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Localized time-lapse elastic waveform inversion using wavefield injection and extrapolation: 2-D parametric studies

Abstract : We present a methodology to invert seismic data for a localized area by combining source-side wavefield injection and receiver-side extrapolation method. Despite the high resolving power of seismic full waveform inversion, the computational cost for practical scale elastic or viscoelastic waveform inversion remains a heavy burden. This can be much more severe for time-lapse surveys, which require real-time seismic imaging on a daily or weekly basis. Besides, changes of the structure during time-lapse surveys are likely to occur in a small area rather than the whole region of seismic experiments, such as oil and gas reservoir or CO2 injection wells. We thus propose an approach that allows to image effectively and quantitatively the localized structure changes far deep from both source and receiver arrays. In our method, we perform both forward and back propagation only inside the target region. First, we look for the equivalent source expression enclosing the region of interest by using the wavefield injection method. Second, we extrapolate wavefield from physical receivers located near the Earth's surface or on the ocean bottom to an array of virtual receivers in the subsurface by using correlation-type representation theorem. In this study, we present various 2-D elastic numerical examples of the proposed method and quantitatively evaluate errors in obtained models, in comparison to those of conventional full-model inversions. The results show that the proposed localized waveform inversion is not only efficient and robust but also accurate even under the existence of errors in both initial models and observed data.
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Submitted on : Wednesday, August 10, 2022 - 11:07:33 AM
Last modification on : Thursday, August 11, 2022 - 3:47:25 AM


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Shihao Yuan, Nobuaki Fuji, Satish Singh, Dmitry Borisov. Localized time-lapse elastic waveform inversion using wavefield injection and extrapolation: 2-D parametric studies. Geophysical Journal International, 2017, 209, pp.1699-1717. ⟨10.1093/gji/ggx118⟩. ⟨insu-03748855⟩



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