The Finite-Offset Common-Reflection-Surface (CRS) Stack: an - PowerPoint PPT Presentation

W I T The Finite-Offset Common-Reflection-Surface (CRS) Stack: an alternative stacking tool for subsalt imaging Steffen Bergler ∗ , Jürgen Mann, German Höcht, and Peter Hubral Wave Inversion Technology Geophysical Institute University of Karlsruhe, Germany SEG 72nd Annual Meeting, Salt Lake City 2002 – p.1

Overview W I T Motivation SEG 72nd Annual Meeting, Salt Lake City 2002 – p.2

Overview W I T Motivation Development of the CRS Stack SEG 72nd Annual Meeting, Salt Lake City 2002 – p.2

Overview W I T Motivation Development of the CRS Stack Implementation SEG 72nd Annual Meeting, Salt Lake City 2002 – p.2

Overview W I T Motivation Development of the CRS Stack Implementation Real data example SEG 72nd Annual Meeting, Salt Lake City 2002 – p.2

Overview W I T Motivation Development of the CRS Stack Implementation Real data example Test of CO CRS on Sigsbee 2A data SEG 72nd Annual Meeting, Salt Lake City 2002 – p.2

Overview W I T Motivation Development of the CRS Stack Implementation Real data example Test of CO CRS on Sigsbee 2A data Conclusions SEG 72nd Annual Meeting, Salt Lake City 2002 – p.2

Motivation W I T offset [kf] 5 10 15 20 25 3 Goal: Use far-offset 4 reflections 5 6 Time [s] 7 8 9 10 SEG 72nd Annual Meeting, Salt Lake City 2002 – p.3

Motivation W I T offset [kf] 5 10 15 20 25 3 Goal: Use far-offset 4 reflections 5 by CRS Stack 6 Time [s] 7 8 9 10 SEG 72nd Annual Meeting, Salt Lake City 2002 – p.3

Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking SEG 72nd Annual Meeting, Salt Lake City 2002 – p.4

Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 3 parameters SEG 72nd Annual Meeting, Salt Lake City 2002 – p.4

Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 2-D finite-offset 3 parameters 5 parameters SEG 72nd Annual Meeting, Salt Lake City 2002 – p.4

Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 2-D finite-offset 3 parameters 5 parameters 3-D zero-offset 8 parameters SEG 72nd Annual Meeting, Salt Lake City 2002 – p.4

Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 2-D finite-offset 3 parameters 5 parameters 3-D zero-offset 3-D finite-offset 8 parameters 13 parameters SEG 72nd Annual Meeting, Salt Lake City 2002 – p.4

Implementation W I T Data volume 1.2 1.1 . 1 t [s] 0.9 . 0.8 0.4 0.7 h [km] 0.2 0.6 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 2 2.2 2.4 xm [km] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.5

Implementation W I T Data volume 1.2 1.1 . 1 t [s] 0.9 . 0.8 0.4 0.7 h [km] 0.2 0.6 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 2 2.2 2.4 xm [km] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.6

Implementation W I T Data volume 1.2 1.1 . 1 t [s] 0.9 . 0.8 0.4 0.7 h [km] 0.2 0.6 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 2 2.2 2.4 xm [km] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.7

Implementation W I T Data volume 1.2 1.1 ZO grid 1 t [s] 0.9 . 0.8 0.4 0.7 h [km] 0.2 0.6 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 2 2.2 2.4 xm [km] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.8

Implementation W I T Data volume 1.2 1.1 ZO grid 1 t [s] 0.9 ZO CRS 0.8 0.4 operator 0.7 h [km] 0.2 0.6 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 2 2.2 2.4 xm [km] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.9

Implementation W I T Data volume 1.2 1.1 CO grid 1 t [s] 0.9 CO CRS 0.8 0.4 operator 0.7 h [km] 0.2 0.6 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 2 2.2 2.4 xm [km] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.10

Consequences W I T Approach is purely data-driven SEG 72nd Annual Meeting, Salt Lake City 2002 – p.11

Consequences W I T Approach is purely data-driven Use of full multi-coverage data volume SEG 72nd Annual Meeting, Salt Lake City 2002 – p.11

Consequences W I T Approach is purely data-driven Use of full multi-coverage data volume Each CRS stacked sample carries information of SEG 72nd Annual Meeting, Salt Lake City 2002 – p.11

Consequences W I T Approach is purely data-driven Use of full multi-coverage data volume Each CRS stacked sample carries information of Stacked amplitude SEG 72nd Annual Meeting, Salt Lake City 2002 – p.11

Consequences W I T Approach is purely data-driven Use of full multi-coverage data volume Each CRS stacked sample carries information of Stacked amplitude CRS Stack attributes: Kinematic wavefield attributes SEG 72nd Annual Meeting, Salt Lake City 2002 – p.11

