Proceedings of the 3rd International Conference on Computer Science and Service System

Oil production predicting with modified BP neural network method

Authors
Liu Haohan, Li Wei, Zhang Songlin
Corresponding Author
Liu Haohan
Available Online June 2014.
DOI
10.2991/csss-14.2014.33How to use a DOI?
Keywords
Oil field;oil production; neural network; predicting accuracy
Abstract

Feasibility of oil production predicting results influence the annual planning and long-term field development plan of oil field, so the selection of predicting models plays a core role. In this paper, a common and useful model is introduced, it is,the neural network model. By using this model to predict the oil production in DAQ oilfield in China, advantages and disadvantages of the model has been discussed. The predicting results show: the fitting accuracy by the neural network model is high, and the prediction error is smaller than 10%, so neural network model can be used to short-term forecast of oil production, after changing the weighting value in training, we can also improve the predicting accuracy, however, this process takes much time. Next, our team will try to develop new theory to shorten the training time.

Copyright
© 2014, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Computer Science and Service System
Series
Advances in Intelligent Systems Research
Publication Date
June 2014
ISBN
978-94-6252-012-7
ISSN
1951-6851
DOI
10.2991/csss-14.2014.33How to use a DOI?
Copyright
© 2014, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liu Haohan
AU  - Li Wei
AU  - Zhang Songlin
PY  - 2014/06
DA  - 2014/06
TI  - Oil production predicting with modified BP neural network method
BT  - Proceedings of the 3rd International Conference on Computer Science and Service System
PB  - Atlantis Press
SP  - 146
EP  - 148
SN  - 1951-6851
UR  - https://doi.org/10.2991/csss-14.2014.33
DO  - 10.2991/csss-14.2014.33
ID  - Haohan2014/06
ER  -