Conference Proceedings
                        Project Evaluation 2007
Conference Proceedings
                            Project Evaluation 2007
Automated Mineralogy for Ore Characterisation and Plant Optimisation
                            
Traditionally, characterisation of the mineralogy and textures of ore and rock samples were based on observations of hand specimens and thin sections using an optical microscope. The extent of the data collection was limited by the available tools and thus variations in mineralogy and texture were generally not described by quantitative data. These qualitative to semi-quantitative approaches, even though well established over the years, resulted in variable observations and data sets. The data were unlikely to be representative of a sample and limited statistical validity meant the results could not be reliably used in modern digital mining design and planning. With recently developed SEM based quantitative mineralogy tools and the corresponding methodologies, ore textures can be quantified and compared numerically. The numerical data can not only enhance the understanding of an orebody in geological terms, but can also be used in the creation of metallurgical models for mine and mineral processing design and simulation. These capabilities provide valuable inputs to risk assessment studies and the evaluation of mineral projects._x000D_
FORMAL CITATION:Burrows, D, Fandrich, R and Gu, Y, 2007._x000D_
Automated mineralogy for ore characterisation and plant optimisation, in Proceedings Project Evaluation 2007, pp 179-188 (The Australasian Institute of Mining and Metallurgy: Melbourne).
                    
                        FORMAL CITATION:Burrows, D, Fandrich, R and Gu, Y, 2007._x000D_
Automated mineralogy for ore characterisation and plant optimisation, in Proceedings Project Evaluation 2007, pp 179-188 (The Australasian Institute of Mining and Metallurgy: Melbourne).
                                    
                                        Contributor(s):
                                    
                                    D Burrows, R Fandrich, Y Gu
                                
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                                - Published: 2007
- PDF Size: 2.772 Mb.
- Unique ID: P200704020
