Presentations

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.

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.