The estimated economic value of a stratiform mineral deposit is often very sensitive to the modelling of thickness in a conformable sequence of beds. A coregionalisation model of thickness expresses the assumed underlying spatial relationships of bedding thickness on a regional scale. Joint simulation of thickness directly models the cross-correlation of bedding thickness in such a model. Many of the current techniques of joint simulation are limited in the number of variables that can be simulated due to the multiplicative increase in processing times, based on the number of variables and number of samples simulated. To minimise processing times some methods make use of simplifying assumptions on the coregionalisation model. For example the Markov model, in which the dependence of one variable on the other is limited to the collocated data, would be unlikely to apply to the thickness of conformable bedding in a stratiform deposit. Transforming the thickness variables to remove correlation, simulating, and then back transforming to original data space offered a possible solution. The Minimum/Maximum Autocorrelation Factor (MAF) technique was chosen as one most likely to successfully decorrelate numbers of thickness variables, if the assumptions regarding a two-structure linear coregionalisation model were reasonably satisfied by the sampled data. The assumptions are that a simple intrinsic model of coregionalisation can represent both a lower correlation (‘noise’) component and a higher correlation (‘signal’) component of the modelled data. This implies that the final coregionalisation model (noise plus signal) is made up of linear combinations of a single basic structure at different spatial scales. In a number of previous applications, this had not proved to be a particularly restrictive requirement of the model. The decorrelated variables can be independently simulated, and back transformed twice; firstly using a MAF back-transformation to obtain correlated Gaussian variables, and finally to original data space. The McArthur River silver/lead/zinc stratiform deposit in the Northern Territory of Australia was chosen as the case study because it had many of the characteristics needed to test and evaluate the MAF technique in a typical stratiform deposit. The orebody model contained seventeen (17) mineralised units forming a conformable sequence which had varying thickness and degrees of mineralisation, and which had good continuity across the deposit. Cross-correlation between the thicknesses of the seventeen stratigraphic units was significant. The deposit was heavily folded in certain areas and true thickness of the bedding was calculated from drillhole log data, and used for the simulation studies. A simple unfolding algorithm was utilised to effectively flatten the deposit to allow the application of 2-D simulation techniques. Drillhole intersections often did not contain the full stratigraphic sequence of beds due to a series of normal faults criss-crossing the deposit. Therefore, incomplete data in the drillhole would need to be removed from the data set, or the number of beds in the joint simulation would need to be reduced, to utilise the MAF technique. A method was developed and validated for the generation of missing thicknesses at a sample point which removed the requirement to delete real incomplete sub-sets of the data when utilising MAF. Sequential Gaussian Simulation (SGS) was used to simulate the MAF decorrelated variables under the assumption that the multi-Gaussian assumptions held. Bedding surface simulations were generated by the addition of true thickness perpendicular to a basal reference surface. The 2-D joint simulations of thicknesses and surfaces were considered successful within a domain of the deposit where drillholes were approximately perpendicular to bedding after unfolding. The univariate, bivariate and spatial statistics of the original thickness data were reproduced accurately in the joint simulation model, including the crossvariograms of original thickness; especially compared to those obtained using independent simulation of thickness. It was concluded that the techniques could be successfully applied to other stratiform deposits if the recommended validation steps were carried out. No further difficulties should be encountered in applying the method to 2-D joint simulation of grades in a stratiform deposit. The full 3-D joint simulation of variables in any deposit using MAF would be assisted by the technique to generate missing variables at a point.

