Laplace–Fourier-Domain Waveform Inversion for Fluid–Solid Media

Full waveform inversion algorithms are widely used in the construction of subsurface velocity models. In the following study, we propose a Laplace–Fourier-domain waveform inversion algorithm that uses both Laplace-domain and Fourier-domain wavefields to achieve the reconstruction of subsurface veloc...

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Vydané v:Pure and applied geophysics Ročník 169; číslo 12; s. 2165 - 2179
Hlavní autori: Kang, Seung-Goo, Bae, Ho Seuk, Shin, Changsoo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel SP Birkhäuser Verlag Basel 01.12.2012
Springer
Springer Nature B.V
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ISSN:0033-4553, 1420-9136
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Shrnutí:Full waveform inversion algorithms are widely used in the construction of subsurface velocity models. In the following study, we propose a Laplace–Fourier-domain waveform inversion algorithm that uses both Laplace-domain and Fourier-domain wavefields to achieve the reconstruction of subsurface velocity models. Although research on the Laplace–Fourier-domain waveform inversion has been published recently that study is limited to fluid media. Because the geophysical targets of marine seismic exploration are usually located within solid media, waveform inversion that is approximated to acoustic media is limited to the treatment of properly identified submarine geophysical features. In this study, we propose a full waveform inversion algorithm for isotropic fluid–solid media with irregular submarine topography comparable to a real marine environment. From the fluid–solid system, we obtained P and S wave velocity models from the pressure data alone. We also suggested strategies for choosing complex frequency bands constructed of frequencies and Laplace coefficients to improve the resolution of the restored velocity structures. For verification, we applied our Laplace–Fourier-domain waveform inversion for fluid–solid media to synthetic data that were reconstructed for fluid–solid media. Through this inversion test, we successfully restored reasonable velocity structures. Furthermore, we successfully extended our algorithm to a field data set.
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ISSN:0033-4553
1420-9136
DOI:10.1007/s00024-012-0467-7