Full Waveform Inversion Using a High-Dimensional Local-Coherence Misfit Function

Youcai Yu

doi:10.1109/TGRS.2023.3263501

2023-01-01

PRE

Youcai Yu

Jidong Yang

黄

黄建平 (Jianping Huang) *

Weiqi Wang

Shanyuan Qin

Zhenchun Li

DOI：10.1109/TGRS.2023.3263501

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摘要

En 中文

Conventional full-waveform seismic inversion (FWI) tries to estimate a subsurface model that can accurately predict surface records by minimizing an L-2-norm misfit between observed and synthetic data. If the initial model is far away from the true model, the cycle-skipping issue might occur and the L-2-norm-based FWI produces a spurious model. To mitigate this problem, we present a novel FWI scheme using a high-dimensional local coherence misfit function. A 2-D/3-D window is first used to extract local seismic waveform from the common-shot gathers. Then, we apply a normalized cross-correlation to measure the coherence of local synthetic and observed records, which is used as the misfit to iteratively update the subsurface velocity model. The new misfit function enhances the contribution of phase fitting while reducing the amplitude contribution, which helps to increase the tolerance of FWI to an inaccurate initial velocity model. In addition, the computation of local waveform coherence along the temporal and spatial axes can adaptively balance the adjoint source amplitudes for strong near-offset reflections and weak far-offset refractions, which improves the low-wavenumber updates. Numerical experiments for synthetic and field data demonstrate that the proposed FWI scheme has a better tolerance to inaccurate starting models and is less sensitive to cycle-skipping issues compared with the conventional FWI method.

Keyword:

Computational seismology

full waveform inversion

high-dimensional local coherence