surface wave prediction and subtraction by interferometry + deconvolution
DESCRIPTION
Surface Wave Prediction and Subtraction by Interferometry + Deconvolution. Yanwei Xue Feb. 7, 2008. Outline. Motivation 2D Interferometry + Deconvolution Theory and Field Data Test 3D Proposed Algorithm and Field Data Test Conclusions & the Road Ahead. Motivation. - PowerPoint PPT PresentationTRANSCRIPT
Surface Wave Prediction and Subtraction Surface Wave Prediction and Subtraction by Interferometry + Deconvolutionby Interferometry + Deconvolution
Yanwei XueYanwei Xue
Feb. 7, 2008Feb. 7, 2008
OutlineOutline
MotivationMotivation 2D Interferometry + Deconvolution Theory and 2D Interferometry + Deconvolution Theory and
Field Data TestField Data Test 3D Proposed Algorithm and Field Data Test3D Proposed Algorithm and Field Data Test Conclusions & the Road AheadConclusions & the Road Ahead
MotivationMotivation
ProblemProblem:: Find a better way to predict and rem Find a better way to predict and remove surface waves by interferometryove surface waves by interferometry
Solution:Solution: Inteferometry + DeconvolutionInteferometry + Deconvolution
Background:Background:
Interferometric Prediction (Dong, 2005)Interferometric Prediction (Dong, 2005)
Interferometry + NLF prediction (Xue, 2006) Interferometry + NLF prediction (Xue, 2006)
OutlineOutline
MotivationMotivation 2D Interferometry + Deconvolution Theory and 2D Interferometry + Deconvolution Theory and
Field Data TestField Data Test 3D Proposed Algorithm and Field Data Test3D Proposed Algorithm and Field Data Test Conclusions & the Road AheadConclusions & the Road Ahead
U(s|g,ω)= W(s,U(s|g,ω)= W(s,ωω)G(s|g))G(s|g)
gg g’g’
u(g,g’)u(g,g’)
2D Interferometric Surface Wave Prediction2D Interferometric Surface Wave Predictionu (s,g)u (s,g) u (s,g’)u (s,g’)
g’g’SS
gg
C(g |g’,ω)C(g |g’,ω)=|W(s,ω)| G(g|g’)=|W(s,ω)| G(g|g’)Using crosscorrelation
D(g |g’)D(g |g’)= G(g|g’)= G(g|g’)Using deconvolution
U(g|g’,ω)= D(g|g’)U(g|g’,ω)= D(g|g’)W(s,ω)W(s,ω)
U(s|g’,ω)= W(s,U(s|g’,ω)= W(s,ωω)G(s|g’))G(s|g’)
Basic workflowBasic workflowWindow the surface
waves outInput data d
Interferometry + Deconvolution prediction
G
Source wavelet Predicted
d^
Least squares subtraction
d= min || d – d ||^ 2^̂
Surface waves removed completely?
Output data d̂
yes
d = d^̂
no
0
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Original Data Interferometric prediction of 1st Iteration
2D Field Data Test2D Field Data Test
Raw Data vs 1st Prediction
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Result after 1st IterationOriginal Data
Raw Data vs 1st Removal
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Result after 3rd IterationResult after 1st Iteration
3rd Removal vs 1st Removal
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Result after 3rd IterationOriginal Data
Raw Data vs 3Raw Data vs 3rdrd Removal Removal
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Surface Waves RemovedOriginal Data
Raw Data vs Removed SW
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Result of Interferometry+ NLF
Result of Interferometry+ Deconvolution
Interferometry + Deconvolution vs Interferometry + NLF
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Surface Waves Removed
by Interferometry + NLF
Surface Waves Removed by Interferometry + Deconvolution
SW by Interferometry + Deconvolution vs by Interferometry + NLF
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OutlineOutline
MotivationMotivation 2D Interferometry + Deconvolution Theory and 2D Interferometry + Deconvolution Theory and
Field Data TestField Data Test 3D Proposed Algorithm and Field Data Test3D Proposed Algorithm and Field Data Test Conclusions & the Road AheadConclusions & the Road Ahead
S2
S1
S3
Challenge for 3D ExtensionChallenge for 3D Extension
l1
l2
l3
l1
l2
2D: l2 - l1 = l3
3D: l2 - l1 < l3
Proposed 3D InterferometryProposed 3D Interferometry
S1
S2
S3
Physical Meaning Physical Meaning
z z
3D Test with CREWES Field Data 3D Test with CREWES Field Data 0
40000 4000X (m)
Y (
m)
Acquisition Geometry
Inline: 60 m
Crossline: 260 m
Source Interval
Total 708 Shots
Inline: 60 m
Crossline: 260 m
Receiver Interval
42 receivers per line
Interferometric Test of Line 40
2.00 2500X
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Original predicted
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Interferometric Test of Line 2
predictedOriginal
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Interferometric Test of Line 1
Original predicted
OutlineOutline
MotivationMotivation 2D Interferometry + Deconvolution Theory and 2D Interferometry + Deconvolution Theory and
Field Data TestField Data Test 3D Proposed Algorithm and Field Data Test3D Proposed Algorithm and Field Data Test Conclusions & the Road AheadConclusions & the Road Ahead
SummarySummary I developed and tested a 2D nterferometry + Deconvolution prediction scheme for surface wave removal
I proposed and tested a 3D extension of this workflow , but did not get the expected result.
Results of Interferometry + Deconvolution were compared with the results of Interferometry + NLF
The Road AheadThe Road Ahead
Improve the ability of Interferometry + Deconvolution to separate noise from signal
Use a denser data set to improve our 3D test
Thanks!