Risk quantification in grade variability of gold deposits using sequential Gaussian simulation

Abstract

Risk quantification in grade is critical for mine design and planning. Grade uncertainty is assessed using multiple grade realizations, from geostatistical conditional simulations, which are effective to evaluate local or global uncertainty by honouring spatial correlation structures. The sequential Gaussian conditional simulation was used to assess uncertainty of grade estimates and illustrate simulated models in Sivas gold deposit, Turkey. In situ variability and risk quantification of the gold grade were assessed by probabilistic approach based on the sequential Gaussian simulations to yield a series of conditional maps characterized by equally probable spatial distribution of the gold grade for the study area. The simulation results were validated by a number of tests such as descriptive statistics, histogram, variogram and contour map reproductions. The case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variable such as the gold grade variability and distribution. The simulated models can be incorporated into exploration, exploitation and scheduling of the gold deposit.