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    Sedimentary Basin - a Petroleum Digital Ecosystem

    Access Status
    Fulltext not available
    Authors
    Nimmagadda, Shastri
    Noventianto, A.
    Dreher, Heinz
    Mustoffa, A.
    Halley, P.
    Date
    2013
    Type
    Conference Paper
    
    Metadata
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    Citation
    Nimmagadda, Shastri L. and Noventianto, Andi and Dreher, Heinz and Mustoffa, Aswin and Halley, Parapaty. 2013. Sedimentary Basin - a Petroleum Digital Ecosystem, in Gomes, L. and Huebner, M. (ed), 11th International Conference on Industrial Informatics (INDIN), Jul 29-31 2013, pp. 541-546. Bochum, Germany: IEEE.
    Source Title
    Proceedings 2013 11th IEEE International Conference on Industrial Informatics (INDIN)
    Source Conference
    INDIN 2013
    DOI
    10.1109/INDIN.2013.6622942
    ISBN
    9781479907526
    URI
    http://hdl.handle.net/20.500.11937/40558
    Collection
    • Curtin Research Publications
    Abstract

    Existence of petroleum system and its elements is often narrated for each oil and gas field and for each petroleum-bearing sedimentary basin. Sedimentary basin is an emerging digital ecosystem within a generic petroleum system. On the broader scale, total petroleum system (TPS, where geology has no boundaries) can virtually be envisaged as a digital petroleum ecosystem. The significance of this concept lies in connecting onshore and offshore petroleum subsystems, in a basin (e.g., Indonesian Onshore-Offshore basin, a 19,300 mi2 [50,000 -km2] transition zone), through elements and process attributes and by modeling sub-basins thru contextualization and specification concepts. In this paper, we present an ontology based data warehousing and mining technology in which, conceptualization and contextualization of multiple data dimensions are modeled within a sedimentary basin (e.g., elements and processes of all petroleum systems, existing within basin). In addition to their integration within a data warehouse environment, data mining and visualization of interpretable data views that emerge from petroleum digital ecosystems are made feasible. Multidimensional data warehousing and mining models facilitate an effective interpretation of petroleum ecosystems, minimizing the ambiguities involved during knowledge mapping of geological structure and reservoir qualities - not only for exploration and field development planning, but also for reserve estimations.

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