A suite of representative samples were selected from 5 drill-cores, including 1 drill-core that intersected unmineralized Urquhart Shale (Shovel Flats drill-hole; n = 91) and 4 drill-cores that intersected the main ore bodies at the George Fisher deposit (drill hole 8C K751, n = 61; 10C K795, n = 77; 10C K798, n = 57; 12C I797, n = 30). The samples were selected from the main ore bodies, weakly mineralized sections, barren siltstones and mudstones, and, where possible, from hangingwall stratigraphy.

The samples were studied using a binocular microscope and 95 samples were chosen for polished thin section preparation. The thin sections were examined using transmitted- and reflected-light petrography and backscatter electron (BSE) imaging, see Rieger et al. (2020a) for details. Pyrite from a suite of representative samples was subsampled using a drill press and individual 2 mm pucks were mounted into 3 polished epoxy mounts, as described in Rieger et al. (2020a), which were also used for SIMS analysis.

The whole rock geochemical composition for samples used in this study was determined via ICP-MS, ICP-ES, X-ray fluorescence, and LECO analysis. The mineralogical composition was determined via quantitative X-ray diffraction (XRD). For quality control and to determine pyrite abundances below detection limits of the XRD analysis, pyrite abundance was further also calculated from the molar concentrations of S, Pb, and Zn. For further details regarding the analytical methods see Rieger et al. (2020b); Rieger et al. (2021).

Quantitative wavelength-dispersive spectrometry (WDS) of representative pyrite samples (n = 22) was carried out on a JEOL Superprobe JXA 8230 and a Hyperprobe JXA 8500F at the GFZ Helmholtz Centre Potsdam. Mounted samples and thin sections were carbon coated and 336 quantitative analyses of S, Fe, Co, Ni, Zn, As, and Pb were conducted at 15 keV, 20 nA, and a beam size of 1 µm. Counting times on the peaks were between 5 and 40 s. The instrument was calibrated on certified natural and artificial reference samples: pentlandite (Fe, Ni, S), sphalerite (Zn), galena (Pb), GaAs (As), and (Co, Ni)As₃ (Co) and ZAF-data correction was carried out. At these conditions, the detection limits were: 139 ppm for S; 149 ppm for Ni; 115 ppm for Co; 447 ppm for Zn; 132 ppm for As; and 499 ppm for Pb. Data were deemed acceptable at totals of 100 ± 3 wt.%.

In total, 1989 analyses were performed on pyrite from 28 samples contained within the 3 epoxy mounts and 16 additional polished thin sections. The LA-ICP-MS instrumentation comprised an Analyte Excite 193 nm ArF* excimer-based laser ablation (LA) system (Teledyne Photon Machines, Bozeman, MT, USA), coupled to a quadrupole-ICP-MS iCAP from Thermo Scientific. The LA-system is equipped with a HelEx II 2-volume ablation cell. Helium was used as a carrier gas for aerosol transport from the sample surface to the ICP and was mixed downstream with Ar as a make-up gas before entering the plasma. Operational parameters of the ICP-MS instrument and LA-unit were tuned for maximum sensitivity, low oxide formation based on the ²³²Th¹⁶O/²³²Th ratio and low laser-induced elemental fractionation based on the ²³⁸U/ ²³²Th ratio using NIST SRM 610. Elements were calibrated using MASS1 as the certified reference material and ⁵⁷Fe as the internal standard. Samples were ablated for 30 s using a spot size between 20 and 30 μm, with a repetition rate of 10 Hz and an energy density of 2–3 J/cm². The data was reduced using the commercial software Iolite™ (Paton et al., 2011) and the data reduction scheme X_trace_elemets_IS (Woodhead et al., 2007).

The fine grain size and complex paragenetic relationships of the sulfides meant a number of data processing procedures were necessary to ensure data quality. The time series for data integration (Figure 2) was carefully evaluated to ensure mixed ablations of pyrite and non-pyrite mineral phases were identified in the ablation profiles and rejected. Additionally, analyses with >5 wt.% Zn or Pb were rejected to reduce the influence of mixed analyses with sphalerite or galena. Data quality control resulted in the rejection of 338 and the retention of 1,651 pyrite analyses. The data quality was further confirmed following a comparison with electron probe micro-analysis (EPMA) data.

