selecting robust parameters for migration deconvolution
DESCRIPTION
Selecting Robust Parameters for Migration Deconvolution. Jianhua Yu. University of Utah. Outline. Problem and Goal. Main parameter selection. Examples. Conclusions. 0.6. MD. 2-D Poststack MIG (Unocal). Depth (km). 2.8. 3-D Point Scatterer Model. 3 km. 3 km. 0. 0. Depth Slides. - PowerPoint PPT PresentationTRANSCRIPT
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Selecting Robust Parameters for Selecting Robust Parameters for
Migration DeconvolutionMigration Deconvolution
University of Utah University of Utah
Jianhua Yu Jianhua Yu
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Problem and Goal
OutlineOutline
Main parameter selectionExamples Conclusions
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2-D Poststack MIG (Unocal)2-D Poststack MIG (Unocal)0.6
Dep
th (
km
)
MDMD
2.8
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00
3 km3 km
00
3-D Point Scatterer Model
3 km3 km
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X (km)
Am
plit
ud
e
10 3 0Y (km)
MDMIGX (km)0 3 0Y (km)
1 km
3 km
5 km
Depth Slides
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X (km)
Am
plit
ud
e
0 3 0Y (km)MDMIG
X (km)0 3 0Y (km)
7 km
9 km
10 km
Depth Slides
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Problem:Problem:
Improving the stability of MDAlgorithm
Developed a stable MD filter
Solution:Solution:
Unstable MD at some data sets
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OutlineOutline
Main parameter selectionExamples Conclusions
Problem and Goal
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Prestack Migration DeconvolutionPrestack Migration Deconvolution
ReflectivityReflectivityMigrated SectionMigrated Section
MD is to eliminate this blurring influence in migration image by designing MD operator F
TTMM = = L LL L RRMig:Mig:
F= (L L )TT -1-1
RR = F = F MMMD:MD:
Blurring Blurring operatoroperator
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PSMD algorithm:PSMD algorithm:
Calculating migration Green’s function with geometry, velocity, and depth level
Inverted MD fiter by inversion
End of loop on iz
Velocity cube
For iz=1, nz (depth or time slice)
Migrated cube
Define the MD filter lengthMD filter length
Aperture width variation along the depth
Inversion algorithm-regularization (Hu, 2001)
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Depth Level Depth Level ii
N
CDP
Dep
th (
km
)
L
L
N: MD filtering length L: Aperture width parameter
Depth Level Depth Level 11
L
Depth Level Depth Level NN
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Improved PSMD algorithm:Improved PSMD algorithm:
End of loop on iz
For iz=1, nz (depth or time slice)
Define the MD filter length
Calculating migration Green’s function with the varied aperture width along the depth and associated with geometry, velocity
Inverted MD filter by inversion and applied to the migrated image
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OutlineOutline
Main parameter selectionExamples Conclusions
Problem and Goal
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00
3 km3 km
00
3-D Point Scatterer Model
3 km3 km
11 X 11 Receivers11 X 11 Receivers
Imaging: dx=dy=50 m
dz=100 m
3X3 Sources; 3X3 Sources;
10 k
m
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0
3 X (km)03
Y (km)0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
MIG MD
Z=1 km
Z=3 km
Z=5 km
Depth SlicesDepth Slices
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0
3 X (km)03
Y (km)0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
MIG MD
Z=7 km
Z=9 km
Z=10 km
Depth SlicesDepth Slices
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0
3 X (km)03
Y (km)0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
MIG MD(new)
Z=7 km
Z=9 km
Z=10 km
Depth SlicesDepth Slices
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Z=1 km
Z=3 km
Z=5 km
Ky
Kx
Ky
Kx
Ky
Kx
Ky
Kx
Ky
Kx
Ky
Kx
Spectrum of Green’s function (New)Spectrum of Green’s function (Old)
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Z=7 km
Z=9 km
Z=10 km
Ky
Kx
Ky
Kx
Ky
Kx
Ky
Kx
Ky
Kx
Ky
Kx
Spectrum of Green’s function (New)Spectrum of Green’s function (Old)
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0
3 X (km)03
Y (km)0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
MD MD (new)
Z=1 km
Z=3 km
Z=5 km
Depth SlicesDepth Slices
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0
3 X (km)03
Y (km)0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
0
3 X (km)03
Y (km)
Z=7 km
Z=9 km
Z=10 km
MD MD (new)Depth SlicesDepth Slices
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OutlineOutline
Main parameter selectionExamples: 2-D Meandering Model
Conclusions
Problem and Goal
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00
3 km3 km
00
3-D Point Scatterer Model
3 km3 km
Source: 5X5 Receiver: 21X 21Source: 5X5 Receiver: 21X 21
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Model
Meandering Stream ModelPSDM Image MD
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OutlineOutline
Main parameter selectionExamples: 2-D marine data
Conclusions
Problem and Goal
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Poststack MIG from UnocalPoststack MIG from Unocal0.6D
epth
(k
m)
MDMD
2.8
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MDMD0.6D
epth
(k
m)
MDMD
2.8
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MIGMIG0.6D
epth
(k
m)
MDMD
2.8
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P-P PSTM by UnocalP-P PSTM by Unocal
0.5
5
Tim
e (s
)
MDMD
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MIGMIG MDMD
0.5
5
Tim
e (s
)
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MIGMIG
Tim
e (s
)
MDMD
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OutlineOutline
Main parameter selectionExamples2-D PS marine data Conclusions
Problem and Goal
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PS PSTM Image ( by Unocal)PS PSTM Image ( by Unocal)
0 6X (km)
0
8
Tim
e (s
)
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0 6X (km)
0
8
Tim
e (s
)
MDMDPSTMPSTM PSTMDPSTMD
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0 6X (km)
0
8
Tim
e (s
)
MDMDPSTMPSTM PSTMDPSTMD
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OutlineOutline
Main parameter selectionExamples 2-D Land data Conclusions
Problem and Goal
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MD
Tim
e (s
)Mig
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Tim
e (s
)
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OutlineOutline
Main parameter selectionExamples 3-D SEG/EAGE data Conclusions
Problem and Goal
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3-D SEG/EAGE Salt Model
1.0-1.4 km
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MD (z=1 km)Mig (z=1 km)X (km)
3
10
Y (
km
)
5 9.8 5 9.8X (km)
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Problem and Goal
OutlineOutline
Main parameter selectionExamples Conclusions
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ConclusionsConclusions
Filter length N=5-11; Parameter that controls aperture width ranges from 0.005-0.04.
Varied aperture width in MD with thedepth improved the stability of MD
Aperture width and filter length in designing MD filter are two key parameters
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AcknowledgmentsAcknowledgments• Thank Thank Alan Leeds Alan Leeds for his constructive for his constructive
suggestions and providing challenging data to suggestions and providing challenging data to test our MD in Chevron.test our MD in Chevron.
• Thank 2002 UTAM sponsors for their Thank 2002 UTAM sponsors for their financial supportfinancial support
• Thank Thank Aramco, ChevronTaxco, and Aramco, ChevronTaxco, and Unocal Unocal for providing the data setsfor providing the data sets