SPECIAL TOPIC: LEADING GEOSCIENCES IN A NEW ERA
Cover mapping with passive seismics at
the Boulia Prospect, Mount Isa Province,
Queensland, Australia
Charles D. Beard1,2*, Nicholas Arndt1,2, Richard Lynch1 and Jamin Cristall3 demonstrate that the
ambient-noise surface-wave tomographic method can accurately and inexpensively map the
thickness of sedimentary cover that obscures potentially mineralised regions globally.
Abstract
To determine the thickness of sedimentary cover overlying
Proterozoic basement, an ambient-noise surface-wave tomographic (ANSWT) survey was conducted in the Boulia region
of the Mt Isa Province in Queensland, Australia. An array of 100
three-component seismic nodes was deployed along a 30 km
section and ambient seismic noise was recorded for 19 days. In
the resultant seismic model, the top-basement contact is resolved
as a sharp, subhorizontal interface at a depth of about 700 m,
where seismic velocity (Vs) increases downward from about
2500 to 3500 m/s. The accuracy of the retrieved top-basement
contact was confirmed by comparison with drill hole intersections
and with results from active seismic and magnetotelluric surveys.
This study demonstrates that the ANSWT method can accurately
and inexpensively map the thickness of sedimentary cover that
obscures potentially mineralised regions globally.
Introduction
Near-surface mineral deposits are becoming exhausted and
mining companies are now required to explore deeper (e.g.,
Schodde 2017), commonly below surficial layers of younger
sedimentary rocks, alluvium, glacial deposits or laterites in
tropical regions (e.g., Blewett 2013; Arndt et al. 2017; Gonzalez-Alvarez et al. 2020). Superficial sediments cover a very large
fraction of potentially mineralised zones, obscuring an estimated
80% of the Australian continent. To open up these areas for
mineral exploration, the Australian government has supported the
UNCOVER programme which supports the development of new
technologies for exploring beneath covered areas in Australia and
similar programmes are underway in Canada and other countries.
While geochemical methods can provide some indications of
the presence of ore bodies buried beneath pre-mineral cover by
tracing the aureoles that overlie certain types of mineralization
(e.g., Guffey et al. 2018), geophysical methods provide the only
reliable approach to determine the thickness and architecture
of the cover and to image mineralised zones beneath it. Inductive-source electromagnetic and magnetotelluric soundings have
limited ability to resolve the base of conductive cover while
1
Sisprobe SAS |
*
Corresponding author, E-mail: cdb53@cam.ac.uk
2
depth estimates from gravity and magnetic data are ambiguous.
Active-source reflection seismic surveys have a long and successful history in hydrocarbon exploration (e.g., Hanssen 2011;
Polychronopoulou 2018) and have been used in several regions
for the exploration for mineral deposits (e.g., Salisbury and
Snyder 2007; Malehmir et al. 2012) but they are not optimised
for determination of absolute cover thickness and are currently
too expensive to be applied widely in this industry.
Ambient-noise surface-wave tomography
Passive seismic methods, which use ambient sources of seismic
vibrations, including ocean swells, wind in trees or traffic, were
developed as a research tool to investigate the structure of the
crust and mantle. (e.g., Shapiro and Campillo 2004; Sabra et al.
2005; Campillo 2006; Brenguier et al. 2007). These methods do
not require the deployment of sources for seismic waves, such
as explosives or vibroseis trucks and therefore have a lower
environmental impact, are easier to deploy, and cost much less
than active seismic surveys (Ramm et al., 2019; Dales et al.,
2020). Microseismic events can be used as sources for body
wave tomography (Nakata and Nishida, 2019), a technique that
is widely used in monitoring volcanos and faults (Vanorio et al.,
2005; Mitchell et al., 2013; Brenguier et al., 2019; Hillers et al.,
2019), and in civil engineering applications. This approach is
rarely suitable for mineral exploration, however, because image
quality depends on the magnitude and distribution of earthquakes,
and many exploration sites are in regions with little seismic
activity. The passive seismic approach has also been used in the
oil and gas industry, commonly as a complement to active seismic
surveys (e.g., Chmiel et al., 2019), but it has been taken up by
mineral exploration companies only recently and tentatively.
