Presentations
Kenex staff regularly present their work at conferences and workshops in New Zealand, Australia and Internationally. Have a look at our latest video presentations or scroll back through our archives below.
New Zealand Gold Potential – Using Mineral Prospectivity Modelling to Evaluate Gold-Bearing Mineral Systems in an Underexplored Country
New Zealand has an established history of gold production beginning with the gold rushes of the 19th century in the Coromandel, Nelson/Marlborough, West Coast and Otago regions. Despite this, the number of significant modern hard rock gold operations has been limited in recent years due to a lack of sustained exploration capital and not limited geological prospectivity. The New Zealand Government is actively encouraging explorers to invest in New Zealand through a series of targeted promotional visits, more importantly through the acquisition of precompetitive regional geophysical data. Data collection has been completed over the prospective Northland epithermal district and a large portion of the South Island’s west coast that is prospective for both orogenic gold and intrusive related gold. Analysis of new data has been an important component in aiding the generation of exploration targets from prospectivity modelling. Determining the prospectivity of an area involves reviewing all the available data and analysing it with respect to the most up-to-date mineral system model for the mineralisation style of interest. Using the weights of evidence modelling approach, the most prospective areas for epithermal gold-silver, orogenic gold and intrusion-related gold have been identified. The key exploration parameters relevant to each mineral system are first represented spatially and then statistically combined into a single prospectivity map. New potentially economic deposits could be found by focusing exploration on targets identified from these models. The prospectivity modelling approach can greatly reduce the risk involved in mineral exploration.
New Insights into the Origin and Distribution of Phosphate Deposits on the Chatham Rise
Geochemistry in prospectivity modelling: investigating gold mineralisation in the Taupo Volcanic Zone, New Zealand
From exploration to extraction: The consequences of resource morphology for mining operation on the Chatham Rise
Substantial consideration has been given to the implications that the morphology of the Chatham Rise deposit will have on mining operations. The glacio-tectonic processes involved in the distribution of nodules on the rise have in several areas been quite significant. The recent cruises by Chatham Rock Phosphate Limited (CRPL) have collected data which has affirmed the assumptions previously made and catered for in historic resource estimations. The deformation and displacement of the phosphorite during glacial periods and the redistribution of the mobile sand during interglacial periods is interpreted to have produced a highly variable pattern of phosphorite concentration (kg phosphorite/m2) and coverage (% phosphorite/sample weight). The phosphorite resource probably has a significant spatial variability at a scale of tens of metres. Results of recent surveys show phosphorite-rich patches alternating with phosphorite-poor areas at distances of less than 20 m. The high spatial variability of the deposit has had a bearing on how historical information for the project has been regarded and integrated with the recent exploration approach and data collection process. This coupled with the proposed extraction tool has influenced the size, nature, extent and siting of the proposed mining blocks.
3D prospectivity modelling – a new era in exploration targeting
The use of computers in the mineral industry has dramatically changed the way exploration targeting is carried out over the last twenty years. This is especially true in the last five years where computer and GPS technology has developed to the stage where it is possible to digitally locate, accurately store, visualise and manipulate geological data in three dimensions (3D) at the scale of a mineral system. These tasks are commonly carried out using a Geographic Information System (GIS), which has become as an important tool to a geologist as his hammer. Most GIS store, manage and manipulate data in two dimensions (2D), with some having the ability to visualise information in 3D. However, there are now a number of packages that allow full GIS functionality including querying and modelling in 3Dgiving geologists a tool to carry out exploration targeting in 3D. A regional scale weights of evidence 2D prospectivity model was developed for the Taupo Volcanic Zone in New Zealand to assess the potential for epithermal Au mineralisation. A number of prospective areas have been identified including the known Ohakuri hydrothermal deposit. While this model has been successful at identifying mineralised areas the 2D data that is used gives little understanding of what is happening below the surface. Because geology does not just operate in 2D, trying to visualise 3D geometries in 2D can be challenging in exploration targeting. The development of 3D GIS such as GoCad and Geomodeller now give us the tools and techniques to use fuzzy logic and weights of evidence techniques for targeting in mineral exploration in 3D. A prospectivity modelling exercise using the weights of evidence modelling technique (developed by Bonham-Carter of the Canadian Geological Survey), was completed over the Ohakuri epithermal gold deposit in both 2D and 3D.
