processing, inversion and interpretation of the vtem

Processing, inversion and interpretation of the VTEM airborne electromagnetic survey data over the Blue Billy Project in the Proterozoic Edmund Basin, Western Australia

Camilla Soerensen, Sam Spinks and Shane Mulè.

EP189873

6 December 2018

AusQuest Ltd.

South32 Ltd.

MINERAL RESOURCES

ISBN: 978-1-4863-1212-2

CSIRO Mineral Resources (Discovery)

Citation

Soerensen C, Spinks S and Mulè S (2018) Processing, inversion and interpretation of the VTEM

airborne electromagnetic survey data over the Blue Billy Project in the Proterozoic Edmund Basin,

Western Australia.

Copyright

© Commonwealth Scientific and Industrial Research Organisation 20XX. To the extent permitted by

law, all rights are reserved and no part of this publication covered by copyright may be reproduced

or copied in any form or by any means except with the written permission of CSIRO.

Important disclaimer

CSIRO advises that the information contained in this publication comprises general statements

based on scientific research. The reader is advised and needs to be aware that such information may

be incomplete or unable to be used in any specific situation. No reliance or actions must therefore

be made on that information without seeking prior expert professional, scientific and technical

advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all

liability to any person for any consequences, including but not limited to all losses, damages, costs,

expenses and any other compensation, arising directly or indirectly from using this publication (in

part or in whole) and any information or material contained in it.

CSIRO is committed to providing web accessible content wherever possible. If you are having

difficulties with accessing this document please contact [email protected].

mailto:[email protected]

Processing, inversion and interpretation of the VTEM airborne electromagnetic survey data over the Blue Billy Project in the Proterozoic Edmund

Basin, Western Australia | i

Contents

Acknowledgments ........................................................................................................................... iv

Executive summary ......................................................................................................................... v

1 Introduction ........................................................................................................................ 1

1.1 Scope of study ....................................................................................................... 1

2 Methods and Approach ...................................................................................................... 2

2.1 Principles of airborne electromagnetic methods .................................................. 2

2.2 Factors affecting ground conductivity ................................................................... 3

2.3 VTEM airborne electromagnetic survey ................................................................ 4

2.4 VTEM data processing ........................................................................................... 6

2.5 VTEM data inversion.............................................................................................. 6

2.6 TEMPEST survey .................................................................................................. 11

3 Results ............................................................................................................................. 14

3.1 Inversion Results .................................................................................................. 14

3.2 Conductivity depth slices ..................................................................................... 15

3.3 Comparisons to borehole information ................................................................ 21

4 AEM Interpretation ........................................................................................................... 27

4.1 Geological interpretation of AEM models ........................................................... 27

5 Conclusions ....................................................................................................................... 32

6 References ........................................................................................................................ 33

ii | Processing, inversion and interpretation of the VTEM airborne electromagnetic survey data over the Blue Billy Project in the Proterozoic

Edmund Basin, Western Australia

Figures

Figure 1. The VTEM survey configuration. ...................................................................................... 3

Figure 2. Schematic overview indicating electrical properties of sediments, regolith materials and

water. Overlapping responses are an indication that responses obtained from an AEM system

could be caused by a range of different materials (adapted from Palacky, 1983). ....................... 4

Figure 3. VTEM flight path map shown along with the original 4 drill holes in the area as well as

the Capricorn regional TEMPEST lines. ........................................................................................... 5

Figure 4. Schematic showing the principle of laterally constrained inversion. .............................. 8

Figure 5. Schematic overview of the process of allowing prior information to migrate along or

through a series of soundings acquired by an AEM system when they are inverted using the

spatially constrained inversion procedure. .................................................................................... 9

Figure 6. The depth of investigation for the VTEM Blue Billy survey. .......................................... 10

Figure 7. Smooth (top) and sharp (bottom) inversions of VTEM line 3620. The transparent white

areas indicate the depth of investigation. Caution should be exercised when interpreting

conductivity values at or below this depth. .................................................................................. 11

Figure 8. TEMPEST line 1003201 (top) and VTEM line 2860 (bottom). ........................................ 12

Figure 9. TEMPEST line 1003301 (top) and VTEM line 3110 (bottom). ........................................ 12

Figure 10. TEMPEST line 1003401 (top) and VTEM line 3360 (bottom). ...................................... 13

Figure 11. TEMPEST line 1003501 (top) and VTEM line 3610 (bottom). ...................................... 13

Figure 12. The original CDI models of the VTEM data (top) and the smooth full non-linear 1D

inversion using the AarhusInv inversion algorithm (bottom). White areas indicate the depth of

investigation, and values at or below the DOI should be interpreted with care. ........................ 14

Figure 13. The conductivity-depth slice for the 0-20m interval. .................................................. 15

Figure 14. The conductivity-depth slice for the 40-60m interval. ................................................ 16

Figure 15. The conductivity-depth slice for the 80-100m interval. .............................................. 17

Figure 16. The conductivity-depth slice for the 140-160m interval. The interval has been cut by

DOI, which results in no values in areas below the DOI. .............................................................. 18







Figure 20. The measured resistivity log (black line) for drill hole 17BBDD001 and the nearest VTEM

inverted model (in red), with the DOI shown as a red horizontal line. Also shown are the sample


Basin, Western Australia | iii

values for Zn, Mo and P2O5 as well as the rough interpreted lithological log. Distance between

