CycleFCN: A physics-informed data-driven seismic waveform inversion method-Reference-Cited by-同舟云学术

CycleFCN: A physics-informed data-driven seismic waveform inversion method

Published:2020-09-30 Issue: Volume: Page:
ISSN:
Container-title:SEG Technical Program Expanded Abstracts 2020
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Author:

Jin Peng¹,Feng Shihang¹,Lin Youzuo¹,Wohlberg Brendt¹,Moulton David¹,Cromwell Erol²,Chen Xingyuan²

Affiliation:

1. Los Alamos National Laboratory

2. Pacific Northwest National Laboratory

Publisher

Society of Exploration Geophysicists

Link

https://library.seg.org/doi/pdf/10.1190/segam2020-w13-05.1

Reference21 articles.

1. Feng, S., L. Fu, Z. Feng, and G. T. Schuster, 2019, Multiscale phase inversion of anisotropic data: SEG Technical Program Expanded Abstracts 2019: SEG, 1430–1434.

2. Two‐dimensional nonlinear inversion of seismic waveforms: Numerical results

3. Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks

4. Ioffe, S., and C. Szegedy, 2015, Batch normalization: Accelerating deep network training by reducing internal covariate shift: arXiv preprint arXiv:1502.03167.

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