Application of neural network in the identification of the cumulative production from ab unit in main pays reservoir of south rumaila oil field
Joint Authors
al-Jawad, Muhammad Salih
Jreou, Ghazwan N. S.
Source
Iraqi Journal of Chemical and Petroleum Engineering
Issue
Vol. 10, Issue 2 (30 Jun. 2009), pp.37-46, 10 p.
Publisher
University of Baghdad College of Engineering
Publication Date
2009-06-30
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Topics
Abstract EN
A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumania Oil Field.
One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells.
This paper demonstrates an application of neural network with reservoir simulation technique as decision tool.
A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy.
Sets of available input data were collected from the exploited grids and used in the training and testing of the used network.
A comparison between the calculated and observed cumulative oil production has been carried out through the testing steps of the constructed ANN, an absolute average percentage error of the used network was reached to 4.044%, and this is consider to be an acceptable limit within engineering applications, in addition to that, a good behavior was reached with (FFNNW) and suitable re-entry wells location were identified according to the reservoir configuration (pressure and saturation distribution) output from SRF simulation model at the end of 2005.
American Psychological Association (APA)
al-Jawad, Muhammad Salih& Jreou, Ghazwan N. S.. 2009. Application of neural network in the identification of the cumulative production from ab unit in main pays reservoir of south rumaila oil field. Iraqi Journal of Chemical and Petroleum Engineering،Vol. 10, no. 2, pp.37-46.
https://search.emarefa.net/detail/BIM-262125
Modern Language Association (MLA)
al-Jawad, Muhammad Salih& Jreou, Ghazwan N. S.. Application of neural network in the identification of the cumulative production from ab unit in main pays reservoir of south rumaila oil field. Iraqi Journal of Chemical and Petroleum Engineering Vol. 10 (Jun. 2009), pp.37-46.
https://search.emarefa.net/detail/BIM-262125
American Medical Association (AMA)
al-Jawad, Muhammad Salih& Jreou, Ghazwan N. S.. Application of neural network in the identification of the cumulative production from ab unit in main pays reservoir of south rumaila oil field. Iraqi Journal of Chemical and Petroleum Engineering. 2009. Vol. 10, no. 2, pp.37-46.
https://search.emarefa.net/detail/BIM-262125
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 41-42
Record ID
BIM-262125