VTEM sounding and drill hole was 122m. ..................................................................................... 23



values for Zn, Mo and P2O5 as well as a simplified lithological log. Distance between VTEM

sounding and drill hole was 14m. ................................................................................................. 24




VTEM sounding and drill hole was 50m. ....................................................................................... 25




VTEM sounding and drill hole was 68m. ....................................................................................... 26

Figure 24. The TEMPEST model from the GALEI inversion of the nearest sounding to bore hole

17BBDD002. .................................................................................................................................. 26

Figure 25. The VTEM survey lines (3010, 3410, 3620 and 3790 from west to east) plotted on top

of the 1:100000 interpreted bedrock geology. The four lines which intersect the 2017 diamond

drill holes are shown in cyan color. .............................................................................................. 27

Figure 26. The conductivity-depth section for VTEM line 3010 (top) and the 1:100000 interpreted

bedrock geology (bottom). Location of Line 3010 is indicated with the cyan color, and the location

of drill hole 17BBDD004 is also shown. The section is displayed from south to north. The color

scale for conductivities can be seen in Figure 19. ........................................................................ 28













iv | Processing, inversion and interpretation of the VTEM airborne electromagnetic survey data over the Blue Billy Project in the Proterozoic


Acknowledgments

This study was co-funded by AusQuest Ltd. and Joint Venture Partners South 32; The Australian

Government Department of Industry, Innovation and Science Innovation Connections (grant

number ICG000558); and CSIRO Mineral Resources. The researchers also acknowledge the expert

assistance of Ken Green in facilitating the funding of this project. The authors would also like to

thank Dr Teagan Blaikie and Dr Jelena Markov for their comments that helped improve the

manuscript.


Basin, Western Australia | v

Executive summary

An airborne electromagnetic (AEM) survey using the VTEM helicopter system was acquired in 2007

by Aurora resources over the Blue Billy Zn-Pb shale hosted project area. Flight line spacing was a

nominal 200m in a north-south direction. As part of the Innovation-Connections CSIRO-AusQuest

project, CSIRO undertook processing and inversion of a subset (~808 km) of the original survey and

results from a full non-linear 1D inversion of the processed data are reported.

The analysis incorporates drill hole constraints such as lithologies and geophysical logs available

from four diamond drill holes drilled in 2017 by AusQuest Ltd. Interval conductivity grids were

generated detailing the spatial variation of ground conductivity as it varies with depth. Conductivity-

depth sections were generated along each flight line with specific attention to the flight lines near

the four drill holes.

The modelled depth of investigation (DOI) indicates that the AEM system was able to resolve

conductivity variations to approximately 600m in the north-west part of the survey area where the

Blue Billy Formation is not present near surface. In other areas where the conductive Blue Billy

Formation is closer to the surface the depth of investigation is limited to just below the Formation.

Arguably the full non-linear inversion of the Blue Billy VTEM data provide a basis for a better

understanding of the spatial distribution of the Blue Billy Formation in the subsurface, host to the

target horizon of interest.


Basin, Western Australia | 1

1 Introduction

Stratiform sediment-hosted zinc (Zn) deposits occur throughout the Proterozoic McArthur and Isa

basins in northern Australia, hosted within shale-siltstone depositional units deposited ~1.6 billion

years ago (Ga). This forms one of the planet’s most prospective and metallogenic provinces and is

thus a critical source of key metals such as zinc (Zn). As reserves of Zn are steadily depleted, new

discoveries must be made in order to ensure security of supply for the future. However, the rate of

major new discoveries in this province (and others) is critically low, and whilst explorers currently

face the reality of having to explore deeper and under cover, innovative approaches to exploration

in new frontiers must now be considered.

The Mesoproterozoic Edmund Basin in WA, deposited during a time of intraplate rifting and

extension following the relaxation of the Capricorn Orogen (Cutten et al., 2016, Johnson, 2013), also

contains shale and siltstone units deposited at a similar time to the prospective units in the

McArthur and Isa basins (~1.6 Ga). One such unit, the Blue Billy Formation, comprises black

carbonaceous pyritic shales and siltstones deposited in an intracratonic basin with underlying and

overlying carbonate units and is proximal to a major fault zone. The strongest Zn regolith

geochemical anomalies in the Capricorn Orogen terrane occur at surface overlying the Blue Billy

Formation. Limited exploration drilling during the 2nd half of the 20th Century identified intersections

of low-grade stratiform Zn sulfide (sphalerite) mineralization in the black shale facies of the Blue

Billy Formation, but very little remains known about the mineral system or how widespread it is.

In 2017, AusQuest Ltd. in Joint Venture with South 32 Ltd., whilst exploring for McArthur River-type

sediment-hosted Zn mineralization drilled four diamond holes to test strong conductive units

identified by Airborne Electromagnetics (AEM) that were interpreted to reflect black pyritic shale

horizons in the Blue Billy Formation. These drill holes represent the first opportunity to test the

prospectivity for a McArthur River-type mineral system in the Blue Billy Formation by a combination

of 3D geochemical vectoring and airborne geophysics.

This report examines the potential of AEM, through constrained inversion, to better define the

geology and structure associated with the interbedded shales and siltstones of the prospective Blue

Billy Formation. It also offers the opportunity to examine whether AEM directly maps mineralised

horizons within the prospective shale units.

1.1 Scope of study

VTEM airborne electromagnetic data acquired in 2007 were processed and inverted using the

AarhusInv inversion algorithm with the aims of:

1) More accurately define layer boundaries to aid the definition of geology and structure.

