74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

A seismic reflection imaging workflow based on

the Common-Reflection-Surface (CRS) stack:

theoretical background and case study

T. Hertweck1 C. Jäger J. Mann*E. Duveneck2 Z. Heilmann

1now: Fugro-Robertson Ltd, Swanley, UK2now: SINTEF Petroleum Research, Trondheim, Norway

Wave Inversion Technology (WIT) ConsortiumGeophysical Institute, University of Karlsruhe (TH)

October 14, 2004

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Overview

Introduction

The project

Data example

Comparison

Conclusions

Acknowledgments

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Seismic imaging

Conventional Processing

e.g. NMO/DMO etc.

Structural Imaging & Further Analysis

Dep

thTi

me Data−driven Processing

e.g. ZO CRS stack

Prestack/Poststack time migration

Velocity updating

Kinematic wavefield

(CRS) attributes

Prestack depth

migration

Poststack depth

migration

Acquisition & Preprocessing

Estimation of macro model

yellow = tools developed at Karlsruhe University

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Seismic imaging

Conventional Processing

e.g. NMO/DMO etc.

Poststack depth

migration

Velocity updating

Kinematic wavefield

(CRS) attributes

Structural Imaging & Further Analysis

Dep

thTi

me Data−driven Processing

e.g. ZO CRS stack

Prestack depth

migration

Prestack/Poststack time migration

Acquisition & Preprocessing

Estimation of macro model

yellow = tools developed at Karlsruhe University

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-Reflection-Surface stack

I Alternative to standard NMO/DMO/stack approach

I Output: zero-offset section (2D) or volume (3D) ofhigh S/N ratio

I Additional output: variety of kinematic wavefieldattributes (so-called CRS attributes)

I Principle: generalized, high-density, multiparameter,multidimensional stacking velocity analysis tool

I Automated coherence-based application

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-Reflection-Surface stack

I Alternative to standard NMO/DMO/stack approach

I Output: zero-offset section (2D) or volume (3D) ofhigh S/N ratio

I Additional output: variety of kinematic wavefieldattributes (so-called CRS attributes)

I Principle: generalized, high-density, multiparameter,multidimensional stacking velocity analysis tool

I Automated coherence-based application

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-Reflection-Surface stack

I Alternative to standard NMO/DMO/stack approach

I Output: zero-offset section (2D) or volume (3D) ofhigh S/N ratio

(from Müller, "The Common Reflection Surface Stack Method", 1999)

I Additional output: variety of kinematic wavefieldattributes (so-called CRS attributes)

I Principle: generalized, high-density, multiparameter,multidimensional stacking velocity analysis tool

I Automated coherence-based application

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-Reflection-Surface stack

I Alternative to standard NMO/DMO/stack approach

I Output: zero-offset section (2D) or volume (3D) ofhigh S/N ratio

I Additional output: variety of kinematic wavefieldattributes (so-called CRS attributes)

I Principle: generalized, high-density, multiparameter,multidimensional stacking velocity analysis tool

I Automated coherence-based application

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-Reflection-Surface stack

I Alternative to standard NMO/DMO/stack approach

I Output: zero-offset section (2D) or volume (3D) ofhigh S/N ratio

I Additional output: variety of kinematic wavefieldattributes (so-called CRS attributes)

I Principle: generalized, high-density, multiparameter,multidimensional stacking velocity analysis tool

I Automated coherence-based application

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-Reflection-Surface stack

I Alternative to standard NMO/DMO/stack approach

I Output: zero-offset section (2D) or volume (3D) ofhigh S/N ratio

I Additional output: variety of kinematic wavefieldattributes (so-called CRS attributes)

I Principle: generalized, high-density, multiparameter,multidimensional stacking velocity analysis tool

I Automated coherence-based application

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Basic concepts

I second-order approximation of reflection events

I spatial stacking operator

I limited number of stacking parameters:first and second spatial derivatives of traveltime

I geometrical interpretation:propagation direction and curvatures of hypotheticalwavefronts

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Basic concepts

I second-order approximation of reflection events

I spatial stacking operator

I limited number of stacking parameters:first and second spatial derivatives of traveltime

