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Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June 7, 2012

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Page 1: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Mitigation of RTM Artifacts

with Migration Kernel DecompositionGe Zhan* and Gerard T. Schuster

King Abdullah University of Science and Technology

June 7, 2012

Page 2: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Outline

• Introduction

• Method

• Examples Two-layer model BP salt model

• Conclusions0 25

12.5

0

X (km)

Depth (km)

0 84

0

X (km)

Depth (km)

2 km/s3 km/s

Page 3: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Outline

• Introduction

• Method

• Examples Two-layer model BP salt model

• Conclusions

Page 4: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Introduction --- Reverse-time migration (RTM)

Benefits:Images any dipping structure;Accounts for multiple arrivals; and etc.

Problems:intensive computational costssevere migration artifacts

Page 5: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Introduction--- RTM artifacts

RTM artifacts usually present as strong-amplitude, low-frequency noisesin the migration image.

artifacts contaminate image

Various remedies have been proposed to suppress RTM artifacts: Smooth the velocity model before migration (Loewenthal et al., 1987); Low-cut filtering on migrated images (Mulder and Plessix, 2003);

Directional damping to non-reflection wave equation (Fletcher et al., 2005); Least-squares migration (Nemeth et al., 1999; Guitton et al., 2006); Migration deconvolution (Hu et al., 2001; Yu et al., 2006);

Poynting-vector imaging condition (Yoon and Marfurt, 2006); Wavefield decomposition using Hilbert transform (Liu et al., 2007; 2011).

Page 6: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Outline

• Introduction

• Method

• Examples Two-layer model BP salt model

• Conclusions

Page 7: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method--- Seismic Survey

Page 8: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method--- Seismic Modeling

Recorded seismic data

Page 9: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Reverse Time Migration (RTM)

Migration of seismic data

Page 10: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Reverse Time Migration (RTM)

Migration of seismic data

Page 11: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Reverse Time Migration (RTM)

Migration of seismic data

Page 12: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Reverse Time Migration (RTM)

Migration of seismic data

Page 13: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Reverse Time Migration (RTM)

Migration of seismic data

Page 14: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Reverse Time Migration (RTM)

Migration of seismic data

Page 15: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method --- Generalized Diffraction Migration (GDM)

Migration of seismic data

Page 16: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Method--- GDM Workflow

1. Compute & save Green’s functions for a given migration velocity;

2. Filter the Green’s functions into downgoing and upgoing components in F-K domain;

3. Convolve the appropriate components of filtered Green’s function to form the migration kernel; 4. Dot product of the migration kernel with the recorded seismic data to get the migration image. T

x

shotgather

T

x

Migration Kernel

Page 17: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Outline

• Introduction

• Method

• Examples Two-layer model BP salt model

• Conclusions

Page 18: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

0 84

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GDM

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2 km/s3 km/s

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RTM

Examples--- two-layer model

Page 19: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Outline

• Introduction

• Method

• Examples Two-layer model BP salt model

• Conclusions

Page 20: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Examples--- BP salt model

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Vp

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1-shot RTM image

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Stacked RTM image

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High-pass-filtered RTM image

Page 21: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Examples--- BP salt model

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Standard RTM w/ filtering

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Horizontal GDM image

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Vertical GDM image

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Stacked GDM image

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Page 22: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Outline

• Introduction

• Method

• Examples Two-layer model BP salt model

• Conclusions

Page 23: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

1). The kernel of RTM imaging operator is decomposed into products of downgoing and upgoing Green’s functions.2). This decomposition leads to an imaging algorithm with fewer artifacts and a higher-quality RTM image.3). Advantage: deterministic filtering of RTM kernel can be directly applied to reduce migration artifacts, mitigate multiples and eliminate aliasing artifacts.4). Drawback: significantly more storage capacity and I/O time than standard RTM.

Conclusions

5). There are still some residual artifacts, which can be further eliminated by least-squares migration.

Page 24: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

We thank the sponsors of the Center for Subsurface Imaging and Fluid Modeling (CSIM) at KAUST for their support.

Acknowledgments

We also thank BP for making the BP 2007 salt model available.

Page 25: Mitigation of RTM Artifacts with Migration Kernel Decomposition Ge Zhan* and Gerard T. Schuster King Abdullah University of Science and Technology June

Question or Suggestion?

Thank you for your attention!