2) Extend the current knowledge of the conductivity structure with depth by extending the

discretisation models and by including a measure of the depth of investigation.

3) Examine potential links between higher conductive zones of the Blue Billy Formation and

pyrite/sphalerite content.

2 | Processing, inversion and interpretation of the VTEM airborne electromagnetic survey data over the Blue Billy Project in the Proterozoic


2 Methods and Approach

A helicopter-borne electromagnetic survey using the VTEM system (Witherly et al. 2004) was carried

out in the Bangemall Basin, Western Australia during the period of September 27th and October 19th

2007 by Geotech Airborne Pty Ltd for Aurora Minerals Limited. Original processing of the data was

carried out by Geotech Airborne Pty Ltd in Perth Western Australia, with the original results

presented as profiles and raw gridded channels.

For the Innovation Connections CSIRO-AusQuest project, CSIRO undertook processing and inversion

of a subset (~808 km) of the original survey (which covered 5688 line km) with the aim to better

map subsurface conductivity structures by using a full non-linear inversion approach.

A large regional AEM survey was flown in 2014 covering the Capricorn Orogen using the TEMPEST

fixed wing AEM system. This included flight lines over the AusQuest project area and although this

survey was acquired at a regional scale (5km line spacing) inversions of these data over the Blue

Billy area has been included for comparisons with the VTEM conductivity-depth models.

Furthermore this comparison provides additional context for the models of conductivity structure

defined in the helicopter data set.

2.1 Principles of airborne electromagnetic methods

Time domain electromagnetic methods are based on the principle of inducing eddy currents in the

ground due to a magnetic field that varies in time. The transmitter wire loop carries a current which

generates a magnetic field. The current is turned off abruptly which induces an electrical field and

a current in the ground. The induced current generates a secondary magnetic field. As time passes,

the resistance in the ground weakens the induced current, resulting in a decaying secondary

magnetic field which is measured by the receiver coils (see Figure 1). Just after the transmitter

current is turned off, the current in the ground will be near surface and therefore the measured

signal will reflect conductivities of near surface layers. At later times the current propagates deeper

into the ground and the measured signal will contain information of the conductivity of these deeper

layers. The recorded dataset is organised in time-windows, which are typically logarithmically

increasing to improve the signal to noise ratio at later times, where the signal can be weak.

Materials that are highly conductive produce strong secondary electromagnetic fields. Sediments

(alluvium), soils or other regolith materials that contain saline pore water generate such fields. The

shape of the decaying signal provides information about the vertical conductivity structure of the

subsurface. Most AEM systems map contrasts in ground conductivity that are then interpreted on

the basis of experience and with the support of ancillary data, including surface and bore water EC,

downhole conductivity measurements, lithology logs from drilling, surface geophysical

investigations and other observations.



Figure 1. The VTEM survey configuration.

2.2 Factors affecting ground conductivity

Subsurface materials display a very large range of electrical conductivity values (Figure 2). Whereas

fresh rock is generally a poor conductor, layers of graphite and certain metallic minerals containing

copper, iron or nickel are very good conductors, making the electromagnetic method effective for

exploration for these targets. Highly conductive minerals are rare in a majority of geological settings

and the conductivity of a formation is largely determined by porosity, saturation and the salinity of

the water filling the gaps between minerals. Pure water has a low conductivity whereas seawater

contains high levels of dissolved salts.



Figure 2. Schematic overview indicating electrical properties of sediments, regolith materials and water. Overlapping

responses are an indication that responses obtained from an AEM system could be caused by a range of different

materials (adapted from Palacky, 1983).

2.3 VTEM airborne electromagnetic survey

2.3.1 The VTEM system

The VTEM (Versatile Time-Domain electromagnetic) (Witherly et al., 2004) is a helicopter borne time

domain electromagnetic system with a base frequency of 25Hz. It uses a central loop configuration

and both the transmitter and receiver loop are towed beneath the helicopter (see Figure 1). The

transmitter coil diameter is 26m with 4 turns, with a peak current of 155A and a peak dipole moment

of 329009 NIA. Nominal transmitter height is 30m above the ground (see Geotech Airborne Pty Ltd.

(2008) for further details).

2.3.2 The Blue Billy survey area

A total of 808.6 line kilometres were processed and inverted as part of this project. The flight line

direction was primarily N-S with additional tie lines flown in an E-W direction. Line spacing was 200m

and 2000m for the tie lines (Figure 3). Line length varied between 6 and 10 km.

2.3.3 AEM system spatial resolution

The spatial resolution of an AEM system varies with the system type, sample time or frequency, and

with ground conductivity (Reid et al., 2006, Spies & Woodgate, 2005). Due to acquisition and

processing factors the spatial resolution is different in the horizontal and vertical direction. Commonly

the system spatial resolution is considered in terms of the volume of the ground that contributes

most of the response for each sounding or measurement. Helicopter systems such as VTEM return

a weighted average response over lateral distances of up to 100 metres or more, dependent upon



flying height and the speed of the survey. The smallest lateral (horizontally-orientated) features that

can be resolved near surface are around 30-60 m (dependent on stacking/filtering) for helicopter

systems where good conductivity contrasts are present. Due to electrical field propagation the spatial

resolution of a system these figures increases with depth. Normally the highest resolution is

measured along a flight line, with the perpendicular resolution being determined by line spacing. It

is important that the spatial resolution of AEM is considered when comparing models of ground

conductivity or other products derived from the AEM data to information collected from drill hole

data where the spatial resolution is usually sub-metre in dimension.

