Prestack Migration Deconvolution Jianxing Hu and Gerard T. Schuster University of Utah

Outline MotivationMotivation MethodologyMethodology Numerical TestsNumerical Tests ConclusionsConclusions

Comparison of Poststack MD Depth Slices 6 8 Y (km) Y (km) X (km) X (km) Kirchhoff Image Kirchhoff Image MD Image MD Image 6 8 Y (km) Y (km) X (km) X (km)

Comparison of Prestack Migration and MD Images X (km) X (km) Depth (km) Depth (km) X (km) X (km) Depth (km) Depth (km) Prestack Kirchhoff Migration Image of Prestack Kirchhoff Migration Image of a North Sea Data Set a North Sea Data Set MD Image

Outline MotivationMotivation MethodologyMethodology Numerical TestsNumerical Tests ConclusionsConclusions

Modeling and Migration Seismic data Reflectivity Green’s Function Model Space Migrated Image Data Space Seismic Data Forward Modeling: Migration: Wavelet

Model Space Where: Denote as the migration Green’s Function Relation of Migrated Image and Reflectivity Distribution Relation of Migrated Image and Reflectivity Distribution Data Space

Reflectivity Modulated by Migration Green’s Function Model Space

Migration Deconvolution Model Space Model Space --- reference position of migration Green’s function

Lateral Velocity Variation Multi-Reference migration Green’s function Subdivide the migration image area and use multi- reference migration Green’s function to account for lateral velocity variation and far-field artifacts

Methodology Calculate migration Green’s function Recording geometry & migrated image dimension Velocity Model + Traveltime Table Migration Green’s function

Methodology Apply migration deconvolution filter to the stacked prestack migration image 5 Offset(km) Depth (km) RTM Migration Image Deconvolved Image Deconvolved Image Pseudo-Convolution Offset(km) Depth (km) RTM

Difference between Poststack MD and Prestack MD Zero-offset trace location & migrated image dimension Velocity Model Traveltime Table migration Poststack migration Green’s function Green’s function + migration Prestack migration Green’s function Green’s function Recording Geometry & migrated image dimension +

Outline MotivationMotivation MethodologyMethodology Numerical TestsNumerical Tests ConclusionsConclusions

Numerical Tests 3-D point scatterer model3-D point scatterer model 3-D meandering stream model3-D meandering stream model 2-D SEG/EAGE overthrust model2-D SEG/EAGE overthrust model 2-D Husky data set (Canadian Foothills)2-D Husky data set (Canadian Foothills) 3-D SEG/EAGE salt model3-D SEG/EAGE salt model 3-D West Texas data set3-D West Texas data set

5 X 5 Sources; 21 X 21 Receivers (0, 0) (1km, 0) (1km, 1km) (0, 1km) Point scatterer Recording Geometry Wavelet frequency 50 Hz

Prestack KM vs. Prestack MD Y X Y X Y X Y X

Prestack KM vs. Poststack MD Y X Y X Y X Y X

Numerical Tests 3-D point scatterer model3-D point scatterer model 3-D meandering stream model3-D meandering stream model 2-D SEG/EAGE overthrust model2-D SEG/EAGE overthrust model 2-D Husky data set (Canadian Foothills)2-D Husky data set (Canadian Foothills) 3-D SEG/EAGE salt model3-D SEG/EAGE salt model 3-D West Texas data set3-D West Texas data set

(0, 0) (1 km, 0) (1 km,1 km) (0, 1 km) A river channel Recording Geometry 5 X 5 Sources; 21 X 21 Receivers Wavelet frequency 50 Hz

Meandering River Model X (m) Y (m)

Kirchhoff Migration Image X (m) Y (m)

MD Image X (m) Y (m)

Numerical Tests 3-D point scatterer model3-D point scatterer model 3-D meandering stream model3-D meandering stream model 2-D SEG/EAGE overthrust model2-D SEG/EAGE overthrust model 2-D Husky data set (Canadian Foothills)2-D Husky data set (Canadian Foothills) 3-D SEG/EAGE salt model3-D SEG/EAGE salt model 3-D West Texas data set3-D West Texas data set

Prestack Migration Image Prestack Migration Image Deconvolved Migration Image Deconvolved Migration Image 0 km 20 km 20 km 0 km 4 km 20 km 0 km 0 km 0 km 4 km X(km) Depth (km)

Zoom View of KM and MD Prestack KM Prestack MD Depth (km) 37 X (km) Depth (km) 37 X (km)

Numerical Tests 3-D point scatterer model3-D point scatterer model 3-D meandering stream model3-D meandering stream model 2-D SEG/EAGE overthrust model2-D SEG/EAGE overthrust model 2-D Husky data set (Canadian Foothills)2-D Husky data set (Canadian Foothills) 3-D SEG/EAGE salt model3-D SEG/EAGE salt model 3-D West Texas data set3-D West Texas data set

Husky Prestack Migration Image 4 6X(km) Depth (km)

Velocity Model for Husky Data 6X(km) Depth (km) Velocity (m/s)

MD with 20 reference positions 6X(km) Depth (km) A

KM X(km) Depth (km) MD X(km) Depth (km)

MD with 20 reference positions 6X(km) Depth (km) B

KM X(km) Depth (km) MD X(km) Depth (km)

MD with 20 reference positions 6X(km) Depth (km) C

KM X(km) Depth (km) MD X(km) Depth (km)

Numerical Tests 3-D point scatterer model3-D point scatterer model 3-D meandering stream model3-D meandering stream model 2-D SEG/EAGE overthrust model2-D SEG/EAGE overthrust model 2-D Husky data set2-D Husky data set 3-D SEG/EAGE salt model3-D SEG/EAGE salt model 3-D West Texas data set3-D West Texas data set

KM Inline (97,Y) Section MD Inline (97,Y) Section 58 Y (km) Depth (km)

KM Crossline (X,97) Section MD Crossline (X,97) Section 04 2 Depth (km) 118 X (km) 118 X (km) 04 2

Numerical Tests 3-D point scatterer model3-D point scatterer model 3-D meandering stream model3-D meandering stream model 2-D SEG/EAGE overthrust model2-D SEG/EAGE overthrust model 2-D Husky data set2-D Husky data set 3-D SEG/EAGE salt model3-D SEG/EAGE salt model 3-D West Texas data set3-D West Texas data set

KMMD03 X(kft)46 8 Depth (kft) X(kft)

46 8 Depth (kft) KMMD4 6 8 X(kft)

Outline MotivationMotivation MethodologyMethodology Numerical TestsNumerical Tests ConclusionsConclusions

Conclusions Works well on 2-D land and 3-D synthetic marine prestack data More work is needed to remedy the problems in MD for 3-D land prestack data Standard post-migration processing procedure ?

Acknowledgement Thank 1999 UTAM sponsors for their financial supportThank 1999 UTAM sponsors for their financial support