I geometrical interpretation:propagation direction and curvatures of hypotheticalwavefronts

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Basic concepts

I second-order approximation of reflection events

I spatial stacking operator

I limited number of stacking parameters:first and second spatial derivatives of traveltime

I geometrical interpretation:propagation direction and curvatures of hypotheticalwavefronts

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Basic concepts

I second-order approximation of reflection events

I spatial stacking operator

I limited number of stacking parameters:first and second spatial derivatives of traveltime

I geometrical interpretation:propagation direction and curvatures of hypotheticalwavefronts

–1

0

1 2 3

S G

RN x0RNIP

0

1

α

Dep

th [k

m]

Distance [km]

v

v

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Applications of CRS attributes

I Automated, approximate, data-driven time migration

I Approximation of geometrical spreading factor

I Approximation of projected Fresnel zone➥ Optimization of limited-aperture (true-amplitude)

Kirchhoff depth migration

I Most important: attribute-based tomographicvelocity model determination (inversion)➥ Output: smooth macrovelocity model for depth

imaging

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Applications of CRS attributes

I Automated, approximate, data-driven time migration

I Approximation of geometrical spreading factor

I Approximation of projected Fresnel zone➥ Optimization of limited-aperture (true-amplitude)

Kirchhoff depth migration

I Most important: attribute-based tomographicvelocity model determination (inversion)➥ Output: smooth macrovelocity model for depth

imaging

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Applications of CRS attributes

I Automated, approximate, data-driven time migration

I Approximation of geometrical spreading factor

I Approximation of projected Fresnel zone➥ Optimization of limited-aperture (true-amplitude)

Kirchhoff depth migration

I Most important: attribute-based tomographicvelocity model determination (inversion)➥ Output: smooth macrovelocity model for depth

imaging

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Applications of CRS attributes

I Automated, approximate, data-driven time migration

I Approximation of geometrical spreading factor

I Approximation of projected Fresnel zone➥ Optimization of limited-aperture (true-amplitude)

Kirchhoff depth migration

I Most important: attribute-based tomographicvelocity model determination (inversion)➥ Output: smooth macrovelocity model for depth

imaging

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Applications of CRS attributes

I Automated, approximate, data-driven time migration

I Approximation of geometrical spreading factor

I Approximation of projected Fresnel zone➥ Optimization of limited-aperture (true-amplitude)

Kirchhoff depth migration

I Most important: attribute-based tomographicvelocity model determination (inversion)➥ Output: smooth macrovelocity model for depth

imaging

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Applications of CRS attributes

I Automated, approximate, data-driven time migration

I Approximation of geometrical spreading factor

I Approximation of projected Fresnel zone➥ Optimization of limited-aperture (true-amplitude)

Kirchhoff depth migration

I Most important: attribute-based tomographicvelocity model determination (inversion)➥ Output: smooth macrovelocity model for depth

imaging

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Synthesis of our imaging tools

CRS stack ✔

+ Attribute-based tomography ✔

+ (True-amplitude) Kirchhoff depth migration ✔

= CRS-stack-based imaging workflow ✔

I Consistent imaging workflow from prestack timedomain to depth domain

I Flexible, largely automated strategies

I Various useful auxiliary results

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Project definition

I Geothermal project: power station plannedI Seismic survey performed to

I image fractures and faults ☞ water flowI determine precise depth of target horizonI find best possible drilling location

I Subsurface structure in target region:I mainly horizontal layering, slightly dippingI many faults and fracturesI strong velocity contrast above target area

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Project definition

I Geothermal project: power station plannedI Seismic survey performed to

I image fractures and faults ☞ water flowI determine precise depth of target horizonI find best possible drilling location

I Subsurface structure in target region:I mainly horizontal layering, slightly dippingI many faults and fracturesI strong velocity contrast above target area

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Project definition

I Geothermal project: power station plannedI Seismic survey performed to

I image fractures and faults ☞ water flowI determine precise depth of target horizonI find best possible drilling location

I Subsurface structure in target region:I mainly horizontal layering, slightly dippingI many faults and fracturesI strong velocity contrast above target area

