author_facet Biondi, B.
Tisserant, T.
Biondi, B.
Tisserant, T.
author Biondi, B.
Tisserant, T.
spellingShingle Biondi, B.
Tisserant, T.
Geophysical Prospecting
3D angle‐domain common‐image gathers for migration velocity analysis
Geochemistry and Petrology
Geophysics
author_sort biondi, b.
spelling Biondi, B. Tisserant, T. 0016-8025 1365-2478 Wiley Geochemistry and Petrology Geophysics http://dx.doi.org/10.1111/j.1365-2478.2004.00444.x <jats:title>ABSTRACT</jats:title><jats:p>Angle‐domain common‐image gathers (ADCIGs) are an essential tool for migration velocity analysis (MVA). We present a method for computing ADCIGs in 3D from the results of wavefield‐continuation migration. The proposed methodology can be applied before or after the imaging step in a migration procedure. When computed before imaging, 3D ADCIGs are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-1.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-1" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-3.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-3" />)</jats:styled-content>; we derive the geometric relationship that links the offset ray parameters to the aperture angle γ and the reflection azimuth φ. When computed after imaging, 3D ADCIGs are directly produced as functions of γ and φ.</jats:p><jats:p>The mapping of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-5.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-5" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-7.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-7" />)</jats:styled-content> into the angles (γ, φ) depends on both the local dips and the local interval velocity; therefore, the transformation of ADCIGs computed before imaging into ADCIGs that are functions of the actual angles is difficult in complex structure. By contrast, the computation of ADCIGs after imaging is efficient and accurate even in the presence of complex structure and a heterogeneous velocity function. On the other hand, the estimation of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-9.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-9" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-11.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-11" />)</jats:styled-content> is less sensitive to velocity errors than the estimation of the angles (γ, φ). When ADCIGs that are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-13.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-13" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-15.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-15" />)</jats:styled-content> are adequate for the application of interest (e.g. ray‐based tomography), the computation of ADCIGs before imaging might be preferable.</jats:p><jats:p>Errors in the migration velocity cause the image point in the angle domain to shift along the normal to the apparent geological dip. By assuming stationary rays (i.e. small velocity errors), we derive a quantitative relationship between this normal shift and the traveltime perturbation caused by velocity errors. This relationship can be directly used in an MVA procedure to invert depth errors measured from ADCIGs into migration velocity updates. In this paper, we use it to derive an approximate 3D residual moveout (RMO) function for measuring inconsistencies between the migrated images at different γ and φ. We tested the accuracy of our kinematic analysis on a 3D synthetic data set with steeply dipping reflectors and a vertically varying propagation velocity. The tests confirm the accuracy of our analysis and illustrate the limitations of the straight‐ray approximation underlying our derivation of the 3D RMO function.</jats:p> 3D angle‐domain common‐image gathers for migration velocity analysis Geophysical Prospecting
doi_str_mv 10.1111/j.1365-2478.2004.00444.x
facet_avail Online
finc_class_facet Chemie und Pharmazie
Physik
Geologie und Paläontologie
Geographie
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imprint Wiley, 2004
imprint_str_mv Wiley, 2004
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match_str biondi20043dangledomaincommonimagegathersformigrationvelocityanalysis
publishDateSort 2004
publisher Wiley
recordtype ai
record_format ai
series Geophysical Prospecting
source_id 49
title 3D angle‐domain common‐image gathers for migration velocity analysis
title_unstemmed 3D angle‐domain common‐image gathers for migration velocity analysis
title_full 3D angle‐domain common‐image gathers for migration velocity analysis
title_fullStr 3D angle‐domain common‐image gathers for migration velocity analysis
title_full_unstemmed 3D angle‐domain common‐image gathers for migration velocity analysis
title_short 3D angle‐domain common‐image gathers for migration velocity analysis
title_sort 3d angle‐domain common‐image gathers for migration velocity analysis
topic Geochemistry and Petrology
Geophysics
url http://dx.doi.org/10.1111/j.1365-2478.2004.00444.x
publishDate 2004
physical 575-591
