Understanding the formation of economically important porphyry Cu–Au
deposits requires knowledge of the magmatic-to-hydrothermal processes
that act within the much larger magmatic system and the timescales on which
they occur. We apply high-precision zircon geochronology (chemical abrasion–isotope dilution–thermal ionisation mass spectrometry; CA–ID–TIMS) and
spatially resolved zircon geochemistry (laser ablation inductively coupled plasma mass
spectrometry; LA-ICP-MS) to constrain the magmatic
evolution of the underlying magma reservoir at the Pliocene Batu Hijau
porphyry Cu–Au deposit. We then use this extensive dataset to assess the
accuracy and precision of different U–Pb dating methods of the same zircon
crystals.
Emplacement of the oldest pre- to syn-ore tonalite (3.736±0.023 Ma)
and the youngest tonalite porphyry to cross-cut economic Cu–Au mineralisation
(3.646±0.022 Ma) is determined by the youngest zircon grain from
each sample, which constrains the duration of metal precipitation to fewer
than 90±32 kyr. Overlapping spectra of single zircon crystallisation
ages and their trace element distributions from the pre-, syn and post-ore
tonalite porphyries reveal protracted zircon crystallisation together with
apatite and plagioclase within the same magma reservoir over >300 kyr. The presented petrochronological data constrain a protracted early
>200 kyr interval of melt differentiation and cooling within a
large heterogeneous magma reservoir, followed by magma storage in a highly
crystalline state and chemical and thermal stability over several tens of thousands of years
during which fluid expulsion formed the ore deposit. Irregular trace element
systematics suggest magma recharge or underplating during this final short
time interval.
The comparison of high-precision CA–ID–TIMS results with in situ LA-ICP-MS
and a sensitive high-resolution ion microprobe (SHRIMP) U–Pb geochronology data from the same zircon grains allows a
comparison of the applicability of each technique as a tool to constrain
dates and rates on different geological timescales. All techniques provide
accurate dates but with different precision. Highly precise dates derived by
the calculation of the weighted mean and standard error of the mean of
the zircon dates obtained by in situ techniques can lead to ages of unclear
geological significance that are older than the maximum ages of emplacement
given by the CA–ID–TIMS ages of the youngest zircons in each sample. This
lack of accuracy of the weighted means is due to the protracted nature of
zircon crystallisation in upper crustal magma reservoirs, suggesting that
standard errors should not be used as a means to describe the uncertainty in
those circumstances. We conclude from this and similar published studies
that the succession of magma and fluid pulses forming a single porphyry
deposit and similarly rapid geological events are too fast to be reliably
resolved by in situ U–Pb geochronology and that assessing the tempo of ore
formation requires CA–ID–TIMS geochronology.
Introduction
Zircon geochronology is widely applied to date geological events and
constrain timescales of geological processes. Combined with zircon
geochemistry it has improved our understanding of crustal magmatic systems,
such as those forming economically important magmatic–hydrothermal porphyry
Cu–Au deposits. Advances in analytical techniques resulted in a shift from
establishing the ages of magma emplacement or crystallisation to resolving
the durations of magmatic and associated hydrothermal processes, such as
magma accumulation or recharge, fractional crystallisation, or hydrothermal
ore formation, and it has resulted in unprecedented information about the
mechanisms and scales of magma ascent and storage in the earth's crust (e.g.
Vazquez and Reid, 2004; Chamberlain et al., 2014; Barboni et al., 2016; Bucholz
et al., 2017).
Porphyry copper deposits provide successively quenched samples of magma
extracted from large crustal-scale hydrous magma systems. They are therefore
a critical source of information about the processes and rates of magma
ascent, magma storage and fluid generation, bridging those of volcanism and
pluton formation. The identification of the processes that lead to porphyry
deposit formation (e.g. Rohrlach et al., 2005; Audétat et al.,
2008; Richards, 2013; Wilkinson, 2013) and the timescales on which they
operate can provide us with valuable information about arc magmatic
processes but could also potentially help in discriminating possibly fertile
magmatic systems from ubiquitous infertile systems resulting in barren
intrusions or volcanic eruptions.
Porphyry Cu–Au deposits commonly display clear field relationships of
successive generations of porphyritic stocks or dikes, which were injected
into sub-volcanic and other upper-crustal rock sequences (Sillitoe, 2010).
The injected porphyry magmas thus provide snapshots of the underlying,
vertically and laterally extensive magma reservoirs (e.g. Dilles,
1987; Steinberger et al., 2013). Cross-cutting relationships between veins
and intrusive rocks suggest temporal overlap of hydrothermal alteration, ore
mineralisation and porphyry emplacement (Proffett, 2003; Seedorff and
Einaudi, 2004; Redmond and Einaudi, 2010). Strong hydrothermal alteration of
the intrusive rocks associated with ore formation severely disturbs the
geochemical information of most minerals and whole-rock compositions. While
providing important insights into the hydrothermal history of a deposit
(e.g. Roedder, 1971; Dilles and Einaudi, 1992; Landtwing et al., 2005; Cathles
and Shannon, 2007; Seedorff et al., 2008; Large et al., 2016), it limits the
investigation of the magma evolution, especially for the porphyries that are
most intimately associated with ore formation. Zircon is a widespread
mineral in intermediate to felsic rocks that is resistant to nearly all
hydrothermal alteration and can thus provide coherent information about the
evolution of a magmatic system.
Recent advances in high-precision zircon geochronology by chemical abrasion–isotope dilution–thermal ionisation mass spectrometry (CA–ID–TIMS; e.g.
Mattinson, 2005; Bowring et al., 2011; McLean et al., 2011a, 2015; Condon et al.,
2015) now allow dating of the porphyritic intrusions
associated with ore formation with unprecedented precision. The dramatically
improved precision permits the constraint of rapid events, such as individual
porphyry emplacement and hydrothermal mineralisation phases (<100 kyr; von Quadt et al., 2011; Buret et al., 2016; Tapster et al., 2016), that
typically occur at the end of a longer-term period of volcanism and
intrusive magma emplacement extending over several million years (e.g. Deino
and Keith, 1997; Halter et al., 2004; Maksaev et al., 2004; Rohrlach et al.,
2005; Lee et al., 2017). The integration of the temporal and chemical
information gained from zircon is referred to as zircon petrochronology and
can yield time-calibrated information about magma chemistry, thermal
evolution and crystallinity during zircon crystallisation in magmatic
systems (e.g Schoene et al., 2012; Chelle-Michou et al., 2014; Samperton et
al., 2015; Buret et al., 2016; Szymanowski et al., 2017).
Timescales for magmatic and hydrothermal processes involved in porphyry ore
formation have been suggested based on in situ U–Pb data (e.g. Garwin,
2000; Banik et al., 2017; Lee et al., 2017) and CA–ID–TIMS geochronology,
which became increasingly precise (e.g. von Quadt et al.,
2011; Chelle-Michou et al., 2014; Buret et al., 2016; Tapster et al.,
2016; Gilmer et al., 2017; Large et al., 2018). However, several studies
applying multiple techniques to the same sample sets have resulted in
differing dates (von Quadt et al., 2011; Chiaradia et al., 2013, 2014; Chelle-Michou
et al., 2014; Correa et al., 2016). The discrepancy
demands a more detailed understanding of the precision and accuracy of
the techniques and statistical data treatment that are applied to derive
a geological age. This is not only fundamental for resolving dates and rates
of geological processes in ore deposit research but provides more general
insights into the geological meaning of magmatic dates and rates obtained by
U–Pb geochronology.
For the present paper, we obtained a large dataset of zircon geochemistry
and geochronology by laser ablation inductively coupled plasma mass
spectrometry (LA-ICP-MS) followed by high-precision geochronology of the
same zircon crystals, utilising chemical abrasion–isotope dilution–thermal
ionisation mass spectrometry (CA–ID–TIMS). These coupled data from the
world-class Batu Hijau porphyry Cu–Au deposit allow us to resolve the chemical
evolution and the changing physical state of the magma reservoir over time
as well as the timescales of hydrothermal processes. In addition, previously
published data on the same lithologies permit a critical comparison of two
in situ microanalytical methods (sensitive high-resolution ion microprobe, SHRIMP, data by Garwin, 2000), LA-ICP-MS
presented here) with high-precision U–Pb CA–ID–TIMS geochronology (this
study). This allows us to critically compare the effects of variable degrees
of precision and of the statistical treatment of data on the resulting
interpreted ages, and it provides a means to test the accuracy of the
different techniques.
Geological background
The Pliocene island-arc-hosted world-class porphyry deposit of Batu Hijau is
located on the island of Sumbawa, Indonesia (Fig. 1), and it is one of the largest
Cu and Au resources in the south-west Pacific region (7.23 Mt Cu and 572 t
Au; Cooke et al., 2005). It is currently the only mined porphyry deposit in
the Sunda–Banda volcanic arc, where Cu–Au porphyries are restricted to a
narrow segment of the eastern Sunda–Banda arc from 115 and
120∘ E (Fig. 1), where the Australian plate has been being subducted since
the Eocene (Hall, 2002).
