applications of time-domain multiscale waveform tomography to marine and land data c. boonyasiriwat...

Applications of Time-DomainApplications of Time-DomainMultiscale Waveform TomographyMultiscale Waveform Tomography

to Marine and Land Datato Marine and Land Data

C. BoonyasiriwatC. Boonyasiriwat11, J. Sheng, J. Sheng33, P. Valasek, P. Valasek22, P. , P. RouthRouth22, B. Macy, B. Macy22, W. Cao, W. Cao11, and G.T. Schuster, and G.T. Schuster11

11 Department of Geology and Geophysics, University of Utah Department of Geology and Geophysics, University of Utah22 Seismic Technology Development, ConocoPhillips Seismic Technology Development, ConocoPhillips33 Formerly University of Utah, Currently at Nexus Geoscience Formerly University of Utah, Currently at Nexus Geoscience

OutlineOutline

1

• IntroductionIntroduction

• Time-domain multiscale waveform tomographyTime-domain multiscale waveform tomography

• Processing workflowProcessing workflow

• Field data results:Field data results:

• Gulf of MexicoGulf of Mexico

• Saudi ArabiaSaudi Arabia

• SummarySummary

Waveform TomographyWaveform Tomography

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• Wave-equation based model building technique.Wave-equation based model building technique.

00

44 Dep

th (

km)

Dep

th (

km)

00 1616Horizontal Position (km)Horizontal Position (km)

45004500

10001000

Reconstructed VReconstructed Vpp Velocity Model Velocity Model

True VTrue Vpp Velocity of Marmousi II Model Velocity of Marmousi II Model

45004500

10001000

00

44 Dep

th (

km)

Dep

th (

km)

Boonyasiriwat et al., 2008Boonyasiriwat et al., 2008

Problem and SolutionProblem and Solution

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Problem:Problem:

Find a velocity model from seismic data that minimizes the data residual

Proposed Solution:Proposed Solution:

- Use a gradient-based method

- Use a multiscale method in X-T domain

2

calcobs PP

Observed Wavefield

Waveform TomographyWaveform Tomography

obsP

TrueVelocity

Calculated Wavefield calcP

InitialVelocity

Velocity Update

Wavefield Residualcalcobs PP

Iterate until wavefieldresidual is small

4

OutlineOutline

5

• IntroductionIntroduction

• Time-domain multiscale waveform tomographyTime-domain multiscale waveform tomography

• Processing workflowProcessing workflow

• Field data results:Field data results:

• Gulf of MexicoGulf of Mexico

• Saudi ArabiaSaudi Arabia

• SummarySummary

Why Use Multiscale?Why Use Multiscale?

Low Frequency

High Frequency

Coarse Scale

Fine Scale

Image from Bunks et al. (1995)

Model parameter (m)

Mis

fit f

unct

ion

( f )

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Multiscale Waveform TomographyMultiscale Waveform TomographyMultiscale Waveform TomographyMultiscale Waveform Tomography

1. Collect data d(x,t)1. Collect data d(x,t)

2. Generate synthetic data d(x,t) by FD method2. Generate synthetic data d(x,t) by FD methodsynsyn..

3. Adjust v(x,z) until ||d(x,t)-d(x,t) || minimized by CG.3. Adjust v(x,z) until ||d(x,t)-d(x,t) || minimized by CG.synsyn.. 22

4. To prevent getting stuck in local minima:4. To prevent getting stuck in local minima: a). Invert early arrivals initiallya). Invert early arrivals initially

mute

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b). Use multiscale: low freq. high freq.b). Use multiscale: low freq. high freq.

OutlineOutline

8

• IntroductionIntroduction

• Time-domain multiscale waveform tomographyTime-domain multiscale waveform tomography

• Processing workflowProcessing workflow

• Field data results:Field data results:

• Gulf of MexicoGulf of Mexico

• Saudi ArabiaSaudi Arabia

• SummarySummary

9

Processing WorkflowProcessing Workflow

Pre-Processing of DataPre-Processing of Data

Estimating Source WaveletEstimating Source Wavelet

Generating Initial ModelGenerating Initial Model

Multiscale Waveform TomographyMultiscale Waveform Tomography

Validating Velocity TomogramsValidating Velocity Tomograms

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Processing WorkflowProcessing Workflow

3D-to-2D conversion3D-to-2D conversion

Attenuation compensationAttenuation compensation

Random noise removalRandom noise removal

Pre-Processing of DataPre-Processing of Data

Estimating Source WaveletEstimating Source Wavelet

Generating Initial ModelGenerating Initial Model

Multiscale Waveform TomographyMultiscale Waveform Tomography

Validating Velocity TomogramsValidating Velocity Tomograms

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Processing WorkflowProcessing Workflow

Pre-Processing of DataPre-Processing of Data

Estimating Source WaveletEstimating Source Wavelet

Generating Initial ModelGenerating Initial Model

Multiscale Waveform TomographyMultiscale Waveform Tomography

Validating Velocity TomogramsValidating Velocity Tomograms

Pick the water-bottomPick the water-bottom

Stack along the water-bottomStack along the water-bottom

Generate a stacked sectionGenerate a stacked section

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Processing WorkflowProcessing Workflow

Pre-Processing of DataPre-Processing of Data

Estimating Source WaveletEstimating Source Wavelet

Generating Initial ModelGenerating Initial Model

Multiscale Waveform TomographyMultiscale Waveform Tomography

Validating Velocity TomogramsValidating Velocity Tomograms

Traveltime pickingTraveltime picking

Initial model: RMS velocityInitial model: RMS velocity

Refraction traveltime inversionRefraction traveltime inversion

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Processing WorkflowProcessing Workflow

