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    Incorporating fine-scale ground-penetrating radar data into the mapping of lateral variability of a laterite-type bauxite horizon

    Access Status
    Fulltext not available
    Authors
    Erten, Oktay
    McAndrew, L.
    Kizil, M.
    Topal, Erkan
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Erten, O. and McAndrew, L. and Kizil, M. and Topal, E. 2015. Incorporating fine-scale ground-penetrating radar data into the mapping of lateral variability of a laterite-type bauxite horizon. Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology. 124 (1): pp. 1-15.
    Source Title
    Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology
    DOI
    10.1179/1743286314Y.0000000073
    ISSN
    0371-7844
    School
    Dept of Mining Eng & Metallurgical Eng
    URI
    http://hdl.handle.net/20.500.11937/12824
    Collection
    • Curtin Research Publications
    Abstract

    Ground-penetrating radar (GPR) offers an inexpensive and rapid method for delineating the laterite profiles by acquiring fine-scale data from the ground. In a case study, a GPR survey was conducted at the Weipa bauxite mine in Australia, in which numerous pick points corresponding to the depth to the bauxite/ironstone boundary were acquired from the ground. These pick points were subsequently merged with the available exploration borehole data using four prediction algorithms, including standard linear regression (SLR), simple kriging with varying local means (SKLM), Bayesian integration (BAY), and ordinary co-located cokriging (OCCK). The required structural inputs for the aforementioned algorithms were derived from the modelled auto and cross-semi-variograms. The cross-validation results suggest that the SKLM approach yielded the most robust estimates. The comparison of these estimates with the actual mine floor also indicates that the inclusion of ancillary GPR data substantially improved the estimation quality.

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