Publications
Article · Computer Methods in Applied Mechanics and Engineering · July 20, 2025
Coupled pressure and saturation prediction for two-phase flow in porous media using physics-informed neural networks (PINNs)
Yerzhan Kenzhebek, Timur Imankulov, Samson Dawit Bekele, I. Panfilova, Darkhan Akhmed-Zaki
Model Reduction and Neural NetworksReservoir Engineering and Simulation MethodsEnhanced Oil Recovery Techniquesphysics-informed neural networkstwo-phase flowporous media
More by Samson Dawit Bekele
- Separating Artificial-Viscosity Annealing from the L-BFGS Viscosity in Physics-Informed Neural Networks for Two-Phase FlowBig Data and Cognitive Computing · 2026
- Identifiability and Conditioning of Flux-Parameter Inversion for the Buckley–Leverett EquationMathematics · 2026
- Artificial-viscosity schedules for Buckley–Leverett PINNs: code and reproducibility archiveZenodo · 2026
- Physics-Informed Neural Networks for Coupled Non-Isothermal Two-Phase Flow in Porous Media: Training Pathologies, Remedies, and the Role of Gradient ConflictMachine Learning and Knowledge Extraction · 2026