3. Electronic Theses and Dissertations (ETDs) - All submissions
Permanent URI for this communityhttps://wiredspace.wits.ac.za/handle/10539/45
Browse
3 results
Search Results
Item Improving reconciliations through geostatistical resource model updates of Phoenix deposits, Tati Nickel mine(2019-09-27) Ntshole, MothusiPeriodic resource model updates are necessary to bridge the reconciliation variances between the resource model estimates and actual ore mined. As a tool, Mineral Resources reconciliation focuses on identifying, analysing and managing variance between estimated Mineral Resources and actual ore mined. The aim is to minimize the business risk associated with poor resource model estimate performance against actual ore mined at Phoenix Mine. The Phoenix Mine Mineral Resource model update research project incorporates historical and recently acquired drillhole data, other relevant geological information in the form of geological pit floor and face maps to update the Phoenix Mineral Resource model. Employing appropriate geostatistical estimation methods and improved modelling procedures can highlight and overcome some of the causes of observed reconciliation variances. Each of the five domains of the Phoenix resource was estimated through ordinary kriging and indicator kriging as principal methods. Nearest neighbour (NN) and inverse power of distance (IPD) methods were used as a check and where the above geostatistical methods proved inappropriate. The comparison between model estimates from these various estimation techniques and raw drill hole data was undertaken. The results indicate areas of both good and poor correlation across the different methods and sections of the resource. Areas where there is good correlation coincides with good sampling coverage where as poor correlation coincides mostly with portions of the resource where there is paucity of sampling data. Subjecting the individual domains’ resource estimates from the various estimation methods to a validation check against the sampling data assisted in selecting the estimate that honours the sampling data the most. Such Estimate was selected as the most suitable and reported as the Estimated Resources. Indicator Kriging produced better results compared to the rest of the techniques. In domain four geostatistical methods were unsuccessful thus Inverse power of distance method was used.Item The impact of supply and demand drivers on the iron ore price and cycle(2018) Nortje, Petrus GerhardusIron ore prices rallied from USD15/DMT during 2004 and experienced a significant drop from USD 140/DMT during the latter part of 2013. The purpose of the work is to identify the key drivers impacting on iron ore demand globally. Understanding the supply and demand balance and impact on price, is key to informed decision making relating to the iron ore business. The research methodology applied largely followed a quantitative methodology. Key drivers of iron ore demand, supply and demand balance and the impact on price were evaluated. The method applied consisted of gathering data from secondary sources and a detailed quantitative analysis on GDP, stage of economic development, steel consumption, supply and demand of iron ore and intensity of use. Approximately 98% of all iron ore is used for steel making and on that basis steel consumption is the primary driver for iron ore demand. Steel is mostly used for construction and manufacturing and is driven by emerging economies of which China is currently the largest contributor. Global GDP growth correlates well with steel consumption and is primarily driven by emerging economies. Urbanisation was and still is a key driver for construction in China, to provide housing and related infrastructure for transportation and services. Scrap steel recycling, currently at 15%, affect the demand for new steel and indirectly iron ore. Iron ore is abundant and can easily meet the demand. The significant growth from 2004/5 to 2013/14 and the unprecedented demand for steel resulted in elevated iron ore prices, introducing high cost iron ore, predominantly from Chinese State owned companies. From late 2013, the iron ore prices reduced significantly. This was mainly due to the steel consumption in China slowing down; delivering of large scale, low cost iron ore projects in Australia and Brazil and a significant reduction in oil prices. The key drivers impacting iron ore demand is: global GDP growth, industrialisation and urbanisation of emerging economies, recycling of steel, supply and demand balance of iron ore, the cost of production and the price of global iron ore. For the medium term outlook, the iron ore market will be structurally over-supplied and, as a result, the demand could be met at significantly lower cost of production levels than that seen during the period leading up to the price collapse in 2013. This is primarily because of the increase in low-cost supply from the major suppliers displacing higher cost producers. China will continue to grow and drive the global demand for steel and iron ore during the medium term albeit at much lower rates when compared to the last decade. The demand for steel will increase until 2020 according to various analyst views. The iron ore prices are expected to trade between USD50/DMT to USD70/DMT from 2016 to 2020 mainly because of the over-supply situation and demand being mostly met by large scale, low-cost producers. The decision around the continuation of high cost, state owned Chinese iron ore