Some notable examples in which passive seismic methods have
been used in mining or mineral exploration are Olivier et al.
(2015); Chamarczuk et al. (2018); Ramm et al. (2019); Dales et
al. (2020); Afonin et al. (2021); Gil et al. (2021).
Ambient-noise surface-wave tomography (ANSWT) is a passive seismic method that is relatively new to mineral exploration.
In this method, correlations of seismic ambient noise recorded
Université Grenoble Alpes, Université Savoie Mont Blanc |
3
Anglo American, Australia
DOI: xxx
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at two stations (sensors) are used to reconstruct the response of
the subsurface, as if one of the receivers were acting as a source
and the other one as a receiver. Surface waves are retrieved from
seismic noise, and they are used to compute tomography using
a two-step method described by Mordret et al. (2013) for travel
time tomography, and by Sambridge (1999) and Mordret et al.
(2014) for depth inversion. Technical details of the methods,
with specific reference to the mapping of cover thickness, will be
given in Lavoué et al. (in prep).
Velocity models prepared using surface wave ambient noise
methods have a relatively poor spatial resolution that limits their
ability to directly image ore bodies (Chamarczuk et al., 2018;
Ramm et al., 2019; Afonin et al., 2021; Xu et al., 2021). With the
exception of large massive sulphide deposits or iron ore bodies,
the dimensions of the mineralised zone are usually too small or
the contrast between the seismic velocity of the mineralisation
and surrounding rocks is usually too low. The method can,
however, be used to provide valuable information about the geological setting and the structures that control the mineralisation
(e.g., Xu et al., 2021), and, as is demonstrated in this paper, it is
a valuable tool for mapping the thickness and characteristics of
post-mineralization sedimentary cover. Here we describe how
ANSWT has been used to map sedimentary cover at the Boulia
exploration site in Queensland, Australia.
The Mount Isa Province and Boulia Prospect
The Mount Isa Province in Queensland, Australia, contains
several world-class, sediment-hosted sulphide deposits including
Mount Isa (Forrestal, 1990; Lilly et al., 2017). This enormous,
high-grade deposit has been a major producer of Cu as well as
Pb, Zn and Ag for over a century. Other more recently discovered
deposits, including Century and Hilton, are major sources of Pb,
Zn and Ag (Large et al., 2005). The mineralisation is hosted in
variably metamorphosed Proterozoic shales and is believed to
have formed during the interaction of deep-sourced basinal fluids
with near-surface sedimentary rocks.
The Boulia prospect, located in the south western part of the
Province, is the site of active exploration by several companies
(Figure 1). In this region, the mineralised Proterozoic rocks
are covered by thick sequences of Cambrian to Cretaceous
sedimentary rocks of the Georgina and Eromanga Basins. The
Eromanga Formation consists of Jurassic–Cretaceous sandstone,
mudstone, and siltstone (thickness ∼ 100 m) and crops out mainly
in the eastern part of the study area. Contact relationships indicate
that the base of the Eromanga Formation dips at a shallow angle
to the east. Limestones of the underlying Georgina Formation
(thickness ~ 600 m) crop out mainly to the west. Geological mapping provides little information about the base of the Georgina
Formation nor about the depth and geometry of the contact with
the Proterozoic basement.
The poorly consolidated and weathered Quaternary and Tertiary units can be expected to have the slowest seismic velocities,
followed by intermediate velocities in most of the Cretaceous to
Cambrian units. A sharp downward increase in velocity should
mark the contact between the sedimentary units and the seismically faster metamorphosed rocks of the basement; this change
in velocity will be used to map the depth of sedimentary cover.