The ability of the helicopter-borne systems to fly lower (transmitter and receiver at around 30 m

above the ground) compared to the fixed wing systems where the transmitter is at a height of 100

m does increase the resolution and the potential depth of investigation particularly in resistive

terrains. In conductive terrains low flying systems are better able to penetrate the conductive

overburden (Macnae, 2007).

Figure 3. VTEM flight path map shown along with the original 4 drill holes in the area as well as the Capricorn regional

TEMPEST lines.



2.4 VTEM data processing

For this project we differentiate between the processing of the AEM data and the procedures

involved in their subsequent inversion. Both the processing and subsequent inversion of the data

was carried out in the Aarhus Workbench software package which uses the full non-linear 1D

inversion algorithm AarhusInv (Auken et al., 2015).

The following workflow was employed for the data processing of the VTEM data:

1. Import raw data supplied by client to Workbench and generate a file with system specifications such as waveform, channels, number of turns in the transmitter, filters etc.

2. Divide data into “processing nodes” according to flights, dates of acquisition or some other criteria.

3. For each “processing node” undertake:

• Manual processing of altitude.

• Automatic processing of response data to remove potential late time noise and data affected by cultural noise (should any be present)

• Manual editing of the automatically processed data to remove any cultural and late time noise which the automatic filter settings did not account for.

• Run preliminary lateral constrained inversion to assess if the manual processing was adequate, and to help choose the optimal inversion model parameters.

This workflow and its implementation was aimed at preparing the data for the full non-linear

inversion step that followed.

2.5 VTEM data inversion

The original analysis of the VTEM data was limited to the analysis of the measured amplitude data

and to the transformed data in the form of conductivity depth images (CDI’s). One of the primary

objectives for the inversion of the Blue Billy VTEM survey was to map spatial variations in

conductivity both vertically and laterally. Converting the measured AEM responses to ground

conductivity also allows for a direct comparison to ground data such as borehole logs. The existing

CDI’s are limited to around 300m in depth and have no indication of depth of investigation

associated with them.

Inversion of AEM data requires information about the specific system characteristics such as time

gates, waveform, current, filters etc. The inversion is an iterative process of minimising the misfit

between forward modelled responses (using these system specifications) from an electrical earth

model and the measured AEM response, by changing the parameters of the earth model until an

acceptable misfit is obtained. The result obtained from an inversion of AEM data is however not a

unique result as several conductivity-depth models are able to fit the data within the acceptable

range. This non-uniqueness emphasises the need for verifying the inversion results by independent

information such as drill-holes or other methods such as ground geophysical measurements.



2.5.1 Inversion models

The VTEM data were inverted using a smooth layer model. This type of model typically consists of

15-30 layers with fixed thicknesses, often increasing with depth. Vertical constraints are used to

determine the amount the conductivity between two adjacent layers can vary. The large number of

layers and the gradual change in conductivity in this type of model makes the resulting conductivity

models appear continuous. This in turn can make it difficult to pick layer boundaries as these may

appear rather diffuse.

For the purposes of this study, a 30 layer model was used for the inversion of the VTEM dataset.

The first layer thickness was chosen to be 1m with logarithmically increasing thicknesses to a depth

of 800m which is the depth of the last layer boundary. The starting model was a homogenous half

space with an auto calculated conductivity, which is calculated as the mean of the apparent

resistivity for each sounding. The regularisation constraints (smoothness constraints) were set to a

vertical constraint of 4, a value which allows some vertical structure, without introducing artefacts

caused by overfitting the data. The horizontal constraint was set to 1.8 for all layer intervals.

2.5.2 Laterally constrained inversion (LCI)

The initial inversion of the VTEM data was performed by using the laterally constrained inversion

(LCI) methodology (Auken and Christiansen, 2004; Auken et al., 2005). The lateral constraints, which

are defined for adjacent soundings, allow prior information (e.g., the expected geological variability

of the area) to migrate along the flight lines (Figure 4). The use of constraints along lines enhances

the connection of layer parameters between adjacent soundings.

The inversion for the VTEM data solved for Z-component data as well as the transmitter height using

the one model. This approach yields the maximum possible resolution of model parameters. Results

were presented as conductivity-depth intervals below the ground surface, elevation slices and as

conductivity–depth sections, thereby providing a spatial picture of changes in ground conductivity

across the survey area.



Figure 4. Schematic showing the principle of laterally constrained inversion.

2.5.3 Spatially constrained inversion (SCI)

The Blue Billy VTEM survey was flown at a line spacing of 200m which makes the spatially

constrained inversion an alternative inversion choice for this dataset. The spatially constrained

inversion uses a Delaunay triangulation to connect soundings both along and across lines through

constraints. Obtaining models that honour information from along and across lines can result in a

more smooth appearance of the conductivity distribution as information is carried across from lines.

The constraints in the Delaunay triangulation are given a weight according to distance, so that

soundings closer together are more tightly constrained, and soundings far from each other are not

linked at all (Figure 5).



Figure 5. Schematic overview of the process of allowing prior information to migrate along or through a series of

soundings acquired by an AEM system when they are inverted using the spatially constrained inversion procedure.

