Interferometric Prediction and Interferometric Prediction and Least Squares Subtraction of Least Squares Subtraction of

Surface WavesSurface Waves

Shuqian Dong and Ruiqing HeShuqian Dong and Ruiqing He

University of UtahUniversity of Utah

OUTLINEOUTLINE

Motivation: Surface Wave FilteringMotivation: Surface Wave Filtering

Interfer. Surface Wave TheoryInterfer. Surface Wave Theory

ConclusionsConclusions

Land Field Data TestLand Field Data Test

OUTLINEOUTLINE

Motivation: Surface Wave FilteringMotivation: Surface Wave Filtering

Interfer. Surface Wave TheoryInterfer. Surface Wave Theory

ConclusionsConclusions

Land Field Data TestLand Field Data Test

MotivationMotivation

Problem:Problem:

Surface waves = strong coherent Surface waves = strong coherent

noise blurs seismogramnoise blurs seismogram. . Moveout-Moveout-based filtering not always effective for based filtering not always effective for dispersive waves.dispersive waves.

Solution:Solution:

Interfer. Predict. + Least Squares Interfer. Predict. + Least Squares Subtraction. Accounts for dispersion.Subtraction. Accounts for dispersion.

Offset (m)Offset (m)T

ime

(s)

Tim

e (s

)00

1.01.0

00

72007200

A CSG with Strong Surface WavesA CSG with Strong Surface Waves

Offset (m)Offset (m)T

ime

(s)

Tim

e (s

)00

1.01.0

00

72007200

A CSG with Strong Surface WavesA CSG with Strong Surface Waves

OUTLINEOUTLINE

Motivation: Surface Wave FilteringMotivation: Surface Wave Filtering

Interfer. Surface Wave TheoryInterfer. Surface Wave Theory

ConclusionsConclusions

Land Field Data TestLand Field Data Test

Prediction of multiples by convolution (SRME)Prediction of multiples by convolution (SRME)

Prediction of Primaries by Crosscorrelation (Interferometry)Prediction of Primaries by Crosscorrelation (Interferometry)

AA BB CC AA BB

**⊕⊕

BB CC

u (s,g’)= A(s,g’)u (s,g’)= A(s,g’)eeikxikxsg’sg’

u (s,g)= A(s,g)u (s,g)= A(s,g) eeikxikxsgsg

u (s,g)u (s,g) u (s,g’)u (s,g’)

gg g’g’

u(g,g’)u(g,g’)u(g,g’)u(g,g’)

⊕⊕== u (s,g)u (s,g)u (s,g’)u (s,g’) **

eeik(xik(xSg’Sg’==A(s,g)A(s,g) A(s,g’)A(s,g’)

-x-xsgsg))

Predict Surface Waves by CrosscorrelationPredict Surface Waves by Crosscorrelation

⊕⊕g’g’SS

gg

} xxgg’gg’

ττ

ττ

A B C A B⊕⊕

B C⊕⊕

B C

++A’ B C A’ B

Predict Surface Waves by CrosscorrelationPredict Surface Waves by Crosscorrelation

Coherent Stacking: surface waves (all src pts = stationary)Coherent Stacking: surface waves (all src pts = stationary)

SSgg g’g’

11

gg g’g’

SS22SSNN ……

Incoherent Stacking: primariesIncoherent Stacking: primaries

Coherent Stacking: FS Multiples?Coherent Stacking: FS Multiples? Avoid stationary source pointsAvoid stationary source points

⊕⊕

Surface Waves PredictionSurface Waves PredictionOffset (m)Offset (m)

Tim

e (s

)T

ime

(s)

00

2.02.0

00 36003600

Original DataOriginal Data

3600360000

Tim

e (s

)T

ime

(s)

00

2.02.0

Offset (m)Offset (m)

Predcted Surface WavesPredcted Surface Waves

00 Time (s)Time (s) 2.02.0

Am

pli

tud

eA

mp

litu

de

-1-1

11

00

Least Square Matching FilterLeast Square Matching Filter

dd (t)(t)Refl.Refl. Surf.Surf.

== dd (t)(t) dd (t)(t)++

Pred.Pred.

≈≈dd (t)(t) ** ff (t)(t)dd (t)(t)Refl.Refl.

dd (t)(t)--

-- **ff (t)(t) ==

Surface Waves Filtering ResultsSurface Waves Filtering ResultsT

ime

(s)

Tim

e (s

)

00

2.02.0Offset (m)Offset (m)00 72007200 Offset (m)Offset (m)00 72007200

Tim

e (s

)T

ime

(s)

00

2.02.0

Original DataOriginal Data Filtered DataFiltered Data

Tim

e (s

)T

ime

(s)

00

2.02.0

Tim

e (s

)T

ime

(s)

00

2.02.0Offset (m)Offset (m)00 72007200 Offset (m)Offset (m)00 72007200

Results of f-k methodResults of f-k method Results of interferometric methodResults of interferometric method

Result ComparisonResult Comparison

ConclusionsConclusions

Preliminary results promising for interfer. Preliminary results promising for interfer. Prediction + subtraction surface waves.Prediction + subtraction surface waves.

Future work: iterative prediction + Future work: iterative prediction + subtraction.subtraction.

Can Interferometric Prediction+Subtraction Can Interferometric Prediction+Subtraction work for Irregular 3D Arrays? work for Irregular 3D Arrays?

Answer?:Answer?:Irregular S. Calif. Earthquake ArrayIrregular S. Calif. Earthquake Array

StationsStations

(Andrew Curtis, The Leading Edge, 2006)(Andrew Curtis, The Leading Edge, 2006)

Predicted SurfacePredicted SurfaceWavesWaves

Sta

tio

n O

ffs

et

(km

)S

tati

on

Off

se

t (k

m)

Time (s)Time (s)LongitudeLongitude120 W120 W 115 W115 W

32

N3

2 N

La

titu

de

La

titu

de

38

N3

8 N

Predicted Surface WavesPredicted Surface Waves

-200-200 200200

004

00400

AcknowledgementsAcknowledgements

We thank the UTAM sponsors for the We thank the UTAM sponsors for the support of the research.support of the research.

ThanksThanks