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REPORTS ON DUPORT PROPERTY

DIGHEM SURVEY

KENORA, ONTARIO

FOR

HALO RESOURCES LTD.

JANUARY-MARCH 2007

Condor Consulting Lakewood Colorado USA

CONTENTS

1.SUMMARY................................................................................................................................. 2

2.INTRODUCTION ....................................................................................................................... 2

3.TARGET GEOLOGY.................................................................................................................. 2

4.PROCESSING, ANALYSIS TECHNIQUES AND PRODUCTS ................................................. 4 PROCESSING .................................................................................................................. 4

Layered-earth Inversion (FarEM) .......................................................................... 4 Time constant........................................................................................................ 4 ZS Filtering ............................................................................................................ 5 Picking................................................................................................................... 5 Discrete Features .................................................................................................. 5 Target Zones ......................................................................................................... 5 Ranking of Picks.................................................................................................... 5 Power Line Response ........................................................................................... 6

MAGNETIC RESPONSES................................................................................................ 9 PRODUCTS ...................................................................................................................... 9 Table 4-1 Survey Products................................................................................................ 9

5.SURVEY RESULTS................................................................................................................. 10

6.CONCLUSIONS AND RECOMMENDATIONS........................................................................ 21

7.REFERENCES ........................................................................................................................ 22 APPENDIX A BACKGROUND INFORMATION ON EM PROCESSING ........................ 24 APPENDIX B INFORMATION ON ZS FILTERING......................................................... 25 APPENDIX C ANOMALY LIST ....................................................................................... 26 APPENDIX D ARCHIVE DVD......................................................................................... 36

Report on Duport Dighem Survey Halo Resources Ltd.

Condor Consulting, Inc. March 2007 2

1. SUMMARY

This report covers the processing and analysis of a Dighem frequency-domain EM survey carried out

for Halo Resources Ltd over their Shoal Lake Duport Project, NW Ontario. The purpose of the survey

was to assist in the location of gold mineralization.

The EM data were examined for anomalies that might indicate zones of mineralization. Due to the

presence of conductive lacustrine clays, most EM responses are related to surficial cover. A number

of conductive anomalies, which might be associated with sulfide mineralization were identified in the

data set. Further work, including ground checking would be considered warranted in most cases.

2. INTRODUCTION

Fugro Airborne Survey Corp. (Fugro) undertook a Dighem helicopter EM and magnetic survey over the

Shoal Lake Duport Project, NW Ontario in 2005 using a 50m line spacing (Garrie, 2005). During

January 2007, Condor Consulting, Inc. (Condor) performed an evaluation of survey results over a sub-

set of the DIGHEM survey (Sattel and Witherly 2007); this area is shown in Figure 1. In early March

2007, Condor was requested to evaluate the DIGHEM data over a larger area, also shown in Figure 1.

3. TARGET GEOLOGY

A geological summary of the property is provided in Clow and Valliant (2006).

Feldspar porphyry, quartz feldspar porphyry, quartz diorite, diorite and lamprophyre dykes cut the volcanics in the deposit area. Gold mineralization extends over a drill indicated strike length of 1,200 m and is associ-ated with highly sheared, narrow, thinly bedded, conformable felsic and intermediate tuffs and cherty units that contain sulphide mineralization, generally in the range of 5%-10%. Mineralization strikes N30-35°E and dips 65-75°W. The zones are spatially associated with tuffs and/or interflow material and are generally found in shear zones at or near lithological contacts. The deposit is related to an epigenetic, hydrothermal system. Metallic free gold occurs within narrow, sheared, fractured, often highly silicified felsic and intermediate tuf-faceous interflow rocks that have cherty looking sections and sulphide mineralization consisting of pyrite, arsenopyrite and minor pyrrhotite and chalcopyrite. Gold content is proportional to arsenopyrite. The lithology and structural setting of the Duport deposit is broadly similar to most of the gold deposits in the Red Lake and Timmins areas, in that they are shear hosted in mafic to ultramafic volcanic rocks and are spatially associated with granitoid batholiths.



Figure 1: Focus areas for the January and March 2007 assessments

HALO RESOURCES - DUPORT PROPERTY

Focus area

~ "

o 5km ---_ ...... Scale: 1 :100,000

uary 2007 [?,'~iI

Area of Interest NAO 83. Zone 15

A 352789mE, 5495204mN B 354865mE, 5493957mN C 352515mE, 5490133mN o 350428mE, 5491426mN



4. PROCESSING, ANALYSIS TECHNIQUES AND PRODUCTS

PROCESSING

Layered-earth Inversion (FarEM) FarEM is a product of the University of British Colombia, Geophysical Inversion Facility (Farquharson

and Oldenburg, 2000). The program (informally referred to historically as EM1dFM) is a layered earth

inversion (LEI) routine designed to model frequency domain EM of the variety typically recorded with

Max-Min (ground) or DIGHEM-style helicopter EM systems. The program can recover both

conductivity and magnetic permeability of the subsurface within the limits of the specific acquisition

system being employed.

FarEM Processing Parameters All five EM components (three co-planar & two coaxial) were used in the inversion. A total of 28

logarithmically spaced layers, ranging from 1 m to 26.5 m were used, to a maximum depth of 250 m.

Starting conductivity: 0.0001 S/m (10,000 Ω-m)

Reference conductivity: 0.0001 S/m (10,000 Ω-m)

Fixed Trade-off with Beta: 2

FarEM Plotting Parameters Conductivities are in the form of conductance depth sections (CDS) and are presented in units of ohm-

m and are plotted with a color bar range of 10 - 5,000 Ω-m.

Additional information on the EM processing is provided in Appendix A.

Time constant Time constants (taus) were derived from the Dighem data using proprietary software developed by

EMSolutions LLC. The algorithm derives time constants from the inphase and quadrature responses

at two frequencies making use of the definition of decay currents in frequency-domain as described by

Macnae et al. (1998). Since the impact of noise and magnetic permeability effects is strongest on low-

frequency responses, best results were obtained from the EM responses at the two highest

frequencies (56 kHz and 7,200 Hz).



ZS Filtering While not included in the original deliverables, Condor has begun providing their clients with a suite of

filtered magnetic images produced using algorithms described by Shi and Butt (2004) – this paper is

included in Appendix B.

Picking The MultiPlot™ display was the primary means to identify and rank the anomalies. This overall

process is termed anomaly picking and was done on a line-by-line basis, with several passes being

required to finalize the process.

An EM picking scheme was used that made use of the following data:

• EM profiles

• Power line and spherics profiles

• Time-constant (tau) profiles and grid

• Conductivity-depth sections

The picking data bases generated by Condor are provided in Appendix C and in their native Excel and

Geosoft formats on the archival DVD (Appendix D).

Discrete Features Discrete features are considered to be those EM responses, which are interpreted to be caused by

conductors with limited lateral dimensions.

Target Zones Groupings of conductors are termed Target Zones. A Target Zone is deemed as a logical grouping of

conductors within the data set and is based on an assessment of the distribution of individual

conductor picks, plus any other available geoscience data. The Target Zones are then prioritized for

follow up work based on their overall geophysical character.

Ranking of Picks A ranking scheme, using the following anomaly classification was used:

1- excellent; outstanding response and/or spatially confined.

2- good; strong response.

3- weak; could be related to overburden or stratigraphic conductor.



4- cultural; related to power lines, pipelines, fences, etc.