Existing data sets for the Boulia prospect
Several types of geological and geophysical data for the Boulia
region have been collected by private companies and government
geological surveys, and are available for download from the
Geological Survey of Queensland Open Data Portal (https://
geoscience.data.qld.gov.au/). Knowledge of the geology of the
Figure 1 a) A geological map of the southern portion of the Mount Isa metallogenic province showing geophysical surveys at the Boulia prospect, the Proterozoic Mount Isa
block, and the sedimentary cover sequence. b) A simplified stratigraphic section. The Proterozoic metasedimentary rocks that may contain mineralization are covered by
Cambrian–Ordovician Georgina limestone (thickness ~600 m) and Jurassic–Cretaceous sedimentary rocks of the Eromanga basin (thickness ~100 m map is after Mond et
al. (1977) and uses the Lambert conformal conic projection). The stratigraphic section is after Casey et al. (1960).
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Figure 2 Airphoto of the Boulia Prospect showing the location of passive seismic nodes, the 3D passive seismic Vs model, 2D active-source reflection seismic profiles,
magnetotelluric profiles and three exploration drill holes.
Boulia region is built on mapping and interpretation of drill-hole
data by Green et al. (1963); Kress and Simeone (1993); Withnall
et al. (2013); Cook et al. (2013). Figure 1, a geological map of
the Boulia region, is extracted from the Detailed Digital Surface
Geology dataset provided by the Geological Survey of Queensland https://www.data.qld.gov.au/dataset/queensland-geology-series. Two of three exploration drillholes in the area penetrate the
sedimentary cover and intersected basement.
Geoscience Australia conducted a deep crustal active-source
seismic survey over the Boulia region in 2014 and 2015. Data
were recorded along three traverses, 14GA-CF2 (369 km),
14GA-CF3 (339 km) and 15GA-CF3 (140 km) with the aim
of determining the architecture of Proterozoic basement and
the depth of sediment cover. Links to the raw data and interpretations are provided by Fomin and Costelloe (2015). The
2D active seismic profiles were reprocessed and reinterpreted
by HiSeis (2018). That study focused mainly on structures
within the Proterozoic basement and identified complex folding
and faulting and a possible mafic intrusion. The survey also
identified a strong, subhorizontal reflector, shown in Figure 3,
that is interpreted to mark the base of sedimentary cover. Prestack time-migrated sections from the active seismic surveys
are shown in Figure 3, with the depth conversion having been
computed using the cover–basement contact from a single
exploration drillhole (MJRD0001). For this reason, the depth
of cover in the pre-stack time-migrated sections might be
biased toward shallower or greater depths, depending on lateral
variations in seismic velocity within the cover sequence.
Additional information on cover thickness is provided by
Frogtech Geoscience (2018), which used data from the Geoscience Australia Australian National Gravity Database and satellite
data from Sandwell et al. (2014) to interpret basement structure
and the thickness of sedimentary cover. They also summarise
data and interpretations from Milligan et al. (2009, 2010) who
compiled and interpreted data from airborne magnetic surveys.
An airborne EM survey (approximately 1200 line km) was also
conducted in the survey area.
Simpson and Heinson (2020) describe a magnetotelluric
(MT) survey used to model the depth of the Eromanga and Georgina basins. The survey collected data from 809 broadband MT
and 855 audiomagnetotelluric stations, which were distributed
along E-W transects to the north of, and overlapping with the
active seismic lines, as shown in Figure 1. Downhole resistivity
logs from three petroleum exploration wells near the study area
were used to generate 1D resistivity models which provided a
basis for the 2D interpretation shown in Figure 4.
The passive seismic survey
The aim of this survey was to determine whether the ANSWT
passive seismic technique could resolve the thickness and internal
characteristics of the sedimentary units that overly the potentially
mineralised basement rocks of the Mount Isa Province (Figure 1).
An array of 100 three-component seismic nodes was deployed
along a ∼30 km section of road, the same as that followed by the
active seismic survey line 14GA-CF3 (Figures 1 and 2). This
road runs subparallel to the E-W striking magnetotelluric profiles.