2.5.4 Depth of investigation

The presentation of conductivity models derived from AEM systems can be misleading if there is no

attempt made to qualify the depth of investigation (DOI) of the measurement system. The depth of

investigation is a complex quantity, being a function of the power, sensitivity and accuracy of the

acquisition system, environmental noise levels (e.g. sferic and powerline sources), geologic

complexity, the host conductivity and the target characteristics (e.g. a discrete object or an

extensive layer, conductivity contrast to the surrounds) and the inversion procedure used (Lane,

2000; Christiansen and Auken, 2012). To ensure that the observed variations in measured

conductivity reflect changing ground conditions, rather than inversion or model dependent changes

arising from the inversion process, an estimate of the depth of investigation is calculated and

presented on the conductivity-depth sections. This information assists the interpreter, helping to

quickly evaluate the results and their validity. The DOI provides a depth to which the model is the

most reliable, and model information below the DOI should be used with caution.

The DOI determination used here is based on the cumulative sensitivity of the actual model output

from the inversion (it includes the full system response and geometry) and is described in

Christiansen and Auken (2012). The data noise and the number of data points are integrated into

the calculation, which is based on the final inversion model output and a recalculated sensitivity



(Jacobian) matrix. In general terms the more conductive the ground, the ability to resolve deeper

variations in conductivity (or the depth to which the inverted model is reliable) decreases. In more

resistive ground, the system is able to resolve those variations more reliably to greater depths. The

modelled conductivities in the Blue Billy survey area varies from highly conductive areas near

surface around 17BBDD003 resulting in lower DOI to more resistive areas around 17BBDD004

where, as a consequence, the DOI is deeper (Figure 6).

Figure 6. The depth of investigation for the VTEM Blue Billy survey.

2.5.5 Sharp inversion

Commonly used inversion options include an Occam style regularisation using smoothly varying 1D

models with fixed vertical discretisation, producing very smooth models where layer boundaries are

hard to recognise, and discrete few layer models with a fixed number of layers where the layer

boundaries are allowed to change in the inversion. The smooth layered model have shortcomings



in terms of defining layer boundaries, for the few layer model on the other hand it can be difficult

to pick a number of a layers that will be valid throughout a whole survey, and as a consequence

artefacts can be introduced in areas of unexpectedly complex geology.

The Sharp inversion methodology outlined in Vignoli et al. (2015) is a focussed regularisation

technique which allows for an accurate reconstruction of resistivity distributions while maintaining

the capability to reproduce horizontal boundaries. The methodology promotes solutions that are

compatible with the observed data and at the same time features a minimum number of spatial

(vertical and lateral) model variations.

In Aarhus Workbench, which is the software package used for the processing and inversion of the

Blue Billy VTEM survey, the options of layered, smooth or sharp inversions all exist. The dataset was

initially inverted using a smooth model inversion as a starting point, and subsequently refined using

a sharp inversion as an effort to extract information about the layering in the survey area (Figure 7).

Figure 7. Smooth (top) and sharp (bottom) inversions of VTEM line 3620. The transparent white areas indicate the

depth of investigation. Caution should be exercised when interpreting conductivity values at or below this depth.

2.6 TEMPEST survey

A regional scale fixed wing TEMPEST survey was acquired in the Capricorn Orogen in 2013 (for

specification of the system and the survey see CGG Aviation, 2013) also covering the VTEM Blue Billy

survey area (see Figure 3 for location). Given that the line spacing of the TEMPEST survey was 5km,

only four lines are within the Blue Billy VTEM survey area. These have been processed and inverted

using Aarhus Workbench similarly to the VTEM data (see Figure 8 to Figure 11). When comparing

the conductivity depth models for the two different AEM systems they appear to map similar

conductivity features. Near surface differences can be ascribed to differences in the system

footprint and spatial resolution of the two systems; TEMPEST is a fixed wing system with the

transmitter loop at 120m, whereas VTEM is a helicopter system carrying a slung transmitter loop



much nearer to the ground (30-40m). The latter system will, as a consequence, have a smaller

footprint and better near surface resolution. Overall the models obtained from the inversions of the

two datasets are similar providing confidence in the models from the inversion of the VTEM survey

data.

Figure 8. TEMPEST line 1003201 (top) and VTEM line 2860 (bottom).




3 Results

3.1 Inversion Results

Conductivity-depth transformation such as EMFlow (Macnae et al., 1998) and EmaxAir (Fullagar and

Reid, 2001), are faster than layered earth inversions (LEIs) and provide a quick way to gain

information about the subsurface conductivities. However, these methods are affected by unstable

waveforms, they commonly overestimate shallow conductivities and they do not provide the EM

response of the derived conductivity model nor the error between the modelled and measured

responses which limits the model appraisal.

A comparisons between the conductivity-depth transformation (Figure 12 top) and the full non-

linear 1D inversion using the AarhusInv inversion algorithm (Figure 12 bottom) shows that the

limited depth of 300m of the transformation is likely cutting off some of the conductive features at

depth whereas the full inversion is mapping the extent of these. Also worth noting is the limited

color scale used for the CDI of 1-300 mS/m which can potentially hide changes in conductivity which

could be related to lithological changes.

Figure 12. The original CDI models of the VTEM data (top) and the smooth full non-linear 1D inversion using the

AarhusInv inversion algorithm (bottom). White areas indicate the depth of investigation, and values at or below the

DOI should be interpreted with care.



3.2 Conductivity depth slices

Conductivity-depth intervals were generated from the inversion results of the VTEM data in 20m

intervals from surface to 400m depth. Examples of these are shown in Figure 13 to Figure 18 overlain

on a satellite image. The intervals were gridded using kriging with a cell size of 50m. For reference

the location of the AusQuest drill holes from the 2018 campaign have been included on these

figures.

