skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Discovering State‐Parameter Mappings in Subsurface Models Using Generative Adversarial Networks

Authors:
ORCiD logo [1]
  1. Bureau of Economic Geology, Jackson School of GeosciencesThe University of Texas at Austin Austin TX USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1478427
Grant/Contract Number:  
FE0026515; FE0031544
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Name: Geophysical Research Letters Journal Volume: 45 Journal Issue: 20; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English

Citation Formats

Sun, Alexander Y. Discovering State‐Parameter Mappings in Subsurface Models Using Generative Adversarial Networks. United States: N. p., 2018. Web. doi:10.1029/2018GL080404.
Sun, Alexander Y. Discovering State‐Parameter Mappings in Subsurface Models Using Generative Adversarial Networks. United States. doi:10.1029/2018GL080404.
Sun, Alexander Y. Sat . "Discovering State‐Parameter Mappings in Subsurface Models Using Generative Adversarial Networks". United States. doi:10.1029/2018GL080404.
@article{osti_1478427,
title = {Discovering State‐Parameter Mappings in Subsurface Models Using Generative Adversarial Networks},
author = {Sun, Alexander Y.},
abstractNote = {},
doi = {10.1029/2018GL080404},
journal = {Geophysical Research Letters},
number = 20,
volume = 45,
place = {United States},
year = {2018},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1029/2018GL080404

Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

Save / Share: