75 th SEG Annual Meeting, Houston 2005 Klüver & Mann Event-consistent smoothing and Introduction automated picking in CRS-based 3D CRS stack Velocity determination seismic imaging NIP waves CRS tomography Workflow Tilman Klüver and Jürgen Mann Event-aligned volume Smoothing Picking Wave Inversion Technology (WIT) Results Geophysical Institute, University of Karlsruhe (TH) Conclusions November 8, 2005 W I T
75 th SEG Annual Overview Meeting, Houston 2005 Klüver & Mann Introduction Introduction 3D CRS stack 3D Common-Reflection-Surface (CRS) stack Velocity determination NIP waves CRS tomography Velocity determination with 3D CRS attributes Workflow Event-aligned volume CRS-based workflow Smoothing Picking The event-aligned volume Results Conclusions Event-consistent smoothing Automated picking Results Conclusions W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction ◮ The Common-Reflection-Surface (CRS) stack 3D CRS stack Velocity determination provides NIP waves ◮ high S/N stacked ZO volume CRS tomography ◮ coherence value for each sample Workflow ◮ kinematic wavefield attributes for each sample Event-aligned volume ➥ generalised, high density stacking velocity analysis Smoothing Picking ◮ The CRS attributes can further be used for many Results applications, e. g.: Conclusions ◮ calculation of projected Fresnel zone and geometrical spreading factor ◮ improved AVO-analysis ◮ tomographic determination of macro-velocity models W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction ◮ The Common-Reflection-Surface (CRS) stack 3D CRS stack Velocity determination provides NIP waves ◮ high S/N stacked ZO volume CRS tomography ◮ coherence value for each sample Workflow ◮ kinematic wavefield attributes for each sample Event-aligned volume ➥ generalised, high density stacking velocity analysis Smoothing Picking ◮ The CRS attributes can further be used for many Results applications, e. g.: Conclusions ◮ calculation of projected Fresnel zone and geometrical spreading factor ◮ improved AVO-analysis ◮ tomographic determination of macro-velocity models W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves ◮ CRS attributes are subject to CRS tomography ◮ outliers Workflow ◮ non-physical fluctuations Event-aligned volume Smoothing ➥ Attribute-based applications are impaired Picking Results ◮ Application considered here: Conclusions Tomographic determination of macro-velocity models using CRS-attributes W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves ◮ CRS attributes are subject to CRS tomography ◮ outliers Workflow ◮ non-physical fluctuations Event-aligned volume Smoothing ➥ Attribute-based applications are impaired Picking Results ◮ Application considered here: Conclusions Tomographic determination of macro-velocity models using CRS-attributes W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves ◮ CRS attributes are subject to CRS tomography ◮ outliers Workflow ◮ non-physical fluctuations Event-aligned volume Smoothing ➥ Attribute-based applications are impaired Picking Results ◮ Application considered here: Conclusions Tomographic determination of macro-velocity models using CRS-attributes W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography CRS tomography ◮ Advantages: Workflow ◮ picking in simulated ZO volume of high S/N ratio Event-aligned volume Smoothing (output of CRS) ◮ pick locations independent of each other Picking Results ◮ very few picks required Conclusions ◮ Quality of result depends on quality of input CRS attributes W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography CRS tomography ◮ Advantages: Workflow ◮ picking in simulated ZO volume of high S/N ratio Event-aligned volume Smoothing (output of CRS) ◮ pick locations independent of each other Picking Results ◮ very few picks required Conclusions ◮ Quality of result depends on quality of input CRS attributes W I T
