Evaluation of Rock Mass Quality in Underground Section of Anguran Mine Using Geostatistical Analyst in GIS Environment

Abstract

Rock mass characterization is one of the most important parameters affecting the underground mine design. This study deals with the prediction of rock mass quality using geo-statistical estimator in Anguran underground mine at the level +2740. For this, a database consisting of 427 Q-based rock mass quality data sets was developed during the development of mine drifts. Accordingly, data were analyzed and checked for normality, trend and anisotropy. Analysis on Q-data showed that: 1-they do not have a normal distribution, 2there are neither global nor local outliers in data 3-the data seem to exhibit a trend. In this study, the Universal Kriging was used due to existing trend in datasets. Taking into consideration five estimation error evaluation criteria, the best Variogram model was selected among three models: exponential, spherical and Gaussian. The results showed that spherical variogram model provides the best fit to the data's spatial structure. Cross validation showed high accuracy level for performance of geo-statistical estimator. Accordingly, the rock mass quality map for the area under study built in ArcGIS environment. The analysis results of final rock mass quality map revealed that about 53% of under study area has poor to extremely poor rock mass condition, 8% has fair and 39% has good to extremely good rock mass condition.