Anisotropic modeling and imaging
The presence of sedimentary layers in the earth�s subsurface results in seismic anisotropy, which makes wave velocity dependent on the propagation angle. This phenomenon gives rise to errors in seismic imaging. Among these errors are the mispositioning of migrated events and failure to retain ener...
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2022
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oai:scholars.utp.edu.my:340992023-01-03T07:22:55Z http://scholars.utp.edu.my/id/eprint/34099/ Anisotropic modeling and imaging Alashloo, S.Y.M. Bashir, Y. Ghosh, D.P. The presence of sedimentary layers in the earth�s subsurface results in seismic anisotropy, which makes wave velocity dependent on the propagation angle. This phenomenon gives rise to errors in seismic imaging. Among these errors are the mispositioning of migrated events and failure to retain energy during dip-moveout. Most of hydrocarbon reservoirs are defined as anisotropic media. Anisotropy is necessary not only to avoid distortions in imaging but also provides valuable information about lithology and fracture networks. To consider the influence of seismic anisotropy, an anisotropic wave equation needs to be employed. The main topics, which are discussed in this chapter, are to incorporate anisotropic effects in seismic modeling and Kirchhoff depth imaging for imaging complex structures. Two algorithms are developed, namely, (1) vertical transverse isotropy (VTI) and tilted transverse isotropy (TTI) wave modeling and (2) VTI Kirchhoff depth imaging. In the first part, a new TTI pseudo-acoustic wave equation is suggested for anisotropic forward modeling. In the second part, a VTI fast-marching eikonal solver is constructed for calculating travel times. An anelliptic VTI wave equation, which uses a nonlinear approximation, is utilized to provide the P-wave velocity information. In this study, synthetic data and a real dataset are applied to test the effectiveness of the algorithm. The spectrum comparison confirmed that the VTI algorithm produces images with higher amplitude around 30 more than isotropic condition and thus better resolution. © 2022 Elsevier Inc. All rights reserved. Elsevier 2022 Book NonPeerReviewed Alashloo, S.Y.M. and Bashir, Y. and Ghosh, D.P. (2022) Anisotropic modeling and imaging. Elsevier, pp. 133-178. ISBN 9780323919463; 9780323918879 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138366482&doi=10.1016%2fB978-0-323-91946-3.00001-8&partnerID=40&md5=13aada2cb029507782dc757b8e517fa9 10.1016/B978-0-323-91946-3.00001-8 10.1016/B978-0-323-91946-3.00001-8 10.1016/B978-0-323-91946-3.00001-8 |
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The presence of sedimentary layers in the earth�s subsurface results in seismic anisotropy, which makes wave velocity dependent on the propagation angle. This phenomenon gives rise to errors in seismic imaging. Among these errors are the mispositioning of migrated events and failure to retain energy during dip-moveout. Most of hydrocarbon reservoirs are defined as anisotropic media. Anisotropy is necessary not only to avoid distortions in imaging but also provides valuable information about lithology and fracture networks. To consider the influence of seismic anisotropy, an anisotropic wave equation needs to be employed. The main topics, which are discussed in this chapter, are to incorporate anisotropic effects in seismic modeling and Kirchhoff depth imaging for imaging complex structures. Two algorithms are developed, namely, (1) vertical transverse isotropy (VTI) and tilted transverse isotropy (TTI) wave modeling and (2) VTI Kirchhoff depth imaging. In the first part, a new TTI pseudo-acoustic wave equation is suggested for anisotropic forward modeling. In the second part, a VTI fast-marching eikonal solver is constructed for calculating travel times. An anelliptic VTI wave equation, which uses a nonlinear approximation, is utilized to provide the P-wave velocity information. In this study, synthetic data and a real dataset are applied to test the effectiveness of the algorithm. The spectrum comparison confirmed that the VTI algorithm produces images with higher amplitude around 30 more than isotropic condition and thus better resolution. © 2022 Elsevier Inc. All rights reserved. |
| format |
Book |
| author |
Alashloo, S.Y.M. Bashir, Y. Ghosh, D.P. |
| spellingShingle |
Alashloo, S.Y.M. Bashir, Y. Ghosh, D.P. Anisotropic modeling and imaging |
| author_facet |
Alashloo, S.Y.M. Bashir, Y. Ghosh, D.P. |
| author_sort |
Alashloo, S.Y.M. |
| title |
Anisotropic modeling and imaging |
| title_short |
Anisotropic modeling and imaging |
| title_full |
Anisotropic modeling and imaging |
| title_fullStr |
Anisotropic modeling and imaging |
| title_full_unstemmed |
Anisotropic modeling and imaging |
| title_sort |
anisotropic modeling and imaging |
| publisher |
Elsevier |
| publishDate |
2022 |
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http://scholars.utp.edu.my/id/eprint/34099/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138366482&doi=10.1016%2fB978-0-323-91946-3.00001-8&partnerID=40&md5=13aada2cb029507782dc757b8e517fa9 |
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