results• 3D Field Data Results3D Field Data Results• ConclusionsConclusions
Line 9 Before and After Removal of Surface WavesLine 9 Before and After Removal of Surface Waves
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Line 11 Before and After Removal of Surface WavesLine 11 Before and After Removal of Surface Waves
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Line 13 Before and After Removal of Surface WavesLine 13 Before and After Removal of Surface Waves
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OutlineOutline
• Surface Wave Problem & RemedySurface Wave Problem & Remedy• Theory of Interferometric FilteringTheory of Interferometric Filtering• 2D Field Data Results2D Field Data Results• 3D Field Data Results3D Field Data Results• ConclusionsConclusions
ConclusionsConclusions
•This approach is effective for surface wave removal in both 2D and This approach is effective for surface wave removal in both 2D and 3D cases.3D cases.
•Advantages:Advantages:
•Limitations:Limitations:
•Better than FK method for irregular acquisition geometry.Better than FK method for irregular acquisition geometry.•No need for a near surface velocity model.No need for a near surface velocity model.
•Sensitive to the choice of NLF parameters.Sensitive to the choice of NLF parameters.•Parameter selection can be expensive.Parameter selection can be expensive.
•Future Work:Future Work:•Eliminate need for non-linear local filter.Eliminate need for non-linear local filter.•More tests on 3D data.More tests on 3D data.
AcknowledgementAcknowledgement
I thank the sponsors of 2006 UTAM consortium for their financial support.
THANKS!THANKS!