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

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, w...

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Main Authors: Nimmagadda, Shastri, Dreher, Heinz
Other Authors: Y. Ibrahim
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers (IEEE) Computer Society 2009
Online Access:http://hdl.handle.net/20.500.11937/3419
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author Nimmagadda, Shastri
Dreher, Heinz
author2 Y. Ibrahim
author_facet Y. Ibrahim
Nimmagadda, Shastri
Dreher, Heinz
author_sort Nimmagadda, Shastri
building Curtin Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-14T05:58:06Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T05:58:06Z
publishDate 2009
publisher Institute of Electrical and Electronics Engineers (IEEE) Computer Society
recordtype eprints
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spelling curtin-20.500.11937-34192022-12-07T06:50:51Z Petro-data cluster mining - knowledge building analysis of complex petroleum systems Nimmagadda, Shastri Dreher, Heinz Y. Ibrahim K. Jezernik CH Chakraborty 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. 2009 Conference Paper http://hdl.handle.net/20.500.11937/3419 10.1109/ICIT.2009.4939729 Institute of Electrical and Electronics Engineers (IEEE) Computer Society fulltext
spellingShingle Nimmagadda, Shastri
Dreher, Heinz
Petro-data cluster mining - knowledge building analysis of complex petroleum systems
title Petro-data cluster mining - knowledge building analysis of complex petroleum systems
title_full Petro-data cluster mining - knowledge building analysis of complex petroleum systems
title_fullStr Petro-data cluster mining - knowledge building analysis of complex petroleum systems
title_full_unstemmed Petro-data cluster mining - knowledge building analysis of complex petroleum systems
title_short Petro-data cluster mining - knowledge building analysis of complex petroleum systems
title_sort petro-data cluster mining - knowledge building analysis of complex petroleum systems
url http://hdl.handle.net/20.500.11937/3419