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    Identification of sedimentary-diagenetic facies and reservoir porosity and permeability prediction: An example from the Eocene beach-bar sandstone in the Dongying Depression, China

    Access Status
    Fulltext not available
    Authors
    Wang, J.
    Cao, Y.
    Liu, Keyu
    Liu, J.
    Kashif, M.
    Date
    2017
    Collection
    • Curtin Research Publications
    Type
    Journal Article
    Metadata
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    Abstract

    Accurate prediction of reservoir porosity and permeability is essential for prospecting hydrocarbon reserves and petroleum production capacity. We propose an innovative reservoir porosity and permeability prediction method through identifying sedimentary-diagenetic facies, determining the porosity-permeability trends using core measurement data, extrapolating the spatial distribution of the sedimentary-diagenetic facies using log data through the Bayes discriminant analysis and predicting the reservoir porosity and permeability. The essence of the method was illustrated and its effectiveness was demonstrated using the Eocene beach-bar sandstones in the Dongying Depression, Bohai Bay Basin, eastern China. The Eocene beach bar sandstones are classified into fine sandstone, siltstone, and argillaceous siltstone based on grain sizes, sorting, and matrix contents. The major diagenetic processes that influence the porosity and permeability of the beach-bar sandstones are compaction, carbonate cementation and feldspar dissolution. Seven sedimentary-diagenetic facies were identified in the beach-bar sandstones based on the lithological types, and their corresponding diagenesis and influence extent on reservoir properties. The variation ranges of porosity and permeability (log K) of these sedimentary-diagenetic facies are typically less than 6% and 1.2, respectively. Both the porosity and permeability have well defined functional relationships with depth. The sedimentary-diagenetic facies can be identified effectively from logging data through the use of the Bayes discriminant analysis and corresponding cross-plots. The porosity and permeability (log K) of the well evaluated in the study were predicted with errors in the range of ±3% and ±0.6, respectively, based on the distribution and the fitting equation of the trend lines for the seven sedimentary-diagenetic facies. The predicted porosities and permeability of sedimentary-diagenetic facies match the measured porosities and permeability well.

    Citation
    Wang, J. and Cao, Y. and Liu, K. and Liu, J. and Kashif, M. 2017. Identification of sedimentary-diagenetic facies and reservoir porosity and permeability prediction: An example from the Eocene beach-bar sandstone in the Dongying Depression, China. Marine and Petroleum Geology. 82: pp. 69-84.
    Source Title
    Marine and Petroleum Geology
    URI
    http://hdl.handle.net/20.500.11937/52675
    DOI
    10.1016/j.marpetgeo.2017.02.004
    Department
    Department of Chemical Engineering

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