Crosscorrelation Migration Crosscorrelation Migration of Free-Surface Multiples of Free-Surface Multiples

in RVSP Datain RVSP Data

Jianming ShengJianming Sheng

University of UtahUniversity of UtahFebruary, 2001February, 2001

OutlineOutline• ObjectiveObjective

• Crosscorrelation migrationCrosscorrelation migration

• Numerical examplesNumerical examples

• SummarySummary

ObjectiveObjectiveValidate the feasibility of Validate the feasibility of crosscorrelation migration crosscorrelation migration for RVSP data; for RVSP data;

Image the reflectivity Image the reflectivity distribution without distribution without knowing the source position.knowing the source position.

(Schuster and Rickett, 2000)(Schuster and Rickett, 2000)

OutlineOutline• ObjectiveObjective

• Crosscorrelation migrationCrosscorrelation migration

• Numerical examplesNumerical examples

• SummarySummary

Crosscorrelation MigrationCrosscorrelation Migration

PrinciplePrinciple

Asymptotic analysisAsymptotic analysis

Key stepsKey steps

Principle of CCMPrinciple of CCM

S

G’ G

X

''

SGiedG XGXGSGi

G ed ''

*'* GG dd 'GG

CrosscorrelogramCrosscorrelogram

''' SGXGXGSGie

Principle of CCMPrinciple of CCM

S

G’ G

X

Virtual Virtual sourcesource xm

xGxGie '

Imaging conditionImaging condition

Asymptotic AnalysisAsymptotic Analysis

xm

Migration imageMigration image

Trial image pointTrial image point

xGxGGG '''G

G

S

CrosscorrelogramsCrosscorrelograms

Asymptotic AnalysisAsymptotic Analysis

xmUnder stationary phase conditionUnder stationary phase condition

DDirectirect GGhosthost

Negligible contribution from:Negligible contribution from:

DDirectirect DDirectirect

Contribution from:Contribution from:

GGhosthost GGhosthost

Contribution from:Contribution from:

GGhosthost DDirectirect

...R ...2RReflection coefficientReflection coefficient

Asymptotic AnalysisAsymptotic Analysis

xm ...RCCM image gives the reflectivity CCM image gives the reflectivity distribution except contaminated distribution except contaminated by artifacts up to orderby artifacts up to order 2R

Key Steps of CCMKey Steps of CCMStep 1: Bandpass filter and other preprocess;Step 1: Bandpass filter and other preprocess;

Step 2: Dip filter;Step 2: Dip filter;

Step 5: Migrate the crosscorrelograms.Step 5: Migrate the crosscorrelograms.

Step 3: Generate crosscorrelograms;Step 3: Generate crosscorrelograms;

Step 4: Filter aliasing in crosscorrelograms;Step 4: Filter aliasing in crosscorrelograms;

OutlineOutline• ObjectiveObjective

• Crosscorrelation migrationCrosscorrelation migration

• Numerical examplesNumerical examples

• SummarySummary

Numerical ExamplesNumerical Examples

• Three-layered modelThree-layered model

• Exxon’s Friendswood RVSP Exxon’s Friendswood RVSP

datadata

RECEIVERS

91.4 m

182.8 m

V1 = 762 m/s

V3 = 1372 m/s

V2 = 1067 m/s

SOURCES

Three-Layered ModelThree-Layered Model

98 shots98 shots24 traces 24 traces per shotper shot

1st-CRG1st-CRG

0 150 300 0 150 300 Depth (m)Depth (m)

0 150 0 150 300 300 Depth (m)Depth (m)

00

0.80.8

0.60.6

0.20.2

0.40.4

00

0.80.8

0.60.6

0.20.2

0.40.4

Tim

e (s

ec.)

Tim

e (s

ec.)

Dip-filteredDip-filteredBefore dip-filteredBefore dip-filtered

DirectDirect

PrimaryPrimary

GhostGhost

1st-CSG1st-CSG

00

0.80.8

0.60.6

0.20.2

0.40.4

Tim

e (s

ec.)

Tim

e (s

ec.)

00

0.80.8

0.60.6

0.20.2

0.40.4

Tim

e (s

ec.)

Tim

e (s

ec.)

0 60 120 1800 60 120 180 0 60 120 1800 60 120 180Offset (m)Offset (m) Offset (m)Offset (m)

Shot GatherShot Gather CrosscorrelogramCrosscorrelogramPseudo-Shot GatherPseudo-Shot Gather

DD

GG

High-order GhostHigh-order Ghost

Crosscorrelation migration imageCrosscorrelation migration image

0 90 1800 90 180Offset (m)Offset (m)

00

150150

300300

Dep

th (

m)

Dep

th (

m)

True ReflectorsTrue Reflectors

RECEIVERS

SOURCES

Exxon’s Friendswood RVSP DataExxon’s Friendswood RVSP Data

98 shots98 shots23 traces 23 traces per shotper shot

9.1 m9.1 m

304.8 m304.8 m

7.6 m7.6 m 365.7 m365.7 m

Exxon’s Friendswood RVSP DataExxon’s Friendswood RVSP Data00

200200

300300

Dep

th (

m)

Dep

th (

m)

100100

ReflectivityReflectivityWell-logWell-log CCMCCM

Exxon’s Friendswood RVSP DataExxon’s Friendswood RVSP Data

00

180180

360360

00 1212 2424Offset (m)Offset (m)

Dep

th (

m)

Dep

th (

m)

CCM imageCCM image

OutlineOutline• ObjectiveObjective

• Crosscorrelation migrationCrosscorrelation migration

• Numerical examplesNumerical examples

• SummarySummary

SummarySummary• Asymptotic analysis shows that CCM is capable Asymptotic analysis shows that CCM is capable

of imaging the reflectivity distribution;of imaging the reflectivity distribution;

• The results of synthetic and Exxon’s The results of synthetic and Exxon’s

Friendswood RVSP data validate the Friendswood RVSP data validate the

feasibility of CCM.feasibility of CCM.

Further WorkFurther Work• To attenuate the artifacts generated by To attenuate the artifacts generated by

CCM;CCM;

• To deal with the amplitude preservation To deal with the amplitude preservation

problem.problem.

AcknowledgmentAcknowledgment

I thank the sponsors of the 2000 University I thank the sponsors of the 2000 University of Utah Tomography and Modeling of Utah Tomography and Modeling /Migration (UTAM) Consortium for their /Migration (UTAM) Consortium for their financial support .financial support .