Transcript Document

Interferometric Prediction and
Least Squares Subtraction of
Surface Waves
Shuqian Dong and Ruiqing He
University of Utah
OUTLINE
Motivation: Surface Wave Filtering
Interfer. Surface Wave Theory
Land Field Data Test
Conclusions
OUTLINE
Motivation: Surface Wave Filtering
Interfer. Surface Wave Theory
Land Field Data Test
Conclusions
Motivation
A CSG with Strong Surface Waves
Surface waves = strong coherent
noise blurs seismogram. Moveoutbased filtering not always effective for
dispersive waves.
0
Time (s)
Problem:
Solution:
Interfer. Predict. + Least Squares
Subtraction. Accounts for dispersion.
1.0
0
Offset (m)
7200
OUTLINE
Motivation: Surface Wave Filtering
Interfer. Surface Wave Theory
Land Field Data Test
Conclusions
Prediction of multiples by convolution (SRME)
*
Prediction of Primaries by Crosscorrelation (Interferometry)
A
B
C
A
B
B
C
Predict Surface Waves by Crosscorrelation
u (s,g’)
u (s,g)
u (s,g)= A(s,g)
e
ikx
e
ikx
sg
τ
g’
u (s,g’)= A(s,g’)
x
u(g,g’)
u(g,g’) = u (s,g’) u *(s,g)
τ
g
g’
sg’
= A(s,g) A(s,g’)
e
gg’
}
S
g
ik(x -x sg )
Sg’
Predict Surface Waves by Crosscorrelation
A
B
C
A
B
B
C
+
A’
B
C
A’
B
B
C
Coherent Stacking: surface waves (all src pts = stationary)
Incoherent Stacking: primaries
SN
…
S2
S1
g
g’
g
 Coherent Stacking: FS Multiples?
Avoid stationary source points
g’
Surface Waves Prediction
0
Offset (m)
3600
0
2.0
2.0
Original Data
Amplitude
Offset (m)
3600
Time (s)
Time (s)
0
0
Predcted Surface Waves
1
0
-1
0
Time (s)
2.0
Least Square Matching Filter
d (t)
d
=
Refl.
(t) + d
Surf.
(t)
Pred.
d (t) - d
-
(t) * f (t)
≈ d
Refl.
* f (t) =
(t)
Surface Waves Filtering Results
Original Data
Filtered Data
Time (s)
0
Time (s)
0
2.0
2.0
0
Offset (m)
7200
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Offset (m)
7200
Result Comparison
Results of f-k method
Results of interferometric method
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Time (s)
Time (s)
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2.0
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2.0
Offset (m)
7200
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Offset (m)
7200
Conclusions
Preliminary results promising for interfer.
Prediction + subtraction surface waves.
Future work: iterative prediction +
subtraction.
Can Interferometric Prediction+Subtraction
work for Irregular 3D Arrays?
Answer?:
Station Offset (km)
Predicted Surface
Waves
0
32 N
Latitude
Stations
120 W Longitude
Predicted Surface Waves
400
38 N
Irregular S. Calif. Earthquake Array
115 W
(Andrew Curtis, The Leading Edge, 2006)
-200
Time (s)
200
Acknowledgements
We thank the UTAM sponsors for the
support of the research.
Thanks