Comprehensive prospectivity analysis of the Lachlan fold belt in NSW using the mineral systems approach
Prospectivity modelling has been completed over the Lachlan Fold Belt (LFB) in NSW Australia, using the GIS based weights of evidence modelling technique and porphyry Cu Au, skarn, orogenic Au and VMS Cu mineral system models. The LFB is a 700 km wide belt of deformed Paleozoic marine sedimentary and mafic volcanic rock stretching from Queensland to Tasmania. It dominates eastern NSW and hosts several large producing gold deposits including Cadia and Northparkes. Lithological and structural data from the NSW Geological Survey was combined with stream, drill-hole and rock chip geochemistry and extensive geophysical surveys. The data was used to create predictive maps for each of the four models, constrained by the mineral systems concept which defines the parts of the mineralisation system that are critical to the ore-forming process. Included in all models are layers 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. Training points were chosen from known areas of mining or exploration specific to the relevant mineralisation style (Fig. 1). Prospectivity maps have been created for each mineralisation style giving a comprehensive understanding of the gold and copper mineralisation over the LFB in NSW. Known areas of each deposit type have been identified along with new areas that have potential for porphyry, skarn, orogenic or VMS deposits. These prospectivity maps and exploration GIS create a valuable tool to accelerate exploration and identify new opportunities in NSW’s most productive goldfield.
Taking SDM from the 2D to 3D world
The use of computers in mineral exploration in the last twenty years has changed the way we carry out exploration targeting dramatically. This is especially true in the last five years where 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. These tasks are commonly carried out using a Geographic Information System, which has become as an important tool to a geologist as his hammer. Most GIS store, manage and manipulate data in 2D, with some having the ability to visualise information in 3D. However, there are now a number of packages that allow full GIS functionality including querying and modelling in 3D. This now gives geologists a tool to carry out exploration targeting in 3D. Exploration targeting using Fuzzy Logic and Weights of Evidence techniques is becoming more commonplace in the industry and is being used particularly by government organisations to manage their resources. However, one of the weaknesses of the work to date is that these studies are carried out in 2D, with an approximation of 3D provided by geophysical and drilling data projected to a 2D plane. Geology does not operate in the 2D world and many geological problems relate to 3D geometries and this is particularly true for exploration targeting. The development of 3D GIS such as GoCad and Geomodeller now give us the tools and techniques to use Fuzzy Logic and Weights of Evidence techniques for targeting in mineral exploration in 3D. However, several issues remain to be resolved before these tools become effective and used routinely by the industry. The most important issue is that of training, with graduate geologists not receiving appropriate training in the use of GIS to solve geological problems, particularly related to exploration. The other important problem relates to data availability and data quality, which was an issue for 2D models, but is even more of an issue for work in 3D. Consequently, we are now at the stage where computing power and modelling techniques have overtaken the availability of high quality 3D geological data and trained geologists to maximise their use.
Exploration targeting from prospectivity modelling in the Lachlan fold belt, NSW
Employing an effective exploration targeting method is important when looking for economic concentrations of minerals in a particular country or region. Methods for exploration targeting include geophysical or geochemical anomalies and intuitive decision making. Alternatively, prospectivity modelling allows for a complete picture of the economic potential of a country or region if all relevant mineralisation styles are considered. Prospectivity models can be reclassified to define high priority targets that can be used to focus an existing exploration programme or to pick up new ground. We present an example of this exploration targeting approach using the Lachlan Fold Belt in NSW. Prospectivity models have been completed over the Lachlan Fold Belt for porphyry Cu Au, skarn, VMS Cu, and orogenic Au mineralisation styles. The models use the mineral systems approach to determine key predictive variables that define each mineralisation style using the available data. Targets that delineate highly prospective areas have been defined from each model. The targets either represent existing prospects or mines or areas where new mineralised systems could be discovered with further exploration and development. A number of tools can be used to analyse the targets. Economic and risk factors can be assessed and the targets can be sorted and mapped according to positive and negative exploration risk. Single targets or clusters of targets can be individually assessed providing information such as tenure, geology, geochemistry and magnetic signature. Following this analysis, targets of interest can be highlighted as potential projects for acquisition, or an appropriate exploration programme prepared.