Statistical analysis of the TE dataset was caried out applying principal component analysis (PCA) using the software package ioGAS. Below limit of detection (LOD) values were imputed as 0.5*LOD of the respective analysis and the data (n = 1,513) were log transformed before applying a robust fast minimum covariance determination algorithm with an outlier cut-off of 0.975 and an alpha value of 0.75.

There are three types of sulfides at George Fisher: 1) pre-ore pyrite, 2) three stages of hydrothermal sulfides, and 3) pyrite that occurs in un-mineralized rocks and likely formed post-ore. The relative timing of individual sulfides (paragenesis; Figure 3) has been described in detail by Chapman. (1999); Chapman. (2004) and Rieger et al. (2020a). The samples from Rieger et al. (2020a) are part of the sample set studied here and therefore, the same sulfide paragenesis was used in this study. In the following paragraphs, this paragenesis (Rieger et al., 2020a) is summarized with special emphasis placed on individual pyrite types and textures and, where possible, examples for paragenetic relationships of pyrite types within individual samples are shown.

Pre-ore pyrite (Py-0) occurs predominantly in laminated, carbonaceous siltstones of both background, unmineralized rocks (Py-0_SF; Figures 4A–D) and mineralized rocks at George Fisher (Py-0_GF; Figures 4E–L). Pyrite-0 occurs either as single grains or as grain aggregates (Figures 4G, K) and individual grains are generally very fine grained (<10 µm). This Py-0 typically consists of a (sub-) spheroidal core (Py-0a) and a subhedral to euhedral overgrowth (Py-0b; Figure 4H).

Ore stage 1 at George Fisher chiefly comprises sphalerite, pyrite (Py-1), and minor galena, which postdate and overgrow Py 0 (Figure 5). This ore stage is stratabound in laminated, carbonaceous siltstones and Py-1 is typically anhedral and occurs in 10 s–100 s μm sized nodules and nodular beds (Figure 5).

Ore stage 2 occurs as breccias and veins, in which the matrix mostly consists of galena, sphalerite, pyrrhotite and pyrite. The pyrite (Py-2) is euhedral and 50–500 µm in size (Figure 6). In ore stage 2 samples the host rock and previous sulfides are typically replaced (Figure 6D), deformed (Figures 6A–C), and crosscut (Figures 6E–G).

Ore stage 3 formed either stratabound massive sulfide units or veins and breccias that crosscut all previous lithologies and sulfides. The main sulfide minerals are pyrrhotite and pyrite (Py-3), but galena, sphalerite, and chalcopyrite are also present in the veins and breccias (Figure 7). This ore stage is volumetrically minor and spatially restricted to the western part of the deposit. It is also the only sulfide assemblage that contains chalcopyrite and it is often associated with buff cream-coloured phyllosilicate alteration of the host rock that is distinct from other alteration assemblages at George Fisher (Figure 7E). Pyrite (Py-3) is typically coarse grained (>100 µm) and euhedral to subhedral (Figures 7C, G). During this ore stage previous sulfides were typically replaced or deformed (e.g., Py-1; Figure 7D).

The timing of large (100 s μm) euhedral pyrite (Py-euh) and of hangingwall pyrite (Py-HW) relative to the ore stage sulfides is not well constrained as they only occur in unmineralized rocks. These two generations of pyrite typically occur in late carbonate veins and nodules that postdate Py-0 and are likely post-ore.

Paragenetically constrained sulfur isotope data indicate that 1) Py-0 formed from reduced sulfur produced via open system microbial sulfate reduction, 2) reduced sulfur for Py-1, Py-3, and Py-euh was derived via thermochemical sulfate reduction, whereas 3) Py-2 formed via the replacement, recycling, and recrystallization of pre-existing Py-0 and Py-1 (Rieger et al., 2020a).