Examples for the ranking applied are demonstrated in Figures 2-3. In the preparation of products

(Table 4-1 below), all picked features were displayed on all products (excluding the ZS products).

Power Line Response Upon examination of the Fugro provided data base, Condor assessed that the contractor had left out

the fields relating to the detection of power line responses. Condor contacted Fugro on behalf of Halo

and in early May, Fugro provided Condor with a final data base. This is provided on the archival DVD

(Appendix D). These data were used in the final assessment and ranking of the conductor picks.



Figure 2: Profiles of EM and mag with CDS and examples of Rank 1 and 3 anomalies

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line L21610 «< Coaxial spherics monitor (red) coplanar powerline monitor (blue)

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Report on D

uport Dighem

Survey H

alo Resources Ltd.

Condor C

onsulting, Inc.

March 2007

8

Figure 3: P

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alies

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MAGNETIC RESPONSES

The magnetic response of the picked conductors was noted in Table C-1. However, due to a degree of

inconsistency in the observed EM responses showed when there was a coincident magnetic

response, the presence of magnetic character with EM features while noted but not used explicitly in

the ranking process. A suite of enhanced magnetic images are provided (ZS suite) which provide

additional detail regards lithologies, structure and alteration. A reference (Wallace 2006) on using

magnetic data in the exploration for Archean gold deposits is provided on the archive DVD Appendix

D.

PRODUCTS

Table 4-1 lists the maps and products that are provided.

Base Maps: All maps are created using the following parameters:

Projection Description:

Datum: WGS84 Ellipsoid: GRS80 Projection: UTM (Zone: 15N) Central Meridian: 93ºW False Northing: 0 False Easting: 500,000 Scale Factor: 0.9996 WGS84 to Local Conversion: Molodensky

Table 4-1 Survey Products TargetMaps @ 1:25,000 (one copy of each)

TargetMaps include the Condor EM Picks EM

• TMI

• 1st Vertical Derivative of TMI

• Tilt angle of the TMI

In addition, the ZS suite of magnetic derivative products is provided in poster format; scale 1:40,000

MultiPlots™ @ 1:40,000 (PDFs only)

On each MultiPlot™ the picked anomalies are indicated along with the following:

• Conductivity-depth section with EM system height

• Profile 1: Coplanar Inphase and Quadrature: 925 Hz



• Profile 2: Coaxial Inphase and Quadrature: 1113 Hz

• Profile 3: Coaxial Inphase and Quadrature: 5517 Hz



• Profile 6: Total magnetic intensity (TMI), 1st Vertical Derivative of TMI

• Profile 7: Coaxial and Coplanar Tau

• Profile 8: Magnetic Analytic Signal and 1st vertical derivative

Survey Report (1 copy)

On the archive DVD (Appendix D) the following files are provided:

-Digital grid archives in Geosoft format

-Profile Analyst session file (to create MultiPlots™)

-Anomaly data bases in Excel and Geosoft formats

-PDFs of TargetMaps and MultiPlots™

-Survey report (PDF)

5. SURVEY RESULTS

Figures 4-12 summarize the EM interpretation and outcomes. The EM anomaly picks are dis-

played on the Dighem flight path (Figure 4), total magnetic intensity (Figure 5), first vertical deriva-

tive of the TMI (Figure 6), time constant (Figure 7), apparent resistivity 56kHz (Figure 8), topogra-

phy (Figure 9) and the coplanar power line grid (Figure 10). Rank 1 anomalies are shown in red,

rank 2 in orange, rank 3 in yellow and rank 4 in green. The anomaly picks are listed in Appendix A

and are compared in Figure 11 with the Fugro picks. Examination of the Fugro picks not included

in the Condor picks indicated that these anomalies are related to surficial clay.

The anomalies were grouped into Target Zones as shown in Figure 12. The confidence in these

Target Zones decreases with increasing Target Zone number. Target Zones 1-5 contain strong

anomalies that might be related to discrete or stratigraphic conductors. Target Zones 6-9 contain

strong conductors that might be related to cultural sources rather than subsurface conductors.

Target Zones 10-18 and anomalies not grouped into Target Zones might be related to overburden

edges rather than sulfides.



Figure 4: Dighem flight path map with EM anomaly picks



Figure 5: Dighem TMI grid with EM anomaly picks



Figure 6: Dighem 1VD grid with EM anomaly picks



Figure 7: Dighem tau grid (derived from 7 and 56 kHz data) with EM anomaly picks



Figure 8: Dighem 56 kHz apparent resistivity grid with EM anomaly picks



Figure 9: Dighem DTM grid with EM anomaly picks

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Figure 10: Dighem coplanar power line grid with EM anomaly picks



Figure 11: Dighem flight path map with EM anomaly picks and Fugro picks (black dots)



Figure 12: Dighem TMI grid with Target Zones

In order to detect zones of silicification, the data were examined for zones of high resistivity. This

examination indicated a very close relation between ground resistivity and topography. This is

illustrated in Figure 12, which shows DEM contours overlain on the apparent resistivity grid from

the 56 kHz response. The two data sets show a very high degree of correlation and thereby



confirm the earlier observation, that the EM data are dominated by the response due to surficial

clays related to the drainage system.

Figure 13: DTM contours on 56 kHz apparent resistivity grid

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6. CONCLUSIONS AND RECOMMENDATIONS

This report provides a description of the processing and analysis undertaken on a Dighem EM survey

over the Shoal Lake (Duport) Project, Ontario. Picking and ranking of outcomes was based on

processed EM data. Over much of the study area the EM response is dominated by low level

responses attributed to lacustrine clays. In addition, a number of promising EM anomalies were picked

that might relate to sulfide mineralization. The selected Target Zones are felt to warrant ground follow-

up so as to better assess their likelihood of being zones of mineralization.

Respectfully submitted,

Daniel Sattel/Ken Witherly

CONDOR CONSULTING, Inc.

March 29, 2007



7. REFERENCES

Clow, G. and Valliant, W., (2006) Technical Report on Duport Project, Northwestern Ontario, Canada

prepared for Halo Resources Ltd., NI 43-101 report Roscoe Postle Associates INC., January 2006.

Farquharson, C. G., & Oldenburg, D. W., (2000), Automatic estimation of the trade-off parameter in

nonlinear inverse problems using the GCV and L-curve criteria: SEG 70th Annual Meeting, Calgary,

Alberta, 6-11 August 2000 Garrie, D., (2005) Dighem Survey for Halo Resources Ltd. Duport Project Kenora, Ontario; report

number # 05053; Report by Fugro Airborne Surveys, November 2005.

Macnae, J., King, A., Stolz, N., Osmakoff, A., and Blaha, A., (1998), Fast AEM data processing and

inversion: Exploration Geophysics 29, 163-169.

Sattel, D., Witherly, K., (2007) Report on Duport Dighem Survey; report for Halo Resources Ltd. by

Condor Consulting, Inc., January 2007

Wallace, Y., (2006) 3D Modelling of Banded Iron Formation Incorporating Demagnetization – A Case

Study at the Musselwhite Mine, Ontario, Canada; presented at AESC2006, Melbourne, Australia July

2006



8. APPENDIXES



APPENDIX A BACKGROUND INFORMATION ON EM PROCESSING

What is a CDI?

The term CDI is short for Conductivity Depth Imaging. The purpose of CDI processing is to convert multichannel

EM data1 into the equivalent conductivity distribution in the earth that would produce the observed EM response.