The exposed islands of the Sunda–Banda arc are characterised by late
Oligocene to early Miocene calc-alkaline basaltic to andesitic arc rocks
that are overlain or intruded by a late Miocene to Pleistocene calc-alkaline
volcanic and plutonic rock suite ranging from basaltic to rhyolitic
compositions (Hamilton, 1979; Hutchison, 1989). The magmatic arc hosts a
variety of ore deposit types, including porphyry Cu–Au deposits; high-,
intermediate- and low-sulfidation epithermal deposits; and a volcanic-hosted massive sulfide (VMS)
deposit on Wetar (Fig. 1).
Tectonic map of South East Asia and the south-west Pacific. The Batu
Hijau porphyry Cu–Au deposit (enlarged red square) is located on Sumbawa on
the subduction-related magmatic Sunda–Banda arc within a small corridor
between 110 and 120∘ E that hosts several porphyry
deposits. Arrows display plate motion relative to the Eurasian plate
(Sundaland shield) but do not indicate velocity. HS: high
sulfidation; IS: intermediate sulfidation; LS: intermediate
sulfidation; VMS: volcanic hosted massive sulfide deposit. Most deposit
locations are from Garwin et al. (2005).
The geology of the island of Sumbawa, hosting the Batu Hijau deposit, is dominated
by early Miocene to Holocene volcanic arc successions deposited on oceanic
crust that is 14–23 km thick (Hamilton, 1979; Barberi et al., 1987).
Thickened continental crust observed in most other porphyry-mineralised
magmatic arcs and commonly considered a prerequisite for porphyry Cu
formation (Rohrlach et al., 2005; Chiaradia, 2015; Lee and Tang, 2020)
is lacking beneath Sumbawa (Garwin et al., 2005). The distribution of
volcano-sedimentary units, intrusions and the current coastline of Sumbawa
are controlled by a major arc-transverse, left-lateral oblique-slip fault
zone (Arif and Baker, 2004; Garwin et al., 2005). The fault zone strikes
south-south-west to north-north-east about 30 km east of the Batu Hijau deposit, coinciding with the north-easterly projection of the Roo Rise oceanic plateau (Fig. 1).
Geological map (a) and north-to-south cross-sections with
lithological information and grade contours (b–e) of the open pit at Batu
Hijau. The intermediate and young tonalite intruded into a volcanic lithic
breccia and the equigranular quartz diorite (a, b). Note that the extent of
the old tonalite is not displayed but is included in the intermediate
tonalite. The dashed line in panel (a) is the N–S section displayed in (b)–(e). Thin grey
lines in panel (a) indicate mine benches. Cu and Au grades (c, d) are enveloped
around the tonalites and a deep, central barren core. High-grade Cu and
Au mineralisation is cut by the young tonalite. The ratios of Cu to Au (e)
illustrate strong Au enrichment proximal to the intermediate tonalite and
Cu-dominated distal mineralisation. Map, section and grades are based on
company information from May 2016.
The hypabyssal stocks in the Batu Hijau district are intruded into an early
to middle Miocene volcano-sedimentary rock sequence (<21 Ma based
on biostratigraphy; Adams, 1984; Berggren et al., 1995) that reaches
a thicknesses of up to 1500 m in south-western Sumbawa. The low-K2O,
calc-alkaline, sub-volcanic intrusive rocks in the Batu Hijau district have
andesitic to quartz-dioritic and tonalitic compositions (Foden and Varne,
1980; Garwin, 2000) and were emplaced in several pulses during the late
Miocene and Pliocene (Garwin, 2000). Over this multi-million-year magmatic
history, a continuous geochemical evolution towards more fractionated
lithologies is indicated by whole-rock chemistry and Fe-isotopic evidence of
the magmatic rock suite in the Batu Hijau district (Garwin, 2000; Wawryk and
Foden, 2017). Within the Batu Hijau deposit, andesite porphyries and
different quartz diorite bodies are the earliest recognised stocks, whereas
three tonalite porphyries are the youngest exposed intrusions (Clode, 1999).
These tonalite porphyries, which are associated with economically important
Cu–Au mineralisation and pervasive hydrothermal alteration at Batu Hijau,
were emplaced as narrow, semi-cylindrical stocks into a broad east-north-east trending
structural dome between ∼3.9 and 3.7 Ma (Fig. 2; Garwin,
2000). Based on petrography and cross-cutting relationships, they were termed
old tonalite, intermediate tonalite and young tonalite (Fig. 3; Meldrum et
al., 1994; Clode, 1999; Setynadhaka et al., 2008).
All three tonalite intrusions are petrographically similar and are
geochemically described as low-K calc-alkaline tonalites (Idrus et al.,
2007). The least altered specimens contain phenocrysts of plagioclase,
hornblende, quartz, biotite and magnetite with or without ilmenite hosted in an aplitic
groundmass of plagioclase and quartz (Fig. 3; Mitchell et al., 1998; Clode,
1999; Garwin, 2000; Idrus et al., 2007). Notably, all three porphyry
intrusions lack potassium feldspar. Identified accessory minerals include
apatite, zircon and rare titanites. Relicts of clinopyroxene can be
identified within the tonalites. Vein density, ore grade and alteration
intensity decrease from the old to young tonalite. The old tonalite is the
volumetrically smallest, occurring mostly at the edges of the composite
stock. It can clearly be identified in drill core, where its veins are
truncated by later intrusions (Fig. 3), but it is currently not separated
from the intermediate ionalite by the mine geology department at Batu Hijau
because their phenocryst proportion is almost indistinguishable (Fig. 2). It
locally contains the highest ore grades (>1 % Cu and
>1 g t-1 Au), and its matrix is characteristically the coarsest of the
three tonalite intrusions. The intermediate tonalite is the volumetrically
largest of the three porphyry intrusions and is strongly mineralised (Fig. 2).
The intermediate tonalite is porphyritic with phenocrysts, including
characteristic euhedral quartz phenocrysts, which are <8 mm in diameter (Fig. 3b). The young tonalite is the youngest intrusive rock, and it cuts
most vein generations, ore mineralisation and alteration (Fig. 3c,
e). It is strongly porphyritic with the largest-observed phenocrysts, including
euhedral quartz phenocrysts, and contains elevated but subeconomic metal
grades (<0.3 % Cu and <0.5 g t-1 Au).
Rock specimens of the different tonalite porphyries and zircon CL
images at Batu Hijau. Mineral assemblage in all tonalites is dominated by
plagioclase, quartz and biotite. (a) Phenocrysts in the slightly
propylitically altered, pre- to syn-Cu–Au-mineralisation, equigranular old
tonalite are <3 mm. (b) Phenocrysts of the syn-Cu–Au-mineralisation,
porphyritic intermediate tonalite are <5 mm. (c) The
post-mineralisation porphyritic young tonalite contains the largest
phenocrysts (<8 mm) and is characterised by a higher abundance of
“quartz eyes”. (d) Abundant veins in the equigranular old tonalite are
truncated by the later porphyritic intermediate tonalite. (e) Strongly veined
intermediate tonalite is truncated by the barren and little-altered young
tonalite. Dashed-green lines indicate intrusive contacts. (f) Representative
zircons that display dominant oscillatory zoning and areas with little
zoning. Circles indicate domains selected for LA-ICP-MS analyses (30 µm
in diameter).
Copper and gold are systematically zoned within the deposit. High-Au zones
are tightly enveloped around the tonalite stocks, whereas high copper grades
extend further out into the volcanic lithic breccia and the equigranular
quartz diorite (Fig. 2). The lowest Cu/Au ratios occur towards and below the
current pit floor, and higher Cu/Au ratios are recorded peripheral to the
central porphyry stock and towards the upper, already-mined part of the ore
body. A positive correlation between vein density and Cu and Au contents was
described at Batu Hijau (Mitchell et al., 1998; Clode, 1999; Arif and Baker,
2004). A veins were suggested to comprise ∼80 % of all
quartz veins and contain a similar fraction of Cu (Mitchell et al.,
1998). Most earlier authors suggested that the bulk of Cu and Au was
precipitated as bornite during early A vein formation and converted to later
chalcopyrite and gold associated with AB and B vein formation (Clode,
1999; Arif and Baker, 2004; Proffett, 2009). More recent studies on vein
relationships and mineralogy using scanning electron
microscopy cathodoluminescence (SEM-CL) petrography combined with fluid
inclusion analyses suggest that Cu–Au ore mineralisation including bornite,
chalcopyrite and gold all precipitated with a late quartz generation
post-dating high-temperature A and AB vein quartz at a lower temperature
together with the formation of brittle fractures associated with thin
chlorite, white mica halos (∼ C veins and “paint veins”;
Zwyer, 2011; Schirra et al., 2019). Irrespective of the debated timing of
stockwork quartz veins and economic ore metal introduction in the old and
intermediate tonalites, the young tonalite cuts through all high-grade Cu
and Au zones, demonstrating its late, largely post-mineralisation emplacement
(Figs. 2, 3e). Therefore, the maximum duration of economic mineralisation is
bracketed by the emplacement ages of the Cu–Au-rich old tonalite predating
it and the young tonalite post-dating it.
