TY - JOUR N2 - Safe mine operations and optimal economical decision making in the context of lignite resources require an adequate level of knowledge about the spatial distribution of critical attributes in terms of geometry and quality in the deposit. Therefore, ore body models are generated using different approaches in geostatistics, depending on the problem to be solved. In this article the analysis of geostatistical methods used for deposits modeling has been presented. Based on exploration data concerning caloric value Q, models of one exemplary lignite deposit has been made. Two models of deposit were prepared using two different methods: ordinary kriging (OK) and sequential Gaussian conditional simulation (SGSIM). Different models of the same deposit were analyzed and compared with source data using criterion of fidelity to statistical attributes like: mean value, variance, statistical distribution. Models, which have been created based on exploration data, were compared with in-situ data gained from survey activities in the exploitation process. As a result of comparison correlation factor and measures of deviations were computed: average relative error, absolute relative error. Models were compared with in situ data, considering statistical features and local variability as well. In conclusion, the study gives valuable information into the benefits of using certain geostatistical approaches for variable tasks and problems in the lignite deposits design process. For the assessment of average values of deposit parameters ordinary kriging provides appropriate effects. Geostatisical simulation (e.g. sequential Gaussian simulation - SGSIM) provides much more relevant information for tasks connected to probability (or risk) of defined threshold exceedences than ordinary kriging. Models made with simulation method are characterized by high fidelity of spatial distribution in comparison to source data. L1 - http://www.czasopisma.pan.pl/Content/85640/PDF/art-05-naworyta-benndorf.pdf L2 - http://www.czasopisma.pan.pl/Content/85640 PY - 2012 IS - No 1 EP - 101 DO - 10.2478/v10269-012-0005-3 KW - modelling of deposits KW - kriging KW - conditional simulation KW - geostatistics KW - accuracy A1 - Naworyta, Wojciech A1 - Benndorf, Jörg PB - Komitet Zrównoważonej Gospodarki Surowcami Mineralnymi PAN PB - Instytut Gospodarki Surowcami Mineralnymi i Energią PAN VL - vol. 28 DA - 2012 T1 - Accuracy assessment of geostatistical modelling methods of mineral deposits for the purpose of their future exploitation - based on one lignite deposit SP - 77 UR - http://www.czasopisma.pan.pl/dlibra/publication/edition/85640 T2 - Gospodarka Surowcami Mineralnymi - Mineral Resources Management ER -