The nominal inter-station distance was 300 m with a minimum
of 250 m. Ambient seismic noise was recorded by 99 receivers
for 19 days from 27/11/2019 to 13/12/2019 (one node was not
operational during the acquisition). Frequencies from 0.4–2.5 Hz
were used to compute a 3D shear wave velocity model following
procedures described by Mordret et al. (2013).
The spectral content of the seismic records indicate variations
in the quality of data between stations. Overall the receivers
recorded low-quality seismic noise, as is to be expected for a
location in the middle of a continent and far from centres of
human activity. Even though the quality of ambient seismic noise
in this isolated region is relatively poor, the results described
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below demonstrate that this noise was adequate to achieve the
aims of the project.
The survey area was overlain with a 2D raster onto which
depth profiles were fitted (Figure 2). At each point, a dispersion
curve was determined from the seismic records via a frequency-dependent travel-time tomography analysis. Modelled 1D
velocity depth profiles were then generated by fitting depth and
velocity parameters to describe the observed dispersion curves
following the methodology of Sambridge (1999); Mordret et al.
(2014). Three fitted parameters are depths of interfaces separating
layers of constant shear-wave velocity. Four additional parameters are the shear-wave seismic velocities of these layers (Table
1). A total of 24,000 models were generated. The final model presented is the average of the 300 models with the lowest misfits,
with misfit being defined as the difference in velocity between
the modelled 1D depth profile and the observed local dispersion
curve. This Monte-Carlo technique also allows estimation of
model uncertainties with depth, via the standard deviation of the
distribution of the 300 selected velocity models. Velocity was
interpolated horizontally between the 1D depth profiles to obtain
the final 3D velocity model.
4.1. Results
The passive seismic model covers a wedge-shaped area 32 ×
4 km to a depth of 2 km below present ground surface (Figure 1,
2). In this survey, the top 200 m was not effectively resolved due
Parameters
Units
Min
Max
V0
m/s
1500
4000
V1
m/s
1500
4000
V2
m/s
2000
4000
V3
m/s
2000
4500
D0
m
0
400
D1
m
400
1000
D2
m
1000
2500
Table 1 Parameterisation of the local 1D Vs models.
to a coarse inter-station spacing (nominally 300 m) and a lack of
available high-frequency ambient noise during the survey period.
From 200 m to 600 m depth, the shear-wave velocity is between
2200 and 3000 m/s with strong lateral and vertical variations.
Below 600–700 m velocities are faster, between 3000 and 3900
m/s. The model is well-resolved from about 200 to 1400 m depth,
and with a lateral resolution ranging from 500 to 1000 m. Uncertainties on velocities are less than 10%. Misfits increase toward
the eastern part of the survey area where the 1D depth-profile
models fit the observed dispersion curves less well.
Figure 3 shows a vertical cross-section through the ANSWT
model in the western part of the survey area where it coincides
Figure 3 Vertical cross-sections showing the ANSWT passive seismic model, the 2D active seismic pre-stack time migration model (greyscale, HiSeis 2018) and in the middle
panel, the two techniques superimposed. Inset shows top-basement position in drillhole MSD-003, compared with the ANSWT model and the active seismic profile.
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Figure 4 A vertical cross-section through the Boulia Prospect showing (a) our ANSWT passive seismic velocity model, and (b) 2D magnetotelluric profile MT-04 from Simpson
and Heinson (2020), with isovelocity surfaces from our ANSWT model overlain. Bm-CP is the top basement contact interpreted from the inversion of the MT data.
with 2D active-source seismic survey line 14GA-CF3 and
magnetotelluric line MT-04 (see locations in Figure 1). In this
area, S-wave velocities in the sedimentary cover are relatively
constant, varying from about 2000 to 3000 m/s. At a depth
of around 700 m, the model velocities increase sharply with
increasing depth to 3200 to 3600 m/s.
