Imperial College London

Dr Sajjad Foroughi

Faculty of EngineeringDepartment of Earth Science & Engineering

Research Associate



+44 (0)20 7594 6451s.foroughi Website




440/16Royal School of MinesSouth Kensington Campus





I am a Senior Postdoctoral Researcher in the Imperial-Shell Digital Rocks Program, with over five years of research in modeling and simulating multiphase flow in porous media at pore and continuum scales. My work focuses on the challenges of multiphase flow in porous media. These are key to CO2 and hydrogen storage, understanding underground reservoirs, geothermal energy use, groundwater management, preserving natural construction materials, and advancing process design and battery development. My expertise in pore-scale phenomena is crucial for progressing large-scale energy transition projects.

Current Work

Heterogeneous rocks exhibit a wide variation in pore sizes, ranging from less than 0.1 microns to over 100 microns. Due to this diversity, capturing the entire pore space using micro-CT imaging techniques is challenging. However, the application of differential imaging enables the quantification of sub-resolution porosity and the generation of detailed porosity maps. In our preprint paper, titled ''Incorporation of Sub-Resolution Porosity into Two-Phase Flow Models with a Multiscale Pore Network,' I have developed a comprehensive workflow to integrate this sub-resolution porosity into multiscale pore network models. This methodology significantly enhances the accuracy of our models by accounting for the finer, unresolved details of the pore structure. The resulting 3D image-based, multi-scale pore network model has undergone rigorous validation and has proven effective in simulating drainage and imbibition processes in complex and heterogeneous rock formations.

Research Interest

  • Computational Physics: Multiphase Flow in Porous Media, Pore-Scale Modelling, High-Performance Computing in Physics, Numerical Solutions of Nonlinear Differential Equations, Computational Thermodynamics.
  • Computational Methods: Applied Optimisation, Statistical Analysis, Data Assimilation, Data Science, Machine Learning, and Uncertainty Quantification.




Goodarzi S, Zhang Y, Foroughi S, et al., 2024, Trapping, hysteresis and Ostwald ripening in hydrogen storage: a pore-scale imaging study, International Journal of Hydrogen Energy, Vol:56, ISSN:0360-3199, Pages:1139-1151

Li M, Foroughi S, Zhao J, et al., 2023, Image-based pore-scale modelling of the effect of wettability on breakthrough capillary pressure in gas diffusion layers, Journal of Power Sources, Vol:584, ISSN:0378-7753

Selem AM, Agenet N, Foroughi S, et al., 2023, Pore-Scale Imaging of Emulsification of Oil during Tertiary and Secondary Low Salinity Waterflooding in a Reservoir Carbonate, Energy and Fuels, Vol:37, ISSN:0887-0624, Pages:16368-16377

Zhang G, Foroughi S, Bijeljic B, et al., 2023, A method to correct steady-state relative permeability measurements for inhomogeneous saturation profiles in one-dimensional flow, Transport in Porous Media, Vol:149, ISSN:0169-3913, Pages:837-852

Qu M-L, Blunt MJ, Fan X, et al., 2023, Pore-to-mesoscale network modeling of heat transfer and fluid flow in packed beds with application to process design, Aiche Journal, ISSN:0001-1541

More Publications