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    Ontology based warehouse modeling of fractured reservoir ecosystems-for an effective borehole and petroleum production management: Maximum hoop stress becomes much higher than the radial

    Access Status
    Fulltext not available
    Authors
    Nimmagadda, Dr Shastri
    Dreher, H.
    Date
    2010
    Type
    Conference Paper
    
    Metadata
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    Citation
    Nimmagadda, D.S. and Dreher, H. 2010. Ontology based warehouse modeling of fractured reservoir ecosystems-for an effective borehole and petroleum production management: Maximum hoop stress becomes much higher than the radial, pp. 490-496.
    Source Title
    4th IEEE International Conference on Digital Ecosystems and Technologies - Conference Proceedings of IEEE-DEST 2010, DEST 2010
    DOI
    10.1109/DEST.2010.5610600
    ISBN
    9781424455539
    School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/24324
    Collection
    • Curtin Research Publications
    Abstract

    Exploration business deals with structure and reservoir data. The carbonate reservoirs, (especially of Jurassic age), establish its hydrocarbon potential and production on commercial scale in Middle Eastern onshore petroleum systems. There is an immense scope of exploration and production from the fractured horizons and their associated reservoirs. Most of the fractures are networked or interconnected through fluid media. The wells drilled in carbonate reservoir areas, have been under an unbalanced-stress system that exhibits commonly two types of borehole failures, shear and tensile failure, where the rocks drilled, are replaced with drilling mud. Rocks undergo hoop and radial stresses that occur by drilling and also natural fracturing. A robust methodology is needed to address issues of integrating multiple fracture systems. Issues relevant to borehole management are addressed through ontology modeling of networked fractures. Authors propose data warehousing approach supported by ontology that can integrate data attributes associated with fractures of multiple horizons from several wells, geographically (distantly) located within a producing basin. Authors attempt to make connectivity between structure and reservoir data attributes. Integration is done by mapping and modeling conceptually (more logically) interpreted relationships among multidimensional inter-dependent data structures and attributes through their data property instances that are described from different fracture systems. Data mining can separate out these stresses, so that driller or well planner knows in advance the fracture systems that are being drilled. The proposed methodology is robust and can resolve issues relevant to deviation and smart drilling in the fractured reservoir systems. This approach integrates and makes connectivity among varying common and conceptualized attributes associated with structure and reservoir. If the proposed methodology is successful, it can be applied any fractured shales and tight-gas reservoir systems worldwide. © 2010 IEEE.

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