Automated probabilistic domain assignment to production blast hole assays APCOM 2021

The Southern African Institute of Mining and Metallurgy
K. Silversides A. Melkumyan
Organization:
The Southern African Institute of Mining and Metallurgy
Pages:
12
File Size:
801 KB
Publication Date:
Sep 1, 2021

Abstract

Chemical assays collected from blast holes have the potential to greatly improve the local accuracy of grade models. Assays must be assigned to the correct domain or they will introduce errors. Boundary surfaces created from the widely spaced exploration holes (~50m) do not provide sufficient resolution to correctly delineate domain boundaries between closely spaced (3-5m) blast holes. This paper demonstrates a probabilistic method for classifying production blast holes near domain boundaries. Gaussian processes models are applied to identify the assays and assay ratios most suited to distinguishing particular domains. These models are combined with the exploration based surfaces to classify the blast holes that can be confidently assigned to a particular domain. A reiterative method is used, where information from the blast holes closest to the exploration holes is used to label blast holes further away. This is tested on two domain boundaries in a banded iron formation-hosted iron ore mine.
Citation

APA: K. Silversides A. Melkumyan  (2021)  Automated probabilistic domain assignment to production blast hole assays APCOM 2021

MLA: K. Silversides A. Melkumyan Automated probabilistic domain assignment to production blast hole assays APCOM 2021. The Southern African Institute of Mining and Metallurgy, 2021.

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