DocumentCode :
569795
Title :
Research Method of Fuzzy Neural Network of Reservoir Heterogeneity
Author :
Guorong, Li ; Jingjing, Hu ; Taiping, Liao ; Zhicheng, Lin ; Furong, Zhang
Author_Institution :
Chengdu Univ. of Technol., Chengdu, China
fYear :
2012
fDate :
17-19 Aug. 2012
Firstpage :
1315
Lastpage :
1317
Abstract :
For analysis of the reservoir, due to complexity of the reservoir heterogeneity, the relationship between the logging response value and the non-homogenous reservoir is complex and fuzzy. The use of fuzzy clustering method of neural network combines the adaptivity and the fault tolerance of the neural network organic manner with the fuzzy comprehensive discrimination in the human thinking simulation of fuzzy logic, so as to recognize the reservoir heterogeneity through multi-factor fuzzy comprehensive judgment and reasoning. This method has been used to treat the data about the 135 wells in Xujiahe Group in central Sichuan, and has shown good results, with a coincidence rate as high as 87.6%. The result demonstrates that this method enjoys good adaptivity against the problem of automatic recognition of the reservoir heterogeneity, and could improve the precision of automatic recognition of the reservoir heterogeneity.
Keywords :
fuzzy logic; fuzzy neural nets; inference mechanisms; pattern clustering; reservoirs; well logging; Xujiahe group; central Sichuan; fault tolerance; fuzzy clustering method; fuzzy comprehensive discrimination; fuzzy logic; fuzzy neural network; human thinking simulation; logging response value; multifactor fuzzy comprehensive judgment; neural network organic manner; nonhomogenous reservoir; reasoning; reservoir heterogeneity; wells; Cognition; Educational institutions; Fuzzy logic; Fuzzy neural networks; Neural networks; Partitioning algorithms; Reservoirs; fuzzy neural network; heterogeneity; reservoir;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
Type :
conf
DOI :
10.1109/ICCIS.2012.229
Filename :
6301406
Link To Document :
بازگشت