Presentations

Logging of drillholes using wireline tools is an emerging methodology in mineral exploration that adds valuable data to exploration drilling. RC drilling is relatively cheap and quick, but it comes with the price of lost sample integrity and structural coherence. Wireline logging can cover this loss, by facilitating structural interpretations based on borewall imagery. Rock property data can also be recovered below the sampling resolution, such as optical televiewer (OTV) imagery, density, magnetic properties, natural gamma radiation and acoustic properties on cm and even mm scale. In the field, wireline logging will add just a few days to the drilling programme. A team of wireline technicians run their wireline down a recently completed drillhole using an assortment of tools depending on the requests of the client, at a cost amounting to only a few dollars per metre. The tools are oriented with magnetometers and accelerometers, enabling directional logging of geological features the drilling passed through. Combined with on-site logging of lithology and data from tools used in the field, wireline logging will enable exploration to take a significant step towards complete understanding of the prospect geology. In this paper we show downhole logging results from Tampia Hill, Western Australia, and how this work has been used to establish a structural framework and guide the creation of 3D geological and mineral potential models

The Southern New England Orogen (SNEO) in the northeastern part of New South Wales (NSW) is prospective for intrusion-related tin-tungsten, intrusion-related gold-bismuth-molybdenum-silver and orogenic goldantimony mineral systems. An initiative by the Geological Survey of NSW to conduct mineral potential modelling for these mineralisation styles in the SNEO has resulted in a comprehensive account of the mineral resource potential of the region. The Geological Survey of NSW has a successful strategy of providing high quality pre-competitive data that has been complemented and enhanced by the mineral potential mapping approach. Datasets including seamless basement geology, detailed attribution of faults, and igneous fertility that were created by the survey prior to modelling enabled an extensive number of variables be tested for relevance to each mineral system. The feedback from the data processing and spatial analysis allowed improvements to be made to the data and provided information on the relevance of the datasets to mineral exploration in the region. The outputs of the models are mineral potential maps that map the geological potential of the SNEO for each mineralisation style. The models will be used for land planning and advice purposes, technical resources for improved mineral system studies including global endowment estimations, and for promoting exploration in the SNEO through the generation of prospective targets. Due to the richness of the geological datasets in NSW it is likely that the technique, including the creation of high-quality datasets combined with mineral potential modelling, can be successfully applied to other mineralised regions within NSW.

Mineral prospectivity modelling using geographic information systems (GIS) has been used in New Zealand since 2002 both by the government, to promote mineral exploration in New Zealand, and industry, to inform project acquisition and increase the efficiency of exploration programmes. Over the last 15 years at least 38 mineral prospectivity models have been completed in New Zealand covering most of the hard rock mineralised regions onshore as well as nodular phosphate offshore on the Chatham Rise.

Analysis of highly prospective targets generated from the models already completed in New Zealand provides important information about the mineral potential of the country. Onshore, highly prospective targets over a range of commodities cover only 0.5 percent of the total land area of New Zealand, significantly narrowing the search area for new mineral deposits. 83 percent of the targets occur outside public conservation land, and 45 percent of the targets are unpermitted at the time of writing, suggesting there is potential for increased exploration investment and for new discoveries to be made. Prospectivity modelling has had a measureable positive impact on exploration activity and project development in New Zealand over the last 15 years. Future work should include incorporating new data into existing models, modelling new areas when data becomes available, improving existing mineral occurrence datasets, 3D prospectivity modelling, modelling of other commodities such as coal, alluvial gold and ironsand, infrastructure modelling, and exploration effectiveness analysis.

Prospectivity models in the last ten years have been predominantly used to establish the distribution of potentially mineralised ground over large areas, generally to guide initial exploration programmes in regional and mine camp settings. This approach can also be applied to the mine scale to guide resource estimation, development of reserves, mine and environmental planning, project development and to extend mine life through discovery of new resources. The Chatham Rise phosphate deposit is used as an example of where the results from prospectivity mapping can be used to guide mine planning, help with resource optimisation and provide constraints for project development. In this example the prospectivity results were combined with environmental modelling to help with environmental planning and the avoidance of sensitive areas, as well as guide mine planning. Another example compares a feasibility study to a prospectivity model over the same area. Prospectivity is an indicator of potential mineralisation presence, if not necessarily directly correlated to the actual concentration of resource present. Thus prospectivity mapping can be used to guide resource estimation and steer future efforts of resource definition and upgrading. An effective way this can be done is by using the prospectivity equivalent of the resource lower cut-off value to indicate where mineralisation may potentially be present outside the established regions. Confidence and unique conditions grids can then be used to establish what types of data needs to be gathered and where, to increase the reliability of the result.

