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Geometallurgical programs – critical evaluation of applied methods and techniques
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Geometallurgy is a team-based multidisciplinary approach aimed at integrating geological, mineralogical and metallurgical information and yielding a spatial quantitative predictive model for production management. Production management includes forecast, control and optimization of the product quality (concentrates and tailings) and metallurgical performance (e.g. recoveries and throughput); and minimization of the environmental impact. Favourable characteristics of an ore body calling for geometallurgical model are high variability, low mineral grades, complex mineralogy and several alternative processing routes or beneficiation methods.Industrial application of geometallurgy is called a geometallurgical program. This study undertook a critical review and evaluation of methods and techniques used in geometallurgical programs. This evaluation aimed at defining how geometallurgical program should be carried out for different kinds of ore bodies. Methods applied here were an industry survey (questionnaire) along with development and use of a synthetic ore body build-up of geometallurgical modules. Survey on geometallurgical programs included fifty two case studies from both industry professionals and comprehensive literature studies. Focus in the survey was on answering why and how geometallurgical programs are built. This resulted in a two-dimensional classification system where geometallurgical program depth of application was presented in six levels. Geometallurgical methods and techniques were summarised accordingly under three approaches: traditional, proxy and mineralogical. Through the classification it was established that due to similar geometallurgical reasoning and methodologies the deposit and process data could be organized in a common way. Thus, a uniform data structure (Papers I, II) was proposed.Traditionally the scientific development in geometallurgy takes place through case studies. This is slow and results are often confidential. Therefore, an alternative way is needed; here a synthetic testing framework for geometallurgy was established and used as such alternative. The synthetic testing framework for geometallurgy consists of synthetic ore body and a mineral processing circuit. The generated digital ore body of a kind is sampled through a synthetic sampling module, followed by chemical and mineralogical analyses, and by geometallurgical and metallurgical testing conducted in a synthetic laboratory. The synthetic testing framework aims at being so realistic that an expert could not identify it from a true one while studying data it offers. Important and unique aspect here is that the geological ore body model is based on minerals. This means that synthetic ore body has full mineralogical composition and properties information at any point of the ore body. This makes it possible to run different characterisation techniques in synthetic analysis laboratory.The first framework built was based on Malmberget iron ore mine (LKAB). Two aspects were studied: sampling density required for a geometallurgical program and difference in the prediction capabilities between different geometallurgical approaches. As a result of applying synthetic testing framework, it was confirmed that metallurgical approach presents clear advantage in product quality prediction for production planning purposes. Another conclusion was that optimising the production based solely on head grade without application of variability in the processing properties gives significantly less reliable forecast and optimisation information for the mining value chain.For the iron ore case study it was concluded that the number of samples required for a geometallurgical program must vary based on the parameters to be forecasted. Reliable recovery model could be established based on some tens of samples whereas the reliable concentrate quality prediction (e.g metal grade, penalty elements) required more than 100 samples. In the latter the mineralogical approach proved to be significantly better in the quality of prediction in comparison to the traditional approach based on elemental grades. Model based on proxy approach could forecast well the response in magnetic separation performance with the help of Davis tube test. But the lack of geometallurgical test for flotation and gravity separation caused that in total the proxy approach forecast capability was worse than in mineralogical approach. This study is a part of a larger research program, PREP (Primary resource efficiency by enhanced prediction), and the results will be applied to on-going industrial case studies.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2016. , 104 p.
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
Research subject
Mineral Processing
URN: urn:nbn:se:ltu:diva-26607Local ID: f3023681-d58d-43a4-802b-28c9fee26390ISBN: 978-91-7583-636-2ISBN: 978-91-7583-637-9 (PDF)OAI: diva2:999773
För godkännande; 2016; 20160516 (viklis); Nedanstående person kommer att hålla licentiatseminarium för avläggande av teknologie licentiatexamen. Namn: Viktor Lishchuk Ämne: Mineralteknik/Mineral Processing Uppsats: Geometallurgical Programs – Critical Evaluation of Applied Methods and Techniques Examinator: Professor Pertti Lamberg, Institutionen för samhällsbyggnad och naturresurser, Avdelning: Mineralteknik och metallurgi, Luleå tekniska universitet. Diskutant: PhD Simon Michaux, BRGM, University of Liege, Institution of Genie Mineral, Materiaux et Environment, Brisbane Tid: Torsdag 2 juni, 2016 kl 10.00 Plats: F531, Luleå tekniska universitetAvailable from: 2016-09-30 Created: 2016-09-30

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