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Estimation of ore grade is a time and cost consuming process that requires laboratory-based and exploratory information to present the shape and the ore grade distribution of ore deposit in three dimensional space. The block size is one of the most important parameters which impacts the quality of grade estimates in a resource model. This study aims at spatial modeling of iron ore deposit using geostatistical estimation methods such as Ordinary Kriging based on error estimation, selection of the appropriate size for mining blocks using Vlse Kriterijumsk Optimizacija Kompromisno Resenje method, and performing a three-dimensional block modeling along a grade estimation study for the resource estimation in the C-North iron ore deposit, NE Iran. The variogram that was used in OK estimation was cross validated. Cross validation results showed that compared with the local model, OK with the global model was the most appropriate model for the ore body. Detailed distribution maps of total iron contents in the C-North ore deposit showed a close relationship between structural features and higher iron contents, relative to other areas of the ore deposit. Structural features included the major faults and fault zones along the axial plane. These structures are interpreted to have played a significant role in (re) mobilisation and concentration of the metals, in agreement with observations made elsewhere in the Sangan iron ore complex. Based on the estimation results, 83 million tons of resource was estimated at an average grade of 41.86 % Fe using OK method. The C-North ore deposit has been classified based on the relative estimation error variance and the Australasian Code for Reporting of Mineral Resources and Ore Reserves. It is hoped that this example, taken from very different application fields, will encourage practitioners in applying an OK method with variety of ore deposits. |
