Neural Networks for Prediction of Oil Production

被引：19
|
作者：
Muradkhanli, Leyla [1 ]
机构：
[1] Baku Higher Oil Sch, Baku, Azerbaijan
来源：
IFAC PAPERSONLINE | 2018年 / 51卷 / 30期
关键词：
Artificial neural network; Multilayer perceptron; Neural network model; Training; Backpropagation algorithm; Root means square error;
D O I：
10.1016/j.ifacol.2018.11.339
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Artificial neural networks are popular tool in oil and gas industry. The objective of this paper is to develop an artificial neural network that predicts oil production in State Oil Company of Azerbaijan Republic (SOCAR). Multilayer perceptron neural network is applied to predict oil production. As a result 99 percent accuracy in training procedure is achieved. The accuracy of the developed model was compared with empirical correlations. Great matching between neural network and actual data has been found. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：415 / 417
页数：3
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