Assessment of uncertainty in grade-tonnage curves of a multivariate lateritic bauxite deposit through min/max autocorrelation factor transformation

Erten, O., Kizil, Mehmet S., Beamish, Bevan B. and McAndrew, L. (2011). Assessment of uncertainty in grade-tonnage curves of a multivariate lateritic bauxite deposit through min/max autocorrelation factor transformation. In: Demirel, Nuray, Erdem, Ömer and Erkayaoglu, Mustafa, Proceedings of the 22nd International Mining Congress of Turkey. 22nd International Mining Congress and Exhibition of Turkey-IMCET, Ankara, Turkey, (67-77). 11-13 May 2011.

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
Author Erten, O.
Kizil, Mehmet S.
Beamish, Bevan B.
McAndrew, L.
Title of paper Assessment of uncertainty in grade-tonnage curves of a multivariate lateritic bauxite deposit through min/max autocorrelation factor transformation
Conference Paper Type Fully Published Paper
Conference name 22nd International Mining Congress and Exhibition of Turkey-IMCET
Conference location Ankara, Turkey
Conference dates 11-13 May 2011
Proceedings title Proceedings of the 22nd International Mining Congress of Turkey
Editor Demirel, Nuray
Erdem, Ömer
Erkayaoglu, Mustafa
Place published Ankara, Turkey
Publisher UCTEA The Chamber of Mining Engineers of Turkey
Publication date 2011
ISBN 9786050101034
Start page 67
End page 77
Total pages 11
Collection year 2012
Language eng
Formatted Abstract/Summary Assessing uncertainty in grade-tonnage curves is rather crucial in resource estimation, as these curves provide information on how much ore within the deposit is above/below a given cut-off grade value. Conditional simulation algorithms can provide robust quantification of the ore production by generating multiple realisations of the ore deposits. However, when the ore deposit is characterised by multiple variables that are spatially correlated, these attributes need to be jointly simulated in order to preserve the spatial correlation. The application of co-simulation algorithms to the grade attributes requires large co-kriging matrices to be solved, making the whole process computationally inefficient and impractical. The minimum/maximum autocorrelation factor (MAF) transformation, however, offers a solution to the simulation of the multivariate deposits by transforming the original attributes into non-correlated orthogonal factors which can then be simulated independently, while preserving the spatial correlation among the attributes. This paper discusses the joint simulation of Al2O3, SiO2, Fe2O3, and TiO2 variables of a lateritic bauxite deposit through the MAF transformation and the results of the grade-tonnage curves for each realisation to express the uncertainty.
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Conference Paper
Sub-type: Fully Published Paper
Collections: School of Mechanical & Mining Engineering Publications
Official 2012 Collection
 
Citation counts: Google Scholar Search Google Scholar
Access Statistics: 200 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Wed, 08 Jun 2011, 10:51:05 EST by Dr Mehmet Kizil on behalf of School of Mechanical and Mining Engineering