Materials and methods
Based on detailed core logging and outcrop mapping with company geologists
in May 2016, one sample each from the old tonalite, intermediate tonalite,
young tonalite and equigranular quartz diorite was selected from
locations where the lithologies were in unequivocal relative time relationship (cross-cutting relationship; Fig. 3; see
Supplement for sample locations). Rocks were crushed and zircons
separated with conventional techniques, including Selfrag™
disintegration, panning and heavy liquid mineral separation (methylene
iodide; 3.3 g cm-3). Selected zircons were annealed for 48 h at
900 ∘C, mounted in epoxy resin and polished to reveal their
crystal interior. Polished zircons were carbon-coated and imaged using
SEM-CL (Tescan EOscan VEGA
XLSeries 4 scanning electron microscope) prior to in situ LA-ICP-MS analysis for
trace elements and U–Pb isotopes, employing a 193 nm ASI RESOlution (S155)
ArF excimer laser with a 30 µm spot diameter, 5 Hz repetition rate and
2 J cm-2 energy density coupled to an element SF-ICP-MS. A detailed
description of the method including data reduction and results on secondary
reference materials can be found in Guillong
et al. (2014) and the Supplement. Generally, at least one spot was chosen in the interior
(core) and one on the exterior (rim) part of the zircon, but up to four
individual spots were analysed per zircon (Fig. 3f) to obtain in situ
geochemical information and U–Pb dates. All 206Pb/238U dates were
corrected for initial 230Th–238U disequilibrium in the
238U–206Pb decay chain (e.g. Schärer, 1984). Ratios of
Th/U recorded by zircons cluster around 0.3–0.6, and the dates were
therefore corrected assuming a constant Th/Umelt of 2 based on
partition coefficients (0.25) by Rubatto and Hermann (2007).
Variation in the assumed Th/Umelt by ±0.5 would result in
changes in individual 238U–206Pb dates of <10 kyr, far
below analytical uncertainty.
Titanium concentrations in zircon have been calibrated as a proxy for the
crystallisation temperature of zircons (Watson and Harrison, 2005; Watson et
al., 2006; Ferry and Watson, 2007) and have been widely used in igneous and
ore deposit petrology (e.g. Claiborne et al., 2010b; Reid et al.,
2011; Chelle-Michou et al., 2014; Dilles et al., 2015; Buret et al., 2016; Lee
et al., 2017). The determination of accurate zircon crystallisation
temperatures by Ti-in-zircon thermometry (Ferry and Watson, 2007) requires
reliable estimates for the activity of SiO2 and TiO2 (aSiO2
and aTiO2) during zircon crystallisation. Based on previous studies on
porphyry deposits we utilise an aSiO2 of 1 and an aTiO2 of 0.7
(Chelle-Michou et al., 2014; Buret et al., 2016; Tapster et al., 2016; Lee et
al., 2017; Large et al., 2018), reflecting quartz and titanite saturation
(Claiborne et al., 2006; Ferry and Watson, 2007). Titanite saturation during
zircon crystallisation is ambiguous at Batu Hijau (see discussion), but
changes in the assumed aTiO2 result in systematic changes in all
zircon crystallisation temperatures and will therefore not affect the
interpretation of relative temperature changes: a change in the aTiO2
of ±0.2 would result in a variation of about ±30∘C.
Imaging by cathodoluminescence (CL), followed by low-precision but spatially resolved U–Pb dating
and geochemical microanalysis by LA-ICP-MS, was used to evaluate potential
inherited zircon populations and to select inclusion-free zircons for
subsequent dissolution and analysis by high-precision U–Pb geochronology by
CA–ID–TIMS. Selected crystals were removed from the epoxy mount and chemically
abraded (CA) for 12–15 h at 180 ∘C using techniques modified
from Mattinson (2005). Zircons were spiked with 6–8 µg of the
EARTHTIME 202Pb–205Pb–233U–235U tracer solution (ET2535;
Condon et al., 2015; McLean et al., 2015) and dissolved in high-pressure Parr
bombs at 210 ∘C for >60 h. Dissolved samples were
dried down and redissolved in 6N HCl at 180 ∘C for 12 h.
Sample dissolution, ion exchange chromatography modified from Krogh (1973)
and loading onto zone-refined Re filaments were conducted at ETH Zürich
and are described in detail by Large et al. (2018). High-precision U–Pb
isotopic data were obtained by employing thermal ionisation mass spectrometry
at ETH Zürich (Thermo Scientific TRITON Plus). Pb was measured
sequentially on a dynamic MasCom secondary electron multiplier, and U was
measured in static mode as U oxide using Faraday cups fitted with 1013Ω resistor amplifiers (von Quadt et al., 2016; Wotzlaw et al., 2017).
Data reduction and age calculation were performed using the algorithms and
software described in McLean et al. (2011) and Bowring et al. (2011). All
206Pb/238U dates were corrected for initial 230Th–238U
disequilibrium in the 238U–206Pb decay chain (e.g. Schärer,
1984) using a constant Th/U partition coefficient ratio of 0.25 (Rubatto and
Hermann, 2007), assuming that variations in Th/U of the zircons result from
different Th/U of the crystallising melt and not from variations in relative
zircon-melt partitioning of Th and U. High-precision U–Pb dates were
obtained from 45 zircons, all of which were previously analysed by LA-ICP-MS.
ResultsOptical zircon appearance and SEM-CL petrography
Zircon crystals from all three tonalite samples are colourless, euhedral to
subhedral and variable in size, with c axis lengths of 100–500 µm
and aspect ratios between 1:2 and 1:4 (Fig. 3f). Thin-section observations
reveal zircons that are enclosed by phenocrysts and also occur within the
fine-grained groundmass, suggesting protracted zircon crystallisation within
the magma until emplacement of the tonalite porphyries. Investigation of
mineral separates and mounts with a binocular microscope reveals that many
zircons contain small (≪20µm) mineral or melt
inclusions. SEM-CL imaging reveals few non-zoned and sector-zoned zircon
domains, but most zircons exhibit oscillatory zoning (Fig. 3f).
Only few broken zircon fragments could be identified from heavy mineral
separates of the equigranular quartz diorite, but these indicate originally
euhedral to subhedral shapes. Five of these broken grains, typically
<200µm long, could be identified and were mounted. Four
zircons were non-zoned, and one was oscillatory-zoned.
Spatially resolved zircon trace element composition
At Batu Hijau, zircon geochemical analyses from the three tonalites display
largely overlapping arrays and ranges for all analysed trace element
concentrations and ratios (Fig. 4). Most zircons from the tonalites display
systematically higher heavy rare earth elements (HREEs; e.g. Yb) over middle rare earth elements (MREEs; e.g. Dy) and light rare earth elements (LREEs; e.g. Nd)
contents in their rims relative to their cores (Fig. 4a). This strongly
correlates with core–rim systematics of other differentiation proxies, like
increasing Hf or decreasing Th/U (Fig. 4: Hoskin and Ireland, 2000; Claiborne
et al., 2006, 2010b; Schaltegger et al., 2009; Samperton et
al., 2015). However, some core–rim trends, especially from the young
tonalite, display increasing Th/U and decreasing Yb/Dy ratios (Fig. 4b).
Covariation diagrams (a–e) and probability density plots (f–h) of
in situ geochemical data obtained by LA-ICP-MS. Panels (a)–(c) are plotted against
Th/U as an indicator for fractionation, whereas panels (d) and (e) are plotted
against Hf as the fractionation proxy. Arrows labelled “fractional
crystallisation” indicate the approximate predicted direction zircon
geochemistry would migrate given fractional crystallisation of zircon
± apatite ± titanite ± amphibole. Arrows labelled “plag”
and “tit” point in the predicted direction of zircon geochemistry
evolution during co-crystallisation with plagioclase or titanite. Zircons
from the three tonalite porphyries are considered to have crystallised from
the same magma reservoir, whereas zircons from the equigranular quartz
diorite (purple) are unrelated (see text for discussion). Temperature lines
in panel (d) are calculated with an assumed aSiO2=1 and aTiO2=0.7 based on
Ferry and Watson (2007: see text for discussion). The crosses in the top right corners
illustrate average analytical 2σ uncertainties. Probability density
plots (after Vermeesch et al., 2013) illustrate differences between
different samples and core and rim analyses within each sample. The axes of
probability density plots in panels (f) and (g) are aligned with the axes of panels (d) and (e).
In most zircons, Ti concentrations decrease from core to rim (Fig. 4d, f).
This decrease correlates well with increasing Hf and decreasing Th/U.
Maximum and minimum Ti contents for all intrusions are ∼10 and ∼2 ppm, resulting in model crystallisation
temperatures of 770 to 650 ∘C (see methods for
details). The majority of zircons from the Batu Hijau deposit contain lower
U concentrations (<75 ppm) compared to zircons from most other
porphyry deposits (several 100 ppm), but individual zircons can contain up to
300 ppm (Fig. 4c). The zircons with high U concentrations do not correspond
to the lower-Th/U zircons but also contain high Th concentrations and cover
the whole spectra of Th/U ratios observed at Batu Hijau (Fig. 4c). The
Eu anomaly (Eu / Eu*, which is a means to quantify the negative inflexure of
the normalised rare earth element, REE, diagram), increases (Eu / Eu* decrease) with increasing Hf
concentration (Fig. 4e). Zircon analyses from the equigranular quartz
diorite plot towards the lowest Hf, Yb / Dy, Yb / Nd and Eu / Eu* but highest Th/U
and Ti end of the trends displayed by all tonalite zircons (Fig. 4).
