NDLI: Petro-data cluster mining - knowledge building analysis of complex petroleum systems

Content Provider	IEEE Xplore Digital Library
Author	Nimmagadda, S.L. Dreher, H.
Copyright Year	2009
Description	Author affiliation: School of Information Systems, Curtin Business School, Curtin University of Technology, Perth, WA, Australia (Dreher, H.) \|\| Schlumberger, P O Box 9056, East Ahmadi, Kuwait (Nimmagadda, S.L.)
Abstract	Large volumes of historical petroleum data are available and presently unused primarily because of lack of knowledge. Initially, conceptual data models are derived and warehoused for data mining. For this purpose, petroleum system analysis and knowledge mapping of geological structure, reservoir, well and oil/gas production data are done concentrating on the key issues of geological-structure, reservoir and production data dimensions. Clustering is a data-mining tool for categorizing and analyzing groups of these data dimensions having similar attribute characteristics or properties. Using data warehousing, mining and interpretation strategies, petro-clustering is designed for understanding petroleum systems. Knowledge acquired on petroleum data clusters enhances understanding of relationships among petroleum data attributes, which can optimize economics of oil and gas exploration and development in the petroleum bearing basins.
Starting Page	1
Ending Page	8
File Size	2335890
Page Count	8
File Format	PDF
ISBN	9781424435067
DOI	10.1109/ICIT.2009.4939729
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Hydrocarbon reservoirs Geology Information analysis Australia Production systems Petroleum industry Drilling Large-scale systems Information systems
Content Type	Text
Resource Type	Article

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