Publications
Kenex co-founder Greg Partington and other members of the Kenex team have kept up an incredible track record of publishing papers in conference proceedings and scientific journals since Kenex was founded. You can read them here.
Prospectivity analysis in action: The Auzex Resources Ltd. (AZX) story as applied to granite related mineral systems in Eastern Australia and New Zealand
Prospectivity of the Glen Innes region, new techniques, new mineral systems and new ideas
The QMAP dataset and an example of its application in modelling gold prospectivity in New Zealand
GIS Modelling of Gold Prospectivity in New Zealand – Geology and Exploration of New Zealand Mineral Deposits
Prospectivity Mapping Using GIS With Publicly Available Earth Science Data — A New Targeting Tool Being Successfully Used for Exploration in New Zealand
It is important that risks of developing mineral resources are known as accurately as possible. This process should start at the pre-discovery exploration stage and continue through feasibility to the development stage. Until recently, this type of analysis at the exploration stage has been carried out subjectively, leading to subjective judgements regarding the prospectivity of exploration targets. With GIS and regional scale digital databases now available, probabilistic models can now be generated. A program of digital data compilation has recently been undertaken in New Zealand to allow the use of more probabilistic data analysis techniques, moving away from the traditional expert-system methods. This is the first time that new technologies in IT, database management and Geographic Information Systems have been used outside of research projects. The combination of the new modelling techniques and a national scale digital geological database has successfully led to increased tenement acquisition and helped reduce cost and hence risk early in the exploration phase.
The analysis of the data used in the models proved to be as important as the results of the prospectivity modelling. Data quality was checked and geological models and exploration methodologies were tested using spatial correlation analysis. The analysis allowed the comparison of disparate datasets and associations not easily recognisable between these datasets. These analyses increased the confidence in the exploration models and techniques currently used to explore for gold mineralisation. Working with GIS datasets has highlighted the need for good quality data and data management. This has become a problem, as databases are presently available from a diverse number of groups, resulting in variable data quality and standards. No matter how sophisticated your analytical software if your data is poor the result will be of a similar quality. This applies to all aspects of the exploration industry from spatial mapping (GIS) to resource modelling.
New Perspectives on IOCG deposits, Mt Isa Eastern Succession, northwest Queensland
A current popular model for the formation of IOCG deposits in the Mt Isa Eastern Succession involves fluids derived from the late orogenic granites mixing with a second external fluid source forming Fe- (commonly magnetite-) rich alteration zones that contain vein stockwork, breccia, dissemination or replacement style mineralization. This is assumed to be commonly spatially and temporally associated with felsic pluton emplacement and cooling around 1540-1500 Ma. This contrasts with an alternative model in which the fluids are entirely intra-basinal and amagmatic in origin. Recent dating studies at Osborne have highlighted a potential syn-peak metamorphic timing to mineralization (based on 1595 Ma Re-Os age dates on molybdenite and a 1595 ± 6 Ma U-Pb age date on hydrothermal titanite), with no apparent proximal major intrusion. There is also a potential link between mineralization and widespread mafic intrusive activity, which spans the entire range of known mineralization ages.
In order to investigate this considerable range of potential geological controls on IOCG mineralization a prospectivity analysis was undertaken, aimed at evaluating the relative importance of a range of spatial variables including: host rock type, proximity to felsic granites or mafic intrusives, stream geochemistry (Cu and Au), structure, and geophysics (including magnetics, gravity and wavelet-processed potential field data or “worms”). A data driven approach was taken in view of the considerable uncertainty in genetic models for IOCG deposits.
Important data sources include (1) the northwest Queensland Mineral Province Report, (2) mineral occurrence data and newly available open file geochemistry (Terra Search) available from the Queensland Department of Mines and Energy, (3) regional magnetics and gravity digital datasets available from Geoscience Australia. MapInfo spatial data modeling software (MI-SDM) was utilized in this study. The initial study area comprised six 1:100,000 sheets covering Cloncurry and the area to the south. A conventional weights of evidence analysis was undertaken.
