Conference Proceedings
The Second AusIMM International Geometallurgy Conference 2013
Conference Proceedings
The Second AusIMM International Geometallurgy Conference 2013
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BHP Billiton West Australian Iron Ore Geometallurgy - Past, Present and Future
BHP Billiton (BHPB) West Australian Iron Ore (WAIO) conducts an extensive geometallurgy (geomet) program for its iron ore deposits in the Pilbara. The geomet program provides accurate information to infrastructure engineers, resource geologists, mine planning engineers and the technical marketing team on the performance characteristics of iron ores. Performance metrics include production planning, such as lump/fine splits, processing capability such as the level of ultra-fine iron ore and ironmaking blast furnace properties including tumble index (TI) and reduction disintegration index (RDI). Prior to the introduction of the current geomet program in WAIO, basic geometallurgical information was provided at the deposit level, such as deposit lump percentage and head grade chemistry. As the business value of geometallurgy was realised during the growth period of WAIO, the geomet process was reviewed and formalised into five steps: geomet drill planning laboratory measurement data management algorithm development block estimation._x000D_
The geomet laboratory process produces simulated iron ore products from drill core, which are then subjected to physical geometallurgy test work. With the large amount of geometallurgy data collected, extensive databases are utilised to collate and organise the data to improve its usability within the business._x000D_
Algorithms are created from the data to predict important geomet variables and a block estimation method is used to estimate geometallurgical properties into resource models. The predicted geometallurgy data is regularly reviewed at the different steps against plant and shipping data to allow refinement of the geometallurgy algorithms. It is also recognised that geomet data can be used to optimise the operations in existing processing hubs for improved production rate. In addition, future geomet programs will focus on generating data from all available drill core programs, not just dedicated geomet drill holes, and will incorporate new types of data, such as hyper-spectral information, for improved geometallurgical estimation.CITATION:Wright, B, Carroll, T, Flanagan, M, Sua, T and Van Dijken, B, 2013. BHP Billiton West Australian iron ore geometallurgy - past, present and future, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 105-110 (The Australasian Institute of Mining and Metallurgy: Melbourne).
The geomet laboratory process produces simulated iron ore products from drill core, which are then subjected to physical geometallurgy test work. With the large amount of geometallurgy data collected, extensive databases are utilised to collate and organise the data to improve its usability within the business._x000D_
Algorithms are created from the data to predict important geomet variables and a block estimation method is used to estimate geometallurgical properties into resource models. The predicted geometallurgy data is regularly reviewed at the different steps against plant and shipping data to allow refinement of the geometallurgy algorithms. It is also recognised that geomet data can be used to optimise the operations in existing processing hubs for improved production rate. In addition, future geomet programs will focus on generating data from all available drill core programs, not just dedicated geomet drill holes, and will incorporate new types of data, such as hyper-spectral information, for improved geometallurgical estimation.CITATION:Wright, B, Carroll, T, Flanagan, M, Sua, T and Van Dijken, B, 2013. BHP Billiton West Australian iron ore geometallurgy - past, present and future, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 105-110 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Contributor(s):
B Wright, T Carroll, M Flanagan, T Sua, B Van Dijken
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- Published: 2013
- PDF Size: 5.95 Mb.
- Unique ID: P201310013