Least Squares Migration

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:

Motivation: Poor Acquisition Geomtery

Motivation: Poor Illumination * g SALT Uneven Illumination under Salt

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

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

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

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

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

Kirchhoff MD

Kirchhoff MD

Kirchhoff MD

Kirchhoff MD

Kirchhoff MD

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