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The estimation of formation permeability in a carbonate reservoir using an artificial neural network
, Article Petroleum Science and Technology ; Vol. 30, issue. 10 , Apr , 2010 , p. 1021-1030 ; ISSN: 10916466 ; Masihi, M ; Fatholah,i S ; Sharif University of Technology
Abstract
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 estimation of formation permeability in a carbonate reservoir using an artificial neural network
, Article Petroleum Science and Technology ; Volume 30, Issue 10 , 2012 , Pages 1021-1030 ; 10916466 (ISSN) ; Masihi, M ; Fatholahi, S ; Sharif University of Technology
2012
Abstract
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...