Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties
Author:
Affiliation:
1. Department of Energy Science and Engineering Stanford University Stanford CA USA
2. Scientific Computing and Artificial Intelligence (SCAI) Laboratory University of Notre Dame South Bend IN USA
Funder
National Science Foundation
TotalEnergies
Advanced Research Projects Agency - Energy
Publisher
American Geophysical Union (AGU)
Subject
Water Science and Technology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR031438
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1. Identification of Contaminant Source Location and Release History in Aquifers
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