Relative geologic time estimation using a deep convolutional neural network-Reference-Cited by-同舟云学术

Relative geologic time estimation using a deep convolutional neural network

Published:2019-08-10 Issue: Volume: Page:
ISSN:
Container-title:SEG Technical Program Expanded Abstracts 2019
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Author:

Geng Zhicheng¹,Wu Xinming¹,Shi Yunzhi¹,Fomel Sergey¹

Affiliation:

1. The University of Texas at Austin

Publisher

Society of Exploration Geophysicists

Link

https://library.seg.org/doi/pdf/10.1190/segam2019-3214459.1

Reference39 articles.

1. Bader, S., K. Spikes, and S. Fomel, 2018, Missing well-log data prediction using Bayesian approach in the relative-geologic time domain: 88th Annual International Meeting, SEG, Expanded Abstracts, 804–808, doi: 10.1190/segam2018-2997278.1.

2. Multidimensional wavefront estimation from differential delays

3. Stratigraphic surfaces in the depositional and chronostratigraphic (Wheeler-transformed) domain

4. Eigen, D., C. Puhrsch, and R. Fergus, 2014, Depth map prediction from a single image using a multi-scale deep network: Advances in Neural Information Processing Systems, 2366–2374.

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