description <jats:title>ABSTRACT</jats:title><jats:p>Angle‐domain common‐image gathers (ADCIGs) are an essential tool for migration velocity analysis (MVA). We present a method for computing ADCIGs in 3D from the results of wavefield‐continuation migration. The proposed methodology can be applied before or after the imaging step in a migration procedure. When computed before imaging, 3D ADCIGs are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-1.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-1" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-3.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-3" />)</jats:styled-content>; we derive the geometric relationship that links the offset ray parameters to the aperture angle γ and the reflection azimuth φ. When computed after imaging, 3D ADCIGs are directly produced as functions of γ and φ.</jats:p><jats:p>The mapping of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-5.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-5" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-7.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-7" />)</jats:styled-content> into the angles (γ, φ) depends on both the local dips and the local interval velocity; therefore, the transformation of ADCIGs computed before imaging into ADCIGs that are functions of the actual angles is difficult in complex structure. By contrast, the computation of ADCIGs after imaging is efficient and accurate even in the presence of complex structure and a heterogeneous velocity function. On the other hand, the estimation of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-9.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-9" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-11.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-11" />)</jats:styled-content> is less sensitive to velocity errors than the estimation of the angles (γ, φ). When ADCIGs that are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-13.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-13" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-15.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-15" />)</jats:styled-content> are adequate for the application of interest (e.g. ray‐based tomography), the computation of ADCIGs before imaging might be preferable.</jats:p><jats:p>Errors in the migration velocity cause the image point in the angle domain to shift along the normal to the apparent geological dip. By assuming stationary rays (i.e. small velocity errors), we derive a quantitative relationship between this normal shift and the traveltime perturbation caused by velocity errors. This relationship can be directly used in an MVA procedure to invert depth errors measured from ADCIGs into migration velocity updates. In this paper, we use it to derive an approximate 3D residual moveout (RMO) function for measuring inconsistencies between the migrated images at different γ and φ. We tested the accuracy of our kinematic analysis on a 3D synthetic data set with steeply dipping reflectors and a vertically varying propagation velocity. The tests confirm the accuracy of our analysis and illustrate the limitations of the straight‐ray approximation underlying our derivation of the 3D RMO function.</jats:p>
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author Biondi, B., Tisserant, T.
author_facet Biondi, B., Tisserant, T., Biondi, B., Tisserant, T.
author_sort biondi, b.
container_issue 6
container_start_page 575
container_title Geophysical Prospecting
container_volume 52
description <jats:title>ABSTRACT</jats:title><jats:p>Angle‐domain common‐image gathers (ADCIGs) are an essential tool for migration velocity analysis (MVA). We present a method for computing ADCIGs in 3D from the results of wavefield‐continuation migration. The proposed methodology can be applied before or after the imaging step in a migration procedure. When computed before imaging, 3D ADCIGs are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-1.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-1" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-3.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-3" />)</jats:styled-content>; we derive the geometric relationship that links the offset ray parameters to the aperture angle γ and the reflection azimuth φ. When computed after imaging, 3D ADCIGs are directly produced as functions of γ and φ.</jats:p><jats:p>The mapping of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-5.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-5" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-7.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-7" />)</jats:styled-content> into the angles (γ, φ) depends on both the local dips and the local interval velocity; therefore, the transformation of ADCIGs computed before imaging into ADCIGs that are functions of the actual angles is difficult in complex structure. By contrast, the computation of ADCIGs after imaging is efficient and accurate even in the presence of complex structure and a heterogeneous velocity function. On the other hand, the estimation of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-9.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-9" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-11.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-11" />)</jats:styled-content> is less sensitive to velocity errors than the estimation of the angles (γ, φ). When ADCIGs that are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-13.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-13" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-15.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-15" />)</jats:styled-content> are adequate for the application of interest (e.g. ray‐based tomography), the computation of ADCIGs before imaging might be preferable.</jats:p><jats:p>Errors in the migration velocity cause the image point in the angle domain to shift along the normal to the apparent geological dip. By assuming stationary rays (i.e. small velocity errors), we derive a quantitative relationship between this normal shift and the traveltime perturbation caused by velocity errors. This relationship can be directly used in an MVA procedure to invert depth errors measured from ADCIGs into migration velocity updates. In this paper, we use it to derive an approximate 3D residual moveout (RMO) function for measuring inconsistencies between the migrated images at different γ and φ. We tested the accuracy of our kinematic analysis on a 3D synthetic data set with steeply dipping reflectors and a vertically varying propagation velocity. The tests confirm the accuracy of our analysis and illustrate the limitations of the straight‐ray approximation underlying our derivation of the 3D RMO function.</jats:p>
