Can Deep Learning Extract Useful Information about Energy Dissipation and Effective Hydraulic Conductivity from Gridded Conductivity Fields?

Can Deep Learning Extract Useful Information about Energy Dissipation and Effective Hydraulic Conductivity from Gridded Conductivity Fields?

We confirm that energy dissipation weighting provides the most accurate approach to determining the effective hydraulic conductivity (K<sub>eff</sub>) of a binary K grid. A deep learning algorithm (UNET) can infer K<sub>eff</sub> with extremely high accuracy (R<sup>2<...

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Bibliographic Details
Main Authors: Mohammad A. Moghaddam, Paul A. T. Ferre, Mohammad Reza Ehsani, Jeffrey Klakovich, Hoshin Vijay Gupta
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Water
Subjects:
deep learning
machine learning
hydrogeology
effective hydraulic conductivity
energy dissipation
UNET
Online Access:https://www.mdpi.com/2073-4441/13/12/1668

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