Predicting the wind: Wind Farm prospecting using GIS
Developing Wind and Mineral Exploration Models using GIS for Project Development in Argentina
Kenex in partnership with Emprendimientos Energeticos y Desarrollos S.A (EEDSA) have recently completed a number of strategic business development projects in Argentina to develop wind energy and mineral resources. A partnership was developed with EEDSA in 2010 to explore for and develop wind energy opportunities in Argentina using Kenex’s recently developed wind prospecting techniques. These techniques have been successfully used to map wind farm locations in New Zealand and rank each site according to its economic potential. After a year of data collection and modelling, which has successfully mapped potential wind farm sites in a number of provinces in Argentina, the partnership decided to expand into mineral exploration. Spatial Data Modelling techniques were used to map potential mineral exploration opportunities for gold, copper, base-metals, tin, tungsten and uranium at a regional scale in Argentina and Chile. Regional scale prospectivity models were developed for Argentina and Chile to identify prospective areas for a variety of metals and mineralisation styles. Fuzzy logic techniques were used to develop the wind prospectivity maps and Weights of Evidence modelling techniques were used to develop the mineral potential maps in Argentina and Chile. The models have successfully identified areas that are prospective for wind energy and gold, copper and silver and have also identified areas where new mineralised systems could be discovered with further exploration and development. Economic and risk factors will be included and target areas can then be sorted and mapped according to positive and negative exploration risk. A similar analysis will be carried out for the wind targets. This will lead to the development of an Argentina wide database of prioritised metal and wind energy targets for exploration and development. The prioritised targets will then be combined with social and logistical factors to highlight projects for acquisition. The regional targeting work for both wind energy and mineral resources has now been completed and the partnership is in the process of developing a number of business.
Using predictive modelling to aid planning in the mineral exploration and mining sector, a case study using the Powelliphanta Land Snail
The weights of evidence spatial data modelling technique has been used to create a predictive map that identifies possible locations of alpine Powelliphanta land snails in the South Island of New Zealand. This technique is commonly used in the mineral exploration industry to identify locations most likely to host mineralisation and is becoming more widely used in environmental fields as data becomes available in a digital form. Climatic, soil, topographic, and botanical data used in the model came from various organisations including NIWA and Landcare Research. The model uses the known locations of five Powelliphanta “taxa” that occur in high elevation, isolated alpine habitats to find other areas that may support similar Powelliphanta populations. The weights of evidence technique allows data to be assessed and weighted according to how great its influence is in relation to the current known locations of Powelliphanta snails. The most important variables identified from this spatial analysis were combined to produce a map showing the most likely places for Powelliphanta snails to be found. The resulting predictive model for snail habitat locations shows that mountain ranges in north-western part of the South Island have the highest probability of finding Powelliphanta land snails. It also shows that high altitude, low temperature and high rainfall condition are favoured by the snails. The model has been validated in the field and some areas not covered by the training points that were classified as highly probable by the model have recorded sightings of snails. Knowing the locations of species that will be affected, as well as knowing the potential relocation sites could help facilitate decision making during mineral exploration and mine planning.
Energy in the wind: integrating the transmission network for a better approach to wind farm prospecting
The availability of suitable transmission grid connectivity is quickly becoming a key factor for developing new wind farms globally. While wind speed remains the most important requirement for a successful wind farm along with other key parameters such as suitable terrain, current land use and distance from populated areas which are essential for site selection; a good grid connection is a significant factor in determining the economics pre-construction and future profitability of the wind farm. In the past three years, Kenex and Aurecon have developed advanced spatial modelling techniques that combine wind speed and direction, advanced terrain analysis, land use and social acceptability parameters to define the extent of potential wind farms at regional and country-wide scales. Our modelling has been successfully used by New Zealand developers to quickly and effectively target new wind farm opportunities and define the potential extent of an individual wind farm. Kenex and Aurecon have now refined the spatial modelling by integrating grid connection variables so as to identify not only the most suitable sites for a wind farm, but also which sites may potentially have the best available connections to the grid, and subsequently more preferable project economics.