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75 th SEG Annual Meeting, Houston 2005 Klver & Mann Event-consistent smoothing and Introduction automated picking in CRS-based 3D CRS stack Velocity determination seismic imaging NIP waves CRS tomography Workflow Tilman Klver and

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-consistent smoothing and automated picking in CRS-based seismic imaging

Tilman Klüver and Jürgen Mann

Wave Inversion Technology (WIT) Geophysical Institute, University of Karlsruhe (TH) November 8, 2005

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Overview

Introduction 3D Common-Reflection-Surface (CRS) stack Velocity determination with 3D CRS attributes CRS-based workflow The event-aligned volume Event-consistent smoothing Automated picking Results Conclusions

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

◮ The Common-Reflection-Surface (CRS) stack

provides

◮ high S/N stacked ZO volume ◮ coherence value for each sample ◮ kinematic wavefield attributes for each sample

➥ generalised, high density stacking velocity analysis

◮ The CRS attributes can further be used for many

applications, e. g.:

◮ calculation of projected Fresnel zone and

geometrical spreading factor

◮ improved AVO-analysis ◮ tomographic determination of macro-velocity

models

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

◮ The Common-Reflection-Surface (CRS) stack

provides

◮ high S/N stacked ZO volume ◮ coherence value for each sample ◮ kinematic wavefield attributes for each sample

➥ generalised, high density stacking velocity analysis

◮ The CRS attributes can further be used for many

applications, e. g.:

◮ calculation of projected Fresnel zone and

geometrical spreading factor

◮ improved AVO-analysis ◮ tomographic determination of macro-velocity

models

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SLIDE 5

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

◮ CRS attributes are subject to

◮ outliers ◮ non-physical fluctuations

➥ Attribute-based applications are impaired

◮ Application considered here:

Tomographic determination of macro-velocity models using CRS-attributes

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SLIDE 6

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

◮ CRS attributes are subject to

◮ outliers ◮ non-physical fluctuations

➥ Attribute-based applications are impaired

◮ Application considered here:

Tomographic determination of macro-velocity models using CRS-attributes

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SLIDE 7

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

◮ CRS attributes are subject to

◮ outliers ◮ non-physical fluctuations

➥ Attribute-based applications are impaired

◮ Application considered here:

Tomographic determination of macro-velocity models using CRS-attributes

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SLIDE 8

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

CRS tomography

◮ Advantages:

◮ picking in simulated ZO volume of high S/N ratio

(output of CRS)

◮ pick locations independent of each other ◮ very few picks required

◮ Quality of result depends on quality of input CRS

attributes

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SLIDE 9

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

CRS tomography

◮ Advantages:

◮ picking in simulated ZO volume of high S/N ratio

(output of CRS)

◮ pick locations independent of each other ◮ very few picks required

◮ Quality of result depends on quality of input CRS

attributes

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SLIDE 10

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Introduction

CRS − stack Smoothing

  • ptional restacking

automated picking NIP−wave tomography Migration

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

3D CRS attributes

Traveltime depends on eight attributes: t2 (∆ξ ξ ξ,h) =

  • t0 +2pξ ·∆ξ

ξ ξ 2 +2t0

  • ∆ξ

ξ ξ TMξ ∆ξ ξ ξ +hTMh h

  • −1000

−500 500 1000 100 200 300 400 −600 −400 −200 0.2 0.4 0.6 Depth [m] Time [s]

ξ

( , t )

Time [s] Depth [m] Midpoint [m]

CRS surface

h [m]

pξ = 1

v0 (sinα cosψ,sinα sinψ)T

Mh = 1

v0 DKNIPDT

Mξ = 1

v0 DKNDT

NIP: normal incidence point

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

3D CRS attributes

Traveltime depends on eight attributes: t2 (∆ξ ξ ξ,h) =

  • t0 +2pξ ·∆ξ

ξ ξ 2 +2t0

  • ∆ξ

ξ ξ TMξ ∆ξ ξ ξ +hTMh h

  • ξ

ξ

α α

NIP NIP NIP N

R R

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

NIP waves and velocities

ξ ξ ξ

p ξ ξ ξ NIP , , T , ) ( Mh

CRS attributes Mh and pξ at (t0,ξ ξ ξ) describe second-order traveltime approximation of emerging NIP wave.

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

NIP waves and velocities

ξ ξ ξ

p ξ ξ ξ NIP , , T , ) ( Mh

In consistent velocity models, NIP waves focus at zero traveltime.

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Tomography with CRS attributes

Find a velocity model in which all considered NIP waves, described by kinematic wavefield attributes, are correctly modelled.

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Tomography with CRS attributes

Find a velocity model in which all considered NIP waves, described by kinematic wavefield attributes, are correctly modelled. Remark: in 3D, Mh is only required for one azimuth.

