Adaptive Grid Reverse-Time Migration

1
Adaptive Grid Reverse-Time Migration

• Yue Wang

2
Outline

• Motivation and Objective
• Reverse Time Methodology
• Salt Dome Model Test
• Field Data Test
• Conclusions

3
Problem

• Kirchhoff migration is not optimal for complex
  velocity model.

4
Marmousi Model
0
Depth (km)
Low-velocity wedge
3
0
9
Distance (km)
5
Problem
Kirchhoff migration

• Using first arrival time

Difficulty in imaging
6
Problem
Reverse-Time Migration RTM)

• Using multi-arrival time

Image complex structure
Expensive
7
Solution
Variable grid size
Variable time step
Fast RTM
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Objective

• Develop fast reverse time migration for land and
  marine multi-component data

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Outline

• Motivation and Objective
• Reverse Time Methodology
• Salt Dome Model Test
• Field Data Test
• Conclusions

?
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Reverse Time Operator
A 2-4 staggered-grid FD solver

• Elastic wave equation

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Variable Grid Size
Low velocity
High velocity
Depth
Distance
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Variable Grid Size
Fine grid (dx dz)
Coarse grid (3dx 3dz)
z
13
Variable Grid Size
Fine grid
Use wave equation to propagate waves
Coarse grid
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Variable Time Step
coarse grid, fine time step
Depth
coarse grid, coarse time step
Distance
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Variable Time Step
t
z
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Variable Time Step
t
Fine time step
Use wave equation to propagate waves
Coarse time step
z
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Variable Time Step
Falk et al. (1998, Geophys. Pros. )
1. Non-staggered-grid FD 2.
2x time step change
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Variable Time Step
The new method 1.
Staggered-grid FD 2. 3x time step
change
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Numerical Results
Time t1
Amplitude
Depth
Fine time step
Coarse time step
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Outline

• Motivation and Objective
• Reverse Time Methodology
• Salt Dome Model Test
• Field Data Test
• Conclusions

?
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Salt Model
0
Depth (km)
2.7
0
4.5
Distance (km)
22
Velocity Profile
P
S
0
0
Depth (km)
Depth (km)
2.7
2.7
1.5
4
0
2
Velocity (km/s)
Velocity (km/s)
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Velocity Profile
P
S
Fine grid size Fine time step
0
Coarse grid size Coarse time step
Depth (km)
2.7
1.5
4
0
2
Velocity (km/s)
Velocity (km/s)
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Shot Gather
Normal Stress
Vertical
Horizontal
0
Time (s)
2
Distance (km)
0.9
3.6
Distance (km)
0.9
3.6
Distance (km)
0.9
3.6
25
Kirchhoff Migration
0
Depth (km)
2.5
0.45
4.05
Distance (km)
26
Kirchhoff Migration
0
Depth (km)
2.5
0.45
4.05
Distance (km)
27
Reverse Time Migration
0
Depth (km)
2.5
0.45
4.05
Distance (km)
28
Reverse Time Migration
0
Depth (km)
2.5
0.45
4.05
Distance (km)
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Outline

• Motivation and Objective
• Reverse Time Methodology
• Salt Dome Model Test
• Field Data Test
• Conclusions

?
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Processed CSG
Radial Component
Vertical Component
0
Time (s)
2.7
0
80
0
80
Trace Number
Trace Number
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Common Offset Gather(Vertical Component)
0
Depth (km)
Signal/Noise Ratio High
4
0
27
Distance (km)
32
Common Offset Gather(Radial Component)
0
Depth (km)
Signal/Noise Ratio Low
4
0
27
Distance (km)
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Kirchhoff Migration(Vertical Component)
0
Depth (km)
4
0
27
Distance (km)
34
Kirchhoff Migration(Radial Component)
0
Depth (km)
4
0
27
Distance (km)
35
RTM
0
Depth (km)
4
0
27
Distance (km)
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Comparison
RTM
KM
0
Depth (km)
4
0
27
0
27
Distance (km)
Distance (km)
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Outline

• Motivation and Objective
• Reverse Time Methodology
• Salt Dome Model Test
• Field Data Test
• Conclusions and Future Work

?
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Conclusions

• Variable RTM 10 times faster than standard RTM
• Migrates Land and marine multi-component data
• Use primary and multiple reflections for imaging

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Acknowledgement

• We are grateful to the 1999 sponsors of the UTAM
  consortium for the financial support

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Raw CSG
Radial Component
Vertical Component
0
Time (s)
2.7
0
80
0
80
Trace Number
Trace Number
41
Main Processing Flow
Geometry assignment, datuming and so on
Trace editing
Surface wave attenuation, amplitude balancing
P-velocity analysis
S-velocity analysis
Relative gain compensation, surface velocity
estimation
KM
RTM
42
Shallow Velocity
0
Depth (km)
0.4
0
27
Distance (km)
43
Future Work

• Apply the RTM scheme for data set with more
  complex structures.