Pore-Scale modeling for NMR and PC measurements using Random-Walk, Finite-Elements and Machine-Learning

King Abdullah University of Science and Technology
April 15, 2024
Offerd Salary:Negotiation
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Contract Type:Other
Working Time:Negotigation
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King Abdullah University of Science and Technology: Postdoc Positions:

Physical Science and Engineering Division (postdoc): Energy Resources and Petroleum Engineering (Postdoc)


Saudi Arabia

Open Date

Apr 05, 2022


The wire-line nuclear magnetic resonance (NMR) tool is a well-borehole logging technology that is routinely used for exploration and reservoir characterization. NMR logging is a fast imaging technology that can be applied while drilling within the wellbore to provide various spatially continuous measurements, such as formation porosity, permeability, water, and hydrocarbon distributions. This technology has enabled major advances in the oil & gas industry related to exploration, reservoir characterization, and management. However, its capability is not fully exploited.

The objective of this project is to develop a modeling framework including the use of Random-Walk method to predict NMR measurements, pore-scale finite- element modeling on 3D digital models, generated from CT-images to predict capillary pressure, and data-driven, physics-driven machine-learning.

Applications are sought for a two-year postdoc position, and will work closely with an industry partner. 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 computational sciences, geoscience, petrophysics, reservoir engineering, or a closely related field. The candidate should be experienced with multiphase flow in porous media, pore-scale modeling, random-walk or Lattice Boltzmann method, familiar with NMR and MICP technologies and measurements, and proficient in scientific coding, including C++ , Python, Matlab, and physics-driven machine learning.


  • Excellent problem-solving skills
  • Excellent communication skills in English
  • Good record of publications in quality journals
  • Application Instructions
  • Single Page Cover letter including a description of research experience and research interests
  • CV including list of publications
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