Pre-Processing of DataPre-Processing of Data

Estimating Source WaveletEstimating Source Wavelet

Generating Initial ModelGenerating Initial Model

Multiscale Waveform TomographyMultiscale Waveform Tomography

Validating Velocity TomogramsValidating Velocity Tomograms

Low-pass filteringLow-pass filtering

Inversion from low- toInversion from low- to

high-frequency bandshigh-frequency bands

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Processing WorkflowProcessing Workflow

Pre-Processing of DataPre-Processing of Data

Estimating Source WaveletEstimating Source Wavelet

Generating Initial ModelGenerating Initial Model

Multiscale Waveform TomographyMultiscale Waveform Tomography

Validating Velocity TomogramsValidating Velocity TomogramsMigration imagesMigration images

Common image gathersCommon image gathers

OutlineOutline

10

• IntroductionIntroduction

• Time-domain multiscale waveform tomographyTime-domain multiscale waveform tomography

• Processing workflowProcessing workflow

• Field data results:Field data results:

• Gulf of MexicoGulf of Mexico

• Saudi ArabiaSaudi Arabia

• SummarySummary

515 Shots480 Hydrophones

12.5 mdt = 2 msTmax = 10 s

1 1.5 2 2.5

0

0.5

1

1.5

2

2.5

3

Offset (km)

Tim

e (s)

b) Original CSG 1

1 1.5 2 2.5

0

0.5

1

1.5

2

2.5

3

Offset (km)Tim

e (s)

a) Virtual CSG 1

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Gulf of Mexico DataGulf of Mexico Data

Low-pass FilteringLow-pass Filtering

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Offset (km)

Tim

e (s)

(a) Original CSG

0 2 4

0

0.5

1

1.5

2

2.5

3

3.5

4

Offset (km)

Tim

e (s)

(b) 5-Hz CSG

0 2 4

0

0.5

1

1.5

2

2.5

3

3.5

4

Offset (km)Tim

e (s)

(c) 10-Hz CSG

0 2 4

0

0.5

1

1.5

2

2.5

3

3.5

4

Reconstructed VelocityReconstructed Velocity

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Velocity (m/s)

Velocity (m/s)

Kirchhoff Migration ImagesKirchhoff Migration Images

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Kirchhoff Migration ImagesKirchhoff Migration Images

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Comparing CIGsComparing CIGs

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Comparing CIGsComparing CIGs

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CIG from Traveltime Tomogram CIG from Waveform Tomogram

Comparing CIGsComparing CIGs

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Comparing CIGsComparing CIGs

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CIG from Traveltime Tomogram CIG from Waveform Tomogram

Comparing CIGsComparing CIGs

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Comparing CIGsComparing CIGs

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CIG from Traveltime Tomogram CIG from Waveform Tomogram

OutlineOutline

21

• IntroductionIntroduction

• Time-domain multiscale waveform tomographyTime-domain multiscale waveform tomography

• Processing workflowProcessing workflow

• Field data results:Field data results:

• Gulf of MexicoGulf of Mexico

• Saudi ArabiaSaudi Arabia

• SummarySummary

Saudi Arabia Land SurveySaudi Arabia Land Survey

0 km0 km

1.6 km1.6 km

X-Coord. (km)X-Coord. (km)00 5050

Y-Coord. (km)Y-Coord. (km)

-3.6-3.6 3.63.6Offset (km)Offset (km)

00

22

Tim

e (s

)T

ime

(s)

100 m100 m

1. 1279 CSGs, 240 traces/gather1. 1279 CSGs, 240 traces/gather

4. Pick 246,000 traveltimes4. Pick 246,000 traveltimes

2. 30 m station interval, 2. 30 m station interval, max. offset = 3.6kmmax. offset = 3.6km

3. Line Length = 46 km3. Line Length = 46 km

5. Traveltime tomography -> V(x,y,z)5. Traveltime tomography -> V(x,y,z)

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Brute Stack SectionBrute Stack Section00

2.02.0

Tim

e (s

)T

ime

(s)

39203920 50705070CDPCDP23

Traveltime Tomostatics + StackingTraveltime Tomostatics + Stacking00

2.02.0

Tim

e (s

)T

ime

(s)

39203920 50705070CDPCDP24

Waveform Tomostatics + StackingWaveform Tomostatics + Stacking00

2.02.0

Tim

e (s

)T

ime

(s)

39203920 50705070CDPCDP25

OutlineOutline

26

• IntroductionIntroduction

• Time-domain multiscale waveform tomographyTime-domain multiscale waveform tomography

• Processing workflowProcessing workflow

• Field data results:Field data results:

• Gulf of MexicoGulf of Mexico

• Saudi ArabiaSaudi Arabia

• SummarySummary

SummarySummaryAcoustic waveform inversion was successfully applied to Acoustic waveform inversion was successfully applied to both marine and land datasets, and can provide accurate both marine and land datasets, and can provide accurate velocity subsurface structures.velocity subsurface structures.

Issues:Issues:• Cost > 100 iterations: How to reduce cost?Cost > 100 iterations: How to reduce cost?• Acoustic vs. Elastic: How far can we go with acoustic?Acoustic vs. Elastic: How far can we go with acoustic?• Anisotropy needed?Anisotropy needed?• Source wavelet important: Source-independent inversion.Source wavelet important: Source-independent inversion.• Missing low frequencies: Better initial model via Missing low frequencies: Better initial model via

reflection tomography.reflection tomography.

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AcknowledgmentAcknowledgment

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We would like to thankWe would like to thank• UTAM sponsors for financial support.UTAM sponsors for financial support.• Amarada Hess and Saudi Aramco for providing Amarada Hess and Saudi Aramco for providing

us the datasets.us the datasets.