Transcript Migration Deconvolution - King Abdullah University of

V.2 Wavepath Migration
Overview
Kirchhoff migration smears a reflection along a fat
ellipsoid, so that most of the reflection energy is placed in
regions far from the actual specular reflection point. This is
both inefficient and artifact-prone. To place the reflection
energy at or near its specular reflection point we first perform a
local slant stack on the trace, and propagate it along its
associated wavepath cosnistent with the incident angle of the
arrival. The reflection is now smeared along the portion of the
wavepath centered about the specular reflection point. Thus
wavepath migration smears the reflection energy along a small
portion of a wavepath, which reduces both cost and aliasing
artifacts. The drawback is the sensitivity of the incidence angle
calculation due to noise or inaccurate migration velocities.
Outline
•
•
•
•
•
Problem & Motivation
Theory
Synthetic Numerical Examples
Field Data Numerical Examples
Conclusions
Migration Accuracy vs $$$
Full-Wave
Target RTM
No Approx.
Ray-Beam Phase-Shift
Kirchhoff
Expense
Multiple Arriv
Anti-aliasing
Problem
B
R
C
A
S
A
B
C
3-D KM of a Single Trace
Problem & Solution
Problem: Kirchhoff Migration Expensive;
O(N3 ) per Trace
Reflection Energy Smeared All
Along Ellipse
Solution: Wavepath Migration. Smear
Energy along Wavepaths not
1.5
Ellipses; O(N )per Trace
Smear Reflection along Wavepath
Inc. Angle
by Slant Stack
S
R
Image
Point
Fresnel Zone
MVA Objectives
• Can WMVA effectively improve the
migration velocity?
• Whether the WMVA updated velocity
differs much from the KMVA updated
velocity?
• Can WMVA be much faster than
KMVA?
Solution
B
R
C
A
S
A
B
C
3-D WM of a Single
Trace
Problem & Solution
Problem: Kirchhoff Migration Expensive;
O(N3 ) per Trace
Reflection Energy Smeared All
Along Ellipse
Solution: Wavepath Migration. Smear
Energy along Wavepaths not
1.5
Ellipses; O(N )per Trace
Numerical Tests
• 3-D Pt. Scatterer Model
3-D Prestack KM Point Scatterer Response
Reflectivity
Z0-9
0.4
Reflectivity
0.1
-0.05
Z0-1
-0.2
1
1
1
Y Offset (km)
Y Offset (km)
X Offset (km)
0
X Offset (km)
0
Reflectivity
0.02
Reflectivity
1
Z0
1
-0.5
Z0+8
-0.01
1
1
Y Offset (km)
X Offset (km)
0
1
1
Y Offset (km)
X Offset (km)
0
3-D Prestack WM Point Scatterer Response
Reflectivity
Z0-9
0.4
Reflectivity
0.1
-0.05
Z0-1
-0.2
1
1
1
Y Offset (km)
Y Offset (km)
X Offset (km)
0
X Offset (km)
0
Reflectivity
0.02
Reflectivity
1
Z0
1
-0.5
Z0+8
-0.01
1
1
Y Offset (km)
X Offset (km)
0
1
1
Y Offset (km)
X Offset (km)
0
Numerical Tests
• 3-D Pt. Scatterer Model
• 2-D SEG/EAGE overthrust
model
Velocity Model
0km
0
Depth (m)
10km
15km
6000
Velocity (m/sec)
150
0
5km
3000
4500
250
0
Wavepath vs Kirchhoff Migration
WM Image (CPU: 0.088)
(Slant Stack)
4
Depth (km)
0.5
2.5
Offset (km)
10
KM Image (CPU: 1.0)
Structure
4
Offset (km)
10
4
Offset (km)
10
Numerical Tests
• 3-D Pt. Scatterer Model
• 2-D SEG/EAGE overthrust model
• 2-D Canadian Land Data
A Raw CSG of Husky Field Data
1
Time (sec)
0
3.0
Trace Number
300
Husky Field Data Results
KM (CPU:1.0)
0
WM (CPU: 2.23)
Offset (km)
14
0
Depth (km)
A
14
A
B
7
Offset (km)
0
B
Husky Field Data Results
KM Image (Box A)
5.5
2.5
2.5
2.5
Depth (km)
Offset (km)
Depth (km)
2.5
WM Image (Box A)
5.0
5.0
Offset (km)
5.5
Husky Field Data Results
KM (CPU:1.0)
0
WM (Slant Stack, CPU: 0.24)
Offset (km)
14
0
Offset (km)
14
0
Depth (km)
A
A
B
7
B
Numerical Tests
• 3-D Pt. Scatterer Model
• 2-D SEG/EAGE overthrust model
• 2-D Canadian Land Data
• 3-D SEG/EAGE Salt Model
Receiver Distribution
Crossline (m)
1920
2320
1920
Inline (m)
4480
Inline Velocity Model
0
Offset (km)
9.2
Depth (km)
0
3.8
SALT
Inline KM (CPU=1)
0
Depth (km)
0
3.
