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    Estimation of P-wave velocity from other borehole data

    Access Status
    Fulltext not available
    Authors
    Kieu, D.
    Kitzig, M.
    Kepic, Anton
    Date
    2016
    Type
    Conference Paper
    
    Metadata
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    Citation
    Kieu, D. and Kitzig, M. and Kepic, A. 2016. Estimation of P-wave velocity from other borehole data, in Near Surface Geoscience 2016 - First Conference on Geophysics for Mineral Exploration and Mining , Sep 4-8 2016. Barcelona, Spain: EAGE.
    Source Title
    Near Surface Geoscience 2016 - First Conference on Geophysics for Mineral Exploration and Mining
    DOI
    10.3997/2214-4609.201602122
    School
    Department of Exploration Geophysics
    URI
    http://hdl.handle.net/20.500.11937/6887
    Collection
    • Curtin Research Publications
    Abstract

    P-wave velocities are a key parameter for seismic processing and the absence of this parameter reduces the robustness of the images from very expensive seismic surveys. The P-wave velocities in an area are particular to the area, as the P-wave velocity depends on many factors and varies with geological conditions. Hence, using a localized model predicts P-wave velocity better than the application of a generic model for the entire dataset. In this work, we utilized fuzzy c-means (FCM) clustering to build a "fuzzy" relationship that estimates Vp. Our method was tested on a dataset from the Kevitsa Ni-Cu-PGE deposit in northern Finland. The borehole data comprises P-wave velocity, density, natural gamma, magnetic susceptibility, resistivity and assay data of Ni of six boreholes. In this area, there are many boreholes, but very few have P-wave velocity logged or the data is corrupted by tool limitations. Therefore, it is beneficial to predict the velocity from other data to help seismic processing. In order to demonstrate the robustness of our program, we used the data from five holes for training and one hole for Vp testing. The results show that our method can reasonably estimate P-wave velocity from other borehole data.

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