producers, new large-scale low cost production and the oil price will impact on the price outlook.Item Optimization of dense medium cyclone plant for the beneficiation of low grade iron ore with associated high proportion of near-density material at Sishen Iron Ore Mine(2016) Tom, PhakamileThe research report is premised on three aspects which are critical in the heavy mineral beneficiation. These aspects are classified as (i) understanding the densimetric profile of the available ore body, (ii) understanding the properties of the heavy medium utilised at the plant to beneficiate the ore, and (iii) the automation and modelling of the processing plant in order to maximise plant efficiency. Ore characterisation is mainly focused on understanding the densimetric profile of the ore body, in order to determine the probability of producing a saleable product as well as predicting the expected yields and quality. This is done to utilise the endowment entrusted upon the operating entity by the government and shareholders to treat the mineral resource to its full potential. Understanding of the beneficiation potential of the ore body will assist the mine planning and processing plant to optimise the product tons and quality. This will ensure the marketing plans are in accordance with the expected product as beneficiation will vary depending on the mining block reserves. The mining blocks have potential to produce varying product grades with different recoveries. Ore characterisation was conducted on the GR80 mining block, low-grade stockpiles (i.e. C-grade ore reserves & Jig discard and dense medium separation (DMS) run-of-mine (ROM) material. The GR80 material was characterised as having low proportion of near-density material and would be easy to beneficiate as well as produce high volumes of high grade product. Furthermore, it was revealed that the 2014 DMS ROM had an increased proportion of low-density material; however this material was also had low proportion of near-density material. The low-grade stockpiles was characterised by high proportion of near density material, which necessitate the beneficiation process to operate at high density in excess of 3.8 t/m3. Maintaining a higher operating density requires more dense medium which leads to viscosity problems and impact performance. The characterisation of the FeSi medium was imperative to understand its behaviour and potential influence on beneficiation of low-grade stockpiles and mining blocks with elevated proportion of near-density material. As the proportion of near-density waste material increases in the run-of-mine (ROM), it is necessary to beneficiate the material at elevated operating medium densities. However, when cyclones are operated at high densities, the negative influence of the medium viscosity becomes more apparent and thus influences the separation efficiency. Heavy medium, ferrosilicon (FeSi) characterisation looked at identifying the effects of viscosity on the FeSi stability and whether there would be a need for a viscosity modifier. Thus, the importance of controlling the stability, viscosity, and density of the medium cannot be under-estimated and can very often override the improvements attainable through better designs of cyclones. Furthermore, the slurry mixture of the heavy medium utilised for the purpose of dense medium separation should be non-detrimental to the effectiveness of separation in the DMS Fine cyclone plant. Medium characterisation showed that removal of ultra-fines leads to unstable media as indicated by faster settling rates. This would result in medium segregation in the beneficiation cyclone thereby leading to unacceptable high density differential which will negatively impact the cut-point shift and cause high yield losses to waste. The overall control of the metallurgical processes at Sishen’s Cyclone Plant is still done on manually and thus operation still varies from person-to-person and/or from shift-to-shift. This result in some of the process data and trends not being available online as well as being captured inaccurately. Furthermore, this negatively affects the traceability and reproducibility of the production metallurgical key performance indicators (KPI’s) as well as process stability and efficiency. It has been demonstrated that real-time online measurements are crucial to maintaining processing plant stability and efficiency thereby ensuring that the final product grade and its value is not eroded. Modelling and automation of the key metallurgical parameters for the cyclone plant circuit was achieved by installation of appropriate instrumentation and interlocking to the programmable logic control (PLC). This allowed for the control of the correct medium sump level, cyclone inlet pressure, medium-to-ore ratio as well as online monitoring of density differential as “proxy” for medium rheological characteristics. The benefit of modelling and simulation allows the virtual investigation and optimisation of the processing plant efficiency as well as analysis of the impact of varying ore characteristics, throughput variations and changing operating parameters. Therefore it is imperative that all cyclone operating modules are operated at the same efficiency which can be achieved by optimized process through proper automation and monitoring, thereby improving the total plant profitability. Keywords: dense medium separation; densimetric profile; dynamic modelling; FeSi rheology; iron-ore beneficiation; process automation; process control.