Probability density functions (Vermeesch, 2012) are used to test for
statistically significant differences between the overlapping zircon
populations of the different tonalites and between core and rim analyses
from the same tonalite porphyries (Fig. 4f, g, h). The Hf and Ti
concentrations as well as the Eu anomaly of zircons display overlapping
distributions for the intermediate and young tonalites. The old tonalite
zircon population peaks at higher Ti concentrations and Eu / Eu* as well as
lower Hf concentrations than the younger tonalites. Core and rim analyses
from zircons of the old tonalite document decreasing Ti and Eu / Eu* together
with increasing Hf concentrations from cores to rims. Hafnium contents of
the rim analyses peak at higher concentrations than the core analyses within
the intermediate and young tonalite, whereas Eu / Eu* displays the opposite
effect. Populations illustrating titanium concentrations of the two younger
tonalites, however, display no systematic changes between core and rim.
CA–ID–TIMS geochronology
We dated 16 zircons of each the old and intermediate tonalite and 13 zircons
of the young tonalite by high-precision CA–ID–TIMS geochronology. The
youngest zircon each of the old, intermediate and young tonalite yields
230Th-238U disequilibrium-corrected 206Pb/238U
zircon dates of 3.736±0.023, 3.697±0.018 and 3.646±0.022 Ma (individual grain ±2σ, Fig. 5). We interpret
these dates as the time of respective porphyry emplacement based on the
assumption that zircons grew at depth up to the point that the magma cooled
rapidly upon injection into the sub-volcanic environment (cf. Oberli et al.,
2004; Schaltegger et al., 2009; von Quadt et al., 2011; Samperton et al.,
2015; Large et al., 2018). Reproducibility of the individual dates is
corroborated by reproducible dates for all analysed CA–ID–TIMS standards
analysed during the time of analyses of the presented samples.
Standards include the Aus_Z7_5 (von Quadt et
al., 2016), which contains similarly low amounts of radiogenic Pb (0.5–4 pg) and is of Pliocene age.
Despite the small differences in emplacement age, the age sequence is
consistent with field observations documenting the emplacement sequence
(Fig. 3). The time intervals between emplacement of the old and intermediate
tonalite and between the intermediate and young tonalite can therefore be
constrained to 39±29 and 51±28 kyr, respectively. The
minimum duration of zircon crystallisation, as recorded by the oldest and
youngest zircon of each sample, spreads over 246±28, 212±32 and 171±26 kyr for the old, intermediate and young tonalite
(Fig. 5). The overall duration of recorded zircon crystallisation is 336±27 kyr. Using the youngest zircon population rather than the
youngest individual zircon as the best approximation for porphyry
emplacement (cf. Samperton et al., 2015; Buret et al., 2016; Tapster et al.,
2016) would result in slightly older emplacement ages (∼20 kyr) but nearly identical durations of zircon crystallisation and time
intervals between porphyry emplacement events (see Supplement).
Our high-precision CA–ID–TIMS dates precisely constrain protracted zircon
crystallisation over several hundred thousand years and successive emplacement of the three
porphyritic tonalite bodies at Batu Hijau within 90±32 kyr.
Ratios of Th/U obtained by CA–ID–TIMS analyses on the same sample volume
illustrate no systematic variation with time. Values vary inconsistently
between 0.4 and 0.6 over the whole recorded time interval (Fig. 6).
High-precision U–Pb CA–ID–TIMS zircon dates from the three
tonalite porphyries. Vertical bars are individual analyses including
analytical uncertainty (2σ). The youngest crystallisation age is
used as the best approximation for porphyry emplacement. The extended range
in zircon crystallisation ages in each sample indicates protracted
crystallisation. The yellow box indicates maximum duration of ore formation as
constrained by the emplacement age of the old tonalite and the young
tonalite. The grey box illustrates the duration of zircon crystallisation
recorded by CA–ID–TIMS geochronology. The vertical bars in the grey box are
emplacement ages of the tonalites, demonstrating >200 kyr of
zircon crystallisation before emplacement of the first porphyry intrusion
and start of Cu–Au mineralisation.
In situ U–Pb geochronology
Trace element and U–Pb isotopic data were obtained for each LA-ICP-MS spot
(Fig. 7) prior to CA-IC-TIMS dating. Low uranium concentrations and the
young ages of the analysed zircons resulted in high individual uncertainties
for individual in situ U–Pb dates (mean: 10 %; minimum: 3 %; maximum:
41 %). All individual spot analyses of the three tonalites that were not
discarded due to common Pb or strong discordance yield Pliocene dates (2.98±1.06–4.95±0.54 Ma; Fig. 7) with no apparent inherited
zircons. All in situ dates of individual samples illustrate continuous
arrays and do not indicate more than one population of zircons per sample
(Fig. 7). Weighted means of all zircon analyses from each tonalite are 3.879±0.027, 0.065, 0.32 (n=207; mean square weighted deviation, MSWD =2.1), 3.778±0.023,
0.061, 0.62 (n=189, MSWD =2.5) and 3.751±0.023, 0.060, 0.29 Ma (n=158, MSWD = 2.6) from oldest to youngest (Fig. 7), where the
stated uncertainties are the standard error of the weighted mean, the
standard error including an external uncertainty of 1.5 % as suggested by
Horstwood et al. (2016) to incorporate excess variance, and the standard
deviation of zircon dates from each sample. These weighted averages do not
overlap within uncertainty with the emplacement ages constrained by
CA–ID–TIMS but overlap with the mean of the respective population. The few
in situ analyses (n=8) on zircons from the diorite result in overlapping
late Miocene dates. The weighted mean of all LA-ICP-MS analyses of the
equigranular diorite results in an apparent age of the equigranular diorite
of 6.37±0.40, 0.41, 0.37 Ma (n=8, MSWD =0.46).
Th/U ratios plotted against time. Both values obtained from
CA–ID–TIMS analyses of the same sample volume.
Garwin (2000) previously published SHRIMP U–Pb data on zircons from the Batu
Hijau tonalites. Similar to the LA-ICP-MS analyses in this study, individual
uncertainties of the dates were elevated (0.12–0.30 Ma, ∼5 %–10 % uncertainty) due to low U concentrations and the young zircon
crystallisation ages. As all dates of each sample statistically formed
single populations (Supplement), weighted means were calculated
of all zircons of a sample; these were interpreted as the intrusion
ages of the tonalites by Garwin (2000). The reported zircon dates were not
corrected for 230Th–238U disequilibrium. For comparability we will
only consider zircon dates that are corrected for initial Th/U
disequilibrium (Schärer, 1984; for details consult the Supplement). Correction increases the individual zircon dates by
∼60–100 kyr, and recalculation of the weighted mean
averages and standard errors results in dates of 3.74±0.14 Ma (MSWD
=1.2, n=8), 3.843±0.094 (MSWD =1.2, n=18) Ma and 3.81±0.2 Ma (MSWD =2.35, n=7) for the old, intermediate and young
tonalite, respectively.
In situ U–Pb geochronology by LA-ICP-MS of zircons from the
equigranular quartz diorite (a), the old tonalite (b), the intermediate
tonalite (c) and the young tonalite (d). Vertical lines illustrate individual
U–Pb dates including analytical uncertainty (2σ). As no zircon
populations can be separated, the weighted mean average of all analyses is
calculated. Standard error (2SE, lightest grey), standard error +1.5 %
(light grey) to incorporate excess variance (Horstwood et al., 2016) and
standard deviation of all individual dates (dark grey) are calculated and
plotted. Duration of zircon crystallisation as obtained by CA–ID–TIMS is
illustrated as a box for comparison. Lower boundary of the coloured box
indicates youngest CA–ID–TIMS date or the emplacement age. Note the
different vertical scale in panel (a). Zircon dates from the equigranular quartz
diorite are ∼2 Myr older than zircons from the tonalites.
DiscussionTiming and duration of magmatic and hydrothermal processes leading to
porphyry Cu formation
The three tonalite intrusions each record protracted zircon crystallisation
over ∼200 kyr, as resolved by high-precision ID-TIMS
geochronology. The older zircon dates from the young and intermediate
tonalites overlap with the younger zircons of the older intrusion(s) (Fig. 5). This overlap, together with the largely overlapping trace element
systematics recorded by zircons, is used here to infer zircon
crystallisation within the same mid- to upper crustal magma reservoir that
sourced magmas forming the three tonalitic porphyry stocks but most likely
also volatiles and metals to form the porphyry Cu–Au deposit. High-precision
geochronology records a total duration of zircon crystallisation of 336±27 kyr, which is also a minimum estimate for the lifetime of the
deeper reservoir underlying Batu Hijau. The first exposed and highly
mineralised tonalite intrusion (old tonalite) was injected into the upper
crust 246±28 kyr after the onset of zircon crystallisation.