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Project definition

I Geothermal project: power station plannedI Seismic survey performed to

I image fractures and faults ☞ water flowI determine precise depth of target horizonI find best possible drilling location

I Subsurface structure in target region:I mainly horizontal layering, slightly dippingI many faults and fracturesI strong velocity contrast above target area

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Project definition

I Geothermal project: power station plannedI Seismic survey performed to

I image fractures and faults ☞ water flowI determine precise depth of target horizonI find best possible drilling location

I Subsurface structure in target region:I mainly horizontal layering, slightly dippingI many faults and fracturesI strong velocity contrast above target area

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Project definition

I Geothermal project: power station plannedI Seismic survey performed to

I image fractures and faults ☞ water flowI determine precise depth of target horizonI find best possible drilling location

I Subsurface structure in target region:I mainly horizontal layering, slightly dippingI many faults and fracturesI strong velocity contrast above target area

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Data acquisition

I 2 parallel seismic lines, 12 km length each

I Source: 3 vibrators, linear upsweep 12-100 Hz,source separation ∆s=50 m

I Receivers: ≈ 240 groups (12 geophones each),receiver group separation ∆r=50 m

I Recording time after deconvolution: 4 s;sampling interval: 2 ms

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Data acquisition

I 2 parallel seismic lines, 12 km length each

I Source: 3 vibrators, linear upsweep 12-100 Hz,source separation ∆s=50 m

I Receivers: ≈ 240 groups (12 geophones each),receiver group separation ∆r=50 m

I Recording time after deconvolution: 4 s;sampling interval: 2 ms

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Data acquisition

I 2 parallel seismic lines, 12 km length each

I Source: 3 vibrators, linear upsweep 12-100 Hz,source separation ∆s=50 m

I Receivers: ≈ 240 groups (12 geophones each),receiver group separation ∆r=50 m

I Recording time after deconvolution: 4 s;sampling interval: 2 ms

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Data acquisition

I 2 parallel seismic lines, 12 km length each

I Source: 3 vibrators, linear upsweep 12-100 Hz,source separation ∆s=50 m

I Receivers: ≈ 240 groups (12 geophones each),receiver group separation ∆r=50 m

I Recording time after deconvolution: 4 s;sampling interval: 2 ms

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

CRS stack: simulated ZO section

0

0.5

1.0

1.5

2.0

2.5

3.0

Tim

e [s

]

450 500 550 600 650 700 750 800CMP no.

horizontal extent ≈ 12 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

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Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Tomographic inversion: velocity model

0

1000

2000

3000

Dep

th [m

]

400 450 500 550 600 650 700 750 800CMP no.

2000

3000

4000

velo

city

[m/s

]

horizontal extent ≈ 12 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

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Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Kirchhoff poststack depth migration

500

1000

1500

2000

2500

3000

3500

Dep

th [

m]

450 500 550 600 650 700 750 800CMP no.

horizontal extent ≈ 12 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

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Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Kirchhoff prestack depth migration

500

1000

1500

2000

2500

3000

3500

Dep

th [

m]

450 500 550 600 650 700 750 800CMP no.

horizontal extent ≈ 12 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

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Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Common-image gathers

1

2

3

Dep

th [k

m]

1 2 3 4 5 6 7 8 9

CIG Location [km]

maximum offset ≈ 3000 m

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

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Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Preliminary structural interpretation

500

1000

1500

2000

2500

3000

3500

Dep

th [

m]

450 500 550 600 650 700 750 800CMP no.

horizontal extent ≈ 12 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Comparison to standard processing

I Largely automated processing

I Generally higher resolution of reflectors and faults,particularly in the target area

I Reliable depth location of reflectors, according towell data and other geological and geophysicalinformation

I Faults can be traced from near-surface to depths aslarge as 3 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Comparison to standard processing

I Largely automated processing

I Generally higher resolution of reflectors and faults,particularly in the target area

I Reliable depth location of reflectors, according towell data and other geological and geophysicalinformation

I Faults can be traced from near-surface to depths aslarge as 3 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Comparison to standard processing

I Largely automated processing

I Generally higher resolution of reflectors and faults,particularly in the target area

