Download presentation
Presentation is loading. Please wait.
1
Arbitrary Parameter Extraction, Stationary Phase Migration, and Tomographic Velocity Analysis Jing Chen University of Utah
2
Outline Parameter Extraction Parameter Extraction Stationary Phase Migration Stationary Phase Migration Tomographic Velocity Analysis Tomographic Velocity Analysis Conclusions Conclusions
3
Parameter Extraction Extract specular-ray related parameters from prestack migration SG R
4
Why Specular-Ray Parameters Needed ? Prestack Depth Migration Prestack Depth Migration Traveltime Inversion Traveltime Inversion Tomographic MVA Tomographic MVA AVO AVO Etc... Etc...
5
Prestack Migration Operator ImageWeightDataAperture
6
Stationary Phase Approximation
7
Weighted Prestack Migration Operator ImageWeightDataAperture Parameter
8
Stationary Phase Approximation
9
Specular-Ray Related Parameters
10
R Source Receiver Midpoint Traveltime Reflector Normal Departure Angle Emergence Angle Incidence Angle
11
Parameter Extraction Synthetic Data Examples: Migrate a COG; Migrate a COG; Extract Midpoint Coordinates, Extract Midpoint Coordinates, Traveltimes, and Incidence Angles. Traveltimes, and Incidence Angles.
12
Kirchhoff Migration of a COG Distance (km) Depth (km) 4 2 0 1680 1 3 412
13
Weighted Kirchhoff Migration of a COG Distance (km) Depth (km) 4 2 0 1680 1 3 412 Extra Weight
14
Division of Two COG Images =
15
COG Incidence Angles 0 10 20 (Degrees ) Distance (km) Depth (km) 4 2 0 1680
16
COG Incidence Angles 0 10 20 Distance (km) Depth (km) 4 2 0 1680 (Degrees )
17
COG Traveltimes 0 3.5 (Seconds) Distance (km) Depth (km) 4 2 0 1680 1.75
18
COG Traveltimes 0 3.5 Distance (km) Depth (km) 4 2 0 1680 1.75 (Seconds)
19
COG S-R Midpoint Coordinates 0 20 (km) Distance (km) Depth (km) 4 2 0 1680 10
20
COG S-R Midpoint Coordinates 0 20 Distance (km) Depth (km) 4 2 0 1680 10 (km)
21
Verification of Extracted Parameters Distance (km) Depth (km) 4 2 0 1680 1 3 412
22
COG S-R Midpoint Coordinates 0 20 Distance (km) Depth (km) 4 2 0 1680 10 (km)
23
COG Traveltimes 0 3.5 Distance (km) Depth (km) 4 2 0 1680 1.75 (Seconds)
24
Verification of Extracted Parameters Trace Midpoint Coordinates Time (sec) 2 1 151311 Trvaeltimes Extracted
25
Applications Stationary Phase Migration Stationary Phase Migration Tomographic Velocity Analysis Tomographic Velocity Analysis
26
Stationary Phase Migration Migrate traces within Fresnel zone Migrate traces within Fresnel zone Reject traces out of Fresnel zone Reject traces out of Fresnel zone Suppress alias artifacts Suppress alias artifacts SPM uses specular-ray parameters to :
27
Stationary Phase Migration Algorithm Algorithm Synthetic Data Example Synthetic Data Example Field Data Example Field Data Example
28
Stationary Phase Migration Operator Minimum Aperture Fresnel zone width Stationary phase point Fresnel Zone Schleicher et al. (1997) :
29
Stationary Phase Migration Algorithm Algorithm Synthetic Data Example Synthetic Data Example Field Data Example Field Data Example
30
Kirchhoff Migration of a COG Distance (km) Depth (km) 4 2 0 1680 1 3 412
31
Stationary Phase Mig. of a COG 4 2 0 1680 1 3 412 Distance (km) Depth (km)
32
Migration Operator Trace Contributions
33
Trace Contributions : KM Trace Number Depth (km) 4 2 0 3001500
34
Trace Contributions : SPM Trace Number Depth (km) 4 2 0 3001500
35
Trace Contributions : KM Trace Number Depth (km) 4 2 0 3001500
36
Trace Contributions : SPM Trace Number Depth (km) 4 2 0 3001500
37
Trace Contributions : KM Trace Number Depth (km) 4 2 0 3001500
38
Trace Contributions : SPM Trace Number Depth (km) 4 2 0 3001500
39
0 35 70 (Deg ) Offset (km) Depth (km) 4 2 0 3 0 CIG Offset (km) Depth (km) 4 2 0 30 Incidence Angle
40
0 35 70 (Deg ) Offset (km) Depth (km) 4 2 0 3 0 CIG Offset (km) Depth (km) 4 2 0 30 Incidence Angle
41
Stacked SPM Image After Muting 4 2 0 1680 1 3 412 Distance (km) Depth (km)
42
Stacked SPM Image Without Muting 4 2 0 1680 1 3 412 Distance (km) Depth (km)
43
Stationary Phase Migration Algorithm Algorithm Synthetic Data Example Synthetic Data Example Field Data Example Field Data Example
44
Kirchhoff Migration of a COG Distance (km) Depth (km) 6 4 0 1460 2 2124810