Emplacement of the three tonalites occurred within 90±32 kyr.
Emplacement of the old tonalite was followed by the emplacement of the
intermediate tonalite after 39±29 kyr, and the young tonalite was
emplaced after a further 51±28 kyr.
The maximum duration of ore formation is defined by the time span between the
emplacement of the pre- to syn-mineralisation old tonalite and the
post-mineralisation young tonalite (Fig. 3d, e) and can be therefore
constrained to less than 122 kyr. This maximum duration is in good agreement
with previous geochronological studies indicating timescales of ore
formation from <100 to <29 kyr (Figs. 8, 9; von Quadt et
al., 2011; Buret et al., 2016; Tapster et al., 2016). It is also coherent with
results from thermal modelling studies (Cathles, 1977; Weis et al., 2012) and
modelling of diffusive fluid–rock equilibration (Cathles and Shannon,
2007; Mercer et al., 2015; Cernuschi et al., 2018) suggesting timescales of
ore formation between a few thousand years and 100 kyr. Strongly elevated Cu and
Au grades in the old tonalite and somewhat lower, but still economic, grades
within the intermediate tonalite (Clode, 1999; Garwin, 2000; Arif and Baker,
2004) together with cross-cutting relationships (Fig. 3d, e) indicate that
mineralisation occurred within at least two but possibly more pulses: (i) one strong mineralisation pulse associated with or slightly post-dating the
emplacement of the old tonalite but predating the injection of the
intermediate tonalite (Fig. 3d) and (ii) a second pulse is bracketed by the
intrusion of the intermediate and the young tonalite (Fig. 3e). More than
one episode of mineralisation is also inferred based on detailed mineralogy
and vein petrography (see Geological background section; Arif and Baker, 2004; Zwyer,
2011). This further strengthens the hypothesis that individual ore-forming
hydrothermal pulses are relatively short events, possibly on the millennial
or sub-millennial scale (Cathles, 1977; Weis et al., 2012; Mercer et al.,
2015), but that the formation of large economic Cu–Au deposits occurs in
several pulses over tens of thousands of years but ≤100 kyr (von Quadt
et al., 2011; Weis et al., 2012; Cernuschi et al., 2018).
Reconstructing the chemical and physical evolution of a porphyry-forming
magma reservoir
Th/U ratios and Hf concentrations are commonly used as proxies for the
degree of crystal fractionation within a magma reservoir (e.g. Claiborne et
al., 2006, 2010b; Samperton et al., 2015). The decreasing
Th/U ratios and increasing Hf concentrations between samples and from cores
to rims (Fig. 4) are indicative of progressive melt differentiation during
zircon crystallisation. The good correlation of these melt evolution proxies
with decreasing Ti contents (Fig. 4) further suggests progressive cooling
during differentiation. Ratios of HREE over MREE or LREE (e.g. Yb/Dy, Yb/Nd)
can be utilised to make inferences about the co-crystallising mineral
assemblage. Titanite for example preferentially depletes the melt in MREE, resulting in distinct trace element patterns recorded by co-crystallising
zircon (e.g. Reid et al., 2011; Wotzlaw et al., 2013; Samperton et al.,
2015; Loader et al., 2017). The systematically higher HREE (e.g. Yb) over
MREE (e.g. Dy) and LREE (e.g. Nd) contents in the rims of most zircons
relative to their cores (Fig. 4a) thus indicate zircon crystallisation from
a fractionally crystallising magma with co-crystallisation of minerals that
preferentially incorporate MREE and LREE (e.g. apatite, titanite). At Batu
Hijau apatites were petrographically identified, whereas magmatic titanite
occurs very subordinately. The apparent lack of magmatic titanite is unusual
as it is reported as a common accessory phase in many other porphyry Cu
deposits (e.g. Bajo de la Alumbrera, El Salvador, Ok Tedi, Oyu Tolgoi). The
absence of euhedral titanite within the mineral separates could be the
result of dissolution during intense hydrothermal alteration (van Dongen et
al., 2010).
Trace element compositions of zircons from the equigranular quartz diorite
suggest crystallisation within a hotter and less evolved magma than the
zircons from the tonalites (Fig. 4). In principle, this might indicate that
all zircons analysed in this study have crystallised from the same
reservoir, where the zircons from the equigranular quartz diorite reflect
the earliest crystallised zircons from least evolved melt. However, the
>2 Myr time gap is longer than the thermal lifetime of any
recognised upper-crustal magmatic body (e.g. Schoene et al., 2012; Wotzlaw et
al., 2013; Caricchi et al., 2014; Samperton et al., 2015; Eddy et al.,
2016; Karakas et al., 2017) and longer than considered possible based on
thermal modelling (Jaeger, 1957; Annen, 2009; Barboni et al., 2015). We
therefore consider the zircons within the equigranular diorite to be part of
a separate crustal magmatic system not directly related to the ore-forming
system that sourced the three tonalitic intrusions.
Trace element populations of zircons from the three tonalites demonstrate
that the crystallising magma at the time of emplacement of the old tonalite
was hotter and less fractionated (Fig. 4) than at the time of emplacement of
the younger intermediate and young tonalite (i.e. 39±29 and 90±32 kyr after emplacement of the old tonalite, respectively). The good
correlation of proxies indicating progressive differentiation (Th/U and Hf)
with decreasing Ti concentrations (Fig. 4d) indicates that the magma
reservoir cooled during concurrent crystallisation and melt evolution.
In situ analyses of cores and rims are evidence of an evolving magma
reservoir over the course of individual zircon crystallisation (decreasing
Hf; Fig. 4h). Core–rim systematics of zircons from the old tonalite further
demonstrate cooling during protracted zircon growth (Fig. 4f). Rarely
recorded coherent zircon trace element systematics recording melt
differentiation over time are commonly inferred to result from zircon
crystallisation within a homogeneous magma that evolved continuously (e.g.
Wotzlaw et al., 2013; Large et al., 2018). The lack of such systematic
temporal changes in the chemistry of the zircons (Fig. 6) indicates that the
magma reservoir at Batu Hijau was not evolving homogenously. This could be
explained by incremental recharge or assembly of the magma reservoir.
However, this would imply at least partial resetting of the intra-grain
systematics recorded in zircons from the old tonalite (Buret et al.,
2016; Large et al., 2018). To explain the intra-grain and inter-sample
systematics but absence of temporal trends (Figs. 4, 6), we favour different
degrees of crystallinity in the magma reservoir. Overall, the reservoir is
generally hotter and less evolved at the time of emplacement of the old
tonalite than thereafter (Fig. 4). We therefore suggest that the magma
reservoir underlying Batu Hijau progressively but heterogeneously cooled and
crystallised over at least 246±28 kyr, with potential incremental
recharges until emplacement of the old tonalite.
A change from a differentiating, crystallising and cooling magma reservoir
to a state of chemical and thermal stability is recorded between emplacement
of the old and young tonalite (separated by 90±32 kyr) as
demonstrated by the trace element systematics of the intermediate and young
tonalite porphyries. The indistinguishable, highly fractionated and low-temperature zircon characteristics (Fig. 4) indicate that the magma
reservoir remained in near-steady-state conditions between emplacement of
the old and young tonalite as coherent intra-grain systematics are not
pronounced (Hf) or are absent (Ti) in zircons from the younger tonalites (Fig. 4f, h).
Irregular zircon trace element systematics in other intrusive magmatic
settings have been associated with crystallisation in non-homogenised and
small melt batches sometimes, with contemporaneous incremental magma addition
to the mushy magma reservoir (e.g. Schoene et al., 2012; Buret et al.,
2016; Tapster et al., 2016). Geochemically similar zircon chemistries of the
intermediate and young tonalite could also result from chemical stability as
the magma reservoir reached the “petrological trap” at a crystallinity of
∼55 %–65 % (Caricchi and Blundy, 2015), where the crystal
fraction does not change over a broad temperature interval. Rim analyses
that plot more outside the mineral co-crystallisation trends than the respective
core analyses (Fig. 4) could suggest late-stage crystallisation within a
nearly solidified magma that can be characterised by unsystematically
variable trace element systematics (Buret et al., 2016; Lee et al., 2017).
Alternatively, they could indicate thermal and possibly chemical
rejuvenation of the magma (Buret et al., 2016). The latter would help
explain the recorded thermal stability over tens of thousands of years. It is not
possible to unambiguously identify one of the two mechanisms as dominant, and
a concurrence of both is feasible. We therefore propose that in between
emplacement of the old and young tonalite the underlying magma reservoir was
in a thermally and chemically stable and crystal-rich state and was most
likely affected by incremental magma recharge or underplating.
Our data of a porphyry-Cu-fertile magmatic system constrain a heterogeneous
magma reservoir that was initially dominated by cooling and melt
differentiation and evolved into a thermally and chemically stable,
crystal-rich magma that possibly experienced incremental recharge. The
likely transitional change of reservoir behaviour can be temporally
constrained to have occurred between emplacement of the old and young
tonalites and coincides with the formation of a world-class Cu–Au reserve.
This suggests that porphyry Cu–Au deposits form after a few hundred thousand years of
cooling and crystallisation, potentially within an originally melt-rich
magma reservoir.