A comparison of Contrast and Student C values for all evidential layers indicates the host lithology as the most important criterion, followed by geochemistry (Cu and then Au), structure, geophysics, felsic and mafic igneous intrusions. The results enable a list of target criteria to be statistically ranked. A comparison of these results can be made with expert driven predictions. The study area is being expanded to include the entire Eastern Succession, including solid geology maps interpreted through cover.
An important outcome for ore genetic models is the recognition that intersections of N to NW structures with other faults have the strongest spatial association with IOCG deposits after host rock and geochemistry. This result implies that fluid pathways are much more important than fluid sources for controlling the distribution of IOCG deposits. This understanding can possibly explain some of the diversity in the range of IOCG deposit types and models. A common mineralizing process could generate deposits in a variety of host rocks depending on the fluid pathways. The dominance of the fluid pathways means that fluid sources cannot be clearly recognized from spatial associations of the deposits alone, and mineralizing fluids may be complex and heterogeneous in view of their possible interactions with a variety of wall rocks. A detailed understanding of fluid pathways and structures at all scales is the most important direction for future research. Mechanical modeling directed at understanding fluid flow in the Mt Isa Eastern Succession based on this structural knowledge will also be an important tool.
New Exploration in NZ Stimulated by the Crown Minerals Prospectivity Modeling Studies for Gold
The Epithermal and Mesothermal Gold Prospectivity modeling projects carried out by Crown Minerals provided explorers in New Zealand with a new compilation of historical exploration data combined with new geological information from the GNS QMap 1:250,000 scale mapping project. These data were used to produce predictive mineral potential maps for gold mineralisation in New Zealand.
The aim of these projects, to stimulate mineral exploration and investment in exploration, has been successful with eight new companies acquiring new tenement positions and committing significant exploration expenditure to exploring in New Zealand in the coming years. The projects were done at a national scale and consequently not all exploration data were compiled into the prospectivity models. Several of the new companies recognised the value of the prospectivity modeling work and committed exploration funds to continue the modeling process. They recognised a need to compile the remaining data and run the models again to allow detailed exploration targeting.
Detailed data compilations including digitising historic exploration stream sediment sample, rock chip sample, soil sample and drilling data have been completed. New models have been completed in Otago for mesothermal gold mineralisation and in the Coromandel and Northland for epithermal gold. The new models have been compared with the original regional scale models and used to target prospect scale exploration.
This work has allowed exploration models for epithermal and mesothermal mineralisation in New Zealand to be refined. More importantly this work has identified significant areas with potential to host gold mineralisation with little or no systematic geochemical data including soil sampling or drilling. Exploration work programs have been designed to acquire these missing data and exploration funds have now been committed to test the areas highlighted by the prospectivity modeling.
In summary, the Epithermal and Mesothermal Gold Prospectivity modeling work has successfully attracted new investment and ideas to the exploration scene in New Zealand. The projects had an estimated cost of NA$250,000 and will in the next two years, just through exploration expenditure, attract more than NZ$10 M in investment. If a mine is discovered the return on investment will be considerably greater.
New Exploration Concepts Applied to Neglected and Emerging Exploration Destinations – Project Development Using Computer Modelling in Australia, New Zealand and Africa
The new business models applied by major mining companies depend on the junior segment of the market to successfully carry out grassroots exploration. There is a significant problem with this approach due to most investment capital still being focussed on developing mining operations rather than conceptual exploration. However, current deposits are rapidly being depleted and there will be pressure for new discoveries in the coming years. In addition a significant amount of corporate knowledge has been lost with the recent globalisation of the minerals industry. Consequently the business of exploration, like the mining sector, has to develop new business models and use new innovated techniques to attract new investment to allow these discoveries to be made.