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack NIP−wave tomography Migration

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack NIP−wave tomography Migration ◮ fluctuations in CRS attributes,

which are not consistent with theory, influence the inversion result

◮ manual picking is very time

consuming, especially in 3D

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SLIDE 19

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack NIP−wave tomography Migration ◮ fluctuations in CRS attributes,

which are not consistent with theory, influence the inversion result

◮ manual picking is very time

consuming, especially in 3D

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SLIDE 20

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack NIP−wave tomography Migration ◮ How to remove outliers and

fluctuations in the attributes?

◮ Where to pick the limited

number of locally coherent reflection events needed in NIP-wave tomography?

◮ How to do this automatically?

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SLIDE 21

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack NIP−wave tomography Migration ◮ How to remove outliers and

fluctuations in the attributes?

◮ Where to pick the limited

number of locally coherent reflection events needed in NIP-wave tomography?

◮ How to do this automatically?

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SLIDE 22

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack NIP−wave tomography Migration ◮ How to remove outliers and

fluctuations in the attributes?

◮ Where to pick the limited

number of locally coherent reflection events needed in NIP-wave tomography?

◮ How to do this automatically?

slide-23
SLIDE 23

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack Smoothing

  • ptional restacking

automated picking NIP−wave tomography Migration

Strategy smoothing and picking in volumes aligned with reflection events:

◮ volume size defines locality ◮ usage of locally valid statistics

➥ to remove outliers and fluctuations ➥ to identify valid pick locations

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SLIDE 24

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack Smoothing

  • ptional restacking

automated picking NIP−wave tomography Migration

Strategy smoothing and picking in volumes aligned with reflection events:

◮ volume size defines locality ◮ usage of locally valid statistics

➥ to remove outliers and fluctuations ➥ to identify valid pick locations

slide-25
SLIDE 25

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack Smoothing

  • ptional restacking

automated picking NIP−wave tomography Migration

Strategy smoothing and picking in volumes aligned with reflection events:

◮ volume size defines locality ◮ usage of locally valid statistics

➥ to remove outliers and fluctuations ➥ to identify valid pick locations

slide-26
SLIDE 26

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack Smoothing

  • ptional restacking

automated picking NIP−wave tomography Migration

Strategy smoothing and picking in volumes aligned with reflection events:

◮ volume size defines locality ◮ usage of locally valid statistics

➥ to remove outliers and fluctuations ➥ to identify valid pick locations

slide-27
SLIDE 27

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

CRS-based workflow

CRS − stack Smoothing

  • ptional restacking

automated picking NIP−wave tomography Migration

Strategy smoothing and picking in volumes aligned with reflection events:

◮ volume size defines locality ◮ usage of locally valid statistics

➥ to remove outliers and fluctuations ➥ to identify valid pick locations

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-aligned volume

  • ✁
✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁

P midpoint x midpoint y x0 t 0 y p 2 time seismic event

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75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-aligned volume

  • ✁
✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄

midpoint x midpoint y x0 t 0 y p 2 time smoothing box seismic event

slide-30
SLIDE 30

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Detection of intersecting events

slowness vector: pξ = 1 v0 (cosα sinβ,sinα sinβ,cosβ)T

slide-31
SLIDE 31

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Detection of intersecting events

slowness vector: pξ = 1 v0 (cosα sinβ,sinα sinβ,cosβ)T unit-normal vector to NIP-wavefront: n = (cosα sinβ,sinα sinβ,cosβ)T

slide-32
SLIDE 32

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Detection of intersecting events

slowness vector: pξ = 1 v0 (cosα sinβ,sinα sinβ,cosβ)T unit-normal vector to NIP-wavefront: n = (cosα sinβ,sinα sinβ,cosβ)T event discrimination by dip difference: θ = arccos(n1 ·n2).

slide-33
SLIDE 33

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-consistent smoothing

For each zero-offset sample and CRS-parameter:

◮ align smoothing volume with reflection event using

first traveltime derivatives

◮ reject samples below user-defined coherence

threshold

◮ reject samples with dip difference beyond

user-defined threshold

➥ avoid mixing of events

◮ apply combined filter:

◮ median filter ➥ remove outliers ◮ averaging ➥ remove fluctuations

◮ assign result to zero-offset sample

slide-34
SLIDE 34

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-consistent smoothing

For each zero-offset sample and CRS-parameter:

◮ align smoothing volume with reflection event using

first traveltime derivatives

◮ reject samples below user-defined coherence

threshold

◮ reject samples with dip difference beyond

user-defined threshold

➥ avoid mixing of events

◮ apply combined filter:

◮ median filter ➥ remove outliers ◮ averaging ➥ remove fluctuations

◮ assign result to zero-offset sample

slide-35
SLIDE 35

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-consistent smoothing

For each zero-offset sample and CRS-parameter:

◮ align smoothing volume with reflection event using

first traveltime derivatives

◮ reject samples below user-defined coherence

threshold

◮ reject samples with dip difference beyond

user-defined threshold

➥ avoid mixing of events

◮ apply combined filter:

◮ median filter ➥ remove outliers ◮ averaging ➥ remove fluctuations

◮ assign result to zero-offset sample

slide-36
SLIDE 36

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-consistent smoothing

For each zero-offset sample and CRS-parameter:

