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

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Open access
Authors
Nimmagadda, Shastri
Dreher, Heinz
Date
2009
Type
Conference Paper

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Nimmagadda, Shastri and Dreher, Heinz. 2009. Petro-data cluster mining - knowledge building analysis of complex petroleum systems, in Ibrahim, Y. and Jezernik, K. and Chakraborty, Ch. (ed), 2009 IEEE International Conference on Industrial Technology, Feb 10 2009, pp. 1473-1480. Monash University, Gippsland, Victoria, Australia: Institute of Electrical and Electronics Engineers (IEEE) Computer Society.
Source Title
Proceedings of 2009 IEEE International Conference on Industrial Technology
Source Conference
IEEE International Conference on Industrial Technology. ICIT 2009
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Faculty
School of information Systems
Curtin Business School
School
School of Information Systems
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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 andoil/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.