45
Stationary Phase Mig. of a COG Distance (km) Depth (km) 6 4 0 1460 2 2124810
46
Stacked KM Image Distance (km) Depth (km) 6 4 0 1460 2 2124810
47
Stacked SPM Image Distance (km) Depth (km) 6 4 0 1460 2 2124810
48
Stationary Phase Mig. vs Wavepath Mig. SG Both approaches suppress alias artifacts Both approaches suppress alias artifacts WM measures emergence angles in the data domain WM measures emergence angles in the data domain SPM extracts parameters in the migration domain SPM extracts parameters in the migration domain SPM extracts more parameters SPM extracts more parameters WM is faster WM is faster SPM may be more robust in parameter estimations SPM may be more robust in parameter estimations
49
Applications Stationary Phase Migration Stationary Phase Migration Tomographic Velocity Analysis Tomographic Velocity Analysis
50
Build up Initial Migration Velocity Build up Initial Migration Velocity Migrate Seismic Data Migrate Seismic Data Obtain S & R Coordinates Obtain S & R Coordinates Find Specular-Ray Paths Find Specular-Ray Paths Pick Depth Residual Moveouts Pick Depth Residual Moveouts Pick Reflector Positions Pick Reflector Positions Update Velocities Update Velocities Migrate Seismic Data With Migrate Seismic Data With Updated Velocities Updated Velocities Repeat Above Steps Repeat Above Steps Steps in Tomographic MVA
51
Layer-Stripping Iteration Layer-Stripping Iteration Partial Migration Iteration Partial Migration Iteration Reflector Adjustment Iteration Reflector Adjustment Iteration SIRT Iteration SIRT Iteration Four Recursive Iterations
52
Seismic Data Initial Migration Velocities Kirchhoff Migration + Stationary Phase CIGs Source Xs( Xi,h ) Receiver Xr( Xi,h ) ZO Image Auto Scan Residual Moveouts DZ( Xi,h ) Reflector Positions Xi Xi Preparing Input For Velocity Update Xi DZ( Xi,h ) Xs( Xi,0 ) Xr( Xi,0 ) Xs( Xi,h ) Xr( Xi,h )
53
Velocity Updating Scheme DZ --> DT 2 Pt. Ray Tracing Initial Mig. Velocity Back Projection: SIRT DT --> DS New Slowness : S=S+DS New DT Misfit Func. Decrease? YesNo SIRT Iteration Adjust Reflector Depths New DZ DZ --> DT Misfit Func. Decrease? STOP No Yes ReflectorAdjustmentIteration
54
Initial Migration Velocity 4900 10000 (ft/sec) Distance (km) Depth (km) 3 1 0 15100 7450 5 2
55
Image With Initial Velocity Distance (km) Depth (km) 1.0 0.3 151005 2.0
56
Peak-Amplitude Positions Distance (km) Depth (km) 1.0 0.3 151005 2.0
57
Reflectors Picked Distance (km) Depth (km) 1.0 0.3 151005 2.0
58
Reflectors Picked Distance (km) Depth (km) 1.0 0.3 151005 2.0
59
Depth Residuals Picked Horizontal Coordinates Along Reflector (km) Depth Residual Moveouts (m)
60
Depth Residuals Picked After Median Filtering and Muting Horizontal Coordinates Along Reflector (km) Depth Residual Moveouts (m)
61
Raypaths Distance (km) Depth (km) 1.0 0.3 151005 2.0
62
Raypaths Distance (km) Depth (km) 1.0 0.3 151005 2.0
63
Misfit Function vs Iteration No. SIRT Iterations Reflector Adjustment Iterations Misfit Function Iteration Number
64
Velocity Increment -50 150 (ft/sec) Distance (km) Depth (km) 3 1 0 15100 50 5 2
65
Image With Updated Velocity Distance (km) Depth (km) 1.0 0.3 151005 2.0
66
Image With Initial Velocity Distance (km) Depth (km) 1.0 0.3 151005 2.0
67
Common Image Gathers Depth (km) 1.2 0.5 2.0 With Initial Velocity
68
Common Image Gathers Depth (km) 1.2 0.5 2.0 With Updated Velocity
69
Conclusions Specular-ray related parameters can be accurately estimated from presatck migration Specular-ray related parameters can be accurately estimated from presatck migration SPM produces fewer alias artifacts and improves horizon continuity SPM produces fewer alias artifacts and improves horizon continuity Automatic tomographic velocity analysis is able to update the migration velocity Automatic tomographic velocity analysis is able to update the migration velocity
70
Acknowledgements I thank the 1999 UTAM sponsors for their supports I thank the 1999 UTAM sponsors for their supports I thank Fuhao Qin, Yonghe Sun and JC Wan of Hess for their helps I thank Fuhao Qin, Yonghe Sun and JC Wan of Hess for their helps
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.