Data-Driven Ringed Residual U-Net Scheme for Full Waveform Inversion

Xingguo Huang

doi:10.1109/TGRS.2024.3436688

2024-01-01

PRE

DOI：10.1109/TGRS.2024.3436688

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摘要

En 中文

Full waveform inversion (FWI) is a powerful means for accurately reconstructing subsurface velocity models at high resolution. Yet it is nevertheless a nonlinear and ill-posed problem. Physics-driven FWI methods employ gradient-based optimization algorithms to minimize the error between the observed seismic data and the synthetically generated seismic data. The solution may converge to a local rather than global minimum. The cycle-skipping problem occurs when the synthetic data exceed a half-wavelength shift relative to the observed data. FWI relies on an accurate initial velocity model to mitigate the cycle-skipping problem. Moreover, due to the increasing size and desired resolution of seismic data, FWI costs a great deal of computational time. To obviate these problems, we present a data-driven FWI scheme based on a deep learning architecture called U-Net. The network consists of the ringed residual unit, which integrates residual propagation and residual feedback. It beneficially achieves correspondence between the seismic data domain and the velocity model domain. The features of the shallow layers are connected with the deep layers by a skip connection to facilitate seismic data spatial information propagation and utilization. They improve inversion accuracy and make the network more generalizable and robust. We utilize the Society of Exploration Geophysicists (SEGs)/European Association of Geoscientists and Engineers (EAGE) overthrust and salt models to verify our proposed method's impressive performance. The experimental results clearly demonstrate that the proposed method can produce high-quality velocity models. Compared with the conventional physics-informed FWI, it has advantages in both computational time and initial model dependence.

Keyword:

Computational modeling

Feature extraction

Mathematical models

Data models

Training

Computer architecture

Accuracy

Acoustic wave

full waveform inversion (FWI)

ringed residual unit

U-Net