header
Local cover image
Local cover image
Image from OpenLibrary

Artificial intelligence applications for pore pressure and fracture pressure prediction from seismic attributes analysis and well logs data / Mohamed Atta Farahat Mohamed ; Supervised Abdelalim Hashem Elsayed , Abdulaziz Mohamed Abdulaziz

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohamed Atta Farahat Mohamed , 2018Description: 103 P. : photographs ; 30cmOther title:
  • تطبيقات الذكاء الاصطناعى فى التنبؤ بضغط المسام و ضغط الكسر بتحليل بيانات السمات الزلزالية السيزمية وتسجيلات الابار [Added title page title]
Subject(s): Online resources: Available additional physical forms:
  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering Summary: This study aims to investigate the pore and fracture pressure of sub-surface formations. Eaton{u2019}s method is applied to predict pore and fracture pressure of wells. Inversion process with numerous algorithms are applied to seismic area of the field. Prediction methods are applied to investigate best attributes such as single, multiple seismic attribute analysis and neural network. Well logs and seismic attributes obtained from inversion process and seismic data are used to train ANN. ANN is validated using blind wells which are not included in training process. The correlations of ANN training and validation are good so ANN is applied for prediction of pore and fracture pressure for 3D seismic area of field
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.12.M.Sc.2018.Mo.A (Browse shelf(Opens below)) Not for loan 01010110076827000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.12.M.Sc.2018.Mo.A (Browse shelf(Opens below)) 76827.CD Not for loan 01020110076827000

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

This study aims to investigate the pore and fracture pressure of sub-surface formations. Eaton{u2019}s method is applied to predict pore and fracture pressure of wells. Inversion process with numerous algorithms are applied to seismic area of the field. Prediction methods are applied to investigate best attributes such as single, multiple seismic attribute analysis and neural network. Well logs and seismic attributes obtained from inversion process and seismic data are used to train ANN. ANN is validated using blind wells which are not included in training process. The correlations of ANN training and validation are good so ANN is applied for prediction of pore and fracture pressure for 3D seismic area of field

Issued also as CD

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer

Local cover image