crosscorrelation migration of free-surface multiples in rvsp data jianming sheng university of utah...
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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.