Application of geostatistical simulation for mineral resource estimation by modelling of drillhole data-case study on an iron ore mine

The unpredictable fluctuations in metal prices, political instability, and socio-economic problems in resource rich areas are among the reasons why the mining industry needs to look for ways to maximize returns of mining projects whilst keeping operating costs at their lowest. In this paper, firstly, the potential of improving exploration programs was investigated using a drillhole data modelling scheme based on the geology of the deposit. Secondly, the application of geostatistical Simulation for mine design was investigated. A dataset consisting of 539 drillholes was used as a case study with grid dimensions of x (3100 m) by y (3800 m). Through drillhole data modelling, the drillholes were segmented into groups using geological features and, based on these features; five (5) possible geological patterns were consttucted. The applicability of geostatistical simulation in mine design was assessed by simulating each geological pattern 500 times to capture the space of uncertainty, and the simulated realizations for each pattern was averaged to produce one block model per pattern. This modelling technique showed how the geological information can be used optimally to reduce drilling requirement during resource evaluation, and from analysis, it was concluded that the project would save of the drilling and sample analysis cost combined by a margin of 32% using this method.