Automatic well failure analysis for the sucker rod pumping systems / Ramez Maher Aziz Zaky Abdalla ; Supervised Ahmed Hamdy Elbanbi , Mahmoud Abuelela Mohamed

By:

Ramez Maher Aziz Zaky Abdalla

Contributor(s):

Material type: Text

TextLanguage: English Publication details: Cairo : Ramez Maher Aziz Zaky Abdalla , 2018Description: 85 P. : charts ; 30cmOther title:

تحليل مشاكل الآبار لمضخات العمود الماصة [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: Sucker rod pumping is one of the most common forms of the artificial lift technologies. Monitoring the working condition of the sucker rod pumping system is a hard task which requires several details in order to sustain acceptable productivity levels. Hence, a description model for the dynamometer cards was established. Then, machine learning techniques were trained to predict downhole pumping condition. The proposed model is trained by using real field data of about 6,385 dynamometer cards. The results show that the developed model achieved Percent Error of 1.51%

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Home library	Call number	Copy number	Status	Barcode
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.12.M.Sc.2018.Ra.A (Browse shelf(Opens below))	76428.CD	Not for loan	01020110076428000
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.12.M.Sc.2018.Ra.A (Browse shelf(Opens below))		Not for loan	01010110076428000

Browsing المكتبة المركزبة الجديدة - جامعة القاهرة shelves Close shelf browser (Hides shelf browser)

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	Cai01.13.12.M.Sc.2018.Om.D Development of an analytical model for the prediction of miscible eor methods performanc /	Cai01.13.12.M.Sc.2018.Om.D Development of an analytical model for the prediction of miscible eor methods performanc /	Cai01.13.12.M.Sc.2018.Ra.A Automatic well failure analysis for the sucker rod pumping systems /	Cai01.13.12.M.Sc.2018.Ra.A Automatic well failure analysis for the sucker rod pumping systems /	Cai01.13.12.M.Sc.2018.Ra.C Coal flotation in mixtures of inorganic salts /	Cai01.13.12.M.Sc.2018.Ra.C Coal flotation in mixtures of inorganic salts /	Cai01.13.12.M.Sc.2018.Sh.P Production data analysis techniques for shale gas reservoirs : Comparison study /	Next

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

Sucker rod pumping is one of the most common forms of the artificial lift technologies. Monitoring the working condition of the sucker rod pumping system is a hard task which requires several details in order to sustain acceptable productivity levels. Hence, a description model for the dynamometer cards was established. Then, machine learning techniques were trained to predict downhole pumping condition. The proposed model is trained by using real field data of about 6,385 dynamometer cards. The results show that the developed model achieved Percent Error of 1.51%

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