Title :
Ontology based data warehouse modelling - a methodology for managing petroleum field ecosystems
Author :
Nimmagadda, Shastri L. ; Dreher, Heinz
Author_Institution :
Sch. of Inf. Syst., Curtin Univ. of Technol., Perth, WA
Abstract :
Petroleum field ecosystems offer an interesting and productive domain for ontology based data warehousing model and methodology development. This paper explains the opportunities and challenges confronting modellers, methodologists, and managers operating in the petroleum business and provides some detailed techniques and suggested methods for constructing and using the ontology based warehouse. Ecologically sensitive operations such as well drilling, well production, exploration, and reservoir development can be guided and carefully planned based on data mined from a suitable constructed data warehouse. Derivation of business intelligence, simulations and visualisation can also be driven by online analytical processing based on warehoused data and metadata.
Keywords :
data mining; data warehouses; ontologies (artificial intelligence); petroleum; production engineering computing; data mining; data warehouse; ontology; petroleum field ecosystem; Analytical models; Biological system modeling; Data warehouses; Drilling; Ecosystems; Ontologies; Petroleum; Production; Reservoirs; Warehousing; data mining; data warehouse; ontology; petroleum ecosystems; seismic data;
Conference_Titel :
Digital Ecosystems and Technologies, 2008. DEST 2008. 2nd IEEE International Conference on
Conference_Location :
Phitsanulok
Print_ISBN :
978-1-4244-1489-5
Electronic_ISBN :
978-1-4244-1490-1
DOI :
10.1109/DEST.2008.4635210