Displaying inversion results as conductivity-depth images is a common way to visualise the spatial

distribution of the conductivity within a survey area. In areas with large topographical variations it

can be beneficial to display conductivities not only with depth but also as elevation intervals,

accounting for variations caused by the topography.

Figure 13. The conductivity-depth slice for the 0-20m interval.



Figure 16. The conductivity-depth slice for the 140-160m interval. The interval has been cut by DOI, which results in

no values in areas below the DOI.





3.3 Comparisons to borehole information

In order to understand the veracity of the inversion results we examined the modelled conductivity

structure against lithological and resistivity logs from available drill holes. The focus of this study

was lines (3010, 3410, 3620 and 3790) nearest to the 4 diamond drill holes in the Blue Billy survey

area (17BBDD001, 17BBDD002, 17BBDD003 and 17BBDD004) (see Figure 3 for drill hole locations).

All four drill holes had associated downhole geophysical data acquired by Pilbara Wireline Services

in October 2017. For this study the focus will be on the resistivity logs as these can be directly

compared to the AEM models obtained from the inversion of the data. Figure 20 to Figure 23 show

the measured resistivity logs plotted with the nearest VTEM modelled sounding (red) and the



interpreted lithological log as provided by AusQuest Ltd. Additionally, sample values for Zn, Mo and

P2O5 are also shown as these highlight the “target” horizon in the Black Shales of the Blue Billy

Formation. It should be noted that the resistivity log for 17BBDD003 is limited to covering the depth

range of 23m-44m, limiting the information about the downhole resistivity in that drill hole. Also

the resistivity logs have been subjected to an average filter to remove noise present in the data.

The conductivity of the Black shales of the Blue Billy Formation appear electrically homogenous with

a conductivity of around 30 mS/m as measured in the downhole resistivity logs. For drill holes

17BBDD001, 17BBDD003 and 17BBDD004 there appears to be a correlation between the VTEM

model and target horizon of the Black Shales in the sense that the VTEM conductivities increase in

the Black Shales zone, and the absolute values are in the ball park when compared to the down hole

log. While the VTEM model for drill hole 17BBDD002 on the other hand suggests an increase in

conductivity at depths around the mapped dolerite, the VTEM model still maps the black shale zone

with conductivity values that match the resistivity log well, despite the black shale zone being just

around or below the depth of investigation of the VTEM system.

The VTEM models are generally not sensitive to the dolerite but otherwise the conductivity

structure resembles the one obtained from the resistivity logs quite well.

As an independent check of the model obtained for the sounding near borehole 17BBDD002, we

undertook an inversion of the nearest TEMPEST sounding from the regional scale survey using a

different 1D inversion algorithm (GALEI, (Brodie, 2018)). For the purpose of this modelling the data

set was inverted using a 35-layer reference model, with layer thicknesses ranging from 2.0 to 59.2

metres, and a reference conductivity of 1 mS/m. Conductivity, horizontal and vertical receiver

position were set as inversion parameters. The obtained model (Figure 24) shows a similar

conductivity structure to the VTEM model in Figure 21, with increasing conductivities observed

towards the base of the near surface shale unit (~150m). Neither method resolved the resistive

dolerite unit. Below the indicated DOI the model reverts back to the reference model of 1 mS/m.



Figure 20. The measured resistivity log (black line) for drill hole 17BBDD001 and the nearest VTEM inverted model (in

red), with the DOI shown as a red horizontal line. Also shown are the sample values for Zn, Mo and P2O5 as well as

the rough interpreted lithological log. Distance between VTEM sounding and drill hole was 122m.




red), with the DOI shown as a red horizontal line. Also shown are the sample values for Zn, Mo and P2O5 as well as a

simplified lithological log. Distance between VTEM sounding and drill hole was 14m.






Figure 24. The TEMPEST model from the GALEI inversion of the nearest sounding to bore hole 17BBDD002.



4 AEM Interpretation

4.1 Geological interpretation of AEM models

The initial focus of this study has been on lines 3010, 3410, 3620 and 3790 which were the closest

to the four diamond holes drilled in 2017 (see Figure 25 for line locations).

Figure 25. The VTEM survey lines (3010, 3410, 3620 and 3790 from west to east) plotted on top of the 1:100000

interpreted bedrock geology. The four lines which intersect the 2017 diamond drill holes are shown in cyan color.



Line 3010

A conductivity-depth section for line 3010 is shown in Figure 26 along with the 1:100000 interpreted

bedrock geology (Geological Survey of Western Australia, 2018). This section displays conductivities

from surface at 300m AHD down to an elevation of -300m AHD, although this is quite close to the

depth of investigation which is marked with a translucent white color. This line intersects drill hole

17BBDD004.

The conductivity depth section shows low conductivities from surface to 0m AHD at the south end

(left side) of the section corresponding to the Narimbunna Dolerite. At the northern end of the

profile (right side) there is a similar near surface low conductive layer dipping to the south indicating

the presence of the Narimbunna Dolerite. This is underlain by a high conductivity package possibly

the Cheyne Springs Formation followed by the Blue Billy Formation. In the central part of the

conductivity-depth section around the location of the borehole, higher surface conductivities are

present indicating regolith material (colluvium and calcrete) over the low conductive Cheyne Springs

Formation. Under the Cheyne Springs Formation there are hints of a high conductive layer,

suggesting that the Blue Billy Formation might continue under the Cheyne Springs Formation,

although this is around the limit of the depth of investigation for the system in that conductivity

environment.

