Rock masses are inherently variable in their nature owing to the complex interrelationship between discontinuities and intact rock. The simplest way to account for this uncertainty is through the explicit modelling of the spatial heterogeneity. This is commonly conducted through stochastic simulation, where multiple realizations of studied attributes are produced. Within this paper a geostatistics-based approach to modelling spatial uncertainty which is new to the field of open pit mine design is presented. The method is based on the use of sequential Gaussian simulation to reproduce the spatial heterogeneity observed in studied attributes. The paper presents the formal methodology used for stochastic simulation and the results obtained from the modelling process. Models were constructed by stochastically varying the geological strength index and uniaxial compressive strength within a geomechanical simulation model of the Ok Tedi mine site in Papua New Guinea. Simulations demonstrate the importance of understanding the scale dependent characteristics of sample variance and the effects of spatial heterogeneity on both the critical SRF and projected failure size.
According to the technical guide for grouting method for dam construction in Japan modified in the year 2003, one of the key issues for grouting is quality assurance and effectiveness by minimizing the amount of injected grout. Hence, the grouting management support system was newly developed by combining joint density diagram and geostatistical simulations. In this system, the joint density diagram was used to determine most effective direction for the grout injection boreholes and the hydraulic conductivity fields before/after grout injection were estimated by geostatistical simulations. In this paper, the newly developed system was introduced and applied to the actual underground structure construction site.