Discussion
Interpretation of 3D velocity model
Shear-wave seismic velocities for the sedimentary rocks of
the Eromanga and Georgina Formations are expected to be
about 1500–2500 m/s for sandstone and 2200–3000 m/s for
limestone, based a global compilation of petrophysical studies
(Ji et al., 2002). These velocities are significantly slower than the
3200–3800 m/s expected for the metamorphosed basement rocks.
Across most of the survey area, the S-wave velocity models
resolve a sharp downward increase in shear wave velocity at a
depth of 700 m. Based on the expected petrophysical parameters
and the sharp downward increases in velocity, we interpret the
top-basement contact as a Vs isovelocity value of 3000 m/s. In
the section shown in Figure 3, the 3000 m/s contact is at a depth
of about 700 m and is relatively flat lying. Uncertainty on our
model velocity determinations is less than 10 %, corresponding to
a basement depth precision of about ± 70 m. The contact between
the Eromanga Formation and underlying Georgina Formation
within the cover is not resolved in this ANSWT model (Figures 3
and 4). This could be due to the proximity of this contact to the
ground surface, and the relative insensitivity of this particular
array configuration at depths of less than 200 m. Alternatively,
there may be insufficient contrast in the S-wave velocity between
the two cover formations, limiting the ability of ANSWT to
image the interface between them.
Comparison with existing exploration data sets
The collar of drill hole MSD-003 is 500 m to the north of the
magnetotelluric profile shown in Figure 4, and is located in the
NW of our survey area (Figure 2). Considering the shallow dip of
the undeformed sedimentary formations at the Boulia Prospect, it
provides an independent test for the depth for the top-basement
contact resolved by our passive seismic model (Figure 3). The
top-basement contact in this drill hole is at a true vertical depth of
740 m (measured depth = 789 m) and is in close agreement with
the 3000 m/s isovelocity surface in our passive seismic Vs model.
The 2D reflection active seismic profile 14GA-CF3 was processed using velocity information from drill hole MJRD0001,
which is in the NE of our survey area (Figure 2), and its collar is
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located 900 m south of the active seismic profile. HiSeis (2018)
converted reflection time to depth and the generated a pre-stack
time-migrated reflection profile from the active survey data
(Figure 3). As a result, their top-basement contact is fixed to
the depth of a prominent subhorizontal reflector at the site of
the drill hole. Lateral variations in the velocity structure of the
Eromanga and Georgina Formations (both on and off-profile)
have potential to introduce undetectable bias to these profiles,
deepening or shallowing the resolved ‘top basement’ prominent
reflector relative to reality.
At the position of drill hole MSD-003, the active seismic
profile resolves a prominent subhorizontal reflector 100 m deeper
than the 3000 m/s isovelocity surface in our ANSWT model
(Figure 3). The generally good agreement in position and shape
between this active-seismic reflector and the 3000 m/s passive
seismic isosurface suggests that lateral variations in cover velocity are small, with faster cover in the W, close to hole MSD-003
relative to near hole MJRD0001 in the E. Active-source reflection
seismic sursurveys have several disadvantages. They have the
potential to include undetectable bias in the depth of reflected
interfaces, may be influenced by off-profile geology and are
associated with a high environmental and economic cost. They
are therefore poorly suited for the determination of absolute cover
thickness during province-scale exploration campaigns.
The magnetotelluric survey was conducted along a series
of E-W profiles that partially overlap with the area covered by
the active and passive seismic surveys (Simpson and Heinson,
2020, Figures 1 & 2). Profile MT-04 resolves the Eromanga
sediments as a relatively thin layer (≤ 100 m) near the ground
surface (Figure 4). It shows that the contact with the underlying
Georgina Formation dips to the East, and that the Eromanga
Formation appears to become thinner toward the west, in agreement with the geological map which shows that the younger
Eromanga rocks crop out mainly in the eastern part of the
survey area (Figure 1). The basement top is less well-defined,
interpretation being complicated by a conductive stratum in the
Georgina Formation (Simpson and Heinson, 2020). In contrast
to the Eromanga–Georgina contact, the basement top resolved
by MT dips at a shallow angle (~5°) to the west. This is broadly
consistent with regional geological mapping, which shows that
the Georgina Basin becomes deeper to the northwest (Figure 1,
Casey et al. 1960; Mond et al. 1977). The presence of highly-conductive strata in the cover sequence, highlights the need
to incorporate local petrophysical information when using magnetotelluric data to determine cover thickness. Much like the
active-source seismic profiles, 2D magnetotelluric surveys are
additionally subject to bias introduced by off-profile variations in
geology.
