Samar Saied Abdelrady Shahat Hawary <br/><br/>
Quantification and prediction of carbonate diagenesis from well logs and core data by artificial neural network /  
 التقييم الكمى لتحوارت الصخور الجيرية والتنبؤ بها من معلومات تسجيلات الآبار واللباب الصخرى عن طريق الشبكات الاصطناعية العصبية 
Samar Saied Abdelrady Shahat Hawary ; Supervised Abdulaziz M. Abdulaziz 
 - Cairo :   Samar Saied Abdelrady Shahat Hawary ,   2019 
 - 111 P. :   charts , maps ;   30cm  
<br/><br/>Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering 
<br/><br/> The application of artificial neural networks (ANNs) is used successfully to generate a numerical scale for diagenesis quantification from 0 to 10 with specified particular range for each type of diagenesis. It enhances identifying the rock typing and generated a link between geological and reservoir modeling. Also, a mathematical correlation is generated to directly predict the quantification of diagenesis in carbonate rocks in the study area 
<br/><br/>
<br/><br/><label>Subjects--Index Terms: </label>Carbonate reservoir  Diagenesis Coefficient prediction Well logging