Different timescales of processes related to porphyry Cu–Au
ore formation
To date no clear relationship between the duration of magmatic–hydrothermal
activity and the size of porphyry deposits can be identified from studies
applying high-precision CA–ID–TIMS geochronology. Comparison of published
datasets (Buret et al., 2016; Tapster et al., 2016; Large et al., 2018)
reveals maximum durations of metal forming events of between tens of thousands of years and
105 yr (Fig. 9). Although these studies are so far constrained to
deposits of <10 Mt of contained Cu, they range over at least 1 order
of magnitude in size (Koloula vs. Batu Hijau). A correlation between the
duration of the mineralising or magmatic event and the total mass of deposited
copper had been previously suggested based on compilations of different
geochronological datasets (Chelle-Michou et al., 2017; Chiaradia and
Caricchi, 2017; Chelle-Michou and Schaltegger, 2018; Chiaradia, 2020). High
durations of ore formation (>1 Myr) were suggested based on Re–Os
geochronology on molybdenite at the giant porphyry deposits and deposit
clusters in Chile (>50 Gt Cu; El Teniente, Cannell et al., 2005
and Maksaev et al., 2004; Rio Blanco, Deckart et al., 2012; and
Chuquicamata, Barra et al., 2013). Mineralising timescales of copper (and gold) were calculated by subtracting the youngest from the oldest Re–Os date.
However, recent Re–Os dates from El Teniente (Spencer et al., 2015) indicate
that the spread in dates is more consistent with several short (≤200 kyr) hydrothermal events separated by hiatuses of ∼500 kyr.
Thus, the large tonnage of these deposits could be the result of the
superimposition of several ore-forming mid- to upper crustal magmatic
systems. As the correlation of deposit size and timescales of shallow
magmatic–hydrothermal systems is currently ambiguous, we would argue that
other variables could be the dominant factors controlling the deposit size,
such as magma reservoir size, magma or fluid chemistry, fluid release, and
focusing mechanisms or the metal precipitation efficiency.
Zircon crystallisation over ∼200 kyr before the onset of
porphyry ore formation recorded at Batu Hijau is consistent with other
high-precision geochronological studies on porphyry deposits (Figs. 8, 9:
Buret et al., 2016; Tapster et al., 2016; Large et al., 2018). The lack of
variation observed in these deposits suggests the necessity of a long-lived
and continuously crystallising magma reservoir preceding economic ore
formation. The recorded ∼200 kyr of protracted zircon
crystallisation could indicate a period of volatile enrichment as a result
of fractional crystallisation and cooling of the magma reservoir before
porphyry emplacement.
Compilation of high-precision datasets on several pre-, syn- and
post-ore intrusions at magmatic–hydrothermal Cu–Au deposits. Data for Ok
Tedi, Bajo de la Alumbrera and Koloula are from Large et al. (2018) Buret et
al. (2016) and Tapster et al. (2016), respectively. Coloured vertical bars
are individual analyses including analytical uncertainty (2σ).
Intrusions are categorised as pre-ore, pre-/syn-ore and post-ore intrusion.
Decreasing deposit size from left to right (tonnages from Cooke et al.,
2005).
The geochronological data from the Batu Hijau district are further evidence
that rapid porphyry emplacement and ore formation (<100 kyr) are the
product of a longer-term evolution (a few 100 kyr) of a large magma reservoir
underlying the porphyry deposit that is the main driver of ore formation
(von Quadt et al., 2011; Chelle-Michou et al., 2014; Buret et al.,
2016, 2017; Tapster et al., 2016; Large et al., 2018). Magma
reservoirs capable of forming porphyry deposits are in turn part of a
longer-term (several Myr) evolution of lithosphere-scale magma systems
(Sasso, 1998; Rohrlach et al., 2005; Longo et al., 2010; Rezeau et al., 2016),
which is consistent with the ≫2 Myr record of
intrusive rocks preceding porphyry emplacement and ore formation recorded in
the Batu Hijau district (Garwin, 2000; Wawryk and Foden, 2017).
Overview of high-precision geochronology studies on porphyry
deposits. Data for Ok Tedi, Bajo de la Alumbrera and Koloula are from Large et al. (2018), Buret et al. (2016) and Tapster et al. (2016), respectively. Coloured
vertical bars are emplacement ages of different intrusive rocks described
from these deposits. Intrusions are categorised as pre-ore, pre- and syn-ore, and
post-ore intrusion. Deposit size decreases from left to right (tonnages
from Cooke et al., 2005). Diagrams are aligned so that the onset of zircon
crystallisation overlaps in all deposits. Grey bars indicate the recorded
duration of zircon crystallisation. Yellow bars illustrate the maximum durations
of total ore formation or individual ore formation pulses. The yellow bar fading
out downwards indicates the absence of a post-ore intrusion and the
inability to constrain the total duration of ore formation. Note that we
excluded the sample X176 from Koloula as it is not related to magmatic
history leading to ore formation (Tapster et al., 2016).
Resolving lower crustal magmatic processes from zircon petrochronology
The lack of inheritance within the zircon record at Batu Hijau suggests that
the crustal magmas experienced very minor crustal assimilation. Typically,
magmas that are associated with porphyry ore formation contain diverse
suites of inherited zircons (e.g. Tapster et al., 2016; Lee et al.,
2017; Large et al., 2018), which have been interpreted to represent extended
interaction with arc lithologies (Miller et al., 2007). This apparent lack
of crustal contamination is consistent with the juvenile isotopic signatures
(Pb–Pb, Sm–Nd, Rb–Sr) of intrusions in the Batu Hijau district (Garwin,
2000; Fiorentini and Garwin, 2010). The juvenile and “porphyry-fertile”
magmas at Batu Hijau have been explained by asthenospheric mantle upwelling
through a tear in the subducting slab that resulted from the collision with
the Roo rise (Garwin, 2000; Fiorentini and Garwin, 2010). This would also
explain why the only mined porphyry deposit in the Sunda–Banda arc (Batu
Hijau) and the most promising prospects (Elang and Tumpangpitu) are located
above the inferred margin of the subducting Roo rise (Fig. 1).
The formation of porphyry Cu(–Au) deposits has been commonly associated with
the fractionation of amphibole ± garnet in thickened crust
(e.g. Rohrlach et al., 2005; Lee and Tang, 2020) within lower crustal magma
reservoirs that are active over several million years (Rohrlach et al., 2005). Zircons
have been suggested to directly track this extended lower crustal history
(Rohrlach et al., 2005). At Batu Hijau no zircon was identified that
crystallised in a resolvable way before the main crystallisation period, which we
consider to have occurred in the mid- to upper crust (Fig. 5, and discussion
above). Non-zoned cores surrounded by oscillatory zoned rims (Fig. 3f) could
be interpreted to reflect a two-stage crystallisation process; however, the
depth of these two processes cannot be resolved, and they would have occurred
within the few hundred thousand years of recorded zircon crystallisation (Fig. 5). As most
crystals within a mount are not polished exactly to their centre, the
non-zoned cores could equally likely represent a polishing effect where the
surface of one zone appears as an non-zoned core. Therefore, it is highly
speculative to directly relate zircon textures to a locus or style of zircon
crystallisation.
In the case of Batu Hijau, petrochronological data were used to reconstruct
the mid- to upper crustal magma evolution, but the data can only provide
indirect information about the lower crustal processes involved in the
formation of the deposit. For example, the overall elevated Eu / Eu* of the
investigated zircons (0.4–0.7; cf. Loader et al., 2017) could be the
result of amphibole fractionation in the lower crust, which would have
relatively enriched the residual melt Eu compared to the other REE. This
would be analogous to elevated whole-rock Sr / Y ratios in exposed rocks being
indicative of the lower crustal fractionating assemblage (Rohrlach et al.,
2005; Chiaradia, 2015). The intra-crystal and intra-sample trends of
decreasing Eu / Eu* discussed above describe the evolution within the mid- to
upper crustal magma reservoir that was dominated by plagioclase
crystallisation and do not reflect any lower crustal process. Zircon can
thus directly record the mid- to upper crustal magma evolution, but the
information about lower crustal processes is limited to potentially
identifying the chemistry of melt and magma that was injected from below
into the mid- to upper crust, where zircon started crystallising.
An assessment of the accuracy and precision of CA–ID–TIMS and in situ
U–Pb zircon geochronology
The U–Pb dataset from Batu Hijau allows a critical comparison of the two
zircon U–Pb geochronology techniques (LA-ICP-MS, CA–ID–TIMS) that have
different analytical precision and can analyse samples on varying spatial
scales. Previous investigation of the same lithologies by SHRIMP (Garwin,
2000) allows further comparison. The spatially resolved and fast in situ
U–Pb geochronology techniques – LA-ICP-MS or secondary-ion mass spectrometry (SIMS)–SHRIMP – allow the
investigation of different crystal domains, whereas the much more
time-consuming CA–ID–TIMS analysis of zircons or zircon fragments provides
the highest analytical precision. The in situ techniques can discriminate
between different zircon populations within single crystals (e.g.
inheritance), whereas CA–ID–TIMS geochronology allows for an analytical precision for individual grains that is more than 10 times better, which is required
to resolve rapid geochronological events. To increase precision of the
in situ techniques, large numbers of individual dates that are considered to
represent the same geological event are commonly used to calculate a
weighted mean date and standard error of the mean (Wendt and Carl, 1991). On
the other hand, the CA–ID–TIMS community has started to measure only small
zircon fragments to increase spatial resolution (e.g. Samperton et al.,
2015; Smith et al., 2019). Here, the comparison of the different U–Pb zircon
techniques applied to the same rock suite allows an assessment of the
accuracy of the techniques and of the effect of statistical treatment on the
accuracy and precision of the different techniques.
