S.J. Gardoll

Orogenic gold and geologic time: A global synthesis

AbstractOrogenic gold deposits have formed over more than 3 billion years of Earth’s history, episodically during the MiddleArchean to younger Precambrian, and continuously throughout the Phanerozoic. This class of gold deposit is characteristi-cally associated with deformed and metamorphosed mid-crustal blocks, particularly in spatial association with major crustalstructures. A consistent spatial and temporal association with granitoids of a variety of compositions indicates that melts andfluids were both inherent products of thermal events during orogenesis. Including placer accumulations, which arecommonly intimately associated with this mineral deposit type, recognized production and resources from economicPhanerozoic orogenic-gold deposits are estimated at just over one billion ounces gold. Exclusive of the still-controversialWitwatersrand ores, known Precambrian gold concentrations are about half this amount.The recent increased applicability of global paleo-reconstructions, coupled with improved geochronology from most ofthe world’s major gold camps, allows for an improved understanding of the distribution pattern of orogenic gold in spaceand time. There are few well-preserved blocks of Middle Archean mid-crustal rocks with gold-favorable, high-strain shearzones in generally low-strain belts. The exception is the Kaapvaal craton where a number of orogenic gold deposits arescattered through the Barberton greenstone belt. A few )3.0 Ga crustal fragments also contain smaller gold systems in theUkrainian shield and the Pilbara craton. If the placer model is correct for the Witwatersrand goldfields, then it is possiblethat an exceptional Middle Archean orogenic-gold lode-system existed in the Kaapvaal craton at one time. The latter half ofthe Late Archean ca. 2.8–2.55 Ga was an extremely favorable period for orogenic gold-vein formation, and resulting oresŽ.preserved in mid-crustal rocks contain a high percentage of the world’s gold resource. Preserved major goldfields occur ingreenstone belts of the Yilgarn craton e.g., Kalgoorlie , Superior province e.g., Timmins , Dharwar craton e.g., Kolar ,Ž. Ž . Ž.Zimbabwe craton e.g., Kwekwe , Slave craton e.g., Yellowknife , Sao Francisco craton e.g., Quadrilatero Ferrifero , andŽ. Ž . Ž .Tanzania craton e.g., Bulyanhulu , with smaller deposits exposed in the Wyoming craton and Fennoscandian shield. SomeŽ.workers also suggest that the Witwatersrand ores were formed from hydrothermal fluids in this period.The third global episode of orogenic gold-vein formation occurred at ca. 2.1–1.8 Ga, as supracrustal sedimentary rocksequences became as significant hosts as greenstones for the gold ores. Greenstone–sedimentary rock sequences nowexposed in interior Australia, northwestern Africarnorthern South America, Svecofennia, and the Canadian shield were the

Late-kinematic timing of orogenic gold deposits and significance for computer-based exploration techniques with emphasis on the Yilgarn Block, Western Australia

