Active filters :
Discard Filter
Library

Geometallurgy, Geostatistics and Project Value — Does Your Block Model Tell You What You Need to Know?

$22.00

Want a discount? Become a member!

Author S Dunham and J Vann

Description

The key functions of project evaluation are to assess potential profitability and to develop an effective operational design. For mining projects, design aspects include mining methodology, ore treatment methodology and production rates. All of these characteristics impact on project economics and overall value.

Resource models, which form the ultimate basis of project evaluation, typically consist of tonnes above cut-off, grade above cut-off and the spatial distribution (connectivity) of tonnes/grade above cut-off, for one or more variables. Dilution, ore loss and metallurgical recovery are all modifying factors applied to the resource model during evaluation and determination of profitability. A key issue is: how is the value determined? In addition to traditional combination of in situ tonnes/grade, the following merit serious consideration: the concentration of deleterious elements, throughput rates, mining/processing costs and – importantly – metallurgical recovery.

Geometallurgy is an emerging field targeted at integrating these issues by identifying either direct measures or proxies for throughput (hardness, grindability), recovery (liberation, mineral shape/texture, etc) and concentrate quality from easily collected macro-, meso- and microscopic data. These ‘geometallurgical variables’ drive project costs and revenues in a fundamental way. For geometallurgical characterisation to have a real impact on business design, it must enable improved mine planning. When creating spatial estimates for such variables, it is preferable to find proxies that can be measured as close to the intact rock mass as possible. However, spatial estimation of proxies for geometallurgical properties and responses is complex and requires special consideration. Unlike grades, both proxies and absolute measures of geometallurgical variables are not necessarily linear or additive and therefore require very careful geostatistical consideration. In some cases, models must predict extreme values of geometallurgical attributes rather than averages.

Incorrect characterisation of metallurgical recovery/throughput can (and has) led to misspecification of the scale of projects, and thus can be seriously value destructive. Aspects of geometallurgy have long been important in iron, bauxite, manganese and coal deposits and are increasingly on the radar for base and precious metal miners. However, as more metallurgically complex deposits are developed and mining of large-scale, low-grade deposits becomes more commonplace, the importance of characterising the metallurgical response in order to generate properly optimised projects will rapidly increase. It is possible that in many ‘traditional’ (ie grades and tonnes) reserve models, the variables that drive the project are missing!

FORMAL
CITATION:
Dunham, S and Vann, J, 2007.

Geometallurgy, geostatistics and project value – does your block model tell you
what you need to know? in Proceedings
Project
Evaluation 2007
, pp
189-196
(The
Australasian Institute of Mining and Metallurgy:
Melbourne).