A Canada National Infrastructure spatial analysis has been completed for the Prospectors and Developers Association of Canada (PDAC). The objective was to identify the Canadian districts where strategic investment in enhancing the infrastructure network could stimulate the development of new mines by reducing the overall capital costs of production. This was achieved by spatially analysing the relationship between infrastructure deficient regions and the location of significant, undeveloped mineral deposits. After compiling a comprehensive dataset of the existing infrastructure in Canada, the available information was classified and weighted based of their importance to mineral extraction. The most relevant datasets – including infrastructure, elevation and climatic data as well as cultural data such as distribution of population – have been combined using spatial modelling techniques to create a “remoteness” map of the country.
The “remoteness” map has then been compared with potential mining/advanced exploration projects in order to identify areas where strategic investment by provincial and federal government could stimulate new mineral development and therefore regional economic development. The completed spatial model has highlighted where investment would be most beneficial. Furthermore, a series of more specific cost-related maps have been produced for two categories of mineral commodities, precious minerals and base metals. The two categories differ in mining methods and quantities of minerals extracted; therefore requiring different types of infrastructure for operating. These additional models show the percentage increase of potential costs for building and maintaining a mining project related to the increase in remoteness. The results of the heat maps clearly identify regions where the enhancement of specific types of infrastructure could drastically decrease the overall costs of a precious mineral or base metal project and therefore encourage its development by making it economically feasible. The model results will allow the PDAC to work with appropriate government departments to prioritise the most prospective mining opportunities in infrastructure deficient areas and therefore efficiently propose a workflow of possible enhancements to local infrastructures to encourage the development of new mines in the identified areas.

Here we present a case study of prospectivity modelling over a region with both data-rich and data-poor areas, in the Kumasi Basin, Ghana. Whilst a reasonable amount of geological, geochemical and geophysical data is available over much of the Asankrangwa Gold Belt, host of the large Nkran and Esaase gold deposits (measured, indicated and inferred resources >10 Moz Au), data availability over much of the remainder of the Kumasi Basin is generally poor and of much lower resolution. As part of a comprehensive prospectivity and targeting study undertaken by Corporate Geoscience Group for Asanko Gold, Kenex completed GIS-based prospectivity modelling using the weights of evidence (WoE) technique to delineate high priority targets for orogenic gold. WoE modelling provides a data-driven tool that combines relevant datasets, identifies anomalous thresholds in predictors of mineralisation and produces a map of geological potential.

Statistical methods ensure that when the final geological potential grid is created, areas with missing data coverage are not significantly down-weighted relative to anomalous areas. Areas of poor data coverage in the Kumasi Basin required creative examination to allow successful modelling. For example, Kumasi Basin orogenic deposits are often associated with broad zones of silicic alteration. Consequently, many deposits resist weathering and form topographic ridges, allowing analysis using detailed open-file DEM data. Ridges were extracted and attributed with scale, relative strength and orientation, all of which were tested for spatial correlation with known orogenic deposits. Another example involves limited coverage of available geophysical surveys. Scanned TMI image data was reclassified into a GIS and certain colour bands selected as most accurately representing TMI. Properties such as magnetic slope, a common predictor for orogenic mineralisation, could then be calculated. Many targets identified by the model were located in areas with high data density. By using data intelligently we have also identified targets in data-poor areas.

