Utilising Statistics and Geostatistics to Validate, Characterise and Improve Geological Domaining ù A Case Study From BHP BillitonÆs Yandi Channel Iron Deposit

BHP BillitonÆs Yandi channel iron deposit has a large resource of approximately 1.3 billion tonnes. This is a bulk mining operation with a high degree of selectivity not being practical. In contrast the deposit geology is a complex interrelationship of primary channel facies, secondary enrichment of iron and a secondary redistribution of the major contaminants. These variations in geology and alteration can occur over ranges of hundreds of metres down to knife edge contacts. In addition, differences in primary facies and mobility during alteration often result in the iron and contaminants having different patterns of enrichment and depletion. Despite the scale of these operations, if the geological domaining is not optimal, significant errors in the resource estimate of grades and tonnage will occur. Getting the geology right has become a common clichT among mining professionals. However, in many situations, obtaining optimal geological domains for resource modelling is best achieved when there is input from geology, statistics and geostatistics. In this paper, moving window statistics are utilised to see through locally high variability to identify trends that assist in locating difficult to identify geological boundaries. After the creation of geological domains, univariate and multivariate statistics and principal component analysis assist in validating and characterising geological domains. Finally, variography and domain contact analysis are used to analyse the nature of the boundaries between geological domains. At the Yandi channel iron deposit, the inter-relationship between geological and geostatistical analysis has resulted in significant improvements to geological domaining and the treatment of domain boundaries during estimation of iron and contaminates.