1. Least Squares Migration

2. d=Lm mmig=LTd m =[LTL]-1m mig
Forward Model:
Standard Migration:
mmig=LTd
m =[LTL]-1LTd
Least Sq. Migration :
3D input
5D input
m =[LTL]-1m
mig
Migration Decon:

3. Motivation: Poor Acquisition Geomtery

4. Motivation: Poor Illumination* g
SALT
Uneven Illumination under Salt

5. Wave Equation Migration Before MD
X (km) 20 3
Depth (km) 10

6. Wave Equation Migration after MD
X (km) 20 3
Depth (km) 10

7. Motivation: Better Resolution
Kirchhoff Mig
Beylkin
Kirchhoff MD
Gaussian Beam MD
FFD MD

8. Motivation: Better Resolution
Kirchhoff MD
Motivation: Better Resolution 3
X (km) 3
Y (km)
Meandering Stream 3
Y (km)
Kirchhoff Mig 3
Y (km)
Kirchhoff MD

9. Iterative Least Squares Migration
Kirchhoff MD
Iterative Least Squares Migration
Step 1:
Step 2:
Step 3:
Step 4:

10. Kirchhoff MD

11. Kirchhoff MD

12. Kirchhoff MD

13. Kirchhoff MD

14. Kirchhoff MD

15. Summary 1. LSM resolution twice better than KM
2. LSM >20 times more expensive than KM
3. LSM sensitive to accurate v(x,z)
4. Multisource LSM costs same as KM
Second I compute reflectivity model within this offset range from the velocity and density models.
I also created a source wavelet that mimics an air gun source signature.
Fdom = 25 Hz. 15