DocumentCode :
2282866
Title :
Data Mining for Seismic Exploration
Author :
Ouyang, Zhongbin ; He, Jing ; Zhang, Keliang
Author_Institution :
Res. Center on Fictitious Econ. & Data Sci., Chinese Acad. of Sci., Beijing
Volume :
3
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
424
Lastpage :
427
Abstract :
Seismic exploration plays an important role in petroleum industry. It is widely admitted that there are a lot of limitations of conventional data analysis ways in oil and gas industry. Traditional methods in petroleum engineering are knowledge-driven and often neglect some underlying factors. On the contrary, data mining is to deal with mass of data and never overlook any important phenomena. Due to large volumes of seismic data, we apply data mining to seismic exploration in this paper. K-means based Cluster analysis is applied for the 3-D seismic and well log data. Comparing the clustering results with the well log data, it is easy to display the distribution of lithology in geo-space.
Keywords :
data mining; petroleum industry; K-means; cluster analysis; data mining; petroleum engineering; petroleum industry; seismic exploration; Data analysis; Data mining; Data warehouses; Design optimization; Displays; Gas industry; Impedance; Intelligent agent; Knowledge engineering; Petroleum industry; cluster analysis; data mining; seismic exploration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.161
Filename :
4740813
Link To Document :
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