While the program assumes the earth is layered (meaning all changes in conductivity are vertical), by processing

many points along a line and then gridding the result, a two dimensional (or three dimensional if gridded again)

approximation of the earth’s conductivity can be obtained. The results of CDI processing are then displayed in a

CDS, short for Conductivity Depth Section (central image in the figure below).

In what would be termed a simple conductivity environment where all conductors are expected to be

steeply dipping in a resistive host rock, CDI processing will not likely add much new information when

making target assessments. However, in many situations the target conductivity may be caused by a

mixture of massive and disseminated sulfides and CDI processing will enhance the likelihood of being

able to map the overall conductivity distribution much like IP surveying has been used historically in

VMS exploration. Also, if the overburden is conductive and/or has a variable thickness, CDI processing

helps to identify such changes and reduces the potential ambiguity of mistaking variations in the overbur-

den for targets of interest in the bedrock.

1 Time domain CDIs are discussed here but the same process can as well be applied to frequency domain data as well, this is discussed un-der a companion Technical Note

Condor Consulting, Inc. September 2005 Condor Technical Note-CDI TD



APPENDIX B INFORMATION ON ZS FILTERING

ASEG 17th Geophysical Conference and Exhibition, Sydney 2004. Extended Abstracts

New enhancement filters for geological mapping Zhiqun Shi* Graham Butt Encom Technology Australia Encom Technology Australia [email protected] [email protected]

INTRODUCTION High-resolution aeromagnetic survey data represent a rich source of detailed information for mapping surface geology as well as for mapping deep tectonic structure. Traditional enhancement techniques, such as first vertical and horizontal derivatives (1VD, 1HD), analytic signal (AS), and high-pass in-line or grid filters are used in enhancing magnetic anomalies from near-surface geology.

In recent years the potential field tilt filter has been introduced (Miller and Singh, 1994) and it has achieved recognition for its value in the analysis of potential field data for structural mapping and enhancement of both weak and strong magnetic anomalies (Verduzco et al, 2004). The total horizontal derivative of the TMI reduced to the pole is also widely used for detecting edges or boundaries of magnetic sources (Cordell and Grauch, 1985; Blakely and Simpson, 1986; Phillips, 1998).

Several disadvantages pertain to the use of these traditional filters. They often only diffusely identify source location and

boundaries, particularly in colour image presentations. They usually emphasise short wavelength anomalies at the expense of signal from deeper magnetic sources and the range of amplitudes remaining in the filtered output may dominate the source boundary information being sought. In addition, some traditional filters emphasise noise with resultant impact on the interpretation of source boundaries.

This paper identifies new processes which have been developed to address these disadvantages and provide output which can improve map-based interpretations.

Unless otherwise stated, all filters have been operated on TMI data reduced to the pole (RTP).

METHOD AND RESULTS

Theoretical Model Testing A theoretical 2D grid of total magnetic intensity (TMI) computed at the surface was created by forward 3D modelling of the TMI response from a set of theoretical magnetic sources having variable width, strike extent, depth, depth extent (DE), dip, magnetic susceptibility and strike azimuth. A list of these parameters is presented in Table 1. In two of the sources, remanence was simulated using negative magnetic susceptibility. The TMI of the theoretical models was computed at a geomagnetic inclination of -60 degrees using a notional east–west line spacing of 200 m and a grid cell size of 40 m. The TMI grid was then reduced to the pole (RTP) (Figure 1).

Figure 1. RTP image derived from multiple theoretical 3D magnetic sources, shown as wire frame outlines

A set of traditional filters was operated on the theoretical RTP grid. They include AS, 1VD, modulus of horizontal derivatives (MS) and Tilt and the results are presented in

SUMMARY Two types of filters have been developed for the purpose of enhancing weak magnetic anomalies from near-surface sources while simultaneously enhancing low-amplitude, long-wavelength magnetic anomalies from deep-seated or regional sources. The Edge filter group highlights edges surrounding both shallow and deeper magnetic sources. The results are used to infer the location of the boundaries of magnetised lithologies. The Block filter group has the effect of transforming the data into “zones” which, similar to image classification systems, segregate anomalous zones into apparent lithological categories. Both filter groups change the textural character of a dataset and thereby facilitate interpretation of geological structures.

The effect of each filter is demonstrated using theoretical model studies. The models include both shallow and deep sources with a range of magnetisations. Comparative studies are made with traditional filters using the same theoretical models. In order to simulate real conditions, Gaussian noise has been added to the model response. Techniques for noise reduction and geological signature enhancement are discussed in the paper.

The new approaches are applied to actual magnetic survey data covering part of the Goulburn 1:100 000 scale map sheet area, New South Wales. Some new geological inferences revealed by this process are discussed

Key words: Enhancement filters, magnetic sources, geological mapping.

New enhancement filters for geological mapping Shi and Butt


Figure 2. The output grids variously show discontinuous trending (crossed sources in upper right of AS image), diffuse, weak edges (deep source in centre right of the MS image) and lack of precise source edge definition (1VD and Tilt).

Table 1. List of parameters of theoretical magnetic sources

Figure 2. Comparison of enhancement filters of RTP: AS, 1VD, MS and Tilt filter. The models used are those depicted in Figure 1.

Edge Filters The first avenue of development was to increase the sharpness of the anomalies used to map the edge of the magnetic sources. The MS grid yields anomaly peaks over the source edge locations, whereas these edges coincide with gradients in the 1VD, Tilt and AS filtered outputs. None of these filters produces easily interpreted edges in image form when the sources are weakly magnetised or are deep.

A new linear, derivative-based filter termed the ZS-Edgezone filter has been developed to improve edge detection in these situations. Its effect is shown in Figure 3 using the same theoretical models discussed earlier. The advantages of the filter are greatly increased anomaly sharpness over source edges and compression of the amplitude range so that differences in the original TMI amplitudes do not persist to

dominate the edge interpretation. This has the ancillary effect that the method can be modified to provide automated edge conversion to vectors for use in GIS systems.

Although this filter significantly improves the precision of edge determination, it is subject to normal potential field limitations which determine that source edges cannot be resolved where the source is narrow relative to its depth. The filter also can produce a “halo” type artefact due to superposition of the response of a limited depth extent shallow source (Figure 1, Model 6) on that of deeper sources. A similar “halo” effect can be seen around the edges of remanently magnetised Model 15, also in Figure 1.

The ZS-Edge filter (Figure 4) has also been developed to map source edges. This filter differs from the ZS-Edgezone filter in that a greater contribution of the TMI anomaly amplitude over the source is retained, thereby improving anomaly characterisation at the expense of edge sharpness.

Both these filters produce edges which migrate down-dip towards the deepest edge of the source. This effect produces anomaly asymmetry that can assist interpretation of dip, although this effect is more pronounced for the ZS-Edge filter than for the ZS-Edgezone filter. Down-dip source extensions are depicted in cyan in Figure 1.

Figure 3. Anomaly edge and block enhancements using the ZS-Edgezone (left) and ZS-Block filters (right). Model positions are shown using wire frames.

Block Filters In attempting to improve edge detection filters, an obvious progression is to highlight the magnetic regions whose edges have been mapped. To do this, a set of filters called “block” filters has been developed.

The Block filter group has the effect of transforming the potential field data into “zones” which, similar to image classification systems, segregate anomalous zones into apparent lithological categories. These filters can be imported for use in image classification systems or displayed in RGB space with other grids for empirical classification purposes.