The estimated economic value of a stratiform mineral deposit is often very sensitive to the modelling of thickness in a conformable sequence of beds. A coregionalisation model of thickness expresses the assumed underlying spatial relationships of bedding thickness on a regional scale. Joint simulation of thickness directly models the cross-correlation of bedding thickness in such a model. Many of the current techniques of joint simulation are limited in the number of variables that can be simulated due to the multiplicative increase in processing times, based on the number of variables and number of samples simulated. To minimise processing times some methods make use of simplifying assumptions on the coregionalisation model. For example the Markov model, in which the dependence of one variable on the other is limited to the collocated data, would be unlikely to apply to the thickness of conformable bedding in a stratiform deposit. Transforming the thickness variables to remove correlation, simulating, and then back transforming to original data space offered a possible solution. The Minimum/Maximum Autocorrelation Factor (MAF) technique was chosen as one most likely to successfully decorrelate numbers of thickness variables, if the assumptions regarding a two-structure linear coregionalisation model were reasonably satisfied by the sampled data. The assumptions are that a simple intrinsic model of coregionalisation can represent both a lower correlation (‘noise’) component and a higher correlation (‘signal’) component of the modelled data. This implies that the final coregionalisation model (noise plus signal) is made up of linear combinations of a single basic structure at different spatial scales. In a number of previous applications, this had not proved to be a particularly restrictive requirement of the model. The decorrelated variables can be independently simulated, and back transformed twice; firstly using a MAF back-transformation to obtain correlated Gaussian variables, and finally to original data space. The McArthur River silver/lead/zinc stratiform deposit in the Northern Territory of Australia was chosen as the case study because it had many of the characteristics needed to test and evaluate the MAF technique in a typical stratiform deposit. The orebody model contained seventeen (17) mineralised units forming a conformable sequence which had varying thickness and degrees of mineralisation, and which had good continuity across the deposit. Cross-correlation between the thicknesses of the seventeen stratigraphic units was significant. The deposit was heavily folded in certain areas and true thickness of the bedding was calculated from drillhole log data, and used for the simulation studies. A simple unfolding algorithm was utilised to effectively flatten the deposit to allow the application of 2-D simulation techniques. Drillhole intersections often did not contain the full stratigraphic sequence of beds due to a series of normal faults criss-crossing the deposit. Therefore, incomplete data in the drillhole would need to be removed from the data set, or the number of beds in the joint simulation would need to be reduced, to utilise the MAF technique. A method was developed and validated for the generation of missing thicknesses at a sample point which removed the requirement to delete real incomplete sub-sets of the data when utilising MAF. Sequential Gaussian Simulation (SGS) was used to simulate the MAF decorrelated variables under the assumption that the multi-Gaussian assumptions held. Bedding surface simulations were generated by the addition of true thickness perpendicular to a basal reference surface. The 2-D joint simulations of thicknesses and surfaces were considered successful within a domain of the deposit where drillholes were approximately perpendicular to bedding after unfolding. The univariate, bivariate and spatial statistics of the original thickness data were reproduced accurately in the joint simulation model, including the crossvariograms of original thickness; especially compared to those obtained using independent simulation of thickness. It was concluded that the techniques could be successfully applied to other stratiform deposits if the recommended validation steps were carried out. No further difficulties should be encountered in applying the method to 2-D joint simulation of grades in a stratiform deposit. The full 3-D joint simulation of variables in any deposit using MAF would be assisted by the technique to generate missing variables at a point.

The estimated economic value of a stratiform mineral deposit is often very sensitive to the modelling of thickness in a conformable sequence of beds. A coregionalisation model of thickness expresses the assumed underlying spatial relationships of bedding thickness on a regional scale. Joint simulation of thickness directly models the cross-correlation of bedding thickness in such a model. Many of the current techniques of joint simulation are limited in the number of variables that can be simulated due to the multiplicative increase in processing times, based on the number of variables and number of samples simulated. To minimise processing times some methods make use of simplifying assumptions on the coregionalisation model. For example the Markov model, in which the dependence of one variable on the other is limited to the collocated data, would be unlikely to apply to the thickness of conformable bedding in a stratiform deposit. Transforming the thickness variables to remove correlation, simulating, and then back transforming to original data space offered a possible solution. The Minimum/Maximum Autocorrelation Factor (MAF) technique was chosen as one most likely to successfully decorrelate numbers of thickness variables, if the assumptions regarding a two-structure linear coregionalisation model were reasonably satisfied by the sampled data. The assumptions are that a simple intrinsic model of coregionalisation can represent both a lower correlation (‘noise’) component and a higher correlation (‘signal’) component of the modelled data. This implies that the final coregionalisation model (noise plus signal) is made up of linear combinations of a single basic structure at different spatial scales. In a number of previous applications, this had not proved to be a particularly restrictive requirement of the model. The decorrelated variables can be independently simulated, and back transformed twice; firstly using a MAF back-transformation to obtain correlated Gaussian variables, and finally to original data space. The McArthur River silver/lead/zinc stratiform deposit in the Northern Territory of Australia was chosen as the case study because it had many of the characteristics needed to test and evaluate the MAF technique in a typical stratiform deposit. The orebody model contained seventeen (17) mineralised units forming a conformable sequence which had varying thickness and degrees of mineralisation, and which had good continuity across the deposit. Cross-correlation between the thicknesses of the seventeen stratigraphic units was significant. The deposit was heavily folded in certain areas and true thickness of the bedding was calculated from drillhole log data, and used for the simulation studies. A simple unfolding algorithm was utilised to effectively flatten the deposit to allow the application of 2-D simulation techniques. Drillhole intersections often did not contain the full stratigraphic sequence of beds due to a series of normal faults criss-crossing the deposit. Therefore, incomplete data in the drillhole would need to be removed from the data set, or the number of beds in the joint simulation would need to be reduced, to utilise the MAF technique. A method was developed and validated for the generation of missing thicknesses at a sample point which removed the requirement to delete real incomplete sub-sets of the data when utilising MAF. Sequential Gaussian Simulation (SGS) was used to simulate the MAF decorrelated variables under the assumption that the multi-Gaussian assumptions held. Bedding surface simulations were generated by the addition of true thickness perpendicular to a basal reference surface. The 2-D joint simulations of thicknesses and surfaces were considered successful within a domain of the deposit where drillholes were approximately perpendicular to bedding after unfolding. The univariate, bivariate and spatial statistics of the original thickness data were reproduced accurately in the joint simulation model, including the crossvariograms of original thickness; especially compared to those obtained using independent simulation of thickness. It was concluded that the techniques could be successfully applied to other stratiform deposits if the recommended validation steps were carried out. No further difficulties should be encountered in applying the method to 2-D joint simulation of grades in a stratiform deposit. The full 3-D joint simulation of variables in any deposit using MAF would be assisted by the technique to generate missing variables at a point.

