Predicting multiphase flow behavior of methane in shallow unconfined aquifers using conditional deep convolutional generative adversarial network

Published: 12 September 2022| Version 1 | DOI: 10.17632/vx2rpp2wh9.1
Contributors:
Reza Ershadnia,
,
,
,

Description

The attached CMG-GEM input files and cDC-GANs codes (written by Python) were used to simulate CH4 migration in shallow unconfined aquifer systems.

Files

Categories

Numerical Modeling, Adversarial Machine Learning

Licence