The block filters, like the edge filters, are linear, derivative-based filters which use a combination of derivative and amplitude compression techniques to render the magnetic data into regions whose edges are sharply defined and whose amplitudes have a reduced range in comparison to the original TMI.

The ZS-Block filter (Figure 3) and the ZS-Plateau filter (Figure 4) depict the magnetic data as a 2D plan of apparent magnetic source distribution. Artefacts may occur as discussed for the edge filters.

Model Label Depth (m) Width (m) DE (m) Dip

(deg)

Magnetic Susceptibility

(SI)

Strike Length

(m)

Azimuth(deg)

1 4000 15000 15000 120 0.010 15000 -0502 6000 15000 10000 120 0.010 15000 -0503 10000 15000 10000 120 0.010 15000 -0504 1000 3000 4000 70 0.010 12000 -0555 500 5000 2000 60 0.010 7000 -0506 1000 800 2000 150 0.005 8000 -0307 600 500 2000 120 0.001 20000 -0208 200 500 2000 120 0.001 20000 -0209 500 500 2000 120 0.003 10000 020

10 1000 500 2000 120 0.003 10000 -06011 1000 500 2000 120 0.003 12000 04012 200 400 2000 120 0.001 20000 -05013 500 400 1000 40 0.002 32000 05014 500 400 1000 140 0.001 32000 05015 600 3000 4000 90 -0.002 8000 05516 400 600 2000 120 -0.010 8000 -010



The choice of ZS-Block, ZS-Plateau or ZS-Area filters will depend on the data characteristics of each magnetic survey and on the end-use requirement. The ZS-Plateau filter, for example, yields less variation in amplitude “texture” over a magnetic unit that either the ZS-Block or ZS-Area filters.

Figure 4. Comparison of ZS-Edge, ZS-Edgezone, ZS-Block and ZS-Plateau filtered outputs of RTP data

Effects of Noise The influence of noise on the operation of these enhanced grids was tested by adding a large component of noise to the theoretical TMI profile data. This noise had a Gaussian distribution with a standard deviation equal to ten percent of the TMI standard deviation. The noise-modified TMI profile data were then de-spiked using a non-linear technique. Both the noise-affected and the de-spiked TMI data were then gridded and converted to RTP. The RTP data were then processed both with the traditional and newly developed filters.

Figure 5 shows the effect of the noise on the computations. The image of the noise-affected 1VD RTP data (top right) shows that weak and deep sources have been severely masked by the noise. Significant improvement can be achieved by using de-spiked data (lower left) or by low-pass grid filtering — for example, using an upward continuation filter (lower right).

Figure 6 shows that if real data with significant noise is encountered, a standard de-spiking or low-pass smoothing procedure may be used to achieve successful application of both the traditional and newly developed filters.

Figure 6 also depicts the use of enhanced outputs in RGB space to provide examples of how the combination of amplitude information (red colour) with edge information (green and blue colours) can be used to highlight source boundaries and remanence in a single image.

Figure 5. Comparison of 1VD of original model RTP data (top left) with noise-affected RTP data (top right) and noise-reduced RTP data (lower images)

Figure 6. ZS-Block filter using noise-reduced RTP data (top left) and examples of filter combinations in RGB space using noise-reduced RTP data

Application to Field Data, Goulburn 1:100 000 Scale Map Sheet Area, New South Wales Both the traditional and new enhancement filters were applied to test their suitability for geological definition to airborne magnetic survey data over the Goulburn 1:100 000 scale map sheet area (Johnson et al, 2003). These data were acquired as part of a joint program between the NSW Department of Mineral Resources and Geoscience Australia, with 250 m–spaced east–west flightlines. The magnetometer sensor occupied a nominal terrain clearance of 80 m. This dataset was selected since new detailed geological mapping had been recently completed. All the enhancements have been computed using TMI data reduced to the pole.

Figure 7 shows a comparison of part of the Goulburn 1:100 000 map sheet area surface geology with the ZS-Area



filter output. In the area surrounding location C, the ZS-Area filter transforms the magnetic data into separate magnetic units, which comprise the Devonian Bindook Volcanic Complex. The magnetic regions correlate closely with mapped andesites (Dkqa–cream coloured unit in Figure 7) whilst the intervening less-magnetic units correlate with rhyolitic ignimbrites (Dkqy–red unit in Figure 7)

Figure 7. Comparison of geology and ZS-Area enhance-ment over the Bindook Volcanic Complex

Figure 8 displays some of the advantages of the edge detection filters. At location A, ambiguity concerning the continuity of Quialigo Formation units (cream and red units in Figure 7) is resolved by the ZS-Edgezone filter. At location B, a subtle lineament is confirmed, whilst at location D, the extent of the Bullamalita Conglomerate (green unit in Figure 7) is clearly mapped by the ZS-Edge filter. Structural breaks are often more easily interpreted using these transforms, for example, immediately southwest of location D.

Figure 8. Comparison of ZS-Edge and ZS-Edgezone enhancements over the Bindook Volcanic Complex

Figure 9 shows standard RTP and Tilt transforms over the same area for reference.

Figure 9. Comparison of RTP and Tilt filters over the Bindook Volcanic Complex

CONCLUSIONS Traditional filters used to enhance magnetic data, including the more recently developed potential field tilt filter, are currently used to assist in determination of the location and extent of magnetic units.

Newly developed derivative-based filters may be used to improve the precision of source edge detection and, by extension, the determination of the spatial extent of magnetic units. These filters are demonstrated to perform successfully on both strongly magnetised features as well as on weakly magnetised or deep magnetic features. Artefacts may result particularly where anomaly superposition occurs.

The impact of noise in real data may be accommodated by these new methods provided noise-reduction techniques are employed.

The new filter outputs may be used as part of regional or detailed geological mapping projects, including in classification systems or in RGB space, to improve lithological discrimination and mapping.

The speed of magnetic unit mapping can be considerably increased through reliance on edge detection filters. Further improvements in mapping speed can be envisaged through automated conversion of edge anomalies to vector files.

ACKNOWLEDGMENTS The authors would like to acknowledge the New South Wales Department of Mineral Resources for permission to use aeromagnetic and geological data from the Goulburn 1:100 000 map sheet area and helpful comments by David Robson during the project.

The authors wish to acknowledge Encom Technology for permission to publish the results of research into the proprietary filters used in this paper. The 3D modelling was carried out using Encom ModelVision Pro software, whilst processing and data visualisation were accomplished using Geosoft OASIS montaj and Encom Geoscape.

REFERENCES Blakely, R. J. and Simpson, R. W., 1986, Locating edges of source bodies from magnetic or gravity anomalies, Geophysics, 51, 1494-1498.



Buckingham, A.J, Dentith, M.C., and List, R.D, 2003, Towards a system for content-based magnetic image retrieval: Exploration Geophysics, 34, 195-206.

Cordell, Lindrith, and Grauch, V.J.S., 1985, Mapping basement magnetization zones from aeromagnetic data in the San Juan Basin, New Mexico pp.181-197. In Hinze, W.J., ed,. The utility of regional gravity and magnetic maps: Society of Exploration Geophysicists,

Johnson A.J. et al., 2003, Goulburn 1:100 000 Sheet 8828 Geology Map, New South Wales Department of Mineral Resources.

Miller, H.G., and Singh V., 1994, Potential field tilt — a new concept for location of potential field sources: Journal of Applied Geophysics, 32, 213-217.

