Stacking velocity analysis with CRS Stack attributes Steffen Bergler - - PowerPoint PPT Presentation

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Stacking velocity analysis with CRS Stack attributes Steffen Bergler - - PowerPoint PPT Presentation

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W I T Stacking velocity analysis with CRS Stack attributes Steffen Bergler , Pedro Chira, Jrgen Mann, Kai-Uwe Vieth, and Peter Hubral Wave Inversion Technology Geophysical Institute University of Karlsruhe, Germany EAGE Conference &

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Stacking velocity analysis with CRS Stack attributes

Steffen Bergler∗, Pedro Chira, Jürgen Mann, Kai-Uwe Vieth, and Peter Hubral Wave Inversion Technology Geophysical Institute University of Karlsruhe, Germany

EAGE Conference & Exhibition, Florence 2002 – p.1

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Overview

Development of the CRS Stack

EAGE Conference & Exhibition, Florence 2002 – p.2

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Overview

Development of the CRS Stack How does the CRS Stack work ?

EAGE Conference & Exhibition, Florence 2002 – p.2

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Overview

Development of the CRS Stack How does the CRS Stack work ? What are the CRS attributes good for ?

EAGE Conference & Exhibition, Florence 2002 – p.2

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Overview

Development of the CRS Stack How does the CRS Stack work ? What are the CRS attributes good for ? CRS Stack and high-resolution stacking velocity analysis

EAGE Conference & Exhibition, Florence 2002 – p.2

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Overview

Development of the CRS Stack How does the CRS Stack work ? What are the CRS attributes good for ? CRS Stack and high-resolution stacking velocity analysis Real data example

EAGE Conference & Exhibition, Florence 2002 – p.2

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Overview

Development of the CRS Stack How does the CRS Stack work ? What are the CRS attributes good for ? CRS Stack and high-resolution stacking velocity analysis Real data example Conclusions

EAGE Conference & Exhibition, Florence 2002 – p.2

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Development of the CRS Stack

Multi-parameter moveout operators for data-driven stacking

EAGE Conference & Exhibition, Florence 2002 – p.3

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Development of the CRS Stack

Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 3 parameters

EAGE Conference & Exhibition, Florence 2002 – p.3

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Development of the CRS Stack

Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 3 parameters 2-D finite-offset 5 parameters

EAGE Conference & Exhibition, Florence 2002 – p.3

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Development of the CRS Stack

Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 3 parameters 2-D finite-offset 5 parameters 3-D zero-offset 8 parameters

EAGE Conference & Exhibition, Florence 2002 – p.3

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Development of the CRS Stack

Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 3 parameters 2-D finite-offset 5 parameters 3-D zero-offset 8 parameters 3-D finite-offset 13 parameters

EAGE Conference & Exhibition, Florence 2002 – p.3

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W I T Arbitrary acquisition configuration

  • h = 1

2 xG −xS yG −yS

  • m = 1

2 xG +xS yG +yS

  • X

x y m 2h finite-offset ray zero-offset ray G S A c q u i s i t i

  • n

s u r f a c e Reflector R* R EAGE Conference & Exhibition, Florence 2002 – p.4

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CRS stacking operators for ZO

3-D case: t2

hyp =

  • t0 −

c· m 2 +

  • mTA

m+ hTB h

  • EAGE Conference & Exhibition, Florence 2002 – p.5
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CRS stacking operators for ZO

3-D case: t2

hyp =

  • t0 −

c· m 2 +

  • mTA

m+ hTB h

  • c: two-component vector

A,B: symmetric 2×2 matrices

EAGE Conference & Exhibition, Florence 2002 – p.5

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CRS stacking operators for ZO

3-D case: t2

hyp =

  • t0 −

c· m 2 +

  • mTA

m+ hTB h

  • c: two-component vector

A,B: symmetric 2×2 matrices 2-D case: t2

hyp =

  • t0 −cm

2 +

  • am2 +bh2

EAGE Conference & Exhibition, Florence 2002 – p.5

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Implementation

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 xm [km] 0.2 0.4 h [km] 0.6 0.7 0.8 0.9 1 1.1 1.2 t [s]

Data volume . .

