PhD Position at Université Gustave Eiffel – Navier Laboratory Pore Network Modeling of Multiphase Flow in CO₂-Water-Rock Systems under Variable Thermodynamic and Flow Regimes

Application Process Interested candidates should contact the supervision team no later than the 18th April using the email addresses provided above and submit the following documents: a CV, a motivation letter, two reference letters, and Master’s transcript. After a first interview round, the candidate selected by the supervisors will be invited to an oral exposition in early June, during which they will present their background and discuss the project. Final selection is subject to approval by an external evaluation committee. Job requirements Applicants should meet the following requirements: • Master’s degree (or equivalent) in geosciences, geotechnical engineering, reservoir engineering, or a closely related field • Strong proficiency in English (written and spoken) • Interest in numerical modeling, multiphase flow, and energy transition applications • Motivation to conduct scientific research and autonomy The following skills are highly desirable: • Programming experience (e.g., C++, Python) • Experience with pore network modeling and/or finite volume methods • Experience with modeling of fluid flow in porous media The PhD project This PhD project aims to develop advanced pore network models (PNMs) to simulate CO₂ water multiphase flow in porous media under varying thermodynamic and flow conditions, and to bridge the gap between pore-scale phenomena and reservoir-scale modeling. The research will focus on the following key tasks: • Development of dynamic pore network models integrated with phase equilibria models and equations of state to account for pressure, temperature, and flow regime dependencies on multiphase flow properties. • Representative Elementary Volume (REV), investigating the scale at which relative permeability becomes representative for target rock types and informing experimentalists on appropriate sample sizes. • Development of an upscaling methodology to use robust, state- and pore-structure dependent relative permeability models suitable for reservoir-scale simulations This work will contribute to improving the predictive capability of pore-scale models and enhancing our understanding of how pore-scale physics impacts large-scale CO₂ storage performance.