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Recoverable Resources Calculation Using Non-Linear Methods: A Comparative Study, Matthew Cobb
Recoverable Resources Calculation Using Non-Linear Methods: A Comparative Study, Matthew Cobb
Theses: Doctorates and Masters
The prediction of recoverable resources at an operating manganese mine is currently undertaken using univariate ordinary kriging of the target variable manganese, and 5 deleterious variables. Input data densities at the time of this calculation are considerably lower than at the time of final selection (grade control), and the potential for unnacceptable conditional bias to be introduced through the use of linear geostatistical methods when determining grade estimates over a small support has led to assessment of the potential benefit of employing the local change of support methods Localised Uniform Conditioning (LUC) and Conditional Simulation (CS). Allowances for the operating …
Compositions, Logratios And Geostatistics: An Application To Iron Ore, Clint Ward
Compositions, Logratios And Geostatistics: An Application To Iron Ore, Clint Ward
Theses: Doctorates and Masters
Common implementations of geostatistical methods, kriging and simulation, ignore the fact that geochemical data are usually reported in weight percent, sum to a constant, and are thus compositional in nature. The constant sum implies that rescaling has occurred and this can be shown to produce spurious correlations. Compositional geostatistics is an approach developed to ensure that the constant sum constraint is respected in estimation while removing dependencies on the spurious correlations. This study tests the applicability of this method against the commonly implemented ordinary cokriging method. The sample data are production blast cuttings analyses drawn from a producing iron ore …
Variograms And Kriging In The Analysis Of Spatial Data, Suresh Tripathi
Variograms And Kriging In The Analysis Of Spatial Data, Suresh Tripathi
Theses: Doctorates and Masters
This research is in the area of geostatistics and consists essentially of two parts. The first is an investigation of the variogram and cross variogram and the associated kriging and cokriging methods of spatial prediction and the second is an application of these in the analysis of two (original) data sets. In the first part (chapter 1 to chapter 5), the focus is on summarising and illustrating the various techniques of Exploratory Data Analysis (EDA) and some methods used to estimate and model the experimental variograms and cross variograms for a given data set, together with some of the geostatistical …