Sedimentary deposits are important aquifers in many parts of the world and in order to explore, develop and manage these aquifers, it is necessary to determine the relationship between the hydrogeologic properties and sedimentary facies (aquifer characterization). Within a sedimentary hydrogeologic system, the environment of deposition and the resulting distribution of grain sizes, texture, and facies associations within different individual aquifer bodies influence variations in hydraulic properties. Successful prediction of the quality of the aquifer is dependent on the accurate mapping of both lithologic units and hydrogeologic parameters. In this project, the influence of petrophysical characteristics of the sedimentary rocks to the quality of the aquifer is investigated with a view to finding a correlation between these characteristics, the type and nature of sedimentary rocks present and their hydrogeologic properties. Investigation methods involved the use of geophysical wireline log data, lithological core logging, thin section microscopy and X-Ray Diffraction analysis. All this was done to characterize the sedimentary rocks in terms of composition, grain size and diagenesis. Porosity tests were also performed on the samples collected while permeability data was collected from the Department of Natural Resources and Mines (DNR & M), Australia. The basins of interest for this project are the Bowen Basin in Australia and the Kalahari Basin in Botswana. The two basins are similar, though structurally different. The basins are similar in the sense that they have got similarity in their rock sequence. All the work done on the Bowen Basin and the results obtained are extrapolated to the similar Kalahari Basin. The units of the Bowen Basin are underlain by the Late Carboniferous to Early Permian Camboon Volcanics. The Permian units include the Buffel, Barfield, Flat Top, and Gyranda Formations and the Baralaba Coal Measures. The Triassic units are the Rewan Group, Clematis Sandstone and Moolayember Formation. Within the Bowen Basin the Permian units are generally argillaceous and therefore have generally low porosities and permeabilities and also give low resistivity (RES) base lines and high gamma ray (GR) baselines. However where fractured, the units yield some water from the shale. Boreholes drawing water from the Barfield, Flat Top and Gyranda Formations tap the fractured shales. The Triassic aquifers present a different picture. The best aquifers with high porosities and permeabilities are of the Triassic age and their distribution is influenced by their proximity to the source area. Sedimentary rocks of the Triassic age in the Bowen Basin become more argillaceous at more distal positions from the source area. The Rewan Group in particular shows this trend and hence better aquifers within the Rewan are those close to the source area. The Kalahari Basin Karoo stratigraphy commences with the Late Carboniferous to Early Permian glaciogenic sedimentary rocks of the Dwyka Group. The Dwyka Group is overlain by the argillaceous Permian to Early Triassic sedimentary rocks of The Ecca Group and the Beaufort Group. Overlying the Beaufort Group is the Lebung Group (lower Mosolotsane Formation-dominantly mudstone and siltstone sequence and upper Ntane Sandstone Formation- aeolian sandstone). Basaltic lavas of the stormberg Lava Group cap the Karoo stratigraphy. Few groundwater studies in the Karoo of the Kalahari Basin have shown that the Ecca Group does not posses good aquifer characteristics because of its argillaceous nature. However, thin arenaceous interbeds within the Ecca Group have yielded some groundwater. Non-measurable quantities of groundwater have been recorded from boreholes sunk in the Beaufort Group. Few boreholes penetrating the Mosolotsane Formation yielded very little groundwater whereas Ntane Sandstone have yielded a fair amount of groundwater. Groundwater yield from the Stormberg Lava Group is related to the presence of fractures.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.