TY  - BOOK
AU  - Ramez Maher Aziz Zaky Abdalla
AU  - Ahmed Hamdy Elbanbi , 
AU  - Mahmoud Abuelela Mohamed , 
TI  - Automatic well failure analysis for the sucker rod pumping systems / 
PY  - 2018///
CY  - Cairo : 
PB  - Ramez Maher Aziz Zaky Abdalla , 
KW  -  Back Propagation Neural Networks (BPNN)
KW  - Sucker Rod Pumping System
KW  - Support Vector Machine (SVM)
N1  - Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Metallurgical Engineering; Issued also as CD
N2  - 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%
UR  - http://172.23.153.220/th.pdf
ER  -