Rate of penetration predictive model using artificial neural networks / Mustafa Mohamed Amer ; Supervised Abdelsattar Dahab , Abdelalim Hashem Elsayed
Material type:
TextLanguage: English Publication details: Cairo : Mustafa Mohamed Amer , 2009Description: 78 P. : charts ; 30cmOther title: - نموذج التنبؤ بمعدل الحفر باستخدام الشبكات العصبية الاصطناعية [Added title page title]
- Issued also as CD
| Item type | Current library | Home library | Call number | Copy number | Status | Barcode | |
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Thesis
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.12.M.Sc.2009.Mu.R (Browse shelf(Opens below)) | Not for loan | 01010110054470000 | ||
CD - Rom
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.12.M.Sc.2009.Mu.R (Browse shelf(Opens below)) | 54470.CD | Not for loan | 01020110054470000 |
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering
Bit performance is a key factor to improve drilling performance and reduce drilling costs . The objective of the research is to provide a tool that can predict ROP in order to optimize bit selection . The specific goal of this study is a mean to predict ROP using Artificial Neural Networks ( ANN ) model . Lithology changes , drilling parameters data and bit data were the inputs of our model
Issued also as CD
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