8
Offset (km)
Inline WM (CPU=1/33)
9.2
0
Offset (km)
9.2
Zoom Views of Inline Sections
Kirchhoff
WM
Sub
WM
Model
Offset: 3~6.5 km,
Depth: 0.3~1.8 km
Migration of SEG Salt Data (Crossline Sections)
KM
WM
Model
Sub
WM
Offset: 1.8~4 km,
Depth: 0.6~2.1 km
Migration of SEG Salt Data (Horizontal Slices)
KM
WM
Model
Sub
WM
Inline: 1.8~7.2 km,
Crossline: 0~4 km
Numerical Tests
• 3-D Pt. Scatterer Model
• 2-D SEG/EAGE Overthrust model
• 2-D Canadian Land Data
• 3-D SEG/EAGE Salt Model
• 3-D W. Texas Data
A Common Shot Gather
Time (sec)
0
3.4
54
Trace Number
193
Receiver Distribution
Crossline (km)
3.5
1.2
1.5
Inline (km)
4.5
Receiver Distribution
Crossline (km)
3.5
1.2
1.5
Inline (km)
4.5
Inline KM (CPU=1)
0.4
Depth (km)
0.8
3.8
Offset (km)
Inline WM (CPU=1/14)
4.5
0.4
Offset (km)
4.5
Inline KM (CPU=1)
Inline WM (CPU=1/50)
(subsample)
0.4
Depth (km)
0.8
3.8
Offset (km)
4.5
0.4
Offset (km)
4.5
Crossline KM (CPU=1) Crossline WM (CPU=1/14)
0.3
Depth (km)
0.8
3.3
Offset (km)
3.5
0.3
Offset (km)
3.5
Crossline KM (CPU=1) Crossline WM (CPU=1/50)
(subsample)
0.3
Depth (km)
0.8
3.3
Offset (km)
3.5
0.3
Offset (km)
3.5
Horizontal Slices (Depth=2.5 km)
KM (CPU=1)
WM (CPU=1/14)
Inline: 0~4.6 km,
WM (Sub, CPU=1/50)
Crossline: 0~3.8
Numerical Tests
• 3-D Pt. Scatterer Model
• 2-D SEG/EAGE Overthrust model
• 2-D Canadian Land Data
• 3-D SEG/EAGE Salt Model
• 3-D W. Texas Data
• MVA
Initial Migration Velocity
0
Horizontal Distance (km)
18
2.1
(km /s)
Depth (km)
0
1.5
1.5
0
KM Image with Initial Velocity
18 km
Depth (km)
0
1.5
KMVA Velocity Changes in the 1st Iteration
0
(m /s)
Depth (km)
50
0
1.5
2 km
KM Image with Initial Velocity
Depth (m)
1070
1260
KM Image with Updated Velocity
Depth (m)
1070
1260
9 km
KMVA CIGs with Initial Velocity
Depth (km)
0
1.5
KMVA CIGs with Updated Velocity
0
KMVA Velocity Changes in the 1st Iteration (CPU=6)
18 km
0
(m /s)
Depth (km)
50
0
1.5
WMVA Velocity Changes in the 1st Iteration (CPU=1)
0
(m /s)
Depth (km)
50
0
1.5
2 km
WM Image with Initial Velocity
Depth (m)
1070
1260
WM Image with Updated Velocity
Depth (m)
1070
1260
9 km
WMVA CIGs with Initial Velocity
Depth (km)
0
1.5
WMVA CIGs with Updated Velocity
2 km
KM Image with Initial Velocity
Depth (m)
1070
1260
KM Image with KMVA Updated Velocity
Depth (m)
1070
1260
KM Image with WMVA Updated Velocity
Depth (m)
1070
1260
9 km
Numerical Tests
• 3-D Pt. Scatterer Model
• 2-D SEG/EAGE Overthrust model
• 2-D Canadian Land Data
• 3-D SEG/EAGE Salt Model
• Crosswell Data
Crosswell Imaging of Synthetic Fault Data
Model
KM
Depth (m)
0
210
0
90
WM
Conclusions
• Typically WM has fewer artifacts than
KM
• Typically WM 2-50 times faster than than
KM
• Tradeoff between quality and speed
• Conflicting dip arrivals still an issue
• Slant stack traces essential for efficiency
• Fast velocity analysis tool
Conclusions
Works on synthetic and field
poststack time migration data,
improve resolution, mitigate some
migration artifacts
Subdivision method is able to account
for lateral-velocity variations and
attenuate some far-field artifacts
A post-migration processing: Cost 2X
Migration Accuracy vs $$$
Full-Wave
Target RTM
No Approx.
Ray-Beam Phase-Shift
Kirchhoff
Expense
Multiple Arriv
Anti-aliasing