Publications

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.

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.

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.

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.

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.

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.

A synthesis of new ideas from papers relating to the genesis of the Chatham Rise phosphorite deposit is presented. Since the Sonne and Valdivia Cruises in the late 1970's and early 80's, little has been contributed to further define, quantify or explain the Chatham Rise phosphorite deposit. There have been, however, many advances in geochemistry, paleo-geography, paleo-oceanography and paleo-climatology which have contributed to understanding the genesis of phosphorite deposits worldwide. Recent oil and gas exploration in the Great South and Canterbury Basins has resulted in increased seismic coverage which has yielded in new insights into the deformation sequence on New Zealand's continental shelf marginal out in to the adjoining deep water basins. It is proposed that the Miocene southern ocean, open shelf, replacement type phosphorite deposits (which include the Chatham Rise phosphorite) were formed in response to tectonic movements, the subsequent erosion of the ancient super continent of Gondwana and the migration of ocean fronts in response to changing ocean topography. It follows that a reconstruction of paleo-geography and paleo-oceanography adjacent to the Gondwana supercontinent will provide insight into the development of this large phosphorite resource in time and space.

Prospectivity modelling of orogenic gold mineralisation has been completed over New Zealand using the GIS based weights of evidence modelling technique. New Zealand orogenic gold deposits are restricted to the South Island and lower North Island and are divided into two groups (Paleozoic and Mesozoic) based on their age and host rock association. Modelling of Paleozoic and Mesozoic orogenic gold deposits was undertaken to illustrate the power of GIS modelling in regional and nationwide resource evaluation and how it can be used to quickly identify and rank in terms of prospectivity areas of land where new orogenic gold deposits might exist. The mineral deposit modelling was constrained by the mineral systems concept which defines those parts of a mineralisation system that are critical to the ore-forming process. Both of the New Zealand gold models identified possible sources of metals in the region, structures that could be used for fluid migration, mineral trap zones ideally suited to host a mineral deposit, and outflow zones that may indicate a subsurface deposit. The models were validated against known areas of historical gold mining such as the Reefton deposits (Paleozoic) and Macraes Flat (Mesozoic). Two prospectivity maps showing areas favourable for Paleozoic and Mesozoic orogenic gold formation were produced. The prospectivity modelling successfully identified known areas for both types of orogenic gold mineralisation as well as several new localities not currently covered by existing tenements. The spatial modelling techniques used here can be applied elsewhere to evaluate resource potential, whether for gold, or any other land based resource, and can help planners and land owners manage future developments and their assets more effectively. Both models supersede those undertaken in 2002 by Crown Minerals and GNS Science under the purview of Dr Greg Partington (now Director of Kenex Ltd.). The new models were re-run due to the addition of new data and new modelling techniques and appear to have much better definition and are better for targeting at a prospect scale.

Deep sea mineral exploration has progressed significantly in the past few years, however it remains a nascent industry when compared to terrestrial mineral exploration and mining and the offshore petroleum industry. Given that in general marine exploration is more costly than terrestrial exploration the ability to focus exploration efforts and funds should be highly desirable to those companies involved. Similarly, the detailed understanding and distribution of species or habitats in the marine environment in many areas which coincide with prospective minerals deposits is often limited. Predictive modelling could therefore be a valuable tool for aiding the management of both facets of a marine minerals project. Although a GIS is a perfect way of visualising data and producing maps from that data, GIS also allows you to create new data through using statistically based gridding techniques or predictive maps using spatial data modelling techniques. This modelling is where businesses can really add value, using their data more effectively rather than just passively using it to generate maps and figures. Basic statistical gridding allows you to predict unknown values from within a single layer such as topography, bathymetry, geochemistry, vegetation, hydrology, water temperature or climate data. However the real power of GIS is when spatial modelling is applied to combine several layers to predict outcomes based on probability such as mineral prospectivity, agricultural sustainability, geotechnical risk, environmental risk, and onservation planning. Adapting the technique for locating or ranking prospective seafloor massive sulphide or manganese nodule targets or for aiding baseline and detailed environmental planning are some of the possible applications for predictive modelling for the marine minerals industry.

The use of computers in mineral exploration in the last twenty years has dramatically changed the way we carry out exploration targeting (e.g. Bonham-Carter, 1994; Bonham-Carter et al., 1988; Mihalasky, 2001; Rattenbury and Partington, 2003; Partington and Sale 2004; Partington 2009; Carranza, 2009). 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 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. The aim of this paper is to provide a brief review of the techniques available to explorers using GIS and discuss the advantages and problems associated with using GIS techniques for exploration targeting.

Prospectivity modelling of orogenic gold mineralisation and ideal locations for wind farm development has been completed over southwest Wellington in New Zealand. This modelling used a combination of the GIS based weights of evidence and fuzzy logic techniques. These models were undertaken to illustrate the power of GIS modelling in regional resource evaluation and how they can be used to quickly identify areas of land which should be considered for wind farm development or those where new gold deposits might exist. The mineral deposit modelling was constrained by the minerals systems concept which defines those parts of a mineralisation system that are critical to the ore-forming process. The Wellington gold model identified possible sources of metals in the region, structures that could be used for fluid migration, mineral trap zones ideally suited to host a mineral deposit, and outflow zones that may indicate a subsurface deposit. Similarly, the Wellington wind farm model identified ideal sites to develop a wind farm using elements critical for successful turbine placement such as wind speed, terrain, sources of air turbulence, access and land use. The models were validated against known areas of historical gold mining such as at Terawhiti and the turbine locations of Meridian Energy's new West Wind development. The modelling clearly shows that the resource potential in southwest Wellington is greater for wind energy especially after consideration of potential archaeological and environmental restrictions which may rule out key areas of possible orogenic gold mineralisation identified by the model. The spatial modelling techniques used here can be applied elsewhere in New Zealand to evaluate resource potential, whether for wind, gold, or any other land based resource, and can help planners and land owners manage future developments and their assets more effectively.