There is a general overlap between EPMA and LA-ICP-MS data for analyses that are above the EPMA detection limits (Figures 8A–C). Within individual pyrite types the variability of some LA-ICP-MS element abundances is higher than the variability of EPMA data (Figure 8; e.g., Zn, As, Pb in Py-2 and Py3). These wider LA-ICP-MS data distributions are likely due to: 1) the higher numbers of samples and analyses compared to EPMA; and 2) the lower detection limit for LA-ICP-MS. The LA-ICP-MS data are therefore considered more representative of the individual pyrite types than the EPMA data. The abundances of individual TEs vary across orders of magnitude (10 ppm–5 wt.%) and TE abundances of individual pyrite types can vary significantly (see median and median absolute deviation in Table 1). The most abundant TEs are Zn, As, and Pb, which are most enriched in Py-1, have intermediate abundances in Py-0, and are generally depleted in Py-2, Py-3, Py-euh, and hanging wall pyrite (Table 1; Figures 8A–C). The remaining TEs (Mn, Co, Ni, Cu, Mo, Ag, Sb, and Tl) account for less than half of the total TE budget, but there is major variability in the relative proportions of these elements among the different generations of pyrite (Table 1; Figure 9). Contents of Mn and Sb are highest in Py-0 from the Shovel Flats drill hole (Py-0_SF; Figure 9B). Manganese is also high in Py-0 at George Fisher (Py-0_GF; Figure 9C) and Mn contents of Py-1 are low (Figure 9D). Molybdenum is highest in Py-0_SF and Py-0_GF (Figures 9B, C) and intermediate in Py-1 (Figure 9D). Contents of Sb are highest in Py-0_SF, high in Py-1, and intermediate in Py-0_GF (Figures 9C–E). Abundances of Mn, Mo, and Sb are lowest in Py-2 and Py-3 (Figures 9E, F). Thallium is most abundant in Py-1 (Figure 9D), intermediate in Py-0_SF and Py-0_GF (Figures 9B, C), and lowest in Py-2 and Py-3 (Figures 9E, F). The abundances of Ag are highest in Py-0_GF and Py-1 (Figures 9C, D) and low in Py-0_SF, Py-2, and Py-3 (Figures 9B–F). Abundances of Cu and Co are highest in Py-1 (Figure 9D), although relative to the other TEs the proportions of Cu and Co are highest in Py-0_SF (Figure 9B) and Py-3 respectively (Figure 9F). The abundance of Ni is constant throughout all generations of pyrite (median = 33–88 ppm; median_all-data = 58 ppm; MAD_all-data = 38 ppm), but its relative proportion to the other TEs is much higher in Py-2 (Figure 9E). The full LA-ICP-MS pyrite dataset is available in a datafile (Rieger et al., 2022b) and a summary of the data is shown in Table 1.

The abundances of most TEs (Mn, Co, Cu, As, Mo, Ag, and Sb) in Py-0_SF and Py-0_GF are similar to median values for sedimentary and diagenetic pyrite from the Proterozoic (0.25 < Py-0/Py_Proterozoic < 4; Figure 10A; Large et al., 2014). Significant TE enrichment (Py-0/Py_Proterozoic >4) and depletion (Py-0/Py_Proterozoic <0.25) in Py-0_SF and Py-0_GF is only indicated for Zn and Tl, and Ni, respectively (Figure 10A). Pyrite-0_GF is also enriched in Pb and depleted in Cu (Figure 10A). Relative to literature values for SEDEX pyrite (Gregory et al., 2019), ore stage 1 pyrite (Py-1) has anomalous Tl and Pb enrichment (Py-1/Py_SEDEX >4) similar to hydrothermal pyrite from the Teena deposit (McArthur basin, northern Carpentaria province; Magnall et al., 2022). Hydrothermal Py-1 is also significantly enriched in Zn and Co and has similar TE abundances to SEDEX pyrite in Cu, As, Ag, and Sb. Whereas Py-2 and Py-3 are depleted in all TE except for Co and are therefore distinct from SEDEX or Teena pyrite (Figure 10B).

A principal component analysis shows that 66.7% variance of the dataset can be described by the first 2 principal components (PC1 and PC2; Figures 11A–C). The group of minor TEs (Mn, Co, Ni, Cu, Mo, Ag, Sb, and Tl) are separated into three sub-groups in PC1-PC2 space. The major TEs (Zn, As, and Pb) cluster with Ag, Cu, Sb, and Tl, but with lower scaled coordinates for PC1. Principal component 2 is best described by the variance of the elements Mn and Mo (scaled coordinates ca. 0.7) and Ni and Co (scaled coordinates ca. −0.6 and −0.8; Figure 11A). With respect to the individual pyrite generations, PC1 values are high for Py-1 (median = 1.5), intermediate for Py 0 (median ca. 0.4) and low for all other pyrite generations (median < −2.5; Py-2, Py-3, Py-euh, and hangingwall pyrite (Py-HW); Figure 11B). The values for PC2 are high (median ≥1) for Py-0 and low for all other pyrite generations (median <0; Py 1, Py-2, Py-3, Py-euh, and Py-HW; Figure 11C).