Phillips, J.D., 1998, Processing and interpretation of aeromagnetic data for the Santa Cruz Basin–Patagonia Mountains Area, South-Central Arizona: United States Geological Survey Open-File Report 02-98.

Verduzco, B., Fairhead, J. D., Green, C. M., and MacKenzie, C., 2004, New insights into magnetic derivatives for structural mapping: The Leading Edge, 23 (2), 116-119.



APPENDIX C ANOMALY LIST

Table C-1: Anomaly picks sorted by ranking (discrete=anomaly on one line only, edge=overburden edge, mag=associated mag anomaly, ob=overburden, culture=cultural source) for rankings 1-3. The ranking 4 (cultural) picks are provided in the Excel and Geosoft data bases.

Anomaly ID Line FID X Y Ranking Comment 4 L10290 501 355904.5 5500089 1 5 L10290 535 356892.2 5499434 1 culture? 11 L10300 1108 356836.5 5499366 1 culture? 13 L20010 1367 356742.7 5499290 1 culture? 20 L20020 1926 356708.9 5499275 1 culture? 21 L20030 2289 356663.7 5499230 1 culture? 31 L20043 1917 356630.4 5499205 1 culture? 32 L20050 3111 356583.7 5499148 1 culture?

391 L20980 774 356615.6 5493565 1 521 L21600 2517 352267.1 5492721 1 mag 522 L21610 2882 352244.1 5492689 1 mag 525 L21620 3169 352206.1 5492654 1 mag 619 T19070 2990 357932.9 5494325 1

2 L10280 9263 356983.7 5499506 2 culture? 3 L10280 9292 356064.8 5500109 2 12 L10300 1144 355822.1 5500035 2 27 L20043 1840 358801 5497753 2 mag, culture? 35 L20050 3190 358584.6 5497829 2 36 L20050 3198 358782 5497689 2 mag 37 L20050 3205 359004.1 5497559 2 39 L20060 3701 358762.7 5497659 2 mag 40 L20060 3709 358571.3 5497808 2 43 L20060 3780 356573.4 5499105 2 culture? 44 L20070 4039 356530.2 5499089 2 culture? 47 L20070 4107 358538.9 5497751 2 48 L20070 4114 358743.7 5497608 2 mag 49 L20080 4541 358718.7 5497578 2 mag 50 L20080 4548 358517.6 5497699 2 56 L20091 5076 358685.3 5497528 2 mag 60 L20100 5496 358679.5 5497478 2 mag 65 L20111 5938 358645 5497425 2 mag

195 L20450 403 356757.1 5496657 2 culture? 196 L20460 835 356736.5 5496599 2 mag, culture? 204 L20470 1158 356696.3 5496558 2 culture?



205 L20480 2153 356666.6 5496525 2 culture? 212 L20490 2479 356640.3 5496476 2 culture? 213 L20500 2748 356632.2 5496427 2 culture? 221 L20510 3088 356605.4 5496385 2 culture? 222 L20520 3357 356618 5496308 2 mag, culture? 229 L20530 3751 356542.8 5496318 2 culture? 236 L20550 4331 356532 5496196 2 culture? 239 L20560 4762 354973.7 5497172 2 culture? 240 L20570 5002 354951.9 5497133 2 culture? 277 L20670 8353 354650.2 5496741 2 culture? 279 L20670 8460 357884.2 5494584 2 mag, culture? 280 L20680 8704 357858.7 5494542 2 mag, culture? 282 L20680 8807 354602.9 5496688 2 culture? 285 L20690 9034 354562.2 5496671 2 culture? 289 L20690 9138 357843.6 5494498 2 culture? 290 L20700 9276 357870.8 5494415 2 culture? 294 L20700 9381 354529.7 5496626 2 culture? 295 L20710 9721 354512.5 5496602 2 culture? 299 L20710 9831 357888.7 5494347 2 culture? 300 L20720 10061 357817.8 5494326 2 306 L20730 387 354427 5496521 2 culture? 357 L20870 5272 356919.5 5494021 2 culture? 358 L20880 5684 356915.3 5493960 2 365 L20890 6060 355805.4 5494633 2 mag, culture? 366 L20890 6096 356871.9 5493944 2 367 L20900 6276 356842.8 5493900 2 368 L20900 6308 355787.4 5494593 2 culture? 374 L20910 6714 355753.5 5494557 2 culture? 375 L20910 6750 356830 5493855 2 376 L20920 6925 356794.8 5493819 2 392 L20990 1087 356602.1 5493525 2 culture? 413 L21050 3061 354942.9 5494238 2 mag, culture? 414 L21060 3353 354901.2 5494217 2 mag, culture? 417 L21070 3721 354899.4 5494170 2 mag, culture? 432 L21130 5613 354504.5 5494063 2 mag, culture? 434 L21140 5915 354505.6 5494001 2 mag, culture? 436 L21150 6200 354520.9 5493915 2 mag, culture? 437 L21160 6618 354520.8 5493883 2 mag, culture? 451 L21250 9537 354405.2 5493428 2 culture? 452 L21260 9807 354372.8 5493372 2 mag, culture? 454 L21270 388 354333.2 5493334 2 mag, culture? 456 L21280 587 356668.9 5491728 2 culture? 460 L21290 1091 356597.9 5491705 2 culture? 461 L21300 1209 356594.4 5491676 2 culture? 466 L21310 1628 356525.1 5491635 2 culture? 485 L21380 4031 353019 5493543 2 mag, edge?



518 L21590 2311 352326.3 5492765 2 552 L22240 5762 349383.9 5490798 2 mag 554 L22250 6170 349397.1 5490730 2 mag 555 L22260 6386 349371.8 5490699 2 mag 558 L22270 6788 349332.4 5490664 2 mag 566 L22310 7938 349292.4 5490438 2 mag 574 L22350 392 349361.8 5490156 2 mag 577 L22360 782 349349.9 5490100 2 578 L22360 809 348469.6 5490679 2 mag 582 L22381 1530 349306.3 5490014 2 mag, culture? 608 L30030 8783 356657.1 5493522 2 mag, culture? 609 L30030 8792 356830.3 5493804 2 mag, culture?

7 L10300 1037 358876.6 5498004 3 mag 16 L20010 1433 358859.6 5497902 3 mag 17 L20020 1855 358828.9 5497862 3 mag 24 L20030 2364 358634.4 5497931 3 25 L20030 2371 358808.8 5497797 3 mag 26 L20043 1830 359107.9 5497558 3 mag 28 L20043 1846 358603.9 5497880 3 38 L20060 3694 358975.6 5497501 3 mag 54 L20080 4629 356507.3 5499037 3 55 L20091 5069 358483 5497667 3 59 L20092 4596 356526 5498965 3 mag, culture? 61 L20100 5503 358457.1 5497622 3 edge? 64 L20100 5578 356412.2 5498979 3 culture? 66 L20112 4122 356415.2 5498940 3 70 L20120 6632 358636.6 5497392 3 culture? 73 L20120 6705 356363.4 5498908 3 76 L20131 7047 358582.9 5497355 3 80 L20140 7539 356270.3 5498839 3 culture? 81 L20150 377 356243.3 5498798 3 culture? 87 L20160 924 356210 5498760 3 culture? 88 L20170 1289 356166.5 5498722 3 culture? 93 L20180 1816 356136.3 5498688 3 culture? 94 L20190 365 356119.6 5498654 3 culture? 97 L20201 3382 356079.2 5498598 3 culture?

