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MultiScale Pore Network Modeling to be Compared with Experimental Results

Iraji, Farhad | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52716 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Ayatollahi, Shahab; Jamshidi, Saeed; Kazemzadeh, Ezatollah
  7. Abstract:
  8. The study of porous media, especially in pore-scales (micro and nano scales), is of particular importance in various sciences such as petroleum engineering, chemical, and civil engineering. Determine the physics of the pore scale to understand it better, identify the conditions for it to enforce the laws better, and explain some of the phenomena unknown so far, and finally obtain the parameters performed in the laboratory for specific samples are the main goals of these studies. One of the most well-known methods for analyzing porous media is pore network modeling. These models are always affected by the macroscopic structure of porous media, such as their multiscale state. In this study, an algorithm is presented to obtain a network of multiscale mediums with more compact portions inside. Using this method, which is based on matrices obtained from different microtomography images at different resolutions, their multiscale pore networks are modeled and then petrophysical properties including, porosity, permeability, formation factor, as well as capillary pressure, relative permeability, and resistivity index curves for these multi-scale networks were obtained and compared with laboratory results.By applying this algorithm, on the one hand, multiscale pore networks of complex samples are more easily modeled, and the results are in good agreement with the laboratory data, on the other hand, the runtime to obtain various parameters including absolute permeability and capillary pressure and relative permeability curves, decline significantly. For example, for a carbonate sample, the percentage of absolute permeability error decreased from about 50% to 6% relative to the laboratory results, and its runtime improved by about 9 times.The algorithm can also be used to reduce the computational time to extract pore networks of homogeneous samples and their associated parameters
  9. Keywords:
  10. Porous Media ; Pore-Scale Model ; Microtomography Image ; Multi-Scale Porous Network ; Petrophysical Parameters

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