DocumentCode
3403156
Title
Predicting Parameters of Nature Oil Reservoir Using General Regression Neural Network
Author
Wang, Kejun ; He, Bo ; Chen, Ruolei
Author_Institution
Harbin Eng. Univ., Harbin
fYear
2007
fDate
5-8 Aug. 2007
Firstpage
822
Lastpage
826
Abstract
In this paper the present statement of forecasting nonlinear systems and kinds of factors influencing the data of oil reservoir parameter were discussed. Based on these, a general regression neural network (GRNN) predicting model for oil reservoir parameters was presented. Comparing with corresponding real values, simulation results could show the effectiveness to improve the predicting accuracy and training speed by the proposed GRNN predicting models.
Keywords
hydrocarbon reservoirs; neural nets; nonlinear systems; production engineering computing; regression analysis; general regression neural network; nature oil reservoir; nonlinear systems; parameter prediction; Accuracy; Artificial neural networks; Automation; Hidden Markov models; Hydrocarbon reservoirs; Neural networks; Nonlinear systems; Petroleum; Predictive models; Smoothing methods; GRNN; Oil reservoir parameter; Prediction; Time series;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and Automation, 2007. ICMA 2007. International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-0828-3
Electronic_ISBN
978-1-4244-0828-3
Type
conf
DOI
10.1109/ICMA.2007.4303651
Filename
4303651
Link To Document