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Volume 70, Issue 5
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

The use of dual‐sensor acquisitions enabled different studies using the so‐called vector‐acoustic equations, which admit particle velocity (displacement or acceleration) information instead of solely the pressure wavefield. With cost far from elastic formulations but comparable with the usually used second‐order acoustic equation, previous works involving the use of vector‐acoustic equations along with multicomponent data have been applied to conventional reverse time migration and full‐waveform inversion, always emphasizing the benefits of using wavefields containing directivity information, which make the receiver ghosts interact constructively with the backpropagated reflected wavefield. Thus, generated results are superior to those of conventional single‐component data imaging techniques, particularly with spatial subsampling of marine seismic data. To assess whether the effects of applying the vector‐acoustic equations persist in a linearized inversion, we developed a multiparameter vector‐acoustic least‐squares reverse time migration, inverting reflectivities associated with velocity and density. To demonstrate the method's performance, we apply it to two‐dimensional numerical examples and compare the results with those obtained by the conventional acoustic least‐squares reverse time migration. The results obtained by the vector‐acoustic least‐squares reverse time migration method are accurate for all inverted parameters and also deliver better convergence when compared with the conventional least‐squares reverse time migration.

© 2022 European Association of Geoscientists & Engineers. © 2022 European Association of Geoscientists & Engineers.
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/content/journals/10.1111/1365-2478.13207
2022-05-18
2024-04-20

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http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.13207
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Multiparameter vector‐acoustic least‐squares reverse time migration
Geophysical Prospecting 70, 865 (2022); https://doi.org/10.1111/1365-2478.13207
/content/journals/10.1111/1365-2478.13207
/content/journals/10.1111/1365-2478.13207
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  • Article Type: Research Article
Keyword(s): Imaging; Inversion; Multicomponent; Numerical study

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