3-D Migration Deconvolution Jianxing Hu, GXT Bob Estill, Unocal Jianhua Yu, University of Utah Gerard T. Schuster, University of Utah

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples Conclusions Implementation of MD

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples Conclusions Implementation of MD

Migration noise and artifacts Migration Noise Problems Depth (km) Weak illumination Footprint

Purpose of MD Processing: Improving spatial resolution Enhancing illumination Suppressing migration noise and artifacts

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples Conclusions Implementation of MD

M = L T Migration: Migrated image L R L is modeling operator Reflectivity

T R = (L L ) M 3-D PRESTACK MD Reflectivity Design an improved MD filter Migrated Section MD is to eliminate the blurring influence in migration image by designing MD operator Goal:

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples Conclusions Implementation of MD

MD Implementation Steps: Step 1: Prepare traveltime table Velocity cube Acquisition geometry information or Use migration timetable

Calculate the migration Green’s function MD Implementation Steps: Step 2: Y (km) Depth (km) Depth Level i N L

Step 4: Invert MD image at the depth Z i by solving linear equations MD Implementation Steps: Step 5: Repeat Steps 2-4 until the maximum depth is finished

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples : Synthetic data Conclusions Implementation of MD

0 3 km 0 3-D Point Scatterer Model 3 km 11 X 11 Receivers 11 X 11 Receivers dxg=dyg=0.3 km Imaging: dx=dy=50 m dz=100 m 3X3 Sources; dxshot=dyshot=1.5 km 10 km

0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) MIG MD Z=1 km Z=3 km Z=5 km Depth Slices

0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) 0 3 X (km) 0 3 Y (km) MIG MD Z=7 km Z=9 km Z=10 km Depth Slices

0 2.5 km 0 Meandering Stream Model 2.5 km 5 X 1 Sources; 11 X 7 Receivers 3.5 km

Mig MD Model 0 Y (km) X (km) Z=3.5 KM

km 0 3-D SEG/EAGE Salt Model 12.2 km 9 X5 Sources; dxshot=dyshot=1 km 201 X 201 Receivers Imaging: dx=dy=20 m

3-D SEG/EAGE Salt Model X (km)Y (km) Y=7.12 km

Mig and MD ( z=1.4 km, negative polarity) X (km) 3 10 Y (km) X (km) MDMig

MD (z=1.2 km)Mig (z=1.2 km) X (km) 3 10 Y (km) X (km)

MD (z=1.2 km)Mig (z=1.2 km)

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples: 2-D field data Conclusions Implementation of MD

PS PSTM Image ( by Unocal) 0 6 X (km) 0 8 Time (s)

0 6 X (km) 0 8 Time (s) MD PSTM(courtesy of Unocal) PSTMD

0 6 X (km) 3 8 Time (s) MD PSTM(courtesy of Unocal) PSTMD

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples: 3-D field data Conclusions Implementation of MD

3-D Land Field Data : Receivers : Sources

1.6 s Inline Crossline 3D PSTM (courtesy of Unocal) MD

2.0 s Crossline 3D PSTM (courtesy of Unocal) MD

3 Mig in Inline (Courtesy of Unocal) MD

Mig MD Mig MD

Mig (Courtesy of Unocal) MD Inline Number Crossline Number Inline Number (2 kft)

Fault

(3.6 kft) Inline Number Crossline Number Inline Number Mig (Courtesy of Unocal) MD

Inline Number Depth (kft) 90Inline Number1 Mig (courtesy of Unocal)MD (Crossline=50)

(crossline 200) Depth (kft) Mig (courtesy of Unocal)MD

Depth (kft) Crossline Number (Inline =50) Mig ( Unocal ) MD

Why Do Migration Deconvolution (MD) ? Outline Migration Deconvolution Examples Conclusions Implementation of MD

Conclusions Aperture width and filter length in designing MD filter are two key parameters Improve resolution and suppress migration artifacts MD cost is related with acquisition geometry

Acknowledgments Thank Amramco, Unocal, and Chevron- Texaco for providing the data setsThank Amramco, Unocal, and Chevron- Texaco for providing the data sets Thank 2002 UTAM sponsors for their financial supportThank 2002 UTAM sponsors for their financial support The help and comments from Alan Leeds and George Yao are very appreciatedThe help and comments from Alan Leeds and George Yao are very appreciated