Prediction of penetration rate and cost with artificial neural network for Alhafaya oil field
Other Title(s)
تخمين معدل الحفر و الكلفة بواسطة الشبكة العصابية الصناعية لحقل الحلفاية النفطي
Joint Authors
Abd al-Hadi, Hasan
Manati, Kazim Hammud
Source
Iraqi Journal of Chemical and Petroleum Engineering
Issue
Vol. 19, Issue 4 (31 Dec. 2018), pp.21-27, 7 p.
Publisher
University of Baghdad College of Engineering
Publication Date
2018-12-31
Country of Publication
Iraq
No. of Pages
7
Main Subjects
Abstract EN
Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs.
This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process.
This paper shows a new technique of rate of penetration prediction by using artificial neural network technique.
A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field.
These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT).
Five data set represented five formations gathered from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability.
The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model.
In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.
American Psychological Association (APA)
Manati, Kazim Hammud& Abd al-Hadi, Hasan. 2018. Prediction of penetration rate and cost with artificial neural network for Alhafaya oil field. Iraqi Journal of Chemical and Petroleum Engineering،Vol. 19, no. 4, pp.21-27.
https://search.emarefa.net/detail/BIM-897759
Modern Language Association (MLA)
Manati, Kazim Hammud& Abd al-Hadi, Hasan. Prediction of penetration rate and cost with artificial neural network for Alhafaya oil field. Iraqi Journal of Chemical and Petroleum Engineering Vol. 19, no. 4 (Dec. 2018), pp.21-27.
https://search.emarefa.net/detail/BIM-897759
American Medical Association (AMA)
Manati, Kazim Hammud& Abd al-Hadi, Hasan. Prediction of penetration rate and cost with artificial neural network for Alhafaya oil field. Iraqi Journal of Chemical and Petroleum Engineering. 2018. Vol. 19, no. 4, pp.21-27.
https://search.emarefa.net/detail/BIM-897759
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 27
Record ID
BIM-897759