At Batu Hijau, the youngest individual CA–ID–TIMS U–Pb date of each sample
is used as our best estimate for the emplacement age of the respective
porphyry based on the low number of analyses and high ratio of
crystallisation duration to individual uncertainty (Keller et al., 2018).
The resulting porphyry emplacement ages are 3.736±0.023, 3.697±0.018 and 3.646±0.022 Myr for the old, intermediate and young
tonalite, respectively (Fig. 5). Other statistical means to determine the
emplacement ages would be the calculation of a weighted mean for the
youngest zircon population (e.g. Buret et al., 2016) or a stochastical
sampling approach (Keller et al., 2018). We calculated each alternative and
found that the emplacement ages overlap within uncertainty so that the
timescales and conclusions derived from this study remain identical (see
Appendix). The extended range of concordant zircon dates obtained by
CA–ID–TIMS does not allow us to distinguish between different stages of zircon
crystallisation within each sample (e.g. inherited vs. autocrystic), but the
common geochemical trends support crystallisation within one common magma
reservoir (see above). Thus, the range in zircon dates preceding emplacement
is interpreted to represent zircon crystallisation within the underlying
source magma reservoir over parts or, depending on the onset of zircon
saturation, the entirety of its lifetime. The total recorded duration of
zircon crystallisation is 336±27 kyr.
Even more so than the CA–ID–TIMS dates, in situ analyses by LA-ICP-MS
illustrate an extended range of zircon dates that cannot be separated into
different stages of zircon crystallisation. However, the span in zircon
dates is about a magnitude higher for the in situ analyses (1.41±0.5–2.1±1.1 Myr) than that obtained by CA–ID–TIMS (0.171±0.026–0.246±0.028 Myr). It could be argued that such LA-ICP-MS data in isolation might indicate an extended period of zircon crystallisation not covered by
CA–ID–TIMS data, potentially due to sampling bias or by one sample-set being
inaccurate, but we suggest (see Sect. 5.6 below) that the span within the
in situ data is the result of analytical scatter and potentially minor
amounts of Pb loss or common Pb.
Sampling bias in the selection of the zircons for CA–ID–TIMS geochronology
can be excluded as the analyses were conducted on chemically abraded zircons
(Mattinson, 2005) that cover the oldest and youngest dates obtained by
LA-ICP-MS (Fig. 10). High accuracy of both CA–ID–TIMS and LA-ICP-MS
datasets is suggested by routine measurements of secondary standards
during the LA-ICP-MS analytical run (see Supplement) and regular
measurements of zircon standards by CA–ID–TIMS over the period of data
acquisition including the Pleistocene Aus_Z7_5
(von Quadt et al., 2016; Wotzlaw et al., 2017). The distributions of the
zircon dates of each sample, as illustrated by probability density plots
(Fig. 11), illustrate that the peak of the LA-ICP-MS and SHRIMP dates falls
within the mean of zircon crystallisation as defined by the CA–ID–TIMS
dataset. This suggests that all datasets are accurate but that the in situ
data display more scatter and lower precision. LA-ICP-MS analyses record
younger zircon dates for core analyses than rim analyses in 17 of 47 cases;
however the LA-ICP-MS dates for core and rim always overlap within
uncertainty. Direct comparison of U–Pb dates from the same zircon crystals
by the two techniques (Fig. 10) reveals that the less-precise LA-ICP-MS data
are not correlated with the more precise TIMS ages, and the suggested dates
from the two techniques do not overlap within uncertainty in some cases
(6 in 47 cases for rim analyses; Fig. 10b). This could indicate that uncertainties
calculated for the LA-ICP-MS data have been underestimated in relation
to the achieved precision of the technique. However, due to the high number
of analyses it is more likely that it is purely an effect of analytical
scatter, where 5 % of the data do not fall within the 95 % confidence
interval. This is corroborated by ∼7 % (39/554) of
LA-ICP-MS dates not overlapping with the minimum overall duration of zircon
crystallisation identified by CA–ID–TIMS dates from all porphyries (336±27 kyr). Additionally, minor amounts of Pb loss or common Pb not
identified during data-screening could account for some older and younger
outliers, but the overlapping peaks of the in situ populations and the mean
of CA–ID–TIMS dates support no systematic bias of the bulk population to
younger or older dates. It is therefore concluded that all three techniques
are accurate and represent the ∼300–350 kyr of zircon
crystallisation. The high number of analyses obtained by LA-ICP-MS together
with the lower-precision results in extreme outliers that extend the
apparent duration of zircon crystallisation but can be regarded purely as a
statistical sampling result that does not indicate a more extended duration
of zircon crystallisation. Therefore, we consider alternative methods of
estimating age uncertainties in the following section.
Comparison of in situ LA-ICP-MS dates and CA–ID–TIMS dates on the
same zircons. In the upper panel each CA–ID–TIMS date is aligned with the rim
(filled) and core (empty) LA-ICP-MS date of the same zircon. Coloured bars
indicate individual CA–ID–TIMS analysis, including analytical uncertainty
(2σ). Downward-pointing black arrows indicate that core analyses are
older than rim analyses of the respective zircon, whereas upward-pointing red arrows indicate the opposite. Note that CA–ID–TIMS dates can be
plotted several times, with core and rim analyses of the same zircon. The lower panel compares the CA–ID–TIMS date with the respective rim analysis.
Determining geological ages, uncertainties and rates from in situ U–Pb
data
Understanding the timing of magma emplacement, crystallisation or eruption
is essential for determining dates and rates of magmatic processes and those
directly related to or bracketed by them. Where high-precision CA–ID–TIMS data
are not available, porphyry emplacement ages are commonly inferred by
calculating a weighted mean and standard error from the youngest overlapping
population of in situ U–Pb dates (e.g. Correa et al., 2016; Rezeau et al.,
2016; Lee et al., 2017). In the case of Batu Hijau such a calculation would
include all LA-ICP-MS zircon dates for each sample as there is no apparent
reason to exclude parts of the dataset due to inheritance, common Pb or Pb
loss (Fig. 7). The resulting weighted mean dates for the old, intermediate
and young tonalite are 3.879±0.027/0.064 (MSWD =2.1, n=207),
3.783±0.023/0.061 (MSWD =2.5, n=189) and 3.751±0.023/0.060 (MSWD =2.6, n=158), where the first stated uncertainty is
the standard error including internal uncertainties and those associated
with tracer calibration (Schoene, 2014), and the second includes the added
1.5 % external uncertainty as suggested by Horstwood et al. (2016) to
account for excess variance. The MSWD for each dataset (2.1–2.6) is
elevated in respect to the sample size (n=150–200) based on the
formulation by Wendt and Carl (1991). This suggests either an
underestimation of the individual uncertainties or that the data do not
represent a normal distribution, e.g. by prolonged zircon crystallisation.
However, there is no obvious treatment of the data to obtain more
appropriate MSWDs. Under these conditions weighted means and standard errors
should not be considered geologically meaningful according to Wendt and
Carl (1991), but we nevertheless calculate these numbers to illustrate a
few points below. Analogously, the weighted mean and standard error of all
zircons analysed by SHRIMP from each sample results in weighted means of
3.74±0.14 Myr (MSWD =1.2, n=8), 3.843±0.094 Myr (MSWD =1.2, n=18) and 3.81±0.2 Myr (MSWD =2.35, n=7) for the
old, intermediate and young tonalite, respectively (Fig. 11). The weighted
means of the different tonalites obtained by LA-ICP-MS would be in
accordance with cross-cutting relationships, whereas the SHRIMP dates
overlap within uncertainty. The calculated standard errors for the LA-ICP-MS
dates are significantly smaller than for the SHRIMP data. The decrease in
the standard errors is directly correlated with the increasing sample size
(Wendt and Carl, 1991; McLean et al., 2011b), implying that a comparably high
number of SHRIMP analyses would result in similarly low standard errors.
Irrespective of the different standard errors, the calculated weighted means
by SHRIMP and LA-ICP-MS overlap within uncertainty, thus seemingly
suggesting that both are accurate or similarly inaccurate (see below).
At Batu Hijau, emplacement ages determined by CA–ID–TIMS geochronology are
systematically younger than the weighted mean dates calculated from in situ
data (100–150 kyr, except CA–ID–TIMS and SHRIMP for the old tonalite), and
the emplacement ages determined by CA–ID–TIMS do not overlap with the
LA-ICP-MS mean ages within their attributed uncertainties (Fig. 11). Indeed,
disparities between different U–Pb datasets on the same porphyry samples
have been noted in several studies comparing high-precision CA–ID–TIMS data
with in situ data (von Quadt et al., 2011; Chiaradia et al.,
2013, 2014; Chelle-Michou et al., 2014; Correa et al., 2016).