101 L20230 2026 354437.3 5499503 3 104 L20240 2652 354413.8 5499472 3 105 L20250 345 354374.4 5499420 3 108 L20260 992 354348.7 5499395 3 109 L20270 1145 354294.8 5499364 3 112 L20280 1896 354294.3 5499334 3 edge? 113 L20290 2036 354237.9 5499288 3 edge? 120 L20300 2619 356157.4 5497962 3 culture? 121 L20300 2623 356029.9 5498046 3 culture? 122 L20300 2682 354291.5 5499193 3 edge?



123 L20310 2988 354248 5499157 3 edge? 129 L20320 3704 354941.6 5498646 3 edge? 130 L20330 3896 354178.9 5499075 3 ob? 131 L20330 3901 354304.4 5498988 3 edge? 132 L20330 3916 354753 5498696 3 139 L20340 4627 354726 5498653 3 edge? 140 L20340 4644 354275.7 5498954 3 141 L20340 4649 354145.9 5499048 3 ob? 142 L20350 4796 354089.9 5499024 3 ob? 143 L20350 4801 354227.3 5498927 3 edge? 149 L20360 5405 354464.5 5498702 3 150 L20360 5418 354056.6 5498987 3 edge/ob? 151 L20370 5684 354026.2 5498947 3 edge/ob? 152 L20370 5697 354413.5 5498674 3 156 L20370 5838 358754.7 5495801 3 edge/ob? 159 L20380 6317 353966.8 5498910 3 edge? 160 L20390 6459 353944 5498877 3 edge? 163 L20390 6556 356880.6 5496935 3 culture? 164 L20390 6611 358542.7 5495826 3 edge? 165 L20400 7074 356868.6 5496876 3 culture? 166 L20400 7162 354089.6 5498713 3 edge? 167 L20400 7169 353888.4 5498853 3 edge? 168 L20410 7305 353828.8 5498809 3 edge? 169 L20410 7314 354076 5498668 3 170 L20410 7355 355366.3 5497799 3 ob?, culture? 171 L20410 7381 356219.3 5497240 3 culture? 173 L20410 7402 356844.6 5496838 3 culture? 174 L20420 7832 356830.1 5496795 3 culture? 176 L20420 7852 356182.3 5497220 3 edge?, culture? 177 L20420 7879 355352 5497773 3 ob?, culture? 178 L20420 7925 353799.1 5498791 3 edge? 179 L20430 8151 353752.8 5498759 3 edge? 180 L20430 8201 355324.1 5497731 3 edge?, culture? 181 L20430 8227 356147.2 5497183 3 culture? 183 L20430 8240 356561 5496906 3 ob?, culture? 184 L20430 8248 356797.4 5496736 3 edge?, culture? 185 L20440 8667 356789.5 5496691 3 ob?, culture? 186 L20440 8675 356531.2 5496856 3 mag 188 L20440 8714 355297.8 5497673 3 edge?, culture? 189 L20440 8760 353827.2 5498646 3 190 L20440 8764 353701.1 5498733 3 edge? 191 L20450 304 353665.7 5498700 3 192 L20450 354 355254 5497639 3 edge?, culture? 194 L20450 394 356497.3 5496820 3 mag, culture? 197 L20460 879 355233.7 5497593 3 edge?, culture? 198 L20460 927 353624.4 5498663 3 ob/edge?



199 L20460 933 353451.5 5498777 3 200 L20470 1052 353409.5 5498755 3 201 L20470 1057 353567.9 5498647 3 202 L20470 1110 355196.1 5497560 3 edge?, culture? 203 L20470 1150 356448.7 5496726 3 culture? 206 L20480 2160 356429.6 5496681 3 edge?, culture? 207 L20480 2198 355178.5 5497517 3 edge?, culture? 208 L20480 2256 353348.4 5498730 3 209 L20490 2430 355145.4 5497475 3 edge?, culture?

211 L20490 2470 356390.7 5496642 3 mag, edge?, cul-

ture?

214 L20500 2755 356385.3 5496610 3 mag, edge?, cul-

ture? 216 L20500 2794 355147.4 5497426 3 edge?, culture? 217 L20510 2972 353152.4 5498663 3 218 L20510 3038 355081 5497370 3 edge?, culture?

220 L20510 3078 356352.2 5496560 3 mag, edge?, cul-

ture? 225 L20520 3402 355084.1 5497350 3 edge?, culture? 226 L20530 3702 355050.2 5497295 3 edge?, culture? 230 L20540 4008 356549.1 5496251 3 culture? 233 L20540 4053 355024.9 5497265 3 edge?, culture? 234 L20550 4279 355003.9 5497205 3 edge?, culture? 237 L20560 4716 356450.6 5496180 3 culture? 242 L20570 5050 356440.7 5496145 3 culture? 243 L20580 5281 357560.4 5495340 3 244 L20580 5318 356427.4 5496089 3 culture? 246 L20580 5361 354928.2 5497095 3 culture? 247 L20590 5685 354904.5 5497037 3 culture? 249 L20590 5731 356389 5496055 3 culture? 250 L20600 5994 356372.3 5496015 3 culture? 252 L20600 6040 354869.2 5496996 3 culture? 253 L20610 6263 354831.4 5496966 3 edge?, culture? 255 L20610 6317 356406.5 5495923 3 culture? 256 L20610 6349 357415.3 5495267 3 edge? 257 L20620 6632 357402.8 5495197 3 258 L20620 6666 356386.9 5495895 3 culture? 260 L20620 6712 354811.8 5496933 3 culture? 261 L20630 6944 354776.2 5496886 3 culture? 263 L20630 6995 356366.1 5495833 3 culture? 264 L20630 7030 357369.9 5495181 3 265 L20640 7331 357315.6 5495135 3 edge?, culture? 266 L20640 7362 356347.4 5495786 3 culture? 268 L20640 7410 354735.2 5496850 3 edge? 269 L20650 7757 354707.5 5496814 3 edge?, culture? 271 L20650 7810 356314.5 5495757 3 ob?, culture? 272 L20660 8018 357927.7 5494629 3