Auzex Exploration Limited owns a number of exploration tenements over the historically tin rich Khartoum area near Herberton, north Queensland, Australia and Kenex Ltd has completed both 2-dimensional prospectivity modelling and a 3-dimenional geological interpretation over this region. The initial 2-dimensional prospectivity model of intrusion related tin mineralisation is limited by the 2D nature of the data used, and regions of known Sn mineralisation were not identified, particularly in the contact zones of shallow dipping highly fractionated tin granites. To rectify this, a 3D geological model was created using Leapfrog Geo modelling software, and 3D spatial data has been projected to the surface topography and incorporated into an updated 2D prospectivity model of the region using ArcGIS software. The 2D and 3D models utilise newly compiled digital data including historical exploration data; geological data compiled from detailed geological mapping of north Queensland, academic literature and company exploration mapping; recent geophysical data collect by Fathom Geophysics Australia Pty Ltd; ASTER data analysed for alteration; and historical exploration geochemical data including rock-chip, stream sediment and soil sampling. The weights of evidence modelling technique was used to determine spatial correlations between known deposits and predictive maps in 2D, created from the available data, that represent each component of the currently accepted minerals systems model for intrusion related tin mineralisation defined for this project. The final updated 2D prospectivity model partially resolves the limitations of the initial 2D model, successfully identifying many of the areas originally missed.

Prospectivity modelling has been completed over the Lachlan Fold Belt, New South Wales, Australia, using the GIS based weights of evidence modelling technique to target porphyry Cu-Au, associated skarn Cu-Au, orogenic Au and VMS Au mineralisation. The Lachlan Fold Belt is a 700 km wide belt of Paleozoic accretionary terrains, stretching from Queensland to Tasmania. Porphyry and skarn mineralisation was associated with Ordovician shoshonitic magmatism, which was followed by Silurian regional metamorphism and deposition of orogenic gold deposits. Contemporaneous VMS-style mineralisation resulted in deposits in intra-arc rift basins of the Macquarie Arc. In preparation for the prospectivity modelling, lithological and structural data, extensive geophysical surveys and stream, drill-hole and rock chip geochemistry were used to create predictive maps that represent various parts of the mineral systems being modelled. Included in the models are maps that identify possible sources of heat and mineralised fluids, structures used for fluid migration, mineral trap zones, and outflow zones that may indicate a subsurface deposit. Prospectivity maps have been created for each mineralisation style and new areas of each deposit type located. The models have also independently identified areas of proven mineralisation, including Cadia, Northparkes, Woodlawn and other large producing mines. The prospectivity maps were reclassified to generate targets by delineating highly prospective areas from each model. Targets were compared and overlap examined among the four models, before further analysis of high priority targets. Single targets or clusters of targets were individually assessed by incorporating information such as tenure, geology, geochemistry and geophysical signature. Economic and risk factors were assessed and the targets ranked and mapped according to high and low exploration risk. Following this analysis, targets of interest can be highlighted as potential projects for acquisition, or used to prioritise new exploration data collection.

The use of modern day 3D GIS software packages such as GOCAD, GeoModeller and Leapfrog Geo has dramatically changed the way exploration targeting can be carried out compared to the last twenty years of using 2D Geographic Information System (GIS) for exploration. This is especially true in the last five years in which computer and GPS technology has developed to the stage where it is possible to digitally locate, accurately store, visualise and manipulate geological data in 3D at the scale of a mineral system, which is usually much greater than mine scale where most of the current 3D work is focussed. Most GIS can store, manage and manipulate data in 2D, with some able to visualise information in 3D. However, there are a number of packages that allow full 3D GIS functionality, including querying and modelling, allowing geologists to start exploration targeting in a 3D system. Auzex Exploration Limited owns a number of exploration tenements over the historically tin rich Khartoum area located near Herberton in North Queensland, Australia, exploring for Tin-Tungsten mineralisation. A 3D geological interpretation was created over a 60 km by 60 km region in Khartoum using Leapfrog Geo to improve targeting for tin systems adjacent and above buried granites and shallow dipping granite contacts, followed by 3D targeting using a Multi-Class index Overlay workflow of GoCAD Mining. The ranking of the 3D maps were based on a 2D prospectivity mapping exercise using the weights of evidence technique. By modelling geology and targeting in 3D, complex subsurface relationships and the correct vertical extents can be constrained. This will be invaluable for defining potential drill-hole targets.