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Geostatistical clustering as an aid for ore body domaining: case study at the Rocklea Dome channel iron ore deposit, Western Australia

Geostatistical clustering as an aid for ore body domaining: case study at the Rocklea Dome... An important step in mineral resource estimation process is the grouping of drill hole samples into domains that reflect zones of homogeneous properties for accurate grade estimation and practical exploitation purposes. In practice, this challenging task is performed through a subjective, time-consuming manual interpretation of the mineral deposit. Therefore, various interpretations are possible. The definition of domains can be viewed as a clustering problem consisting of grouping samples into clusters, herein called domains, so that samples belonging to the same cluster are more similar than those in different clusters. Several methods exist for this purpose; however, groups of samples created through traditional clustering tend to show poor spatial contiguity. Alternatively, spatially contiguous clusters can be obtained through geostatistical clustering where the spatial dependency between samples is considered. This paper is devoted to the application of geostatistical clustering to support domaining of an iron ore deposit located in Western Australia. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Earth Science Taylor & Francis

Geostatistical clustering as an aid for ore body domaining: case study at the Rocklea Dome channel iron ore deposit, Western Australia

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Geostatistical clustering as an aid for ore body domaining: case study at the Rocklea Dome channel iron ore deposit, Western Australia

Abstract

An important step in mineral resource estimation process is the grouping of drill hole samples into domains that reflect zones of homogeneous properties for accurate grade estimation and practical exploitation purposes. In practice, this challenging task is performed through a subjective, time-consuming manual interpretation of the mineral deposit. Therefore, various interpretations are possible. The definition of domains can be viewed as a clustering problem consisting of grouping samples...
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Publisher
Taylor & Francis
Copyright
© 2017 Institute of Materials, Minerals and Mining and The AusIMM
ISSN
2572-6838
eISSN
2572-6846
DOI
10.1080/03717453.2017.1415114
Publisher site
See Article on Publisher Site

Abstract

An important step in mineral resource estimation process is the grouping of drill hole samples into domains that reflect zones of homogeneous properties for accurate grade estimation and practical exploitation purposes. In practice, this challenging task is performed through a subjective, time-consuming manual interpretation of the mineral deposit. Therefore, various interpretations are possible. The definition of domains can be viewed as a clustering problem consisting of grouping samples into clusters, herein called domains, so that samples belonging to the same cluster are more similar than those in different clusters. Several methods exist for this purpose; however, groups of samples created through traditional clustering tend to show poor spatial contiguity. Alternatively, spatially contiguous clusters can be obtained through geostatistical clustering where the spatial dependency between samples is considered. This paper is devoted to the application of geostatistical clustering to support domaining of an iron ore deposit located in Western Australia.

Journal

Applied Earth Science – Taylor & Francis

Published: Jan 2, 2018

Keywords: Clustering; domaining; drill hole data; geostatistics; iron ore deposit; mineral resource estimation

References

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