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  • 1.
    Lishchuk, Viktor
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Bringing predictability into a geometallurgical program: An iron ore case study2019Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The risks of starting, operating and closing mining projects have become higher than ever. In order to stay ahead of the competition, mining companies have to manage various risks: technical, environmental, legal, regulatory, political, cyber, financial and social. Some of these can be mitigated with the help of geometallurgy. Geometallurgy aims to link geological variability with responses in the beneficiation process by a wide usage of automated mineralogy, proxy metallurgical tests, and process simulation. However, traditional geometallurgy has neglected the non-technical aspects of mining. This has caused wide-spread discussion among researchers on the benefits of geometallurgy and its place in industry.

    In order to improve predictability in geometallurgy, such programs should cover planning, and the testing of hypotheses, and only then should there be an attempt to develop suitable technical tools. Such approach would ensure that those tools would be useful and are needed, not only from the technical point of view, but also from the users’ perspective. Therefore, this thesis introduces methodology on how to decrease uncertainty in the production planning and thus determine how much effort to put into decreasing uncertainty in geometallurgical programs.

    The predictability improvement of a geometallurgical program starts at the planning stage. The classification system developed here, through the survey (interviews) and literature review, indicates different ways to link geological information with metallurgical responses, and suggests areas where technical development is called for. The proposed developments can be tested before the start of the geometallurgical program with synthetic data. For the iron ore reference study (Malmberget), it was shown that implementation of geometallurgy is beneficial in terms of net present value (NPV) and internal rate of return (IRR), and building geometallurgical spatial model for the process properties (recovery and total concentrate tonnages), and that it requires fewer samples for making a reliable process prediction than concentrate quality. The new process and proxy for mineralogical characterisation models were developed as part of the geometallurgical program for the iron ore case study (Leveäniemi): an estimator of ore quality (ܺ௅்௎), a model for iron recovery in WLIMS, a model for iron-oxides liberation prediction. Additionally, it was found that DT may be applied only for studying marginal ores. The evaluation of different spatial process modelling methods showed that tree methods can be successfully employed in predicting non-additive variables (recoveries).

  • 2.
    Lishchuk, Viktor
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Geometallurgical programs – critical evaluation of applied methods and techniques2016Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    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.

  • 3.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Koch, Pierre-Henri
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    The geometallurgical framework: Malmberget and Mikheevskoye case studies2015Ingår i: Mining Science, ISSN 2300-9586, Vol. 22, nr Special Issue 2, s. 57-66Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Geometallurgy is a growing area within a mineral processing industry. It brings together tasks of geologists and mineral processing engineers to do short and medium term production planning. However, it is also striving to deal with long term tasks such as changes in either production flow sheet or considering different scenarios. This paper demonstrates capabilities of geometallurgy through two case studies from perspective of Minerals and Metallurgical Engineering division Lulea University of Technology. A classification system of geometallurgical usages and approaches was developed in order to describe a working framework. A practical meaning of classification system was proved in two case studies: Mikheevskoye (Russia) and Malmberget (Sweden) projects. These case studies, where geometallurgy was applied in a rather systematic way, have shown the amount of work required for moving the project within the geometallurgical framework, which corresponds to shift of the projects location within the geometallurgical classification system.

  • 4.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Classification of Geometallurgical Programs Based on Approach and Purpose2015Ingår i: Mineral Resources in a Sustainable World / [ed] A.S. Andre-Mayer; M. Cathelineau; P. Muchez; E. Pirard; S. Sindern, 2015, s. 1431-1434Konferensbidrag (Refereegranskat)
    Abstract [en]

    Geometallurgy is a rapidly developing holistic approach for combining geological and metallurgical information for production management purposes in mining operations. The industrial application of geometallurgy is called a geometallurgical program and one of the largest challenges within geometallurgical programs is to select appropriate methods for resource characterization. Aim of such characterization is the prediction of metallurgical performance of different ore types and geometallurgical domains with the required accuracy. More than 25 geometallurgical programs from mining operations around the world were reviewed and a classification system developed with aim to clarify how geometallurgy is used and what methods are applied. The result is summarized as a two-dimensional classification which illustrates what geometallurgical approaches are used and how collected data is applied. In addition the proposed classification system gives a perspective of what are the minimum requirements for a geometallurgical program at different levels of application and who are the main participants that should be engaged in a geometallurgical program. The classification system can also be used as a reference system for benchmarking of different geometallurgical endeavours.

