Journal of the Southern African Institute of Mining and Metallurgy
versión On-line ISSN 2411-9717
versión impresa ISSN 0038-223X
ABZALOV, M.Z.. Localized uniform conditioning (LUC): method and application case studies. J. S. Afr. Inst. Min. Metall. [online]. 2014, vol.114, n.3, pp.205-205. ISSN 2411-9717.
A new method, localized uniform conditioning (LUC), was proposed in 2006 for modelling grades of small blocks of ore when data spacing is too broad for their accurate modelling by the linear regression based techniques, such as kriging (Abzalov, 2006). It represents a modified uniform conditioning (UC) technique that calculates the grade distribution functions for the large panels. LUC uses partitioning of the panels onto the small blocks and then ranks them in increasing order of grade. Based on the block ranks, a single grade value can be deduced for each block from the UC model of the grade-tonnage relationships of the corresponding panel. After being first presented in 2006, the LUC method has been implemented in ISATIS© (commercial software) and became one of the common approaches for grade estimation when data spacing is broad in comparison with the estimated block size. Several years of study on the LUC method and its application to different geological environments, have allowed identification of the strengths and weaknesses of the method, which are as follows: ► The method produces accurate grade-tonnage functions, which are in a good accordance with a volume-variance relationship principles ► An initial ranking of the selective mining unit (SMU) blocks can be made by direct kriging from the sparse data grid. Therefore, the LUC method can be particularly useful at the early stages of exploration and mining project evaluations when sparsely distributed data is often the only available information ► Accuracy of the local estimation depends on the SMU ranking techniques. When ranking performed by direct kriging of the SMU blocks their spatial distribution is approximate. When the variogram of the studied variable is characterized by a large nugget effect, the block ranks produced by kriging can significantly differ from their 'true' distribution ► Block ranking can be improved using auxiliary data, either geophysical or geochemical. This allows use of the LUC method for integrating different data sets. In particular, LUC can be used for grade control in open pits by integrating resource definition data (e.g. drill-hole assays) and blast-hole assays. The latter are used for the block ranking.
Palabras clave : geostatistics; localized uniform conditioning; LUC; resource modelling.