273 L20660 8072 356277.5 5495718 3 ob?, culture? 275 L20660 8121 354676.1 5496769 3 culture? 276 L20670 8318 353617.6 5497421 3 283 L20680 8842 353591.1 5497374 3 284 L20690 9002 353559 5497327 3 287 L20690 9082 356134 5495614 3 culture? 288 L20690 9085 356217.9 5495558 3 culture? 291 L20700 9296 357282.4 5494815 3 ob? 292 L20700 9331 356116.2 5495561 3 culture? 297 L20710 9772 356114 5495547 3 culture? 298 L20710 9809 357263 5494761 3 ob? 301 L20720 10081 357226.3 5494724 3 ob? 302 L20720 10117 356102.2 5495467 3 culture? 304 L20720 10132 355606.7 5495813 3 culture? 305 L20720 10168 354471.5 5496553 3 culture? 310 L20730 478 357198.6 5494681 3 ob?, culture? 311 L20740 798 357157.4 5494647 3 ob? 314 L20740 882 354398 5496469 3 culture? 315 L20750 1111 354375.1 5496430 3 culture? 316 L20750 1150 355505.5 5495665 3 culture? 319 L20750 1203 357139.9 5494595 3 ob? 320 L20760 1533 357089.8 5494570 3 ob? 322 L20760 1619 354350.7 5496377 3 culture? 323 L20770 1848 354301.9 5496341 3 edge?, culture? 325 L20770 1940 357136.9 5494497 3 ob? 326 L20780 2138 357079.7 5494430 3 ob?, culture? 327 L20780 2141 356970.6 5494490 3 culture? 329 L20780 2226 354279.1 5496315 3 edge?, culture? 332 L20790 2598 355989.9 5495119 3 culture? 333 L20790 2631 356971.3 5494479 3 edge?, culture? 334 L20800 2963 355972.9 5495079 3 culture? 341 L20820 3675 354876.5 5495682 3 ob? 343 L20830 4019 356974 5494239 3 347 L20850 4642 355750.3 5494915 3 culture? 350 L20860 4906 355870.1 5494779 3 culture? 351 L20860 4910 355746.6 5494861 3 culture? 355 L20870 5232 355725.2 5494810 3 culture? 356 L20870 5236 355838.9 5494743 3 mag, culture? 359 L20880 5719 355831.9 5494680 3 culture? 360 L20880 5723 355714.2 5494756 3 mag, culture? 362 L20890 5996 353962.2 5495856 3 edge? 364 L20890 6055 355674.7 5494718 3 mag, culture? 369 L20900 6311 355671.4 5494672 3 culture? 371 L20900 6365 353934.5 5495818 3 edge? 372 L20910 6648 353884.6 5495769 3 edge? 377 L20920 6957 355737.4 5494510 3 culture?



382 L20950 7970 356334.3 5493924 3 383 L20950 7980 356644.1 5493728 3 384 L20960 8333 356342.5 5493876 3 386 L20970 8610 353642.6 5495589 3 388 L20970 8705 356660.1 5493610 3 389 L20980 674 353607.6 5495561 3 394 L20990 1135 355115.5 5494507 3 edge?, culture? 395 L20990 1182 353590.4 5495516 3 396 L21000 1426 355054.5 5494470 3 edge?, culture? 398 L21000 1478 356562.3 5493475 3

400 L21010 1813 355024.8 5494436 3 mag, edge?, cul-

ture? 401 L21010 1839 354206.7 5494985 3 edge? 402 L21022 2392 356464.2 5493422 3 406 L21022 2470 354161.6 5494949 3 edge? 407 L21030 2323 356588.4 5493290 3 edge? 411 L21040 2835 356545.1 5493267 3 mag 418 L21080 4012 354863.8 5494144 3 edge?, culture? 420 L21080 4024 355195.9 5493907 3 edge?, culture? 421 L21080 4050 355897.1 5493446 3 culture? 422 L21090 4268 355869.2 5493409 3 culture? 425 L21100 4739 355827.7 5493377 3 culture? 428 L21120 5296 355719.7 5493315 3 edge?, culture? 429 L21120 5309 356095.4 5493071 3 edge?, culture? 430 L21130 5566 355992.3 5493098 3 edge?, culture? 433 L21130 5682 352163.2 5495615 3 edge? 435 L21140 5965 355949.6 5493037 3 edge?, culture? 438 L21160 6634 355032.2 5493555 3 edge?, culture? 440 L21170 6845 355891.6 5492914 3 edge?, culture? 441 L21170 6888 354536.6 5493814 3 mag, culture? 442 L21190 7744 356334.2 5492485 3 edge?, culture? 443 L21200 8140 356301.4 5492455 3 edge?, culture? 444 L21210 8290 356274.9 5492420 3 edge?, culture? 445 L21220 8626 354460.8 5493551 3 edge?, culture? 446 L21220 8695 356623.8 5492119 3 edge?, culture? 447 L21230 8918 356593.3 5492092 3 edge?, culture? 448 L21230 8983 354456.3 5493512 3 edge?, culture? 449 L21240 9272 354421 5493464 3 mag, edge? 453 L21260 9882 356744.1 5491801 3 culture? 455 L21270 462 356693.4 5491777 3 culture? 457 L21280 660 354309.7 5493289 3 culture? 458 L21290 1019 354339.9 5493229 3 edge?, culture? 463 L21300 1283 354306.3 5493183 3 mag, culture? 464 L21310 1556 354254.3 5493145 3 mag, culture? 467 L21320 1847 356510 5491595 3 mag, culture? 469 L21320 1924 354216.8 5493121 3 edge? 470 L21330 2186 354177.2 5493078 3 mag, ob/edge?



473 L21340 2455 354150.6 5493046 3 mag, ob/edge? 474 L21350 2795 354123.2 5492996 3 477 L21360 3419 354252.3 5492867 3 ob?, culture? 478 L21360 3424 354107.1 5492964 3 mag, culture? 479 L21370 3688 353039.8 5493600 3 mag, edge?

480 L21370 3720 354073.3 5492914 3 mag, edge?, cul-

ture? 481 L21370 3724 354216.1 5492815 3 edge?, culture?

484 L21380 3998 354023.6 5492887 3 mag, edge?, cul-

ture? 486 L21390 4342 352978.9 5493507 3 mag, edge? 487 L21390 4372 353992 5492848 3 mag, edge? 490 L21410 4921 354384.6 5492468 3 mag, culture? 492 L21480 7085 352538.8 5493279 3 mag 493 L21490 7398 352444.4 5493263 3 mag 494 L21490 7464 354526.4 5491891 3 edge? 495 L21501 2095 352401.5 5493235 3 mag 496 L21510 8134 350813.9 5494203 3 mag 497 L21510 8155 351496.4 5493779 3 edge? 498 L21510 8181 352352.5 5493208 3 mag, culture? 499 L21520 8452 354431.4 5491753 3 edge? 501 L21520 8545 351469 5493742 3 edge? 502 L21520 8567 350792.8 5494188 3 mag 503 L21530 8688 351419.6 5493723 3 505 L21530 8785 354402.5 5491718 3 507 L21540 478 354184.5 5491808 3 edge? 508 L21550 711 354164.2 5491762 3 edge? 509 L21550 764 352562 5492839 3 mag, edge? 511 L21560 977 352529.7 5492756 3 mag, edge? 512 L21560 1029 354143.5 5491718 3 edge? 513 L21570 1262 354111.1 5491684 3 edge? 515 L21580 1613 351964.5 5493045 3 ob? mag 516 L21580 1625 352337.3 5492785 3 edge? 517 L21580 1685 354078.8 5491640 3 519 L21590 2325 351919.6 5493020 3 ob? mag 520 L21600 2504 351871.9 5492980 3 ob? mag 523 L21610 2895 351838.2 5492963 3 ob? mag, culture? 526 L21630 3520 352191.6 5492620 3 mag 527 L21630 3535 351724.9 5492906 3 ob? mag, culture? 528 L21640 3666 350218.4 5493839 3 529 L21640 3710 351658.6 5492885 3 mag 530 L21640 3723 352118.4 5492592 3 edge? 532 L21650 4133 352105 5492517 3 edge? 533 L21650 4147 351635.7 5492864 3 ob? mag 534 L21650 4190 350185.2 5493799 3 535 L21660 4314 351556.2 5492826 3 ob? mag 536 L21670 4658 352085.4 5492428 3 mag, edge?



