W I T 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
Overview W I T Development of the CRS Stack EAGE Conference & Exhibition, Florence 2002 – p.2
Overview W I T Development of the CRS Stack How does the CRS Stack work ? EAGE Conference & Exhibition, Florence 2002 – p.2
Overview W I T 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
Overview W I T 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
Overview W I T 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
Overview W I T 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
Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking EAGE Conference & Exhibition, Florence 2002 – p.3
Development of the CRS Stack W I T Multi-parameter moveout operators for data-driven stacking 2-D zero-offset 3 parameters EAGE Conference & Exhibition, Florence 2002 – p.3
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 EAGE Conference & Exhibition, Florence 2002 – p.3
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 EAGE Conference & Exhibition, Florence 2002 – p.3
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 EAGE Conference & Exhibition, Florence 2002 – p.3
W I T Arbitrary acquisition configuration G 2h e c a f r y u s m n S o � x G − x S � h = 1 i x t X i � s 0 i u q c 2 y G − y S A � x G + x S � m = 1 finite-offset ray � zero-offset ray y G + y S 2 R R* Reflector EAGE Conference & Exhibition, Florence 2002 – p.4
CRS stacking operators for ZO W I T 3-D case: � 2 + � m T A � h T B � � c · � m m + � h t 2 � t 0 − � � hyp = EAGE Conference & Exhibition, Florence 2002 – p.5
CRS stacking operators for ZO W I T 3-D case: � 2 + � m T A � h T B � � c · � m m + � h t 2 � t 0 − � � hyp = c : two-component vector � A , B : symmetric 2 × 2 matrices EAGE Conference & Exhibition, Florence 2002 – p.5
CRS stacking operators for ZO W I T 3-D case: � 2 + � m T A � h T B � � c · � m m + � h t 2 � t 0 − � � hyp = c : two-component vector � A , B : symmetric 2 × 2 matrices 2-D case: � 2 + am 2 + bh 2 � t 2 � � hyp = t 0 − cm EAGE Conference & Exhibition, Florence 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] EAGE Conference & Exhibition, Florence 2002 – p.6
Implementation W I T Data volume 1.2 ZO grid 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] EAGE Conference & Exhibition, Florence 2002 – p.7
Implementation W I T Data volume 1.2 ZO grid 1.1 1 CRS operator 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] EAGE Conference & Exhibition, Florence 2002 – p.8
Consequences W I T approach is purely data-driven EAGE Conference & Exhibition, Florence 2002 – p.9
Consequences W I T approach is purely data-driven use of full multi-coverage data volume EAGE Conference & Exhibition, Florence 2002 – p.9
Consequences W I T 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
Consequences W I T 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
Consequences W I T 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
Consequences W I T 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
Attributes W I T NIP and Normal wave along ZO ray EAGE Conference & Exhibition, Florence 2002 – p.10
Attributes W I T → CRS Stack attributes have many applications − more accurate stacking velocity EAGE Conference & Exhibition, Florence 2002 – p.11
Attributes W I T → CRS Stack attributes have many applications − more accurate stacking velocity projected Fresnel zone for parsimonious migration EAGE Conference & Exhibition, Florence 2002 – p.11
Attributes W I T → 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
Attributes W I T → 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
Attributes W I T → 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
Attributes W I T → 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
Stacking velocity W I T 2-D case: cos 2 α stack = 2 t 0 1 / v 2 v 0 R NIP EAGE Conference & Exhibition, Florence 2002 – p.12
Stacking velocity W I T 2-D case: cos 2 α stack = 2 t 0 1 / v 2 v 0 R NIP 3-D case: r 2 h = r ( cos φ , sin φ ) T − � → t 2 CMP = t 2 0 + v 2 stack EAGE Conference & Exhibition, Florence 2002 – p.12
Stacking velocity W I T 2-D case: cos 2 α stack = 2 t 0 1 / v 2 v 0 R NIP 3-D case: r 2 h = r ( cos φ , sin φ ) T − � → t 2 CMP = t 2 0 + v 2 stack stack = 2 t 0 ( cos φ , sin φ ) TMT T ( cos φ , sin φ ) T 1 / v 2 v 0 EAGE Conference & Exhibition, Florence 2002 – p.12
Stacking velocity W I T much more traces involved in stacking velocity determination compared to conventional methods EAGE Conference & Exhibition, Florence 2002 – p.13
Stacking velocity W I T 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
Stacking velocity W I T 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
Stacking velocity W I T 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
Real data example W I T Result of NMO/DMO/Stack CMP location approx. 13km 0.5 1.0 Time [s] 1.5 2.0 2.5 3.0 EAGE Conference & Exhibition, Florence 2002 – p.14
Real data example W I T Result of CRS Stack CMP location approx. 13km 0.5 1.0 Time [s] 1.5 2.0 2.5 3.0 EAGE Conference & Exhibition, Florence 2002 – p.15
Real data example W I T Detected stacking velocity in [m/s] CMP 0.5 5000 4500 1.0 4000 Time [s] 1.5 3500 3000 2.0 2500 2000 2.5 EAGE Conference & Exhibition, Florence 2002 – p.16
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