Figure 26. The conductivity-depth section for VTEM line 3010 (top) and the 1:100000 interpreted bedrock geology

(bottom). Location of Line 3010 is indicated with the cyan color, and the location of drill hole 17BBDD004 is also

shown. The section is displayed from south to north. The color scale for conductivities can be seen in Figure 19.



Line 3410

Line 3410 (Figure 27) is to the east of line 3010 and intersects hole 17BBDD003. Similar to line 3010,

the Narimbunna Dolerite is present towards the south end of the conductivity-depth section. Just

north of drill hole 17BBDD003 the Kulkatharra Dolerite is seen in the conductivity-depth section as

a lower conductivity as well. The highly resistive layer to the north end of the sections is interpreted

to be Cheyne Springs Formation, whereas the high conductivities around the drill hole are attributed

to responses associated with the Blue Billy Formation. Generally there is no regolith cover along this

line and the depth of investigation is limited for this section due to the high conductivities of the

Blue Billy Formation which is much closer to the surface than further to the NW.




Line 3620

Line 3620 (Figure 28) intersects hole 17BBDD002 and is east of hole 17BBDD003. Similar to the two

previous lines, the Narimbunna Dolerite is mapped to the south (left side of section) as a low

conductivity layer. The south-dipping conductors identified beneath the dolerite may be southerly

extensions of the Blue Billy Formation, which has also been mapped to the north as a very high

conductivity layer overlain by colluvium. The sharp break in the conductivity structure at northing



7396000 (Figure 28), suggests the presence of a fault with the sediment package to the north

downthrown side. Drill hole 17BBDD003 identified a 65 m thick dolerite at depth of 165m – 230m

intruded into the black shales of the Blue Billy Formation (see Figure 21), but the VTEM sounding

for that drill hole did not show a corresponding low conductivity for the dolerite. The conductivity

depth section suggest a highly conductive layer (interpreted to be the Blue Billy Formation

underneath the Cheyne Formation) above a resistive dolerite, but this is not well defined. The depth

of investigation suggests that anything below the highly conductive layer around the drill hole is not

resolvable.




Line 3790

The last line with an associated drill hole is line 3790 (see Figure 29) which is the furthest to the east.

Drill hole 17BBDD001 is located just to the north of this line, and technically outside of the VTEM

survey area. At a distance of 122m from the drill hole to the nearest VTEM line, it may however still

provide some useful information.

The Narimbunna Dolerite observed in the other interpreted sections is also present to the south

end of this one, as shown on the geological map in Figure 25. The northern half of the section consist

of colluvium, followed by Cheyne Springs Formation/Kangi Creek Formation which is underlain by

the more conductive Blue Billy Formation. For this particular section, the Blue Billy Formation in the



northern part of the section is highly conductive compared to the other parts of the section. As with

the previous section, sharp breaks in the lateral continuation of conductors are interpreted to be

associated with faulting (see for example, the breaks at 7392500, and 7398500).






5 Conclusions

The inversion of the VTEM data using a full non-linear 1D inversion (AarhusInv) has generated

conductivity-depth models which extend the previous knowledge obtained from the original

approximate transforms of the AEM data. The map of depth of investigation (Figure 6) suggest that

to the north-west in the survey area the inverted models are reliable down to around 600m,

substantially deeper than might have been suggested in the original work. This is attributed to the

Cheyne Springs Formation (which sits above the more conductive Blue Billy Formation) being

relatively resistive, therefore allowing for a deeper depth of investigation. The inverted models also

make it possible to better distinguish areas of regolith cover (often transported), as well as map

some variability within the Blue Billy Formation.

We have presented conductivity-depth sections generated via the sharp inversion algorithm,

highlighting both vertical and lateral changes in the sedimentary package. This type of inversion

might aid the interpretation of geological structures in the survey area, of which there appear to be

many.

The regional scale TEMPEST survey which was acquired in 2013, also covered the Blue Billy project

area, although due to the 5km line spacing only four TEMPEST lines fell within the VTEM survey.

When modelling the data from the two different systems using the same inversion platform, it is

possible to obtain remarkably similar conductivity-depth sections (as seen in Figure 8 to Figure 11),

which provides confidence in the inverted VTEM conductivity models.

One of the original aims of the processing and inversion of the VTEM Blue Billy dataset was to

examine whether the mapped conductivities within the Blue Billy Formation are directly related to

the pyrite/sphalerite content in the Black Shales. The resistivity logs obtained in the four diamond

drill holes suggest that elevated conductivities are not commonly associated with the pyritic parts

of the mudrocks of Blue Billy Formation. Disseminated pyrite may not result in high conductivities,

and the overall resistivity of the black shales could be dominating the observed response.

Only drill hole 17BBDD003 is located in a zone of higher conductivity in the black mudrocks of the

Blue Billy Formation. With the lithological log indicating pyrite estimates of 8-10%, it is fair to assume

that the pyrite content is associated with modelled high conductivity, but unfortunately the

resistivity log for this drill hole is only acquired for the depth interval 23m-44m, not providing any

information of resistivities of the higher conductive zone mapped by the VTEM model from

approximately 30-100m.

