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Capillary pressure estimation of porous media using statistical pore size function

Ghazanfari, M. H ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. Publisher: 2006
  3. Abstract:
  4. Real porous media even though seemingly homogenous and isotropic are most often nonuniform, and the nonuniformity may affect the macroscopic properties of porous media such as permeability, capillary pressure which is a result of the tortuous and circuitous nature of the flow paths in medium. In this study a glass type micromodel is considered as a porous media sample. A four parametric probability density function are used to express pore throat size, pore body size and pores length distributions which are measured using image analysis technique of porous model. The statistical models parameters are calculated by fitting the statistical model to the measured data of pore throat pore body and pores length distributions. Integrating the pore size distribution function, capillary pressure saturation mathematical model has been developed which matched quite well with the experimentally measured capillary pressure data of drainage process of porous model. The parameters of capillary pressure model are related to pores size sorting, pore throat geometrical factor, threshold pressure and residual water saturation. Also as a related development the absolute permeability-porosity ratio of model is calculated based on proposed statistical pore model and compared with the measured data. An estimation of the relative permeability curves is also presented which is based on capillary pressure model. The results show that me absolute permeability-porosity ratio is a function of square of average of radius and the estimated absolute permeability-porosity ratio is in a good agreement with the experimentally measured value. Also, it may be relative permeability estimation based on statistical model of pore size distribution, unless mey take into account and make use of me interconnectivity of the pores, can not consider successful. The proposed probability distribution function has the flexibility of representing a wide variety of pore size distribution
  5. Keywords:
  6. Mathematical models ; Pore size ; Porous materials ; Probability density function ; Statistical methods ; Macroscopic properties ; Statistical pore size function ; Capillarity
  7. Source: CHISA 2006 - 17th International Congress of Chemical and Process Engineering, Prague, 27 August 2006 through 31 August 2006 ; 2006 ; 8086059456 (ISBN); 9788086059457 (ISBN)