The close agreement between the results from our ANSWT
test survey, drill logs and the existing geophysical data confirms
the value of passive seismic surveys as a means of mapping
the depth and geometry of cover--basement contacts during
province-scale exploration. The precision of our ANSWT model
at ~700 m depth is better than that of the MT technique (±70 m
cf. ±250 m, Simpson and Heinson 2020). Unlike active-seismic
profiles, the ANSWT model fitting procedure accounts for
lateral changes in the velocity of the cover sequence. Our method
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produces 3D velocity models that are not sensitive to off-axis
geological variations, as is the case with all geophysical surveys
measured along 2D profiles. Prior knowledge of the petrophysics
of local rocks is generally not critical for mapping cover thickness
because strong seismic velocity contrasts usually exist between
fast crystalline basement rocks and slow sedimentary rocks or
unconsolidated sediments. The resolution of ANSWT models
can be greatly improved by the use of 2D grids of seismic nodes,
rather than line profiles. This is especially the case in survey areas
with stronger and higher-frequency sources of ambient seismic
vibrations than were present at the Boulia Prospect.
Where to apply ANSWT in mineral exploration?
The main advantages of ANSWT derive from its relatively low
cost and minimal environmental impact. The seismic nodes are
simple to deploy and do not require the preparation of tracks
nor the cutting of grid lines. Although their location must be
recorded accurately, there is considerable flexibility as to where
they are placed, which means that local unfavourable locations
(outcrops, rivers, swamps, buildings) can be avoided. Because of
the low environmental impact, ANSWT can often be carried out
in sensitive areas where other surveys are prohibited. The method
also produces 3D models and basement depth results that are
not biased by complications such as the presence of conductive
sedimentary units. The main disadvantage is the relatively low
spatial resolution, both vertical and horizontal, especially when
compared to active-source geophysical methods. Due to its
resolution and cost, ANSWT is best applied during exploration
at the province to district scale (100 km to 10 km lateral) to map
in 3D geological features on the order of kilometres to hundreds
of meters in size. In special circumstances it is possible to design
surveys for finer-scale investigation, though this requires the
presence of higher-frequency ambient noise, and application to
features relatively close to the surface. ANSWT is sensitive only
where there are significant variations in the S-wave velocity of
adjacent rocks. As with all geophysical surveys, local petrophysical measurements can be helpful during both survey design and
for the fitting and interpretation of the seismic models.
Summary
Ambient noise surface wave tomography is a promising technique for mapping the thickness and internal characteristics of
sedimentary cover sequences. This survey demonstrates that
the method can accurately and inexpensively map sedimentary
cover overlying prospective regions. The precision with which
the basal contact can be mapped is better than that obtained
using magnetotelluric profiles and far less expensive than activesource seismic surveys. As with other techniques, interpretation
of the generated 3D geophysical models must be done with an
understanding of the geological context and the petrophysical
properties of the local lithologies.
Acknowledgements
The authors wish to thank Anglo American for funding the passive seismic survey, for field logistical support at the Boulia site
and for permission to publish. We thank members of Sisprobe,
especially Anaïs Lavoué for conducting the field work and
SPECIAL TOPIC: LEADING GEOSCIENCES IN A NEW ERA
generating the 3D passive seismic models and Sophie Beauprêtre
for comments on an earlier version of this manuscript.
Lindskog, L., Spicer, B., Carbonell, R., Orlowsky, D., Carriedo, J.
and Hagerud, A. [2021]. Reflection seismic imaging to unravel
subsurface geological structures of the Zinkgruvan mining area,
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