75 th SEG Annual Introduction Meeting, Houston 2005 Klüver & Mann Introduction CRS − stack 3D CRS stack Velocity determination NIP waves CRS tomography Smoothing Workflow Event-aligned volume optional restacking Smoothing Picking Results automated picking Conclusions NIP−wave tomography Migration W I T
75 th SEG Annual 3D CRS attributes Meeting, Houston 2005 Klüver & Mann Traveltime depends on eight attributes: Introduction t 2 ( ∆ ξ � 2 t 0 + 2 p ξ · ∆ ξ � ξ , h ) = ξ ξ ξ 3D CRS stack � � Velocity determination ∆ ξ ξ T M ξ ∆ ξ ξ + h T M h h + 2 t 0 ξ ξ NIP waves CRS tomography Workflow Event-aligned volume CRS surface Smoothing p ξ = 1 v 0 ( sin α cos ψ , sin α sin ψ ) T 0.6 Picking Depth [m] Time [s] Results Time [s] 0.4 M h = 1 v 0 DK NIP D T Conclusions 400 ξ ( , t ) 0.2 0 300 v 0 DK N D T 200 M ξ = 1 h [m] 0 100 0 Depth [m] −200 NIP: normal incidence point −400 −600 −1000 −500 0 500 Midpoint [m] 1000 W I T
75 th SEG Annual 3D CRS attributes Meeting, Houston 2005 Klüver & Mann Traveltime depends on eight attributes: Introduction t 2 ( ∆ ξ � 2 t 0 + 2 p ξ · ∆ ξ � ξ ξ , h ) = ξ ξ 3D CRS stack � � Velocity determination ∆ ξ ξ T M ξ ∆ ξ ξ + h T M h h + 2 t 0 ξ ξ NIP waves CRS tomography Workflow Event-aligned volume Smoothing R R ξ ξ Picking NIP N Results Conclusions α α NIP NIP W I T
75 th SEG Annual NIP waves and velocities Meeting, Houston 2005 Klüver & Mann ( M h p ξ , ) T , , ξ ξ ξ ξ ξ Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results NIP Conclusions CRS attributes M h and p ξ at ( t 0 , ξ ξ ξ ) describe second-order traveltime approximation of W I T emerging NIP wave.
75 th SEG Annual NIP waves and velocities Meeting, Houston 2005 Klüver & Mann ( M h p ξ , ) T , , ξ ξ ξ ξ ξ Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Event-aligned volume Smoothing Picking Results NIP Conclusions In consistent velocity models, NIP waves focus at zero traveltime. W I T
75 th SEG Annual Tomography with CRS attributes Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Find a velocity model in which all considered NIP Event-aligned volume waves, described by kinematic wavefield attributes, Smoothing are correctly modelled. Picking Results Conclusions W I T
75 th SEG Annual Tomography with CRS attributes Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS tomography Workflow Find a velocity model in which all considered NIP Event-aligned volume waves, described by kinematic wavefield attributes, Smoothing are correctly modelled. Picking Results Remark: Conclusions in 3D, M h is only required for one azimuth. W I T
75 th SEG Annual CRS-based workflow Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS − stack CRS tomography Workflow Event-aligned volume Smoothing Picking Results Conclusions NIP−wave tomography Migration W I T
75 th SEG Annual CRS-based workflow Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS − stack CRS tomography ◮ fluctuations in CRS attributes, Workflow which are not consistent with Event-aligned volume theory, influence the inversion Smoothing result Picking Results ◮ manual picking is very time Conclusions NIP−wave tomography consuming, especially in 3D Migration W I T
75 th SEG Annual CRS-based workflow Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves CRS − stack CRS tomography ◮ fluctuations in CRS attributes, Workflow which are not consistent with Event-aligned volume theory, influence the inversion Smoothing result Picking Results ◮ manual picking is very time Conclusions NIP−wave tomography consuming, especially in 3D Migration W I T
75 th SEG Annual CRS-based workflow Meeting, Houston 2005 Klüver & Mann Introduction 3D CRS stack Velocity determination NIP waves ◮ How to remove outliers and CRS − stack CRS tomography fluctuations in the attributes? Workflow Event-aligned volume ◮ Where to pick the limited Smoothing number of locally coherent Picking reflection events needed in Results NIP-wave tomography? Conclusions NIP−wave tomography ◮ How to do this automatically? Migration W I T
Recommend
More recommend