Abstract Orogenic gold deposits are a widespread coherent group of epigenetic ore deposits that are sited in accretionary or collisional orogens. They formed over a large crustal-depth range from deep-seated low-salinity H2O–CO2±CH4±N2 ore fluids and with Au transported as thio-complexes. Regional structures provide the main control on deposit distribution. In many terranes, first-order faults or shear zones appear to have controlled regional fluid flow, with greatest ore-fluid fluxes in, and adjacent to, lower-order faults, shear zones and/or large folds. Highly competent and/or chemically reactive rocks are the most common hosts to the larger deposits. Focusing of supralithostatic ore fluids into dilatant zones appears to occur late during the evolutionary history of the host terranes, normally within D3 or D4 in a D1–D4 deformation sequence. Reactivation of suitably oriented pre-existing structures during a change in far-field stress orientation is a factor common to many deposits, and repeated reactivation may account for multiple mineralization episodes in some larger deposits. Absolute robust ages of mineralization support their late-kinematic timing, and, in general, suggest that deposits formed diachronously towards the end of the 100 to 200 m.y. long evolutionary history of hosting orogens. For example, in the Yilgarn Block, a region specifically emphasised in this study, orogenic gold deposits formed in the time interval between 40 and 90 m.y., with most about 60 to 70 m.y., after the youngest widespread basic-ultrabasic volcanism and towards the end of felsic magmatism. The late timing of orogenic gold deposits is pivotal to geologically-based exploration methodologies. This is because the present structural geometries of: (i) the deposits, (ii) the hosting goldfields, and (iii) the enclosing terranes are all essentially similar to those during gold mineralization, at least in their relative position to each other. Thus, interpretation of geological maps and cross-sections and three-dimensional models can be used to accurately simulate the physical conditions that existed at the time of ore deposition. It is particularly significant that the deposits are commonly related to repetitive and predictable geometries, such as structural heterogeneities within or adjacent to first-order structures, around rigid granitoid bodies, or in specific “locked-up” fold-thrust structures. Importantly, the two giant greenstone-hosted goldfields, Kalgoorlie and Timmins, show a remarkably similar geometry at the regional scale. Computer-based stress mapping and GIS-based prospectivity mapping are two computer-based quantitative methodologies that can utilize and take advantage of the late timing aspect of this deposit type to provide important geological aids in exploration, both in broad regions and more localized goldfields. Both require an accurate and consistent solid geology map, stress mapping requires knowledge of the far-field stresses during mineralization, and the empirical prospectivity mapping requires data from a significant number of known deposits in the terrane. The Kalgoorlie Terrane, in the Yilgarn Block, meets these criteria, and illustrates the potential of these methodologies in the exploration for orogenic gold deposits. Low minimum stress anomalies, interpreted to represent dilational zones during gold-related deformation, coincide well with the positions of known goldfields rather than individual gold deposits in the terrane, and there are additional as-yet unexplained anomalies. The prospectivity analysis confirms that predictable and repetitive factors controlling the siting of deposits are: (i) proximity to, and orientation and curvature of, granitoid-greenstone contacts, (ii) proximity to segments of crustal faults which strike in a preferred direction, (iii) proximity to specific lithological contacts which have similar preferred strike, (iv) proximity to anticlinal structures, and (v) the presence of preferred reactive host rocks (e.g., dolerite). The prospectivity map defines a series of anomalous areas, which broadly conform to those of the stress map (>78% correspondence). The most prospective category on this map covers less than 0.3% of the greenstone belts and yet hosts 16% of the known deposits, which have produced>80% of known gold. Thus, it discriminates in favour of the larger economically more-attractive deposits in the terrane. The successful application of stress mapping and prospectivity mapping to geology-based exploration for orogenic gold deposits indicates that more quantitative analysis of geological map data is a profitable line of research. The computer-based nature of these methodologies is ideal for the production of an ultimate, integrated, deposit target map, which can be compared to other, more conventional, targeting parameters such as geophysical and geochemical anomalies. Such an integrated strategy appears the way forward in the increasingly difficult task of cost-effective global exploration for orogenic gold deposits in poorly exposed terranes.

Reconnaissance-scale conceptual fuzzy-logic prospectivity modelling for iron oxide copper – gold deposits in the northern Fennoscandian Shield, Finland

The conceptual approach used in this study incorporates spatial analysis techniques for data integration and analysis to perform reconnaissance-scale mineral prospectivity mapping for iron oxide copper – gold (IOCG) mineralisation in Finland. The known IOCG occurrences in Finland are characterised by the following features: (i) an epigenetic magnetite-rich host-rock; (ii) an association of Fe – Cu – Au ± Co ± U; (iii) ore minerals comprising magnetite, chalcopyrite, pyrite or pyrrhotite, and native gold; (iv) a gangue dominated by Ca-amphibole ± diopside, albite and biotite; (v) enrichment in Ag, Au, Bi, Ca, CO2, Cu, Fe, S, Te ± As, Ba, Cl, Co, K, LREE, Mo, Na, Pb, Rb, Sb, Se, U; (vi) multi-stage alteration; (vii) formation in the P – T range of 400 – 600°C, 150 – 350 MPa; and (viii) a distinct structural control in regions that have experienced both extensive compression and extension. The datasets used for the prospectivity analysis include a 1:1 000 000 scale geological map, high-resolution airborne geophysics, regional-scale multi-element till-geochemistry data, and a mineral occurrence database. The derived parameters used in the conceptual analysis include: (i) proximity to the craton margin; (ii) intersecting fault structures; (iii) presence of granitic intrusions particularly those with compatible and incompatible element enrichment; (iv) Cu, Co and Fe concentrations in till samples; (v) presence of hematite; and (vi) airborne magnetic highs and radiometric U data. A conceptual fuzzy-logic model was used to predict and locate the most prospective or favourable areas for IOCG exploration in the study area using the above-mentioned data layers. The models identify several permissive and high-potential areas within a significantly reduced potential exploration area. Validation of the modelling was conducted by quantifying the spatial association between the predicted endowment as favourability classes on the prospectivity map and the known mineral deposit sites with IOCG affinities using the Bayesian weights-of-evidence method.

