Defining, Establishing and Piloting of Geometallurgical Model and Simulation Framework for Iron Ores

LKAB Contact Kari Niiranen    LTU Contact
Posted in Sustainable mining

Demands for more effective utilisation of orebodies and proper risk management in mining industry have emerged a new cross-discipline called geometallurgy.  Geometallurgy combines geological and metallurgical information to create spatially-based predictive model for mineral processing plants design and optimisation.


At Luleå University of Technology geometallurgy is a new research area that started in 2010 with establishing the strategic research environment CAMM Centre of Advanced Mining and Metallurgy and its WP1 on Geometallurgy. This application is for a Ph.D. project in this emerging area.

Geometallurgy covers several disciplines from geology, geostatistics, process mineralogy, to minerals processing and aims to develop practical tools to be used in production planning and management in mining operations. The wide area of operation sets challenges for linking the information from different sources. In traditionally approach much of valuable data collected is often lost or remains unused 

At Luleå University of Technology a holistic approach has been taken (Lamberg 2010, work plan of the CAMM WP1) and this study is for further developing and piloting the idea. The approach consists of three quantitative models or modules: 1) geological model, 2) particle breakage model and 3) unit process models combined into a concentration model (see figure below). The geological model describes the mineralogy of the ore body at block level. The particle breakage model characterizes what kinds of particles are formed in comminution. The property based models describe how particles behave in the unit operation as a function of their properties (size, composition, density, magnetic susceptibility). Minerals and particles are the key elements of the geometallurgical approach described above.

Geometallurgical models binds together the modules described above. Critical is to establish interfaces in a way that data content and structures are similar so that ore characterisation includes proper parameters which can be transferred through the process chain.