Simulation of geometallurgical variables through stepwise conditional transformation in Sungun copper deposit, Iran
- PDF / 980,512 Bytes
- 11 Pages / 595.276 x 790.866 pts Page_size
- 56 Downloads / 219 Views
ORIGINAL PAPER
Simulation of geometallurgical variables through stepwise conditional transformation in Sungun copper deposit, Iran Seyed Ali Hosseini & Omid Asghari
Received: 4 February 2014 / Accepted: 29 April 2014 # Saudi Society for Geosciences 2014
Abstract Nowadays, geometallurgical modeling, as a rapidly growing discipline in mining engineering, has significant role in mine designing/planning especially for porphyry copper projects. In porphyry copper deposits, the copper ore often is composed of two main parts including oxide and sulfide ores. The oxide rock type consists a fraction of total copper which would be recovered by heap leaching. Flotation plant is used when the fraction of sulfide ore is high enough. The mineralogical inequality constraint linking both grade variables (total copper and oxide copper) is a difficulty which often complicates the joint modeling and simulation of variables. To simplify such complicated joint simulation, the stepwise conditional transformation technique is presented which transforms multiple variables to the univariate and multivariate Gaussian with no cross correlation. This makes it easy to simulate multiple variables with arbitrarily complex relationships. This study addresses the application of stepwise conditional transformation and sequential Gaussian simulation for reproduction of the total and oxide copper in different rock types of the Sungun porphyry copper deposit honoring the relationship between Cu-oxide and Cu-total of the initial data. Validation results show that the simulation model has a good agreement with the sample data and geological facts of deposit. Keywords Stepwise conditional transformation . Mineralogical constraint . Geometallurgical variables . Sequential Gaussian simulation . Variogram
S. A. Hosseini : O. Asghari (*) Simulation and Data Processing Laboratory, School of Mining Engineering, University College of Engineering, University of Tehran, Tehran, Iran e-mail: [email protected]
Introduction Geometallurgy is a new approach to mineral exploration and production. Geometallurgy integrates aspects of geostatistics and mineralogical properties to study relationships between variables with physical and chemical characteristics of the ore deposits and their influence on specific metallurgical processes. Key outcomes of improved geometallurgical knowledge are improved forecasting, reduced technical risk, enhanced economic optimization of mineral production, and improved sustainability. Simulating and modeling of geometallurgical variables are becoming increasingly important for improved management of mineral resources (Boisvert et al. 2013). Ore variability is a real challenge in the exploitation of any kind of deposit. Geometallurgical methodologies enable us to consider this variability in mine designing, mine planning, and then use forecasting to make strategic decisions about project operation and economic performance (Williams 2013). Porphyry copper deposits are very complex geological systems and exhibit a great extent variabilit
Data Loading...