  • 5.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Classification of geometallurgical programs based on approach and purpose2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    Geometallurgy is a rapidly developing holistic approach for combining geological and metallurgical information for production management purposes in mining operations. The industrial application of geometallurgy is called a geometallurgical program and one of the largest challenges within geometallurgical programs is to select appropriate methods for resourcecharacterization. Aim of such characterization is the prediction of metallurgical performance of different ore types and geometallurgical domains with the required accuracy.More than 25 geometallurgical programs from mining operations around the world were reviewed and a classification system developed with aim to clarify how geometallurgy is used and what methods are applied. The result is summarized as a two-dimensional classification which illustrates what geometallurgical approaches are used and how collected data is applied.In addition the proposed classification system gives a perspective of what are the minimum requirements for a geometallurgical program at different levels ofapplication and who are the main participants that should be engaged in a geometallurgical program. The classification system can also be used as a reference system for benchmarking of different geometallurgicalendeavours.

  • 6.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Evaluation of sampling in geometallurgical programs through synthetic deposit model2016Ingår i: IMPC 2016: XXVIII International Mineral Processing Congress Proceedings, 2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main purpose of geometallurgy is to develop a model to predict the variability in the mineralprocessing performance within the ore body. Geometallurgical tests used for developing such a model need to be fast, practical and inexpensive and include as an input data relevant and measureable geological parameters like elemental grades, mineral grades and grain size. Important in each geometallurgical program is to define the number of samples needed to be sent for geometallurgical testing to enable reliable metallurgical forecast. This is, however, a complicated question that does not have a generic answer.To study the question on sampling a simulation environment was built including a synthetic orebody and sampling & assaying module. A synthetic Kiruna type iron oxide - apatite deposit was established based on case studies of Malmberget ore. The synthetic ore body includes alike variability in rock types, modal mineralogy, chemical composition, density and mineral textures as its real life counterpart. The synthetic ore body was virtually sampled with different sampling densities for a Davis tube testing, a geometallurgical test characterising response in magnetic separation. Based on the test results a forecast for the processing of the whole ore body was created. The forecasted parameters included concentrate tonnages, iron recovery and concentrate quality in terms of iron, phosphorous and silica contents.The study shows that the number of samples required for forecasting different geometallurgicalparameters varies. Reliable estimates on iron recovery and concentrate mass pull can be made with about 5-10 representative samples by geometallurgical ore type. However, when the concentrate quality in terms of impurities needs to be forecasted, the sample number is more than 20 times higher. This is due to variation in mineral liberation and shows the importance of developing techniques to collect qualitative information on mineral and ore textures in geometallurgy.

  • 7.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Evaluation of sampling in geometallurgical programs through synthetic deposit model2016Ingår i: (IMPC 2016), Canadian Institute of Mining, Metallurgy and Petroleum, 2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main purpose of geometallurgy is to develop a model to predict the variability in the mineralprocessing performance within the ore body. Geometallurgical tests used for developing such a model need to be fast, practical and inexpensive and include as an input data relevant and measureable geological parameters like elemental grades, mineral grades and grain size. Important in each geometallurgical program is to define the number of samples needed to be sent for geometallurgical testing to enable reliable metallurgical forecast. This is, however, a complicated question that does not have a generic answer.

    To study the question on sampling a simulation environment was built including a synthetic orebody and sampling & assaying module. A synthetic Kiruna type iron oxide - apatite deposit was established based on case studies of Malmberget ore. The synthetic ore body includes alike variability in rock types, modal mineralogy, chemical composition, density and mineral textures as its real life counterpart. The synthetic ore body was virtually sampled with different sampling densities for a Davis tube testing, a geometallurgical test characterising response in magnetic separation. Based on the test results a forecast for the processing of the whole ore body was created. The forecasted parameters included concentrate tonnages, iron recovery and concentrate quality in terms of iron, phosphorous and silica contents.

    The study shows that the number of samples required for forecasting different geometallurgicalparameters varies. Reliable estimates on iron recovery and concentrate mass pull can be made with about 5-10 representative samples by geometallurgical ore type. However, when the concentrate quality in terms of impurities needs to be forecasted, the sample number is more than 20 times higher. This is due to variation in mineral liberation and shows the importance of developing techniques to collect qualitative information on mineral and ore textures in geometallurgy.

  • 8.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Ghorbani, Yousef
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Evaluation and comparison of different machine-learning methods to integrate sparse process data into a spatial model in geometallurgy2019Ingår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 134, s. 156-165Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A spatial model for process properties allows for improvedproduction planning in mining by considering the process variability ofthe deposit. Hitherto, machine-learning modelling methods have beenunderutilised for spatial modelling in geometallurgy. The goal of thisproject is to find an efficient way to integrate process properties (ironrecovery and mass pull of the Davis tube, iron recovery and mass pull ofthe wet low intensity magnetic separation, liberation of iron oxides, andP_80) for an iron ore case study into a spatial model using machinelearningmethods. The modelling was done in two steps. First, the processproperties were deployed into a geological database by building nonspatialprocess models. Second, the process properties estimated in thegeological database were extracted together with only their coordinates(x, y, z) and iron grades and spatial process models were built.Modelling methods were evaluated and compared in terms of relativestandard deviation (RSD). The lower RSD for decision tree methodssuggests that those methods may be preferential when modelling non-linearprocess properties.

