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Area of Science:

  • Computational physics
  • Porous media science
  • Fluid dynamics

Background:

  • Multiphase flow traditionally relies on laboratory experiments.
  • Computational simulations offer a scalable and efficient alternative for studying complex fluid behaviors.
  • Pore-scale transport phenomena are crucial for understanding macroscopic flow properties.

Purpose of the Study:

  • To generate a comprehensive dataset of two-phase flow simulations.
  • To investigate the impact of wettability, capillary numbers, and porous geometries on flow dynamics.
  • To provide a resource for validating and developing upscaling theories and data-driven models.

Main Methods:

  • Utilized Lattice-Boltzmann simulations on high-performance computing facilities (over 100 million GPU hours).
  • Covered diverse wetting conditions, capillary numbers, and porous geometries.
  • Validated simulation results against synchrotron beamline experiments.

Main Results:

  • Generated a dataset including 50 relative permeability curves and over 25,000 fluid configurations.
  • Revealed key insights into wettability effects and ganglion dynamics.
  • Demonstrated the computational feasibility and value of large-scale simulations for porous media research.

Conclusions:

  • The open-access dataset provides a valuable foundation for porous media research.
  • Enables broad collaboration and future studies on pore-scale transport and relative permeability.
  • Facilitates the development of new data-driven modeling approaches for multiphase flow.