History-Matching of Imbibition Flow in Multiscale Fractured Porous Media Using Physics-Informed Neural Networks (PINNs)

Documenti analoghi

• Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study
  di: Abbasi, Jassem, et al.
  Pubblicazione: (2025)
• Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs)
  di: Abbasi, Jassem, et al.
  Pubblicazione: (2022)
• PTL-PINNs: Perturbation-Guided Transfer Learning with Physics- Informed Neural Networks for Nonlinear Systems
  di: Alexandrino, Duarte, et al.
  Pubblicazione: (2026)
• Assessment of Guidewire‐Induced Deviation in Fractional Flow Reserve: Impact of Lesion Morphology and Pressure Guidewire Malposition
  di: Reza Rasooli, et al.
  Pubblicazione: (2025)
• The Imbibition Mechanism and the Calculation Method of Maximum Imbibition Length during the Hydraulic Fracturing
  di: Zhongwei Wu, et al.
  Pubblicazione: (2024)