عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Underground mine roof collapse is one of the most critical problems encountered by miners. Faults and fractures decrease the strength of overlying strata. As a result, knowledge of the roof geology and quality within coal mining before coal extraction is necessary. In this study, geostatistical estimator was used to predict the roof condition in Tabas coal mine. First, core data from 33 exploration boreholes was gathered. Ordinary Kriging method was chosen as the best estimation method based on the quality of data and the absence of isotropy. Also, the best variogram model was selected among exponential, spherical and Gaussian ones considering the evaluation criteria including MPE, RMSSPE, ASE and RMSPE. Cross validation showed the high accuracy level of the geostatistical estimator. The roof classification map of Tabas coal mine was built using ArcGIS. Based on the obtained results, approximately 22% of total area is under a weak roof, and 78% covered with an intermediate roof. For validity check, the geological experiences obtained during the extraction of panels E1 and E2 and real data were compared with the final ArcGIS map of mine roof classification. The real data regarding the mining operation and downtime for the mined out panels verified the mine roof classification was obtained by geostatistical analyst and ArcGIS model in this study.