DocumentCode :
2585735
Title :
Application of BP Neural Network in Oil Field Production Prediction
Author :
Sun, Lei ; Bi, Yange ; Lu, Guorong
Author_Institution :
Coll. of Geophys. & Inf. Eng., Univ. of Pet., Beijing, China
Volume :
1
fYear :
2010
fDate :
19-20 Dec. 2010
Firstpage :
201
Lastpage :
203
Abstract :
This paper introduces a new Neural Network model which is suitable for oil production prediction with training parameter set. From the comparison between prediction of oil production and real production, the precision of prediction meets the requirements quite well. In addition, this new model offers better self-adaptive ability and can be used in multi-cycle and multi-descending production forecast. In general, BP Neural Network is an ideal mean for oil production prediction.
Keywords :
backpropagation; neural nets; petroleum industry; production engineering computing; BP neural network; oil field production prediction; real production; self-adaptive ability; training parameter set; Artificial neural networks; Petroleum; Prediction algorithms; Predictive models; Production; Training; Transfer functions; Artificial Neural Network; BP Model; Oil Production Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (WCSE), 2010 Second World Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9287-9
Type :
conf
DOI :
10.1109/WCSE.2010.101
Filename :
5718294
Link To Document :
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