Reflection waveform inversion in acoustic VTI media

Abstract
Full waveform inversion (FWI) in transversely isotropic media with vertical symmetry axis (VTI) provides the opportunity to better match the data at the near and far offsets. However, multi-parameter FWI in general suffers from a serious cycle-skipping and trade-off problem. Reflection waveform inversion (RWI) can help us build a background model by minimizing the reflection data residuals. Thus, we apply RWI to acoustic VTI media. According to the radiation patterns analysis, the acoustic VTI media should be described by a combination of the normal-moveout (NMO) velocity vn and the anisotropic parameters ? and d in the RWI applications. To reduce the trade-off, we first invert for the background vn, and then update the background vn and ?, simultaneously to fit the far-offset reflections. We apply Born modeling to produce the reflections for the two stages of the RWI method. For a follow up FWI applications, we use the background vn and ? to calculate the horizontal velocity vh and the parameters ? and e. The acoustic VTI FWI will utilize the diving waves to improve the background, as well as utilize the reflections for high resolution information. We test the inversion algorithm on the modified VTI Sigsbee 2A model (a salt free part). The results show that the approach can converge to a reasonable result starting from an isotropic model with a linearly increasing vn, even in absence of low frequencies.

Citation
Li, Y., & Alkhalifah, T. (2019). Reflection waveform inversion in acoustic VTI media. SEG Technical Program Expanded Abstracts 2019. doi:10.1190/segam2019-3215308.1

Acknowledgements
We would like to thank the Shaheen supercomputing Laboratory in KAUST for their computational support. We thank KAUST for its support and SWAG for collaborative environment.

Publisher
Society of Exploration Geophysicists

Conference/Event Name
Society of Exploration Geophysicists International Exposition and Annual Meeting 2019, SEG 2019

DOI
10.1190/segam2019-3215308.1

Additional Links
https://library.seg.org/doi/10.1190/segam2019-3215308.1

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