Postdoctoral Research Fellow in Modeling Naturally Fractured Reservoirs using Finite-Element based
King Abdullah University of Science and Technology School of Applied Mathematics,Programming Languages
Saudi Arabia

Job Title:Postdoctoral Research Fellow in Modeling Naturally Fractured Reservoirs using Finite-Element based 
Positions:King Abdullah University of Science and Technology
Location:KAUST, Saudi Arabia
Field: Applied Mathematics,Programming Languages


Modeling naturally fractured reservoirs is re-gaining interest in the Oil & Gas industry and academia for application in carbonate fractured reservoirs and unconventional reservoirs where natural fractures can play a key role on production performance. One of the persisting challenges is to create complex 3D fracture networks and solve multiphase flow efficiently. None of the existing tools can integrate complex flow on Discrete Fracture Networks (DFN). The objective of this project is to develop a tool to generate DFN models amenable for multiphase flow, and scale up the model to be usable with conventional simulators. Finite element-based methods such as Mixed-Finite-Element or Control-Volume methods are convenient thanks to their suitability for complex unstructured grids.

Applications are sought for a two-year postdoc position. The position will include a competitive salary based on the candidate's qualifications; benefits include medical and dental insurance, free furnished housing on the KAUST campus, annual travel allowance to visit home country, annual paid vacation, and other generous benefits. The successful applicant will become a part of the Ali I. Al-Naimi Petroleum Engineering Research Center (ANPERC) at KAUST.


Qualified applicants should possess a Ph.D. in Applied Mathematics/Computational sciences, Reservoir Engineering, or a closely related field. The candidate should be experienced with multiphase flow in porous media using FE, FV or FD methods, and should be proficient with a scientific programming language such as Fortran or C/C++. Familiarity with linear/nonlinear solvers, 2D/3D unstructured gridding, and high performance computing is welcome. Candidates with good publishing record will be given preference.

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