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Synthetic dataset of pore scale multiphase flow from direct numerical simulations

  • Unais Ashraf
  • , Saideep Pavuluri*
  • , Mohammed Ishaq
  • , Mohammed Yaqoob
  • , Thomas Daniel Seers
  • , Chaudhry Ali Usman
  • , Rizwan Muneer
  • , Jamal Hannun
  • , Riyadh l. Al-Raoush
  • , Harris Sajjad Rabbani
  • *Corresponding author for this work
  • Texas A&M University at Qatar
  • Hamad bin Khalifa University
  • Qatar University

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding the physics of fluid displacement through the pore spaces in multiphase environments are essential for improving the safety and optimizing the performance of diverse complex subsurface engineering applications. We conduct high-fidelity two phase flow simulations at the pore-scale using direct numerical simulations on six porous media that have different permeability. We consider nine viscosity ratios and ten contact angles, resulting in a total of 540 simulations. The open-source dataset available on Zenodo includes specifics related to the flow patterns, as well as the spatial and temporal variations of pressure and velocity within the pore spaces. This comprehensive dataset can support (i). the training of machine learning algorithms and (ii). serve as a benchmark for flows predicted by computationally efficient tools including machine learning algorithms and pore network models.

Original languageEnglish
Article number942
JournalScientific data
Volume13
Issue number1
Early online dateApr 2026
DOIs
Publication statusE-pub ahead of print - Apr 2026

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