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The permeability is one of the most important reservoir parameters and its accurate prediction is necessary for reservoir management and enhancement. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs [1], these correlations cannot be modified accurately in carbonate reservoir for the wells which are not cored and there is no welltest data. Therefore estimation of these parameters is a challenge in reservoirs with no coring sample and welltest data. One of the most powerful tools to estimate permeability from well logs is Artificial Neural Network (ANN) whose advantages and disadvantages have been discussed by several authors [2]. In this... 

Experimental permeability and diffusivity values for CO2 and CH4 through imidazolium-based ionic liquid 1-hexyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([hmim][Tf2N]) were determined in the temperature range of 300-320K using temperature correction factor defined in our previous study. According to literature, experimental values of permeability and diffusivity obtained in this study for CO2 in [hmim][Tf2N], showed good agreement with predictive models reported by other researchers. In addition, experimental values of permeability and diffusivity for CH4 in [hmim][Tf2N] as a function of pressure have been reported in this study. Considering the results of present study and... 

Reservoir permeability is an important parameter that its reliable prediction is necessary for reservoir performance assessment and management. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs, these correlations cannot be accurately depicted in carbonate reservoir for the wells that are not cored and for which there are no welltest data. Therefore, having a framework for estimation of these parameters in reservoirs with neither coring samples nor welltest data is crucial. Rock properties are characterized by using different well logs. However, there is no specific petrophysical log for estimating rock permeability; thus, new methods... 

Reservoir permeability is an important parameter that its reliable prediction is necessary for reservoir performance assessment and management. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs, these correlations cannot be accurately depicted in carbonate reservoir for the wells that are not cored and for which there are no welltest data. Therefore, having a framework for estimation of these parameters in reservoirs with neither coring samples nor welltest data is crucial. Rock properties are characterized by using different well logs. However, there is no specific petrophysical log for estimating rock permeability; thus, new methods... 

The semi-empirical Kozeny–Carman (KC) equation is the widely used equation for determining permeability of porous media. Recent studies have shown that KC coefficient (CKC ) is a function of porous media parameters. In this study, the relation between parameters of randomly generated porous media is investigated to improve permeability prediction. In particular, site percolation theory is applied to construct random porous media. The static parameters of porous media, including porosity and specific surface area, are evaluated from porous media structure, and dynamic parameters, tortuosity and permeability, are derived from the results of Lattice Boltzmann fluid flow simulation....