It is critical for exploration targeting that effective analysis of the available datasets is carried out with respect to each other and that only the relevant factors to the exploration model being used are extracted and combined into a single mineral potential map by using spatial data modelling techniques. These techniques have been successfully applied in New Zealand, Australia and Namibia to develop new conceptual exploration targets for Au and Cu deposits. Historic data were combined with new genetic models in a GIS to produce mineral potential maps at national and international scales highlighting those areas with the greatest probability of hosting mineralisation. These models were used to raise seed capital and attract investment develop these targets. All targets were unrecognised and acquired 100% at the cost of pegging. On-going fieldwork is proving the effectiveness of the modelling with new mineralisation being discovered in areas neglected by recent exploration. The potential to add significant value to these targets at the grassroots stage of exploration now is very high.
In summary, contrary to current beliefs, grassroots exploration can deliver significant added value to shareholders. The use of new spatial data modelling techniques allows the calculation of probability values that can identify those areas with the best chances of exploration success. This reduces costs, allows integration of data at international scales and brings forward any return on investment hence enhancing value to share holders.
Predictive Spatial Mapping From Gold To Grapes – A New Targeting Tool Being Successfully Used To Increase Investment In New Zealand
It is important that risks of developing and managing new businesses that use spatial information are known as accurately as possible. This process should start at the business planning stage and continue through feasibility to the development stage. Until recently, this type of analysis has been carried out using expert systems, leading to subjective judgements regarding the potential for success. With GIS and regional scale digital databases now available, probabilistic models can now be generated that allow the creation of predictive maps. For example, where is the best land for growing grapes or where are the best places to explore for gold in New Zealand?
A variety of new tools are available for use with computer aided geographic data management systems or Geographic Information Systems (GIS) for evaluating the distribution of spatial data in a statistical framework. These tools were initially developed for other uses such as pattern recognition by defence forces or medical diagnostic systems. Their use now in mineral exploration, energy and agriculture is a classic example of technology transfer and how the industries that depend on spatial data use new technologies in an innovative way.
A program of earth science digital data compilation has recently been undertaken in New Zealand to allow the use of more probabilistic data analysis techniques in mineral exploration, moving away from the traditional expert-system methods. This is the first time that new technologies in IT, database management and Geographic Information Systems have been used outside of research projects. The combination of the new modelling techniques and a national scale digital geological database has successfully led to increased investment in New Zealand.
Prospectivity models and GIS data for the exploration of epithermal gold mineralisation in New Zealand
Gold Prospectivity in New Zealand
Gold production in New Zealand has been significant since the mid 1800s, totalling 900,000 kg (29 M oz) to 2005. In addition, there is potential for an additional 1.23 t (41 M oz) of gold in known and undiscovered deposits. Most gold in New Zealand has originated from mesothermal or epithermal hydrothermal systems. Mesothermal gold occurs in low-medium metamorphic grade sedimentary and schist host rocks, typically within quartz veins or shear zones that were formed during deformation. These deposits are largely confined to Otago, West Coast and Marlborough. Epithermal gold occurs in volcanic terrains associated with near-surface active hydrothermal systems, either in quartz veins or disseminated through strongly altered zones. Major epithermal deposits have been found in Coromandel, and significant prospects are known in Northland and the Taupo Volcanic Zone. Major alluvial gold mining has occurred downstream of mesothermal gold deposits in Otago and the West Coast of the South Island.
Considerable data are available in digital formats to assist exploration for new gold deposits using Geographic Information Systems (GIS) software. These data include modern geological mapping, geochemistry, geophysics, mineral occurrences, topographic data and cultural data, as well as derivative themes such as geophysical interpretation, metamorphic grade, and structural trends. Geological mapping data include rock type, age, and stratigraphic association, as well as alteration zones, faults, folds, dikes, veins, and structural measurement data. The spatial relationships between these data and known gold deposits have been statistically quantified using the Weights of Evidence technique within GIS software. Stronger correlating data have been combined to create map models that quantify prospectivity. Many poorly explored areas of elevated prospectivity have been identified and reinforce the notion that New Zealand has considerable potential for future gold discoveries.