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    On data integration workflows for an effective management of multidimensional petroleum digital ecosystems in Arabian Gulf Basins

    138261_138261.pdf (852.4Kb)
    Access Status
    Open access
    Authors
    Nimmagadda, Shastri
    Dreher, Heinz
    Nawaz, M.
    Laiq, K.
    Sabry, A.
    Ahmed, M.
    Date
    2010
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Nimmagadda, Shastri and Dreher, Heinz and Nawaz, M. and Laiq, K. and Sabry, A. and Ahmed, M. 2010. On data integration workflows for an effective management of multidimensional petroleum digital ecosystems in Arabian Gulf Basins, in Hussain, F. K. and Chang, E. (ed), 4th IEEE international conference on digital ecosystems and technologies, Apr 12 2010, pp. 513-519. Dubai, United Arab Emirates: IEEE.
    Source Title
    Proceedings of the 4th IEEE international conference on digital ecosystems and technologies
    Source Conference
    4th IEEE international conference on digital ecosystems and technologies
    ISBN
    9781424455539
    Faculty
    Curtin Business School
    School of Information Systems
    Remarks

    Copyright © 2010 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/29139
    Collection
    • Curtin Research Publications
    Abstract

    Data integration of multiple heterogeneous datasets from multidimensional petroleum digital ecosystems is an effective way, for extracting information and adding value to knowledge domain from multiple producing onshore and offshore basins. At present, data from multiple basins are scattered and unusable for data integration, because of scale and format differences. Ontology based warehousing and mining modeling are recommended for resolving the issues of scaling and formatting of multidimensional datasets, in which case, seismic and well-domain datasets are described. Issues, such as semantics among different data dimensions and their associated attributes are also addressed by Ontology modeling.Intelligent relationships are built among several petroleum system domains (structure, reservoir, source and seal, for example) at global scale and facilitated the integration process among multiple dimensions in a data warehouse environment. For this purpose, integrated workflows are designed for capturing and modeling unknown relationships among petroleum system data attributes in interpretable knowledge domains.This study is an effective approach in mining and interpreting data views drawn from warehoused exploration and production metadata, with special reference to Arabian onshore and offshore basins.

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