The uses of soft computing techniques comprising artificial neural networks, fuzzy logic and genetic algorithms are emerging for the building of permeability interpretation models in well log data analysis. Regardless of which soft computing techniques are used, they rely on a set of core permeability data to give a better understanding of the formation. However uncertainties and errors with the core permeability data may undetermined the accuracy of permeability determination. This paper examines the problems that could possibly appear in the core permeability data. In most cases, data preprocessing and postprocessing are required to ensure that the permeability determination is successful. In this paper, soft computing techniques that are...
Objectives/Scope: Estimating reservoir petrophysical parameters such as porosity, permeability is vi...
Permeability and rock type are the most important rock properties which can be used as input paramet...
Abstract: The success of an Artificial Neural Network (ANN) based data interpretation model depends ...
This paper introduces a new neural-fuzzy technique combined with genetic algorithms in the predictio...
Permeability is the ability of porous rock to transmit fluids. An accurate knowledge of reservoir pe...
In this paper we compare three different soft computing methods used as the well log data analysis m...
This paper presents a method for predicting permeability as one of the most important parameters in ...
Permeability can be considered as the one of the main petro-physical parameters that plays an import...
This study discussed on determining of reservoir rock permeability in the challenging and heterogene...
Permeability is one of the critical properties of reservoir rocks used to describe the ability in co...
Permeability, along with the porosity, comprises one of the two most important properties in petrole...
The success of an artificial neural network (ANN) based data interpretation model depends heavily on...
Permeability can be directly measured using cores taken from the reservoir in the laboratory. Due to...
Permeability is one of the most important characteristics of hydrocarbon bearing formations. Formati...
International audienceCharacterization of shaly sand reservoirs by well log data is a usual way of d...
Objectives/Scope: Estimating reservoir petrophysical parameters such as porosity, permeability is vi...
Permeability and rock type are the most important rock properties which can be used as input paramet...
Abstract: The success of an Artificial Neural Network (ANN) based data interpretation model depends ...
This paper introduces a new neural-fuzzy technique combined with genetic algorithms in the predictio...
Permeability is the ability of porous rock to transmit fluids. An accurate knowledge of reservoir pe...
In this paper we compare three different soft computing methods used as the well log data analysis m...
This paper presents a method for predicting permeability as one of the most important parameters in ...
Permeability can be considered as the one of the main petro-physical parameters that plays an import...
This study discussed on determining of reservoir rock permeability in the challenging and heterogene...
Permeability is one of the critical properties of reservoir rocks used to describe the ability in co...
Permeability, along with the porosity, comprises one of the two most important properties in petrole...
The success of an artificial neural network (ANN) based data interpretation model depends heavily on...
Permeability can be directly measured using cores taken from the reservoir in the laboratory. Due to...
Permeability is one of the most important characteristics of hydrocarbon bearing formations. Formati...
International audienceCharacterization of shaly sand reservoirs by well log data is a usual way of d...
Objectives/Scope: Estimating reservoir petrophysical parameters such as porosity, permeability is vi...
Permeability and rock type are the most important rock properties which can be used as input paramet...
Abstract: The success of an Artificial Neural Network (ANN) based data interpretation model depends ...