◮ align smoothing volume with reflection event using

first traveltime derivatives

◮ reject samples below user-defined coherence

threshold

◮ reject samples with dip difference beyond

user-defined threshold

➥ avoid mixing of events

◮ apply combined filter:

◮ median filter ➥ remove outliers ◮ averaging ➥ remove fluctuations

◮ assign result to zero-offset sample

slide-37
SLIDE 37

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Event-consistent smoothing

For each zero-offset sample and CRS-parameter:

◮ align smoothing volume with reflection event using

first traveltime derivatives

◮ reject samples below user-defined coherence

threshold

◮ reject samples with dip difference beyond

user-defined threshold

➥ avoid mixing of events

◮ apply combined filter:

◮ median filter ➥ remove outliers ◮ averaging ➥ remove fluctuations

◮ assign result to zero-offset sample

slide-38
SLIDE 38

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Stack, unsmoothed attributes

slide-39
SLIDE 39

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Stack, smoothed attributes

slide-40
SLIDE 40

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Coherence, unsmoothed attributes

slide-41
SLIDE 41

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Coherence, smoothed attributes

slide-42
SLIDE 42

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

slide-43
SLIDE 43

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

slide-44
SLIDE 44

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

slide-45
SLIDE 45

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

slide-46
SLIDE 46

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

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SLIDE 47

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

slide-48
SLIDE 48

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Automated picking

For each selected trace

◮ search (next) coherence maximum ◮ get nearest maximum of stack envelope ◮ align volume with reflection event using first

traveltime derivatives

◮ reject pick if user-defined percentage of all samples

inside the volume

◮ is below a given coherence threshold or ◮ has a dip difference exceeding a given threshold

◮ or if amplitude is below a user-defined threshold

➥ prefer high-energy events

◮ continue on selected trace

slide-49
SLIDE 49

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Picks on selected sections

slide-50
SLIDE 50

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Stacking velocity

slide-51
SLIDE 51

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

“Smoothed” stacking velocity

slide-52
SLIDE 52

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Normal ray emergence angle

slide-53
SLIDE 53

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Smoothed normal ray emergence angle

slide-54
SLIDE 54

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Coherence, unsmoothed attributes

slide-55
SLIDE 55

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Coherence, smoothed attributes

slide-56
SLIDE 56

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Stacking velocity

slide-57
SLIDE 57

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

“Smoothed” stacking velocity

slide-58
SLIDE 58

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Normal ray emergence angle

slide-59
SLIDE 59

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Smoothed normal ray emergence angle

slide-60
SLIDE 60

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Conclusions

◮ fast and efficient smoothing and picking algorithms ◮ account for neighbouring information using windows

aligned with reflection events

◮ no mixing of intersecting events ◮ no interpretation by the user ◮ smoothing can improve the CRS image significantly ◮ automated smoothing and picking close the gap

between CRS stack and NIP-wave tomography

slide-61
SLIDE 61

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Conclusions

◮ fast and efficient smoothing and picking algorithms ◮ account for neighbouring information using windows

aligned with reflection events

◮ no mixing of intersecting events ◮ no interpretation by the user ◮ smoothing can improve the CRS image significantly ◮ automated smoothing and picking close the gap

between CRS stack and NIP-wave tomography

slide-62
SLIDE 62

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Conclusions

◮ fast and efficient smoothing and picking algorithms ◮ account for neighbouring information using windows

aligned with reflection events

◮ no mixing of intersecting events ◮ no interpretation by the user ◮ smoothing can improve the CRS image significantly ◮ automated smoothing and picking close the gap

between CRS stack and NIP-wave tomography

slide-63
SLIDE 63

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Conclusions

◮ fast and efficient smoothing and picking algorithms ◮ account for neighbouring information using windows

aligned with reflection events

◮ no mixing of intersecting events ◮ no interpretation by the user ◮ smoothing can improve the CRS image significantly ◮ automated smoothing and picking close the gap

between CRS stack and NIP-wave tomography

slide-64
SLIDE 64

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Conclusions

◮ fast and efficient smoothing and picking algorithms ◮ account for neighbouring information using windows

aligned with reflection events

◮ no mixing of intersecting events ◮ no interpretation by the user ◮ smoothing can improve the CRS image significantly ◮ automated smoothing and picking close the gap

between CRS stack and NIP-wave tomography

slide-65
SLIDE 65

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Conclusions

◮ fast and efficient smoothing and picking algorithms ◮ account for neighbouring information using windows

aligned with reflection events

◮ no mixing of intersecting events ◮ no interpretation by the user ◮ smoothing can improve the CRS image significantly ◮ automated smoothing and picking close the gap

between CRS stack and NIP-wave tomography

slide-66
SLIDE 66

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

Acknowledgements

This work was kindly supported by the sponsors of the Wave Inversion Technology (WIT) consortium, Karlsruhe, Germany and the Federal Ministry of Education and Research, Germany.

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SLIDE 67

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T

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SLIDE 68

75th SEG Annual Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions

W I T