Complexity gradients in the Yilgarn Craton: Fundamental controls on crustal-scale fluid flow and the formation of world-class orogenic-gold deposits

Fractal-dimension analysis is an effective means of quantifying complex map patterns of structures and lithological contacts, which are conduits for hydrothermal fluid flow during the formation of orogenic-gold deposits. In this study, fractal dimensions, calculated on a 10 km grid across a geologic map of the Yilgarn Craton of uniform data quality, highlight relationships between geologic complexity and the location and size of Archaean orogenic-gold deposits. In the Kalgoorlie Terrane and Laverton Tectonic Zone, the largest gold deposits occur along steep gradients defined by fractal-dimension values. These steep gradients in the greenstone belts occur between massive sedimentary rock sequences of low complexity, and volcanic and intrusive rock units with more complex map patterns. The formation of world-class orogenic-gold deposits requires that hydrothermal fluids become focused from a large volume of well-connected rocks at depth, towards narrow, high-permeability zones near the location of deposit formation. Connectivity is indirectly related to permeability, and the degree of connectivity is related to the density and orientation of fluid pathways, which are quantified in map patterns using fractal-dimension analysis. Thus, fractal dimensions are a measure of the potential for increased connectivity and the likelihood of increased permeability. Greater complexity, as measured by larger fractal dimensions, implies that a certain area has the potential to produce more interconnected pathways, or zones of high connectivity. Therefore, the steep complexity gradients defined in the Kalgoorlie Terrane and Laverton Tectonic Zone correspond to areas that focused large volumes of hydrothermal fluid and enhanced the potential for significant gold mineralisation. Fractal-dimension analysis thus provides a link between empirical map features and the processes that have enhanced hydrothermal fluid flow and resulted in the formation of larger orogenic-gold deposits.

Combined conceptual/empirical prospectivity mapping for orogenic gold in the northern Fennoscandian Shield, Finland

Despite its exploration immaturity, the Central Lapland Greenstone Belt has geodynamic, geological and gold-endowment characteristics to indicate that it is potentially the premier orogenic-gold province in Finland. Previous GIS-based prospectivity mapping of the Central Lapland Greenstone Belt used only empirical geophysical and geochemical datasets based on the weights-of-evidence integration method. In this study, such empirical data are combined with conceptual geological parameters derived from a 1:200 000 scale bedrock map of northern Finland and use the weights-of-evidence, logistic regression and fuzzy-logic methods for integration. A targeting model is developed based both on the empirical data and conceptual parameters defined from understanding of the processes essential to produce large deposits in an orogenic-gold mineral system. Key spatially referenced layers are derived from the empirical data and from critical proxies for essential processes in the targeting model, and the spatial association between these key layers and a training set of known gold deposits and prospects is quantified. Key parameters are then reclassified into binary layers according to maximum spatial association with the training set, and these layers are then integrated into prospectivity maps using both the weights-of-evidence and logistic regression methods. The highest probability class in all models defines <1% of the Central Lapland Greenstone Belt, a remarkable reduction in highest-priority target zones. The resulting maps are evaluated using a set of gold prospects excluded from the original training set as validation sites. The resultant prospectivity maps provide subtle, but significant, improvement on the maps derived solely from empirical data, especially where logistic regression is applied. Proxies for strain gradients appear particularly important. The analysis demonstrates that homogeneous, high-quality, small-scale geological maps, integrated using a robust targeting model, can enhance the predictive capacity of prospectivity maps derived from GIS-based modelling.

