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العنوان
Prediction of geomechanical properties from seismic attributes and well logs data analysis using artificial neural network in F3-block of the North Sea basin, offshore Netherlands /
الناشر
Hajir Oguz Hassan Almula ,
المؤلف
Hajir Oguz Hassan Almula
هيئة الاعداد
باحث / Hajir Oguz Hassan Almula
مشرف / Abdelsattar A. Dahab
مشرف / Abdulaziz M. Abdulaziz
مشرف / Abdel-Alim Hashem El-Sayed
تاريخ النشر
2018
عدد الصفحات
84 P. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة (متفرقات)
تاريخ الإجازة
14/1/2019
مكان الإجازة
جامعة القاهرة - كلية الهندسة - Metallurgical Engineering
الفهرس
Only 14 pages are availabe for public view

from 104

from 104

Abstract

This research aims to integrating seismic attributes and well data using supervised Artificial Neural Networks to identify Geomechanical Properties throughout F3-Block of the North Sea basin, Netherlands.This typically helps wellbore stability, drilling, and hydraulics fracturing. During the development, the engineers struggle to optimize drilling periods, reduce uncertainties and production costs, and make the best optimization of the use of available data. The verification analysis showed that property prediction achieved good results in Young{u2019}s modulus and Vp/Vs ratio but was marginal in Poisson{u2019}s ratio. Accordingly, results indicated a good potential of the proposed methodology in identifying geomechanical properties with accurate mapping and distribution throughout the pay zones and overlying sedimentary succession