I Reliable depth location of reflectors, according towell data and other geological and geophysicalinformation

I Faults can be traced from near-surface to depths aslarge as 3 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Comparison to standard processing

I Largely automated processing

I Generally higher resolution of reflectors and faults,particularly in the target area

I Reliable depth location of reflectors, according towell data and other geological and geophysicalinformation

I Faults can be traced from near-surface to depths aslarge as 3 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Comparison to standard processing

I Largely automated processing

I Generally higher resolution of reflectors and faults,particularly in the target area

I Reliable depth location of reflectors, according towell data and other geological and geophysicalinformation

I Faults can be traced from near-surface to depths aslarge as 3 km

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Conclusions

I Workflow: from time to depth domain

I Successful application in recent exploration project

I Basis: CRS stack producing high quality stacksections and very useful attribute sections

I Subsequent application of tomographic inversionwith CRS attributes and Kirchhoff depth migration

I Various workflow extentions possible (finite-offsetCRS stack & inversion, static corrections,topography handling, AVO analysis, etc.)

I 3D software is available or under development

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Conclusions

I Workflow: from time to depth domain

I Successful application in recent exploration project

I Basis: CRS stack producing high quality stacksections and very useful attribute sections

I Subsequent application of tomographic inversionwith CRS attributes and Kirchhoff depth migration

I Various workflow extentions possible (finite-offsetCRS stack & inversion, static corrections,topography handling, AVO analysis, etc.)

I 3D software is available or under development

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Conclusions

I Workflow: from time to depth domain

I Successful application in recent exploration project

I Basis: CRS stack producing high quality stacksections and very useful attribute sections

I Subsequent application of tomographic inversionwith CRS attributes and Kirchhoff depth migration

I Various workflow extentions possible (finite-offsetCRS stack & inversion, static corrections,topography handling, AVO analysis, etc.)

I 3D software is available or under development

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Conclusions

I Workflow: from time to depth domain

I Successful application in recent exploration project

I Basis: CRS stack producing high quality stacksections and very useful attribute sections

I Subsequent application of tomographic inversionwith CRS attributes and Kirchhoff depth migration

I Various workflow extentions possible (finite-offsetCRS stack & inversion, static corrections,topography handling, AVO analysis, etc.)

I 3D software is available or under development

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Conclusions

I Workflow: from time to depth domain

I Successful application in recent exploration project

I Basis: CRS stack producing high quality stacksections and very useful attribute sections

I Subsequent application of tomographic inversionwith CRS attributes and Kirchhoff depth migration

I Various workflow extentions possible (finite-offsetCRS stack & inversion, static corrections,topography handling, AVO analysis, etc.)

I 3D software is available or under development

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Conclusions

I Workflow: from time to depth domain

I Successful application in recent exploration project

I Basis: CRS stack producing high quality stacksections and very useful attribute sections

I Subsequent application of tomographic inversionwith CRS attributes and Kirchhoff depth migration

I Various workflow extentions possible (finite-offsetCRS stack & inversion, static corrections,topography handling, AVO analysis, etc.)

I 3D software is available or under development

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Acknowledgments

This work was kindly supported by

I HotRock Erdwärmekraftwerk (EWK)Offenbach/Pfalz GmbH, Karlsruhe, Germany

I Deutsche Montan Technologie (DMT) GmbH,Essen, Germany

I the Federal Ministry for the Environment, NatureConservation and Nuclear Safety, Berlin, Germany

I the sponsors of the Wave Inversion Technology(WIT) Consortium, Karlsruhe, Germany

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T

Related presentations

In this session:

SP 4.5 CRS imaging and tomography versusPreSDM: a case history in overthrustgeology

SP 4.6 CRS stack and redatuming for ruggedsurface topography: a synthetic dataexample

SP 4.8 3D focusing operator estimation usingsparse data

74th Annual MeetingSEG, Denver 2004

Hertweck et al.

IntroductionSeismic imagingCRS stackApplicationsSynthesis

The projectProject definitionData acquisition

Data exampleCRS stackInversionPostSDMPreSDMCIGInterpretation

Comparison

Conclusions

Acknowledgments

W I T