Selecting Robust Parameters for Migration Deconvolution University of Utah Jianhua Yu.

Selecting Robust Parameters for Selecting Robust Parameters for

Migration DeconvolutionMigration Deconvolution

University of Utah University of Utah

Jianhua Yu Jianhua Yu

Problem and Goal

OutlineOutline

Main parameter selectionExamples Conclusions

2-D Poststack MIG (Unocal)2-D Poststack MIG (Unocal)0.6

Dep

th (

km

)

MDMD

2.8

00

3 km3 km

00

3-D Point Scatterer Model

3 km3 km

X (km)

Am

plit

ud

e

10 3 0Y (km)

MDMIGX (km)0 3 0Y (km)

1 km

3 km

5 km

Depth Slides

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

Problem:Problem:

Improving the stability of MDAlgorithm

Developed a stable MD filter

Solution:Solution:

Unstable MD at some data sets

OutlineOutline


Problem and Goal

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

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)

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

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

OutlineOutline


Problem and Goal

00

3 km3 km

00


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

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

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


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


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)

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)

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


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

OutlineOutline

Main parameter selectionExamples: 2-D Meandering Model

Conclusions

Problem and Goal

00

3 km3 km

00


3 km3 km

Source: 5X5 Receiver: 21X 21Source: 5X5 Receiver: 21X 21

Model

Meandering Stream ModelPSDM Image MD

OutlineOutline

Main parameter selectionExamples: 2-D marine data

Conclusions

Problem and Goal

Poststack MIG from UnocalPoststack MIG from Unocal0.6D

epth

(k

m)

MDMD

2.8

MDMD0.6D

epth

(k

m)

MDMD

2.8

MIGMIG0.6D

epth

(k

m)

MDMD

2.8

P-P PSTM by UnocalP-P PSTM by Unocal

0.5

5

Tim

e (s

)

MDMD

MIGMIG MDMD

0.5

5

Tim

e (s

)

MIGMIG

Tim

e (s

)

MDMD

OutlineOutline

Main parameter selectionExamples2-D PS marine data Conclusions

Problem and Goal

PS PSTM Image ( by Unocal)PS PSTM Image ( by Unocal)

0 6X (km)

0

8

Tim

e (s

)

0 6X (km)

0

8

Tim

e (s

)

MDMDPSTMPSTM PSTMDPSTMD

OutlineOutline

Main parameter selectionExamples 2-D Land data Conclusions

Problem and Goal

MD

Tim

e (s

)Mig

Tim

e (s

)

OutlineOutline

Main parameter selectionExamples 3-D SEG/EAGE data Conclusions

Problem and Goal

3-D SEG/EAGE Salt Model

1.0-1.4 km

MD (z=1 km)Mig (z=1 km)X (km)

3

10

Y (

km

)

5 9.8 5 9.8X (km)

Problem and Goal

OutlineOutline


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

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

Selecting Robust Parameters for Migration Deconvolution University of Utah Jianhua Yu.

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