Full-waveform inversion using machine learning optimization techniques-Reference-Cited by-同舟云学术

Full-waveform inversion using machine learning optimization techniques

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

de Bragança Ricardo¹,Vamaraju Janaki¹,Sen Mrinal K.¹

Affiliation:

1. University of Texas at Austin

Publisher

Society of Exploration Geophysicists

Link

https://library.seg.org/doi/pdf/10.1190/segam2020-3425831.1

Reference9 articles.

1. Hopfield neural networks, and mean field annealing for seismic deconvolution and multiple attenuation

2. Kingma, D. P., and J. Ba, 2014, Adam: A method for stochastic optimization: arXiv preprint arXiv: 1412.6980.

3. Neelakantan, A., L. Vilnis, Q. V. Le, I. Sutskever, L. Kaiser, K. Kurach, and J. Martens, 2015, Adding gradient noise improves learning for very deep networks: arXiv preprint arXiv: 1511.06807.

4. Richardson, A., 2018, Seismic full-waveform inversion using deep learning tools and techniques: arXiv preprint arXiv: 1801.07232.

5. Ruder, S., 2017, An overview of gradient descent optimization algorithms: arXiv preprint arXiv: 1609.04747.

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