EAGE Conference & Exhibition, Florence 2002 – p.6

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Implementation

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 xm [km] 0.2 0.4 h [km] 0.6 0.7 0.8 0.9 1 1.1 1.2 t [s]

Data volume ZO grid .

EAGE Conference & Exhibition, Florence 2002 – p.7

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Implementation

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 xm [km] 0.2 0.4 h [km] 0.6 0.7 0.8 0.9 1 1.1 1.2 t [s]

Data volume ZO grid CRS operator

EAGE Conference & Exhibition, Florence 2002 – p.8

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Consequences

approach is purely data-driven

EAGE Conference & Exhibition, Florence 2002 – p.9

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Consequences

approach is purely data-driven use of full multi-coverage data volume

EAGE Conference & Exhibition, Florence 2002 – p.9

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Consequences

approach is purely data-driven use of full multi-coverage data volume each ZO sample carries information of

EAGE Conference & Exhibition, Florence 2002 – p.9

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Consequences

approach is purely data-driven use of full multi-coverage data volume each ZO sample carries information of stacked amplitude

EAGE Conference & Exhibition, Florence 2002 – p.9

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Consequences

approach is purely data-driven use of full multi-coverage data volume each ZO sample carries information of stacked amplitude stacking parameters

EAGE Conference & Exhibition, Florence 2002 – p.9

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Consequences

approach is purely data-driven use of full multi-coverage data volume each ZO sample carries information of stacked amplitude stacking parameters coherence value

EAGE Conference & Exhibition, Florence 2002 – p.9

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Attributes

NIP and Normal wave along ZO ray

EAGE Conference & Exhibition, Florence 2002 – p.10

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Attributes

− → CRS Stack attributes have many applications more accurate stacking velocity

EAGE Conference & Exhibition, Florence 2002 – p.11

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Attributes

− → CRS Stack attributes have many applications more accurate stacking velocity projected Fresnel zone for parsimonious migration

EAGE Conference & Exhibition, Florence 2002 – p.11

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Attributes

− → CRS Stack attributes have many applications more accurate stacking velocity projected Fresnel zone for parsimonious migration geometrical spreading factor

EAGE Conference & Exhibition, Florence 2002 – p.11

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Attributes

− → CRS Stack attributes have many applications more accurate stacking velocity projected Fresnel zone for parsimonious migration geometrical spreading factor wavefield separation

EAGE Conference & Exhibition, Florence 2002 – p.11

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Attributes

− → CRS Stack attributes have many applications more accurate stacking velocity projected Fresnel zone for parsimonious migration geometrical spreading factor wavefield separation macro-velocity inversion

EAGE Conference & Exhibition, Florence 2002 – p.11

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Attributes

− → CRS Stack attributes have many applications more accurate stacking velocity projected Fresnel zone for parsimonious migration geometrical spreading factor wavefield separation macro-velocity inversion model-independent time migration

EAGE Conference & Exhibition, Florence 2002 – p.11

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Stacking velocity

2-D case: 1/v2

stack = 2t0

v0 cos2α RNIP

EAGE Conference & Exhibition, Florence 2002 – p.12

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Stacking velocity

2-D case: 1/v2

stack = 2t0

v0 cos2α RNIP 3-D case:

  • h = r (cosφ,sinφ)T −

→ t2

CMP = t2 0 +

r2 v2

stack

EAGE Conference & Exhibition, Florence 2002 – p.12

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Stacking velocity

2-D case: 1/v2

stack = 2t0

v0 cos2α RNIP 3-D case:

  • h = r (cosφ,sinφ)T −

→ t2

CMP = t2 0 +

r2 v2

stack

1/v2

stack = 2t0

v0 (cosφ,sinφ)TMTT (cosφ,sinφ)T

EAGE Conference & Exhibition, Florence 2002 – p.12

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Stacking velocity

much more traces involved in stacking velocity determination compared to conventional methods

EAGE Conference & Exhibition, Florence 2002 – p.13

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Stacking velocity

much more traces involved in stacking velocity determination compared to conventional methods thus stable and accurate (also in presence of high noise level)

EAGE Conference & Exhibition, Florence 2002 – p.13

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Stacking velocity

much more traces involved in stacking velocity determination compared to conventional methods thus stable and accurate (also in presence of high noise level) high vertical and horizontal resolution

