Correct estimation of permeability using experiment and simulation - Graduate Seminar


Estimation of permeability of porous media is essential in many scientific and engineering endeavors. Despite apparent simplicity of permeability measurements, the literature data are scattered, and this scatter not always can be attributed to the precision of experiment or simulation or to sample variability. In this work, we demonstrate an excellent agreement between experiments and simulations performed directly on three-dimensional images of the sample. Analyzing when experiments and simulations agree reveals a major flaw affecting many experimental measurements with the out-of-sample placement of pressure ports, including industry standards. The flaw originates from (1) incorrect calculation of the applied pressure gradient, (2) omitting virtual part of the measured system, and (3) pressure loss at the sample–tube contact. Contrary to common wisdom, the relative magnitude of (3) is defined by the sample–tube diameter ratio and is independent of the size of sample pores. Our findings are applicable to a wide range of permeability measurements, including geological-sample-type (Hassler cell) and membrane-type.


Siarhei Khirevich graduated from Belarusian State University with a diploma in Radiophysics and Electronics. Hereafter he moved to Germany (Magdeburg and later Marburg) to pursue a doctoral degree under the supervision of Prof. Ulrich Tallarek at Universities of Magdeburg and Marburg. Khirevich remained with the group as a Post-doctoral Fellow to perform additional research relating to findings during his Ph.D. studies.  After short-term visit with Prof. Irina Ginzburg (France), Khirevich joined KAUST as a Post-doctoral Fellow, and currently work as a research scientist at Ali I. Al-Naimi Petroleum Engineering Research Center at the group of Prof. Tadeusz Patzek. His research interests include Stokes flow, lattice Boltzmann and random walk particle tracking methods, high-performance computing, packed beds, pore-scale flows from computational and experimental perspectives, computed tomography.

Event Quick Information

01 Feb, 2023
11:45 AM - 12:45 PM
Building 9, Level 2, Lecture Hall 1