DocumentCode
2495430
Title
Predicting oil and gas reservoir and calculating thickness of reservoir from seismic data using neural network
Author
Xing-yao, Yin ; Guo-chen, Wu ; Feng-li, Yang
Author_Institution
Univ. of Pet., Shan Dong, China
Volume
2
fYear
1996
fDate
14-18 Oct 1996
Firstpage
1601
Abstract
Neural networks have been developed and widely used in oil and gas exploration. Combining the neural networks with traditional seismic prospecting methods, we put forward a new method to predict oil and gas reservoirs and calculate the thickness of the reservoirs. This method is applied in oilfields and the results are satisfactory
Keywords
geophysical prospecting; geophysical signal processing; neural nets; seismology; exploration; gas reservoir; neural network; oil reservoir; oilfields; seismic data; seismic prospecting; thickness; Artificial neural networks; Computer networks; Frequency; Geology; Hydrocarbon reservoirs; Intelligent networks; Neural networks; Petroleum; Robustness; Supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 1996., 3rd International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-2912-0
Type
conf
DOI
10.1109/ICSIGP.1996.571194
Filename
571194
Link To Document