Title of article :
Applying Analytical and Quantitative Criteria to Estimate Block Model Uncertainty and Mineral Reserve Classification: A Case Study: Khoshumi Uranium Deposit in Yazd
Author/Authors :
Taghvaeenejad, Mojtaba Department of Mining Engineering - Shahid Bahonar University of Kerman - Kerman, Iran , Shayestehfar, Mohammadreza Department of Mining Engineering - Shahid Bahonar University of Kerman - Kerman, Iran , Moarefvand, Parviz Department of Mining and Metallurgical Engineering - Amirkabir University of Technology - Tehran, Iran
Abstract :
At different stages of mining, we always face a degree of uncertainty. Some of these
uncertainties, such as the amount of reserve and grade of the deposit, are due to the
inherent changes in the deposit and directly affect the technical and economic
indicators of the deposit. On the other hand, the heavy costs of the exploration sector
often limit the amount of exploratory information, which necessitates the use of
accurate estimation methods. In this work,we examines the modeling and estimation
results using the conventional and simple kriging methods and the effects of the
diverse indicators used in the classification of mineral storages or the parameters
defining these indices. 127 exploratory boreholes with an average depth of 95 m are
used to build the block model of the deposit in the Data Mine software. After the
statistical studies, the 3D variographic studies are performed in order to identify the
anisotropy of the region. A grade block model is constructed using the optimal
variogram parameters.Then, using various methods to estimate the block model
uncertainty including the kriging estimation variance, block error estimation, kriging
efficiency and slope of regression, the mineral reserves are classified according to the
JORC standard code. Based on different cut-off grades, the tonnage and average grade
are calculated and plotted. In this work, an innovative quantitative method based on
the grade-number and grade-volume fractal model is used to indicate the classification
of mineral reserves. The use of fractal patterns due to the amplitude of the variation is
greater and more important than the standard and provides us with a better
understanding of the deposit changes per block. The existence of a minimal difference
between the use of the standard and fractal patterns in the slope of the regression
method indicates less error and is a proof of more reliable results
Keywords :
Variogram , Block model uncertainty , Kriging , Reserve classification , Fractal method
Journal title :
Journal of Mining and Environment