As there is no evidence for any systematic errors jeopardising the accuracy
of any of the three methods in this study, all methods are considered
accurate, and the reason for apparent discrepancy must lie in the geological
interpretation of the statistical uncertainties.
Probability density plots for the geochronology data for each
analytical technique. All dates of each technique are combined in panel (a). Plots
in panels (b), (c), and (d) are constructed from the data of the old, intermediate and
young tonalite. Dashed lines indicate the youngest and oldest zircon
crystallisation age as determined by CA–ID–TIMS for the respective
investigated dataset. Weighted means, standard error, standard error +
1.5 % (Horstwood et al., 2016) and standard deviation are shown by bars with
three colours to the right of each diagram. These are identical to those in
Fig. 5.
The protracted zircon crystallisation identified at Batu Hijau has broader
implications for the determination of magma emplacement, crystallisation or
eruption ages. Extended magma reservoir lifetimes are not unique to Batu
Hijau but a commonly described feature (e.g. Miller et al., 2007; Claiborne
et al., 2010a; Reid et al., 2011; Buret et al., 2016). A weighted mean is a
measure to quantify the mean of a population while emphasising the
importance of values with low uncertainties over those with high
uncertainties (Reiners et al., 2017) and is only valid in cases where the
data are normally distributed around one expected value (Wendt and Carl,
1991). This is rarely the case when investigating geological processes, and
indeed the presented in situ datasets record protracted zircon
crystallisation (>300 kyr) in the magma reservoir that results
in zircon population distributions that cannot be easily defined
statistically (e.g. by a normal distribution; Figs. 5, 7; cf. Keller et al.,
2018). The calculated weighted mean thus does not represent the porphyry
emplacement age but the average zircon crystallisation. This is corroborated
by the weighted means of the LA-ICP-MS and SHRIMP dates approximately
describing the mean of the zircon populations defined by CA–ID–TIMS (Fig. 11). Therefore, the calculated weighted mean dates of datasets with a large
number of dates but low precision do not necessarily describe any specific
geological event, especially as the uncertainties indicated by the standard
error for the LA-ICP-MS data are too small to even cover the entire recorded
duration of zircon crystallisation.
Traditionally, problems related to the oversimplification associated
with calculating weighted means and their standard errors in geochronology
were hidden by the larger uncertainties resulting from larger analytical
uncertainties and smaller sample sizes. Due to rapid data acquisition
nowadays by in situ
techniques, calculated standard errors can result in
uncertainty envelopes of <0.1 % for a sample. In the case of the
LA-ICP-MS dates from the Pliocene Batu Hijau porphyry intrusions, the
standard error of the weighted mean (∼1 %, ∼40 kyr) is on the same order of magnitude as an individual CA–ID–TIMS date
and therefore smaller than the geological spread of zircon crystallisation
ages. The combination of using a weighted mean to describe a non-Gaussian
sample distribution with the very small uncertainties attributed to a
weighted mean results in highly precise dates that may have no relation to a
specific geological event.
The MSWD (a reduced chi-square statistic) of a dataset provides a first
measure to indicate whether dates are normally distributed around an
expected value and thus whether the calculated weighted mean and standard
error are of significance (√(2n-1) rule by Wendt and Carl,
1991). As discussed before, the MSWDs for the LA-ICP-MS data are elevated,
implying that weighted means and standard errors should not be calculated to
characterise a geological event. However, the MSWDs for the SHRIMP zircon
analyses of the intermediate and old tonalite are within the 95 %
confidence interval of the MSWD, mainly due to the larger individual
uncertainties. Still, they are similarly affected by protracted zircon
crystallisation, which biases the weighted mean to higher values (Fig. 11).
Furthermore, overestimated individual uncertainties can result in acceptable
MSWDs but similarly inaccurate dates and low standard errors. For example,
increasing individual uncertainties for the 206Pb–238U dates
obtained for the old tonalite by LA-ICP-MS by a factor of 1.5 would result
in an acceptable MSWD (0.95), but the weighted mean and standard error would
be nearly identically precise to those calculated with the actual uncertainties but inaccurate (3.880±0.041, 2SE). Based on the presented data
it is advised not to characterise a geological event by a weighted mean with
an associated standard error if the MSWD is elevated (Wendt and Carl, 1991).
Based on the presented data we recommend using an uncertainty attributed to
the weighted mean that is more representative of the uncertainty of the
individual analyses so that it will most likely cover the event actually dated. Here, we tested the standard deviation of zircon dates from each
sample as a measure for the uncertainty of the weighted mean. This approach
provides a more realistic estimation of the uncertainty associated with
calculating a weighted mean of a geologically young dataset as it describes
the variability in the measurements, (0.29–0.62 Ma, Figs. 7, 11), and,
importantly, it would be independent of the number of analyses. The
resulting values at least for the Pliocene Batu Hijau deposit result in
appropriate uncertainties for the weighted mean as it would cover an
appreciable part of the range of in situ dates and thus the >300 kyr of zircon crystallisation and the emplacement age.
The presented data highlights the importance of CA–ID–TIMS zircon U–Pb
geochronology to resolve complex zircon crystallisation patterns. In the
case of porphyry research, high-precision ID-TIMS dates are required to
resolve the durations of porphyry emplacement and hydrothermal processes, but
in situ data can reliably reconstruct a timeline of magma emplacement events
within porphyry districts over million-year timescales (e.g. Rezeau et al., 2016).
Furthermore, combination with in situ petrochronology techniques (i.e. U–Pb
isotope and geochemical data from the same analyte) allows us to screen zircons
for inheritance and more importantly provides spatially resolved geochemical
information that can be integrated with high-precision dates.
Conclusions
High-precision zircon geochronology by CA–ID–TIMS combined with in situ
zircon geochemistry provides valuable datasets that allow the reconstruction
of geological processes with the highest temporal resolution. At Batu Hijau
zircons record the magmatic-to-hydrothermal evolution of the world-class
Batu Hijau porphyry Cu–Au deposit from the onset of zircon crystallisation
to emplacement of the post-ore young tonalite. The magma reservoir that
sourced the tonalites and the Cu–Au mineralising fluids records zircon
crystallisation over 336±27 kyr. Emplacement of the first exposed
tonalite at the Batu Hijau deposit (old tonalite) occurred after 246±28 kyr of uninterrupted zircon crystallisation in this subjacent reservoir.
Zircon trace element signatures support a dominantly crystallising and
cooling magma reservoir over 285±24 kyr until emplacement of the
intermediate tonalite. After emplacement of the intermediate tonalite the
chemistry of the reservoir remained in rather steady conditions for 51±28 kyr, during which it could have been disturbed by magmatic
recharge or underplating until final emplacement of the young tonalite. Ore
formation is most probably associated with the last stages of the chemically
and thermally evolving magma reservoir. The maximum duration of ore
formation can be constrained to <122 kyr by the emplacement ages of
pre-to syn-ore old tonalite and the post-ore young tonalite. This maximum
duration of ore formation covers different pulses of mineralisation that
could have lasted only a few thousand years. We record a magmatic system that was
active over ∼250 kyr before emplacement of the first porphyry
intrusion and onset of several pulses of hydrothermal activity forming the
world-class ore reserve in less than 100 kyr.
Comparison between in situ LA-ICP-MS and SHRIMP as well as CA–ID–TIMS U–Pb
geochronology reveals that all techniques provide accurate individual dates
(within the stated confidence interval). However, statistical treatment of
in situ data by calculating a weighted mean and standard error can result in
highly precise but inaccurate older ages of questionable geological
significance with apparent uncertainties that do not provide an accurate
measure for the uncertainty of emplacement age. The tempo of magma evolution
and hydrothermal processes associated with magmatic–hydrothermal systems,
such as porphyry deposits, is too fast to be reliably resolved by currently
available in situ U–Pb geochronology and requires ID-TIMS geochronology.
Combination of high-precision geochronology with in situ or TIMS–TEA (thermal ionization mass spectrometry with trace element analysis) geochemistry is currently the most powerful tool in deciphering these
geologically rapid processes.
Data availability
All data used in this paper are available from the Supplement files.
The supplement related to this article is available online at: https://doi.org/10.5194/gchron-2-209-2020-supplement.
Author contributions
SJEL carried out field documentation and conducted the ID-TIMS
measurements. SJEL together with MG conducted the
LA-ICP-MS measurements. The study was designed by SJEL, CAH, AvQ and JFW. Discussion of
the data involved all authors, and SJEL wrote the manuscript and
drafted the figures with input from all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
Extensive logistical support by the geology
department of the Batu Hijau mine, especially Eddy Priowasono, and the
technical staff at the mine site was hugely appreciated. Reviews by Fernando Corfu and Brenhin Keller greatly improved the
quality of this paper.
Financial support
This research has been supported by the Swiss National Science Foundation Grant (grant no. 200026-166151).
Review statement
This paper was edited by Daniela Rubatto and reviewed by Brenhin Keller and Fernando Corfu.
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