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id ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTExMS9qLjEzNjUtMjQ3OC4yMDA0LjAwNDQ0Lng
imprint Wiley, 2004
imprint_str_mv Wiley, 2004
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series Geophysical Prospecting
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spelling Biondi, B. Tisserant, T. 0016-8025 1365-2478 Wiley Geochemistry and Petrology Geophysics http://dx.doi.org/10.1111/j.1365-2478.2004.00444.x <jats:title>ABSTRACT</jats:title><jats:p>Angle‐domain common‐image gathers (ADCIGs) are an essential tool for migration velocity analysis (MVA). We present a method for computing ADCIGs in 3D from the results of wavefield‐continuation migration. The proposed methodology can be applied before or after the imaging step in a migration procedure. When computed before imaging, 3D ADCIGs are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-1.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-1" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-3.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-3" />)</jats:styled-content>; we derive the geometric relationship that links the offset ray parameters to the aperture angle γ and the reflection azimuth φ. When computed after imaging, 3D ADCIGs are directly produced as functions of γ and φ.</jats:p><jats:p>The mapping of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-5.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-5" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-7.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-7" />)</jats:styled-content> into the angles (γ, φ) depends on both the local dips and the local interval velocity; therefore, the transformation of ADCIGs computed before imaging into ADCIGs that are functions of the actual angles is difficult in complex structure. By contrast, the computation of ADCIGs after imaging is efficient and accurate even in the presence of complex structure and a heterogeneous velocity function. On the other hand, the estimation of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-9.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-9" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-11.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-11" />)</jats:styled-content> is less sensitive to velocity errors than the estimation of the angles (γ, φ). When ADCIGs that are functions of the offset ray parameters <jats:styled-content>(<jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-13.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-13" />, <jats:italic>p</jats:italic><jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/tex2gif-sub-15.gif" xlink:title="urn:x-wiley:00168025:media:GPR444:tex2gif-sub-15" />)</jats:styled-content> are adequate for the application of interest (e.g. ray‐based tomography), the computation of ADCIGs before imaging might be preferable.</jats:p><jats:p>Errors in the migration velocity cause the image point in the angle domain to shift along the normal to the apparent geological dip. By assuming stationary rays (i.e. small velocity errors), we derive a quantitative relationship between this normal shift and the traveltime perturbation caused by velocity errors. This relationship can be directly used in an MVA procedure to invert depth errors measured from ADCIGs into migration velocity updates. In this paper, we use it to derive an approximate 3D residual moveout (RMO) function for measuring inconsistencies between the migrated images at different γ and φ. We tested the accuracy of our kinematic analysis on a 3D synthetic data set with steeply dipping reflectors and a vertically varying propagation velocity. The tests confirm the accuracy of our analysis and illustrate the limitations of the straight‐ray approximation underlying our derivation of the 3D RMO function.</jats:p> 3D angle‐domain common‐image gathers for migration velocity analysis Geophysical Prospecting
spellingShingle Biondi, B., Tisserant, T., Geophysical Prospecting, 3D angle‐domain common‐image gathers for migration velocity analysis, Geochemistry and Petrology, Geophysics
title 3D angle‐domain common‐image gathers for migration velocity analysis
title_full 3D angle‐domain common‐image gathers for migration velocity analysis
title_fullStr 3D angle‐domain common‐image gathers for migration velocity analysis
title_full_unstemmed 3D angle‐domain common‐image gathers for migration velocity analysis
title_short 3D angle‐domain common‐image gathers for migration velocity analysis
title_sort 3d angle‐domain common‐image gathers for migration velocity analysis
title_unstemmed 3D angle‐domain common‐image gathers for migration velocity analysis
topic Geochemistry and Petrology, Geophysics
url http://dx.doi.org/10.1111/j.1365-2478.2004.00444.x