AEM data can provide valuable insights into the geology and structure of sedimentary basin units

that may host mineralisation. However, maximising their geological information content in such

settings requires considered processing and, where possible, constrained full inversion. Results from

the fast approximate transform of AEM data can be misleading and consequently should be

employed in exploration with appropriate additional data and knowledge.



6 References

Auken, E. and Christiansen, A.V., 2004, Layered and laterally constrained 2D inversion of resistivity

data. Geophysics, 69, 752-761.

Auken, E., Christiansen, A.V., Jacobsen, B.H., Foged, N. and Sørensen, K.I., 2005, Piecewise 1D

laterally constrained inversion of resistivity data. Geophysical Prospecting, 53, 497–506.

Auken, E., Christiansen, A.V., Kirkegaard, C., Fiandaca, G., Schamper, C., Behroozmand, A. A., Binley,

A., Nielsen, E ., Effersø, F., Christensen, N. B., Sørensen, K., Foged, N. and Vignoli, G., 2015, An

overview of a highly versatile forward and stable inverse algorithm for airborne, ground-based and

borehole electromagnetic and electric data. Exploration Geophysics, 46, 223–235.

Brodie, R.C. (2016). GALEISBSTDEM: A deterministic algorithm for 1D sample by sample inversion of

time-domain AEM data – theoretical details (Version 1). Geoscience Australia. Retrieved from

https://github.com/GeoscienceAustralia/ga-aem/docs/GALEISBSTDEM Inversion Algorithm

Theoretical Details.pdf

Brodie, R. C. (2018). Modelling and Inversion of Airborne Electromagnetic (AEM) Data in 1D:

GeoscienceAustralia/ga-aem. C++, Geoscience Australia. Retrieved from

https://github.com/GeoscienceAustralia/ga-aem

CGG Aviation. (2013). TEMPEST Geophysical Survey: Capricorn Regional Survey, Western Australia

(Logistics and Processing Report) (p. 93). Retrieved from

https://d28rz98at9flks.cloudfront.net/81642/81642_TEMPEST_Report.pdf

Christensen, N.B., 2002, A generic 1-D imaging method for transient electromagnetic data.

Geophysics, 67, 438–447.

Christiansen, A.V. and Auken, E., 2012. A global measure for depth of investigation. Geophysics, 77,

WB171–WB177.

Fullagar, P.K. and Reid, J.E., 2001, Emax conductivity depth transformation of airborne TEM data.

15th Conference and Exhibition, Australian Society of Exploration Geophysicists, Extended

Abstracts.

Geological Survey of Western Australia 2018, 1:100 000 State interpreted bedrock geology of

Western Australia, June 2018 update: Geological Survey of Western Australia, digital data layer,

www.dmp.wa.gov.au/geoview. Compilers of geology: SP Johnson and A Riganti Compiler GIS: PJ

Backhouse

Geotech Airborne Pty Ltd, 2008, Report on a helicopter-borne versatile time domain

electromagnetic (VTEM) geophysical survey, Bangemall Basin Project.

Lane, R., and Pracilio, G., 2000, Visualisation of Sub-Surface Conductivity Derived From Airborne EM.

SAGEEP 2000 Conference Proceedings.

Macnae, J., King, A., Stolz N., Oskamkoff, A. and Blaha A., 1998, Fast AEM processing and inversion.

Exploration Geophysics, 29, 163–169.

https://github.com/GeoscienceAustralia/ga-aem

http://www.dmp.wa.gov.au/geoview



Macnae, J., 2007, Developments in broadband airborne electromagnetics in the past decade. In

Proceedings of Exploration 07: Fifth Decennial International Conference on Mineral Exploration"

edited by Milkereit, B., 387-398.

Palacky, G.J., 1983. Tutorial: Research, applications and publications in electrical and

electromagnetic methods: Geophysical Prospecting, 31, 861-872.

Reid, J.E., Pfaffling, A., and Vrbancich, J., 2006. Airborne electromagnetic footprints in 1D earths.

Geophysics, 71, no. 2, G63–G72, doi: 10.1190/1.2187756

Spies, B.R. and Woodgate, P., 2005. Salinity mapping methods in the Australian Context, June 2005,

236pp.

Vignoli, G., Fiandaca, G., Christiansen, A.V., Kirkegaard, C. and Auken, E., 2015, Sharp Spatially

Constrained Inversion with applications to transient electromagnetic data. Geophysical Prospecting,

63, 243-255.

Witherly, K., Irvine, R., and Morrison, E.B., 2004. The Geotech VTEM time domain helicopter EM

system. SEG Technical Program Expanded Abstracts 2004: pp. 1217-1220. doi: 10.1190/1.1843295.



CONTACT US

t 1300 363 400 +61 3 9545 2176 e [email protected] w www.csiro.au

AT CSIRO, WE DO THE EXTRAORDINARY EVERY DAY

We innovate for tomorrow and help improve today – for our customers, all Australians and the world.

Our innovations contribute billions of dollars to the Australian economy every year. As the largest patent holder in the nation, our vast wealth of intellectual property has led to more than 150 spin-off companies.

With more than 5,000 experts and a burning desire to get things done, we are Australia’s catalyst for innovation.

CSIRO. WE IMAGINE. WE COLLABORATE. WE INNOVATE.

FOR FURTHER INFORMATION

Mineral Resources Dr Camilla Soerensen t +61 8 6436 8628 e [email protected] w www.csiro.au/en/Research/MRF

processing, inversion and interpretation of the vtem

Documents