عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Geostatistical methods are applied for modeling the mineral deposits at the final stage of the detailed exploration. By applying the results of these models, the technical and economic feasibility studies are conducted for the deposits. The geostatistical modeling methods are usually consist of estimation and simulation methods. The estimation techniques, such as Kriging, construct spatial relation (geological continuation model) between data, by providing the best unique guesses for unknown features. However, when applying this technique for a grid of drill-holes over a deposit, an obvious discrepancy exists between the real geological features and the Kriging estimation map. Because of the limited number of sampled data applied for Kriging, it could not appear as the same as the real features. Also the spatial continuity estimated by the Kriging maps, are smoother than the real unknown features. On the other hand, the objective of simulation is to provide some functions or sets of variable values, to be compatible with the existing information. This means that the simulated values have an average and the variance similar to the raw data and may even be the same as the measurements. we studied the Anomaly No.3 of Narigan uranium mineral deposit, located in the central Iran region and applied the Kriging estimation and the sequential Gaussian simulation methods, and finally by comparing the results we concluded that the Kriging estimation method is more reliable for long term planning of a mine. Because of the reconstructing random structures, the results of the simulation methods indicate that they could also be applied for short term planning in mine exploitation.
C. Deutsch and A. Journel, “GSLIB: geostatistical software library and user’s guide,” Oxford University Press, New York, 384 (1998).