Conference Proceedings
Eighth International Mining Geology Conference 2011
Conference Proceedings
Eighth International Mining Geology Conference 2011
Application of Infrared Spectral Data for Predictive Modelling of Alteration-Mineralisation Systems
The use of spectral data has traditionally been for obtaining mineral information and for mapping out alteration systems. The output from these data is typically in the form of mineral assemblages and data on relative proportions of minerals. However there is much more than just mineral information in the spectral data. Most importantly, the data allow the user to obtain vital information on mineral chemistry for some key alteration minerals. The mineral chemistry data allow the users to evaluate multiple phases of alteration of the same key mineral species, and to assess which phase is related to mineralisation. Mineral indices can be extracted from the spectral data and plotted to represent variations in the chemistry and relative proportions of key mineral phases as downhole, section and three-dimensional (3D) plots. These data can also be compared with the spatial distribution of the mineralisation by integration with geochemical and logging data. Through spatial and statistical evaluation the mineral information obtained using spectral analysis can provide vital information to assist in building alteration models and therefore improve targeting for further drilling and exploration._x000D_
FORMAL CITATION:Pontual, S, 2011. Application of infrared spectral data for predictive modelling of alteration-mineralisation systems, in Proceedings Eighth International Mining Geology Conference 2011, pp 403-406 (The Australasian Institute of Mining and Metallurgy: Melbourne).
FORMAL CITATION:Pontual, S, 2011. Application of infrared spectral data for predictive modelling of alteration-mineralisation systems, in Proceedings Eighth International Mining Geology Conference 2011, pp 403-406 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Contributor(s):
S Pontual
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- Published: 2011
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- Unique ID: P201108038