Using three of the elements (Tl, Mo, and Ni) from the different subgroups in PC1-PC2 provides a tool to visualize differences in TE composition among paragenetic stages of pyrite (Figure 11D). Py-0 data are intermediate between the endmembers, whereas Py-1 data are concentrated at the Tl endmember, and Py-2 and Py-3 data are located at the Ni endmember (Figure 11D). Pyrite-euh and Py-HW data are distributed between the Mo and Ni endmembers and overlap only with Py-2 and Py-3, but not with Py-0 and Py-1 (Figure 11D).

In this study, the DTMP is calculated using the median abundance of TE in pyrite (TE_pyrite) as determined by LA-ICP-MS, the whole rock TE abundance (TE_wr), and the whole rock pyrite abundance (pyrite_wr; Rieger et al., 2021). D T M P = T E p y r i t e * p y r i t e w r / T E w r

The DTMP in samples containing only Py-0 from George Fisher and the Shovel Flats drill hole are reasonably comparable, whereas DTMP values in samples containing different proportions of ore stage pyrite are much more variable (Figure 12). In most samples (except for those containing Py-euh and Py-HW), the DTMP for Mn and Zn is generally low (<10%) and high for Co, Ni, and As (>45%). In samples that mostly contain Py-0, the DTMP is high for Cu (>25%), Mo (>25%), Ag (>50%), Sb (ca. 100%), Tl (>50%), and Pb (>25%). Pyrite contains a large proportion of the whole rock budget of Cu (>25%) and Tl (>50%) for samples with dominantly Py-1 and an intermediate proportion for Py-1+Py-2–dominant samples (Cu = 20%; Tl = 40%), whereas those elements are mainly hosted by other phases in Py-3–, Py-euh–, and Py-HW–dominant samples (<10%). The DTMP of Mo, Ag, Sb, and Pb is generally low or intermediate (0%–25%) for Py-1–, Py2–, Py-euh–, and Py-HW–dominant samples, whereas in Py-3–dominant samples pyrite contains an intermediate to high proportion of the Mo–, Ag–, Sb–, and Pb–budget (20%–140%). Significant outliers occur for Co contents in Py-3 samples and for Ag in Py-0 samples.

The degree of trace metal pyritization (DTMP) represents the proportion of TEs in the whole rock that are present in pyrite. Previous studies have focused on organic rich sediments and calculated the DTMP following the analysis of TEs in the whole rock and a separate chemical extraction of pyrite (Huerta-Diaz and Morse, 1990; Huerta-Diaz and Morse, 1992). The samples from George Fisher have a more complicated paragenesis and the whole rock and LA-ICP-MS data have been generated on different scales. Specifically, the LA-ICP-MS data were generated at the thin section scale, whereas whole rock data was produced from 15 to 20 cm drill core intervals (Rieger et al., 2021). This may help to explain some of the variability in the DTMP values, although there are still some useful general observations to make. For example, the DTMP values that strongly exceed 100% likely represent compositional values for pyrite that are not representative of the whole rock pyrite composition. This could be attributed to a) mixed ablations comprising pyrite and minor TE rich sulfide inclusions or b) the presence of a second, TE poor, but volumetrically abundant, type of pyrite in a sample (e.g., Py-0 vs. Py-euh). The low DTMP values then highlight the TEs that are hosted by other mineral phases (e.g., Zn in sphalerite; Mn in carbonate).

