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Quantification and prediction of carbonate diagenesis from well logs and core data by artificial neural network /

Samar Saied Abdelrady Shahat Hawary

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

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering

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



Carbonate reservoir Diagenesis Coefficient prediction Well logging