EAGE Conference & Exhibition, Florence 2002 – p.13

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Stacking velocity

much more traces involved in stacking velocity determination compared to conventional methods thus stable and accurate (also in presence of high noise level) high vertical and horizontal resolution attribute and coherence sections help to identify events

EAGE Conference & Exhibition, Florence 2002 – p.13

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Real data example

Result of NMO/DMO/Stack

0.5 1.0 1.5 2.0 2.5 3.0 Time [s] CMP location

  • approx. 13km

EAGE Conference & Exhibition, Florence 2002 – p.14

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Real data example

Result of CRS Stack

0.5 1.0 1.5 2.0 2.5 3.0 Time [s] CMP location

  • approx. 13km

EAGE Conference & Exhibition, Florence 2002 – p.15

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Real data example

Detected stacking velocity in [m/s]

0.5 1.0 1.5 2.0 2.5 Time [s] CMP 2000 2500 3000 3500 4000 4500 5000

EAGE Conference & Exhibition, Florence 2002 – p.16

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Real data example

Depth migration of NMO/DMO/Stack

1 2 3 4 5 Depth [km] CMP location 13km

EAGE Conference & Exhibition, Florence 2002 – p.17

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Real data example

Depth migration of CRS stack

1 2 3 4 5 Depth [km] CMP location 13km

EAGE Conference & Exhibition, Florence 2002 – p.18

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Real data example

Applications of the attributes

1.6 1.8 2.0 2.2 Time [s] 200 400 600 CMP 1.6 1.8 2.0 2.2 Time [s] 200 400 600 CMP

CMP section CRS section

EAGE Conference & Exhibition, Florence 2002 – p.19

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Real data example

184 284 384 484 584 684 CMP 2.0 2.5 3.0 3.5 4.0 [km/s]

CMP stacking velocity

184 284 384 484 584 684 CMP 2.0 2.5 3.0 3.5 4.0 [km/s]

CRS stacking velocity

EAGE Conference & Exhibition, Florence 2002 – p.20

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Real data example

α [◦] RNIP [km] 1/RN [1/km]

  • 8
  • 6
  • 4

184 284 384 484 584 684 3 5 7 184 284 384 484 584 684 CMP

  • 0.05

0.05

EAGE Conference & Exhibition, Florence 2002 – p.21

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Real data example

184 284 384 484 584 684 CMP 200 300 400 [m]

Projected Fresnel zone

184 284 384 484 584 684 CMP 2 3 4 [sqrt(s)]

Normalized in-plane geometrical spreading

EAGE Conference & Exhibition, Florence 2002 – p.22

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Conclusions

The data-driven CRS Stack has: high signal-to-noise ratio

EAGE Conference & Exhibition, Florence 2002 – p.23

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Conclusions

The data-driven CRS Stack has: high signal-to-noise ratio increased continuity of events

EAGE Conference & Exhibition, Florence 2002 – p.23

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Conclusions

The data-driven CRS Stack has: high signal-to-noise ratio increased continuity of events high vertical and horizontal resolution

EAGE Conference & Exhibition, Florence 2002 – p.23

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Conclusions

The data-driven CRS Stack has: high signal-to-noise ratio increased continuity of events high vertical and horizontal resolution kinematic wavefield attributes

EAGE Conference & Exhibition, Florence 2002 – p.23

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Conclusions

The data-driven CRS Stack has: high signal-to-noise ratio increased continuity of events high vertical and horizontal resolution kinematic wavefield attributes CRS Stack makes velocity analysis more reliable

EAGE Conference & Exhibition, Florence 2002 – p.23

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Acknowledgments

W I T This work was supported by the sponsors of the Wave Inversion Technology Consortium.

EAGE Conference & Exhibition, Florence 2002 – p.24

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Related presentations:

B015 3D zero-offset Common Reflection Surface Stack for land data – real data example B016 Improved resolution in time and depth processing by macromodel independent CRS Stacking E023 Generalization of the Common-Reflection-Surface Stack P165 Topographic correction using CRS parameters P166 2D and 3D ZO CRS stack for a complex top-surface topogr aphy P167 A fourth-order CRS moveout for reflection and diffraction events

EAGE Conference & Exhibition, Florence 2002 – p.25