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formation-permeability
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Application of artificial neural network for estimation of formation permeability in an iranian reservoir
, Article 1st International Petroleum Conference and Exhibition, Shiraz, 4 May 2009 through 6 May 2009 ; 2009 ; Masihi, M ; Fatholahi, S ; Sharif University of Technology
European Association of Geoscientists and Engineers, EAGE
2009
Abstract
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...
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...