Alternatives to Conditional Simulation for the Estimation of Iron Grade Distributions ù A Case Study From BHP BillitonÆs Mt Whaleback Operations

Conditional simulation can be used to determine the probabilities of block iron-grades being above selected cut-offs. However, there are much faster alternatives that can produce acceptable results. In this paper blasthole data from a selected area of Joffre Member hosted ore of the Brockman Iron Formation at the Mt Whaleback orebody is used as the basis of a case study to assess alternatives to simulation. Iron grade, in per cent, is interpolated from a blasthole dataset into a block model using ordinary kriging. Samples are then removed from this blasthole dataset to produce data subsets. A complete distribution of iron grades for points or blocks is obtained utilising the data subsets and the following techniques: conditional simulation, median indicator kriging, the probability from conditional expectation and confidence intervals attached to the estimation of blocks in the framework of the discrete Gaussian model. The complete blasthole dataset is considered to represent the true iron grades at sample point support while the ordinary kriging estimate derived from these samples is considered to represent the true block grades. The distributions obtained from point estimates, block estimates and simulations are compared to each other and to the true estimates of iron grades using graphs and statistics. The conditional expectation technique reproduced the results obtained from conditional simulation extremely well and it is a viable alternative to simulation at point support. At block support the confidence intervals technique reproduced the results of the conditional simulation more closely than the median indicator kriging and in the data subsets tested the confidence intervals technique actually reproduced the true grade distribution more closely than the conditional simulation.