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Full-Text Articles in Mining Engineering
The Simulation Of Material Types In A Western Australian Iron Deposit, Jacqueline Ferreira
The Simulation Of Material Types In A Western Australian Iron Deposit, Jacqueline Ferreira
Theses: Doctorates and Masters
Geostatistical methods are currently used by mining companies to determine a resource model of the tonnage and head grade that may be obtained from a potential orebody, making it one of the first and most vital operational stages in any mining project. Currently long term mine planning is based on the estimated head grades model, which provides vital information on the quality of the ore. The risks associated with mining a particular ore may be reduced if geometallurgical information, such as material types, is incorporated into the operational flow model. Material type proportions are obtained from evaluated reverse circulation (RC) …
Geostatistical Methods For Estimating Iron, Silica And Alumina Grades Within The Hardcap Of The Section Seven Iron Deposit, Tom Price, Philip John Savory
Geostatistical Methods For Estimating Iron, Silica And Alumina Grades Within The Hardcap Of The Section Seven Iron Deposit, Tom Price, Philip John Savory
Theses: Doctorates and Masters
Many iron ore deposits have a weathered zone (Hardcap) near the surface which is highly variable in grades. Estimating the amount of ore grade material (HG) in this zone is difficult as a result of this variability. The Section Seven Deposit at Tom Price is largely mined out and has production data available in the form of grade blocks that were marked out during mining as HG and non- HG. Hardcap domains and a block model representing them were created and estimates were made from original exploration data using Ordinary Kriging, Global Change of Support, Indicator Kriging and Median Indicator …
Fractal Relationships And Spatial Distribution Of Ore Body Modelling, D. J. Kentwell
Fractal Relationships And Spatial Distribution Of Ore Body Modelling, D. J. Kentwell
Theses: Doctorates and Masters
The nature of spatial distributions of geological variables such as ore grades is of primary concern when modelling ore bodies and mineral resources. The aim of any mineral resource evaluation process is to determine the location, extent, volume and average grade of that resource by a trade off between maximum confidence in the results and minimum sampling effort. The principal aim of almost every geostatistical modelling process is to predict the spatial variation of one or more geological variables in order to estimate values of those variables at locations that have not been sampled. From the spatial analysis of these …