  • 9.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Koch, Pierre-Henri
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Mattias, Gustafsson
    LKAB.
    Pålsson, Bertil
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Geometallurgical characterisation of Leveäniemi iron ore: Unlocking the patterns2019Ingår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 131, s. 325-335Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    As part of a geometallurgical program for the Leveänimei iron ore mine, the Davis tube was used as proxy to classify ore types, predict iron recoveries in wet low-intensity magnetic separation (WLIMS), and to estimate liberation of mixed particles. The study was conducted by testing 13 iron ore samples with a Davis tube and a laboratory WLIMS. Ore feed was studied for modal mineralogy and liberation distribution with Automated Scanning Electron Microscopy. Data analyses to detect the patterns and data dependencies were done with multivariate statistics: principal component analysis, and projection to latent structures regression. Results show that a simple index (XLTU) based on mass pull (yield) in the Davis tube is capable of easy classification of magnetite ores. Using Davis tube mass pull and iron recovery, together with iron and Satmagan head grades may predict iron recovery in WLIMS. Also, the variability in Fe-oxides liberation pattern for magnetite semi-massive ores can be explained with the chemical composition of the Davis tube concentrate. It is concluded that the Davis tube test is better used only for marginal ores, since iron oxide minerals tend to be fully liberated in high-grade magnetite massive ores after grinding. The developed models may be used in populating a production block model.

  • 10.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Koch, Pierre-Henri
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Pålsson, Bertil
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Mattias, Gustafsson
    LKAB.
    Geometallurgical characterisation of Leveäniemi iron ore: unlocking the patterns2018Ingår i: Conference in Minerals Engineering / [ed] Jan Rosenkranz, Bertil Pålsson, Tommy Karlkvist, 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Geometallurgy of iron ores aims at linking geological variability and responses in the beneficiation process by a wide usage of automated mineralogy, proxy metallurgical tests (e.g., Davis tube) and process simulation.

    In this study several patterns from iron ore processing, in context of their textural description, are revealed and modelling is attempted. The first one is an ore classification method with a novel quality estimator XLTU. The second one is an algorithm for predicting iron recovery in wet low intensity magnetic separator (WLIMS). The last one is predicting liberation distribution of iron oxides. Process variables are generated with a Davis tube and a WLIMS test. All streams are chemically characterised. Ore feed was studied for modal mineralogy and liberation distribution with QEMSCAN (Quantitative Evaluation of Minerals by Scanning Electron Microscopy). Post-processing for detecting the patterns and data dependencies was done with multivariate statistics: principal component analysis (PCA), and projection to latent structures regression (PLS). The study was done on 13 apatite iron ore type samples from the Leveäniemi mine (LKAB).

    It is concluded that Davis tube test is better used only for marginal ores, since iron oxide minerals tend to be fully liberated in high grade magnetite massive ores after grinding. In addition, they will give high recovery and high mass pull in a Davis tube test.

    The developed models can be used in populating a production block model in the future. Furthermore, future work should cover larger variability of marginal ores in terms of Fe grades and modal mineralogy (e.g. feldspar, amphibole, apatite dominated). Variability of grain size distribution ought to be included into future studies.

  • 11.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Development of a Synthetic Ore Deposit Model for Geometallurgy2016Ingår i: Geomet16: Third AusIMM International Geometallurgy Conference 2016 : Conference Proceedings, Parkville, Victoria: The Australian Institute of Mining and Metallurgy , 2016, s. 275-286Konferensbidrag (Refereegranskat)
  • 12.
    Lishchuk, Viktor
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lund, Cecilia
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Lamberg, Pertti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Miroshnikova, Elena
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Matematiska vetenskaper.
    Simulation of a Mining Value Chain with a Synthetic Ore Body Model: Iron Ore Example2018Ingår i: Minerals, ISSN 2075-163X, E-ISSN 2075-163X, Vol. 8, nr 11, artikel-id 536Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reconciliation of geological, mining and mineral processing information is a costly and time demanding procedure with high uncertainty due to incomplete information, especially during the early stages of a project, i.e., pre-feasibility, feasibility studies. Lack of information at those project stages can be overcome by applying synthetic data for investigating different scenarios. Generation of the synthetic data requires some minimum sparse knowledge already available from other parts of the mining value chain, i.e., geology, mining, mineral processing. This paper describes how to establish and construct a synthetic testing environment, or “synthetic ore body model” by integrating a synthetic deposit, mine production, constrained by a mine plan, and a simulated beneficiation process. The approach uses quantitative mineralogical data and liberation information for process simulation. The results of geological and process data integration are compared with the real case data of an apatite iron ore. The discussed approach allows for studying the implications in downstream processes caused by changes in upstream parts of the mining value chain. It also opens the possibility of optimising sampling campaigns by investigating different synthetic drilling scenarios including changes to the spacing between synthetic drill holes, composite length, drill hole orientation and assayed parameters.

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