Mineral Processing
Khadijeh farokhi nasab; Ali Imamalipour; Amin Hossein-Morshedy
Abstract
Accurate mineral resource estimation is the cornerstone of effective mine planning, especially within geologically intricate deposits like the Janja copper-gold system in southeastern Iran. This study introduces a comprehensive approach that synergizes high-resolution 3D geological modeling with robust ...
Read More
Accurate mineral resource estimation is the cornerstone of effective mine planning, especially within geologically intricate deposits like the Janja copper-gold system in southeastern Iran. This study introduces a comprehensive approach that synergizes high-resolution 3D geological modeling with robust geostatistical techniques, Ordinary Kriging and Inverse Distance Weighting, while leveraging advanced computational methods to enhance grade estimation precision and resource confidence. An extensive dataset from 108 drill holes informs a detailed 3D model integrating lithological diversity, alteration patterns, and assay results. Employing dynamic anisotropic variogram modeling, the framework adeptly captures spatial continuity and complex structural heterogeneity, surpassing conventional stationary models. Rigorous validation through variogram analysis and swath plotting confirms consistent spatial patterns and dependable copper and gold grade predictions, addressing inherent spatial heterogeneity and uneven sampling issues through optimized mineralized boundary delineation and ore-waste differentiation. Conforming to JORC reporting standards, resource classification into Measured, Indicated, and Inferred categories is anchored on spatial variance metrics, culminating in a robust estimate of approximately 482 million tonnes at cutoff grades of 0.1% Cu and 0.2 ppm Au. Geological insights underline the pivotal roles of structural controls and alteration zones in governing mineralization, providing strategic guidance for exploration and mine development. While the dataset is comprehensive, peripheral zones with sparse drilling highlight areas for future investigation to reduce uncertainty. This integrated, replicable methodology offers a scalable blueprint for resource estimation in complex porphyry deposits worldwide, advancing predictive accuracy and fostering sustainable mining practices aligned with responsible resource stewardship.
F. Khorram; O. Asghari; H. Memarian; A. Hoseein Morshedy; X. M. Emery
Abstract
The key input parameters for mine planning and all subsequent mining activities is based on the block models. The block size should take into account for the geological heterogeneity and the grade variability across the deposit. Providing grade models of smaller blocks is more complex and costly than ...
Read More
The key input parameters for mine planning and all subsequent mining activities is based on the block models. The block size should take into account for the geological heterogeneity and the grade variability across the deposit. Providing grade models of smaller blocks is more complex and costly than larger blocks, but larger sizes cannot represent areas with high spatial variability accurately. Hence, a unique block size is not an optimal solution for modeling a mine site. This paper presented a novel algorithm to create an adaptive block model with locally varying block sizes aiming to control dilution and ore loss in Sungun porphyry copper deposit of Iran with a complex geometry characterized by multiple dikes. Three grade block models with different block sizes and simulated by direct block simulation are the inputs of algorithm. The output is a merged block model, assigning the smaller blocks to the complex zones, such as ore-waste boundaries, and larger blocks to the continuous and homogeneous zones of the ore body. The presented algorithm is capable to provide an accurate spatial distribution model with a fewer number of blocks in comparison to the traditional block modeling concepts.
