Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    A reservoir rock porosity estimation through image analysis and fuzzy logic techniques

    Access Status
    Fulltext not available
    Authors
    Kadkhodaie, Ali
    Ghiasi-Freez, J.
    Ziaii, M.
    Honarmand, J.
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Ghiasi-Freez, J. and Ziaii, M. and Kadkhodaie, A. and Honarmand, J. 2014. A reservoir rock porosity estimation through image analysis and fuzzy logic techniques. Energy Sources Part A: Recovery, Utilization, and Environmental Effects. 36 (12): pp. 1276-1284.
    Source Title
    Energy Sources Part A: Recovery, Utilization, and Environmental Effects
    DOI
    10.1080/15567036.2011.574198
    ISSN
    1556-7230
    School
    Department of Petroleum Engineering
    URI
    http://hdl.handle.net/20.500.11937/45736
    Collection
    • Curtin Research Publications
    Abstract

    Petrophysical properties of petroleum reservoir rocks are usually obtained by laborious core laboratory measurements. The present study investigates the capability of petrographic image analysis applied on thin sections of reservoir rock and fuzzy logic for predicting porosity in carbonate rocks. The proposed methodology comprises two steps: first, the petrographic parameters, including porosity type, grain size, mean geometrical shape coefficient of grains, and texture type, were extracted for each thin section based on image analysis techniques. Consequently, the petrographic parameters were formulated to core porosity using a Takagi and Sugeno fuzzy inference system. Petrographic image analysis is an emerging technology, which provides fast and accurate quantitative evaluation from reservoir rock. The results of single petrographic image analysis showed inaccurate estimation of total porosity in all rocks except those that have an extremely isotropic pore structure. A quantitative evaluation of thin section images and fuzzy model was successfully used to improve the accuracy of porosity prediction and the results of thin section analysis were generalized to core plug analysis. The mean square error and correlation coefficient between two-dimensional measurements and core plug were obtained at 0.0262 and 86.3, respectively, which shows acceptable prediction of three-dimensional porosity from two-dimensional thin sections. Therefore, the results confirmed the validity of the propounded methodology.

    Related items

    Showing items related by title, author, creator and subject.

    • Investigation of pressure and saturation effects on elastic parameters: an integrated approach to improve time-lapse interpretation
      Grochau, Marcos Hexsel (2009)
      Time-lapse seismic is a modern technology for monitoring production-induced changes in and around a hydrocarbon reservoir. Time-lapse (4D) seismic may help locate undrained areas, monitor pore fluid changes and identify ...
    • Integration of core data, well logs and seismic attributes for identification of the low reservoir quality units with unswept gas in the carbonate rocks of the world's largest gas field
      Faraji, M.; Kadkhodaie, Ali; Rezaee, M. Reza; Wood, D. (2017)
      © 2017, China University of Geosciences and Springer-Verlag GmbH Germany. Tight zones of the gas bearing Kangan and Dalan formations of the South Pars gas field contain a considerable amount of unswept gas due to their ...
    • Development of a Papua New Guinean onshore carbonate reservoir: A comparative borehole image (FMI) and petrographic evaluation
      Wilson, Moyra; Lewis, D.; Yogi, O.; Holland, D.; Hombo, L.; Goldberg, A. (2013)
      The depositional and diagenetic controls on carbonate platform evolution are notoriously heterogeneous and difficult to determine from standard subsurface wireline logging techniques. Here, a combined borehole image (FMI ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.