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    Log dependent approach to predict reservoir facies and permeability in a complicated shaly sand reservoir

    Access Status
    Open access via publisher
    Authors
    Elkhateeb, Abdelrahman
    Rezaee, Reza
    Kadkhodaie, Ali
    Date
    2019
    Type
    Journal Article
    
    Metadata
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    Citation
    Elkhateeb, A. and Rezaee, R. and Kadkhodaie, A. 2019. Log dependent approach to predict reservoir facies and permeability in a complicated shaly sand reservoir. Exploration Geophysics. 2019 (1).
    Source Title
    Exploration Geophysics
    DOI
    10.1080/22020586.2019.12072924
    ISSN
    0812-3985
    Faculty
    Faculty of Science and Engineering
    School
    WASM: Minerals, Energy and Chemical Engineering
    Department of Petroleum Engineering
    URI
    http://hdl.handle.net/20.500.11937/89577
    Collection
    • Curtin Research Publications
    Abstract

    The prediction of facies and permeability in complicated reservoirs represents a major challenge that necessitates the usage of advanced statistical techniques. A new approach is presented in this paper to generate a log based continuous facies log and permeability index in the shaly sand of the Irwin River Coal Measures Formation. An integration between the density log and the NMR free fluid index has been carried out. This was done to establish a comprehensive electrofacies model and accommodate the large permeability variations. A new Reservoir Index, equivalent to the Flow Zone Indicator (FZI), has been calculated to allow a quantitative reservoir characterisation that includes facies and permeability independent of any core measurements. The modelled electrofacies and permeability from this analysis showed very effective results of high resolution. In order to calibrate the calculated permeability, the repeat formation tester mobility was used as a reference for the generated model. To further validate the results, the created models have been correlated with the core thin sections and core permeability. Four hydraulic flow units have been identified from the Reservoir Index, hence four different permeability models. From the log dependent results, an excellent match to the formation mobility has been achieved despite the reservoir heterogeneity. Furthermore, the outputs showed very encouraging results with the core data, upon which the methodology can be used in uncored wells. The workflow described in this paper shows a new methodology for reservoir characterisation through electric logs. The methodology allows an independent technique for rock typing in the absence of any core data. Regardless of the degree of the reservoir heterogeneity, a high-resolution facies and permeability index can be generated for advanced formation evaluation.

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