Given these uncertainties, samples from Shovel Flats and George Fisher that only contain Py-0 have DTMP values for most TEs that are reasonably comparable (i.e., consistently low, e.g., Mn = 0–4%; consistently intermediate, e.g., Pb = 14–76%; consistently high, e.g., Sb = 97–117%) in (Figure 12A), which confirms pyrite chemistry is relatively homogenous between these samples. The low DTMP_Mn values indicate that pyrite was only a minor sink for Mn, which is likely to be primarily incorporated into carbonate (Rieger et al., 2021). Intermediate to high DTMP_Mo values (averages: Shovel Flats = 33%; George Fisher = 53%; Figures 12A, B) indicate that a large fraction of Mo is incorporated into pyrite, although a significant proportion may also be associated with organic matter in the host rock (e.g., Chappaz et al., 2014). Interpreting DTMP values in ore stage samples is more complicated, due to multiple generations of pyrite and other TE rich sulfide phases (e.g., sphalerite, galena, chalcopyrite). The outlier DTMP values that exceed 100% (e.g., Co, Ag, Sb; Figures 12A, B) indicate the ablation of pyrite that is not representative of the whole rock composition. They could also be generated by the ablation of mineral inclusions of other sulfide phases that could incorporate those elements (e.g., galena, chalcopyrite, sphalerite, sulfosalts) or by the presence of low volume TE rich pyrite overgrowths (e.g., Li et al., 2022; Magnall et al., 2022). Conversely, the low DTMP of Zn, Pb, and Cu, indicates that the whole rock budget of these metals is associated primarily with sphalerite, galena and chalcopyrite respectively. Despite variability among individual ore stages, high DTMP for Co, Ni, As, and Tl (Figure 12) do indicate that these elements are dominantly hosted by pyrite.

Trace element incorporation into pyrite is complex and may be controlled by several factors, including: isovalent or heterovalent substitution into the crystal lattice (e.g., Chouinard et al., 2005), nano to microscopic mineral inclusions (e.g., Deditius et al., 2011), or as a combination of both (e.g., Cook et al., 2009). These different mechanisms of TE incorporation are likely reflected by the three element groupings in the PCA (Figure 11A): 1) Mn and Mo, 2) Cu, Zn, As, Ag, Sb, Tl, and Pb, and 3) Co and Ni.

The distinctive composition of pyrite in each of the ore stages records useful information about the genesis of the George Fisher deposit. Pyrite-1 has high Co/Ni ratios and above background concentrations (>Py-0) of Co, Cu, Zn, As, Ag, Sb, Tl, Pb, and TE totals (Figures 8–10, 14; Table 1). Pyrite-2 and Py-3 have above background concentrations of Co and Ni, and Py-2 has low Co/Ni ratios, whereas Co/Ni ratios of Py-3 are high (Figures 8–10, 14; Table 1). Pyrite-1 is similar or enriched relative to hydrothermal pyrite from the northern Carpentaria province, except for Ni and Mo, whereas Py-2 and Py-3 are depleted in all TE except for Co (cf., Gregory et al., 2019; Magnall et al., 2022).

The paragenetic evolution of pyrite TE geochemistry at George Fisher is consistent with a multi-stage mineralizing system, which supports previous petrographic, structural, mineralogical, geochemical, and isotopic studies (Valenta, 1994; Chapman, 2004; Murphy, 2004; Rieger et al., 2020a; Rieger et al., 2021). The chemistry of Py-1 most closely resembles pyrite from undeformed CD-type deposits of the northern Carpentaria province, which formed via host rock replacement during burial diagenesis (e.g., Spinks et al., 2021; Magnall et al., 2022). Later ore forming events (ore stage 2 and 3) replaced, recycled, and overprinted pre-existing mineralization and led to the redistribution and upgrading, as well as addition of new metals (i.e., Cu) at George Fisher, which are captured by the distinct TE geochemistry of Py-2 and Py-3 (Figures 6–11, 14). The enrichment of ore stage 1 related elements (Ag, Tl, and Pb) in un-/weakly-mineralized rocks at George Fisher may indicate more widespread fluid flow and alteration during ore stage 1 than during subsequent ore stages (2 and 3). The spatial dimension of ore stages 2 and 3 is more restricted and structurally controlled, which could have resulted in limited trace element dispersion into the surrounding wall rock.

Importantly, TEs that are typically incorporated into diagenetic pyrite (e.g., Mo, Co, Ni) are fairly uniform in Py-0 from George Fisher and the Shovel Flats drill hole, whereas those with an ore stage 1 affinity are anomalous, particularly in Py-0_GF (e.g., Tl, Zn, Pb). It is possible that alteration during ore stage 1 produced micro-to nano-scale TE enriched pyrite overgrowths that nucleated on diagenetic Py-0 beyond the ore bodies at George Fisher (cf., Magnall et al., 2022). The identification of distal, potentially fine-scale, pyrite TE halos would help to improve the understanding of fluid flow and alteration in distal parts of basin hosted mineral systems and to de-risk mineral exploration programs. Future studies should refine the 3D distribution of such pyrite TE halos around the George Fisher deposit and employ higher resolution (10–100 nm scale) analyses of pyrite to determine the nature of this TE anomalism.