Developing the tools for geological shape analysis, with regional- to local-scale examples from the Kalgoorlie Terrane of Western Australia

Geological map data are often underused in mineral‐exploration programs, which rely increasingly on regolith geochemistry and geophysical and other remotely sensed data to generate exploration targets. However, solid geology maps, which are progressively being upgraded due to improved interpretations of superior, remotely sensed images and airborne geophysical data, can be useful in targeting specific types of mineral deposits, which formed late in the evolutionary history of the host terrane. In such terranes, the present map geometry is essentially the same as that at the time of deposit formation. This is the case for orogenic lode‐gold deposits, which commonly show predictable structural controls and/or structural geometry. Thus, the shape of a rock body, or combinations of structures and rock bodies, may provide an important guide to the exploration potential for orogenic lode‐gold deposits. However, until recently, there has been a dearth of techniques to quantify the various properties of shape, and hence test the potential of the two‐dimensional shape of geological bodies in map view as an exploration tool. Integrating techniques from the field of pattern recognition with a modern Geographical Information System (GIS) can provide the shape‐analysis tools required to investigate the geometries of geological shapes. Two‐dimensional shape analysis is now possible through the calculation of several shape metrics including, but not restricted to, aspect ratio, blockiness, elongation, compactness, complexity, roundness, spreadness and squareness. Methods are developed for describing the geometries of rock units about mineral deposits, or any geological features, at any scale, which for the first time makes it possible to compare shapes. These shape‐analysis techniques are tested using orogenic lode‐gold deposits, particularly those in the Kalgoorlie Terrane of the highly auriferous Late Archaean Norseman‐Wiluna Belt of Western Australia. On a global scale, shape analysis indicates that those greenstone belts whose volcanic rock sequences have high elongation and relative low roundness, complexity and aspect ratio (e.g. Kalgoorlie Terrane) are likely to be the most richly endowed in gold. On a more local scale, characteristics of the shape of geological features around the Golden Mile deposit are calculated and used to test the likelihood of occurrence of gold deposits with similar geometry elsewhere in the Kalgoorlie Terrane. The area with the most closely matching shape, on the basis of a 2 km clipping‐circle radius, chosen on the basis of available proximity‐analysis data, corresponds to the recently discovered Ghost Crab deposit, illustrating the potential of the shape analysis methodology in mineral exploration. Shape analysis is, at least in part, scale dependent, due to the inherent problem of being able to define rock boundaries more precisely in units that have strong geophysical signatures than those with weak signatures in poorly exposed terranes. Overcoming this problem is a challenge to the application of this methodology.

Rotund versus skinny orogens: Well-nourished or malnourished gold?

Orogenic gold vein deposits require a particular conjunction of processes to form and be preserved, and their global distribution can be related to broad-scale, evolving tectonic processes throughout Earth history. A heterogeneous distribution of formation ages for these mineral deposits is marked by two major Precambrian peaks (2800‐2555 Ma and 2100‐1800 Ma), a singular lack of deposits for 1200 m.y. (1800‐600 Ma), and relatively continuous formation since then (after 600 Ma). The older parts of the distribution relate to major episodes of continental growth, perhaps controlled by plume-influenced mantle overturn events, in the hotter early Earth (ca. 1800 Ma or earlier). This worldwide process allowed preservation of gold deposits in cratons, roughly equidimensional, large masses of buoyant continental crust. Evolution to a less episodic, more continuous, modern-style plate tectonic regime led to the accretion of volcano-sedimentary complexes as progressively younger linear orogenic belts surrounding the margins of the more buoyant cratons. The susceptibility of these linear belts to uplift and erosion can explain the overall lack of orogenic gold deposits at 1800‐600 Ma, their exposure in 600‐50 Ma orogens, the increasing importance of placer deposits back through the Phanerozoic since ca. 100 Ma, and the absence of gold deposits in orogenic belts younger than ca. 50 Ma.

Gis-stereoplot: an interactive stereonet plotting module for ArcView 3.0 geographic information system

Abstract Equal-angle and equal-area stereonets provide a powerful means to display and analyze angular relationships between sets of directional data. However, they are limited in that they are unable to represent the potential spatial relationships which may exist between the sample points. Advances in affordable and user-friendly desk-top Geographic Information Systems (GIS) have allowed this deficiency of conventional stereonets to be addressed. A prototype interactive stereonet-plotting module for the desk top GIS ArcView 3.0, which allows the spatial aspects of directional data to be better appreciated, is presented. This module allows the spatial data selection tools of GIS to be used to select a subset of structural data points which can then be plotted, as points, planes, or poles to planes on either an equal-angle (Wulff) or equal-area (Schmidt) stereonet. Features selected on the stereonet can be related back to the original map data and vice versa.