Prediction of hydraulic properties in carbonate reservoirs using artificial neural network /
Khalaf Gad Salem Ibrahim
Prediction of hydraulic properties in carbonate reservoirs using artificial neural network / التنبؤ بالخواص الهيدروليكية فى الخزانات الجيرية باستخدام الشبكة العصبية الصناعية Khalaf Gad Salem Ibrahim ; Supervised Abdelsattar A. Dahab , Abdulaziz M. Abdulaziz - Cairo : Khalaf Gad Salem Ibrahim , 2017 - 105 P. : charts , facsimiles ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering
The success of applying artificial neural networks (ANNs) to solve complex engineering problems has drawn attention to its potential applications in the petroleum industry especially in formation evaluation. In the present study, models are developed to predict the hydraulic properties (porosity and permeability) in carbonate reservoir from well logging measurements using ANN. The developed ANN model for carbonate reservoir is constructed and validated using numerous dataset collected from various worldwide carbonate reservoirs
Carbonate reservoir Hydraulic properties Prediction Well logging
Prediction of hydraulic properties in carbonate reservoirs using artificial neural network / التنبؤ بالخواص الهيدروليكية فى الخزانات الجيرية باستخدام الشبكة العصبية الصناعية Khalaf Gad Salem Ibrahim ; Supervised Abdelsattar A. Dahab , Abdulaziz M. Abdulaziz - Cairo : Khalaf Gad Salem Ibrahim , 2017 - 105 P. : charts , facsimiles ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering
The success of applying artificial neural networks (ANNs) to solve complex engineering problems has drawn attention to its potential applications in the petroleum industry especially in formation evaluation. In the present study, models are developed to predict the hydraulic properties (porosity and permeability) in carbonate reservoir from well logging measurements using ANN. The developed ANN model for carbonate reservoir is constructed and validated using numerous dataset collected from various worldwide carbonate reservoirs
Carbonate reservoir Hydraulic properties Prediction Well logging