Prediction of porous media fluid flow using physics informed neural networks

Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

(2020) A. M. Tartakovsky et al.   WATER RESOURCES RESEARCH

Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport

(2020) QiZhi He et al.   ADVANCES IN WATER RESOURCES

Modeling Steady-State Foam Flow: Hysteresis and Backward Front Movement

(2019) Muhammad M. Almajid et al.   ENERGY & FUELS

Hidden physics models: Machine learning of nonlinear partial differential equations

(2018) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

DGM: A deep learning algorithm for solving partial differential equations

(2018) Justin Sirignano et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A unified deep artificial neural network approach to partial differential equations in complex geometries

(2018) Jens Berg et al.   NEUROCOMPUTING

Solving high-dimensional partial differential equations using deep learning

(2018) Jiequn Han et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Insights into the fractional flow of low salinity water flooding in the light of solute dispersion and effective salinity interactions

(2018) Hasan Al-Ibadi et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep learning

(2015) Yann LeCun et al.   NATURE