Consequences W I T Approach is purely data-driven Use of full multi-coverage data volume Each CRS stacked sample carries information of Stacked amplitude CRS Stack attributes: Kinematic wavefield attributes Coherence value SEG 72nd Annual Meeting, Salt Lake City 2002 – p.11

Real data example W I T CDP bin no. CDP bin no. 0 50 100 150 200 250 300 0 50 100 150 200 250 300 0 0 0.5 0.5 Time [s] Time [s] 1.0 1.0 1.5 1.5 2.0 2.0 3D NMO/DMO 3D ZO CRS SEG 72nd Annual Meeting, Salt Lake City 2002 – p.12

Real data example W I T CDP bin no. CDP bin no. 0 50 100 150 200 250 300 0 50 100 150 200 250 300 0 0 0.5 0.5 0.40 3 0.35 0.30 2 0.25 Time [s] Time [s] 1 1.0 1.0 0.20 0.15 0 0.10 -1 0.05 -2 0 1.5 1.5 2.0 2.0 Curvature [1/km] Coherence SEG 72nd Annual Meeting, Salt Lake City 2002 – p.13

Attributes W I T CRS Stack attributes have many applications: Macro-velocity inversion Tu. 2.10 pm: Tomographic velocity model inversion using kinematic wavefield attributes – E. Duveneck and P . Hubral, (IT 2.3) SEG 72nd Annual Meeting, Salt Lake City 2002 – p.14

Attributes W I T CRS Stack attributes have many applications: Macro-velocity inversion Tu. 2.10 pm: Tomographic velocity model inversion using kinematic wavefield attributes – E. Duveneck and P . Hubral, (IT 2.3) Accurate redatuming SEG 72nd Annual Meeting, Salt Lake City 2002 – p.14

Attributes W I T CRS Stack attributes have many applications: Macro-velocity inversion Tu. 2.10 pm: Tomographic velocity model inversion using kinematic wavefield attributes – E. Duveneck and P . Hubral, (IT 2.3) Accurate redatuming Projected Fresnel zone SEG 72nd Annual Meeting, Salt Lake City 2002 – p.14

Attributes W I T CRS Stack attributes have many applications: Macro-velocity inversion Tu. 2.10 pm: Tomographic velocity model inversion using kinematic wavefield attributes – E. Duveneck and P . Hubral, (IT 2.3) Accurate redatuming Projected Fresnel zone Geometrical spreading factor SEG 72nd Annual Meeting, Salt Lake City 2002 – p.14

Attributes W I T CRS Stack attributes have many applications: Macro-velocity inversion Tu. 2.10 pm: Tomographic velocity model inversion using kinematic wavefield attributes – E. Duveneck and P . Hubral, (IT 2.3) Accurate redatuming Projected Fresnel zone Geometrical spreading factor Wavefield separation SEG 72nd Annual Meeting, Salt Lake City 2002 – p.14

Attributes W I T CRS Stack attributes have many applications: Macro-velocity inversion Tu. 2.10 pm: Tomographic velocity model inversion using kinematic wavefield attributes – E. Duveneck and P . Hubral, (IT 2.3) Accurate redatuming Projected Fresnel zone Geometrical spreading factor Wavefield separation Model-independent time migration SEG 72nd Annual Meeting, Salt Lake City 2002 – p.14

Sigsbee 2A data W I T Distance [kft] 20 40 60 80 0 14 12 10 Depth [kft] 10 8 20 6 Interval velocity model [kft/s] SEG 72nd Annual Meeting, Salt Lake City 2002 – p.15

Sigsbee 2A data W I T Specific properties: Acoustic FD modeling of marine data Model and data courtesy of SMAART JV. SEG 72nd Annual Meeting, Salt Lake City 2002 – p.16

Sigsbee 2A data W I T Specific properties: Acoustic FD modeling of marine data No water-column related multiples Model and data courtesy of SMAART JV. SEG 72nd Annual Meeting, Salt Lake City 2002 – p.16

Sigsbee 2A data W I T Specific properties: Acoustic FD modeling of marine data No water-column related multiples But: internal multiples Model and data courtesy of SMAART JV. SEG 72nd Annual Meeting, Salt Lake City 2002 – p.16

Sigsbee 2A data W I T Specific properties: Acoustic FD modeling of marine data No water-column related multiples But: internal multiples Virtually no uncorrelated noise Model and data courtesy of SMAART JV. SEG 72nd Annual Meeting, Salt Lake City 2002 – p.16

Sigsbee 2A data W I T Specific properties: Acoustic FD modeling of marine data No water-column related multiples But: internal multiples Virtually no uncorrelated noise Strong variation of model complexity Model and data courtesy of SMAART JV. SEG 72nd Annual Meeting, Salt Lake City 2002 – p.16