537 L21670 4671 351613 5492741 3 mag, ob? 538 L21670 4674 351506.2 5492812 3 ob? mag 539 L21680 4839 351462.6 5492777 3 ob? mag 540 L21680 4843 351577 5492703 3 ob? mag 541 L21680 4857 352038.8 5492395 3 edge? 543 L21690 5268 351537.6 5492671 3 ob? mag 544 L21690 5272 351425.1 5492748 3 ob? mag, culture? 545 L21700 5449 351381.3 5492716 3 ob? mag 546 L21710 5824 351359 5492682 3 mag, ob? 547 L21720 5997 351311.5 5492638 3 ob? mag 548 L21760 7221 353110.7 5491218 3 549 L21770 7563 353083.6 5491166 3 550 L21780 7851 353069.5 5491130 3 551 L21790 8116 353037.7 5491077 3 ob/edge? 553 L22250 6165 349529.8 5490636 3 edge? 556 L22260 6391 349518.7 5490597 3 edge? 557 L22270 6784 349485.2 5490557 3 edge? 559 L22270 6791 349237.1 5490726 3 edge? 560 L22280 6915 349293.5 5490620 3 mag, edge? 561 L22280 6964 350838.7 5489591 3 562 L22290 7270 350817.3 5489560 3 563 L22300 7468 350049 5490005 3 564 L22300 7493 350778.8 5489527 3 565 L22310 7906 350327.2 5489771 3 mag, ob 567 L22320 8062 349265.6 5490394 3 mag, edge? 568 L22320 8095 350287.4 5489725 3 mag 569 L22330 8511 350262.1 5489677 3 mag, ob? 570 L22330 8542 349248.4 5490347 3 mag, edge? 571 L22340 8802 349384.6 5490207 3 mag, ob? 572 L22340 8828 350230.3 5489638 3 mag, ob? 573 L22350 365 348504.9 5490724 3 mag 575 L22350 418 350197.4 5489600 3 mag, ob? 576 L22360 757 350180.9 5489565 3 mag, ob? 579 L22370 896 348412.5 5490655 3 mag 580 L22370 925 349318.7 5490057 3 581 L22381 1497 348364.2 5490630 3 mag 583 L22390 1427 348400.4 5490546 3 mag 584 L22390 1457 349318.8 5489935 3 edge/ob?, culture? 585 L22400 2893 348294.4 5490551 3 mag, edge? 586 L22410 2104 349366.9 5489794 3 587 L22410 2109 349504.3 5489706 3 edge?, culture? 588 L22420 2477 349498.9 5489646 3 mag, edge? 589 L22420 2482 349345.7 5489748 3 590 L22420 2516 348244.5 5490488 3 mag, edge? 591 L22430 2642 349321.5 5489691 3 mag 592 L22430 2646 349479.7 5489590 3 mag, edge?



593 L22440 3021 349315 5489647 3 mag, edge? 594 L22490 2428 348626 5489798 3 edge? 595 L22500 351 348591.7 5489773 3 edge? 596 L22500 383 349605.4 5489093 3 edge? 597 L22510 748 349586.1 5489056 3 edge? 598 L22520 934 349282.3 5489192 3 edge? 599 L22530 1316 349257.9 5489146 3 edge? 600 L22540 1766 353499.5 5486274 3 edge? 601 L22550 1878 353476.7 5486236 3 edge? 602 L22550 2015 348951 5489233 3 603 L22560 2198 348898.9 5489192 3 ob? 604 L22560 2339 353433.3 5486190 3 edge? 605 L22570 2568 349169.9 5488979 3 edge? 606 L22570 2576 348889.7 5489145 3 ob? 611 L30030 8820 357394.8 5494731 3 mag, edge? 613 T19030 5950 352337.7 5493078 3 ob? mag 615 T19050 4658 355768.7 5494653 3 edge?, culture? 617 T19060 3576 357358.2 5495249 3 culture?



APPENDIX D ARCHIVE DVD

3D Modelling of Banded Iron Formation Incorporating Demagnetization – A Case Study at the Musselwhite Mine, Ontario, Canada Yvonne Wallace

Barrick Gold Corporation Locked Bag 12, Cloisters Square, WA 6850 Australia [email protected]

SUMMARY

INTRODUCTION Musselwhite mine is located within the Weagamow – North

Caribou Greenstone Belt of the Sachigo Subprovince, part of

the Archean Superior Province, Canada (Figure 1).

80ºW

50ºN

Figure 1. Location of Musselwhite Mine

A total of 2,756 line km of aeromagnetic data were acquired

in May 2002 at 60m line spacing, with azimuth 090 at 40m

terrain elevation. The Total Magnetic Intensity (TMI) map of

the dataset in Figure 2 shows an anomalous range of

15000nT over BIF. Note that all images and references to

the data are given in mine coordinates, where magnetic north

is to the right of mine grid north at 045.

-799.1

1941.1

4681.2

7421.4

10161.5

12901.6

15641.8

TMI (nT)5 000

5 000

7 500

7 500

10 000

10 000

7 500 7 500

10 000 10 000

12 500 12 500

15 000 15 000

Figure 2. Musselwhite TMI map (sunshaded from NE)

The source of the linear magnetic high is several tightly

folded BIF units plunging to the north at 15º. Mineralization

is predominantly hosted within the BIF and in particular

within garnet-magnetite-grunerite BIF, locally termed the

Northern Iron Formation (NIF). The NIF varies in thickness

from approximately 15 m to 20 m wide along portions of the

northeastern fold limb to greater than 100 m in the hinge

zones of major antiformal closures. The Southern Iron

Formation (SIF) lies stratigraphically beneath the NIF.

The NIF and SIF are strongly layered and anisotropic with a

high degree of variability in magnetic susceptibility. For

modelling purposes a unit value of 2.2SI is assigned.

The overburden is glacial till typically 0-10m in thickness,

and up to 30m under eskers. The aeromagnetic survey

compensates for this to some extent as the thicker overburden

at an esker is a topographic high so the aircraft ground

clearance is less.

There are several TMI anomalies associated with the BIF

which are poorly understood, for example where there are

sharp or subtle dispersed amplitude changes in the magnetic

response which may not be explained by variations in cover

thickness, or the presence of sulphide replacement in faults.

Three dimensional (3D) magnetic forward modelling of

Banded Iron Formation (BIF) as high susceptibility

tabular-style bodies was carried out at the Musselwhite

Mine, Ontario in 2004. BIF is associated with

mineralisation at the mine and the study both created and

validated geologically plausible models. The models are

based on drill sections, and are built from a central axis

of nodes with geometrical and susceptibility attributes

describing each node. The model building process

reveals information about the geometrical nature of the

BIF units. The results highlight the importance of

understanding the interaction of the earth’s magnetic field

with the geometry of these highly magnetically

susceptible bodies (up to 2.5SI) when interpreting the

observed magnetic anomalies. The forward modelling

algorithm includes a calculation for the effect of

demagnetization, and at Musselwhite this is found to be

subtle in nature.

Key words: magnetics, modelling, demagnetization,

banded iron formation, Musselwhite

Mine Grid North

Magnetic

North

3D Magnetic Modelling at Musselwhite Mine, Canada Wallace YC

AESC2006, Melbourne, Australia. 2

During 2004 a two month study was undertaken to improve

understanding of the TMI map by building 3D bodies which

test new and existing models of the BIF units. Models are

built for the majority of the magnetic anomalies on the TMI

map using the WinDisp BIF Builder tool. The forward

modelling algorithm uses the MAGNET code as developed

by Logan and Angus (1997) and includes a calculation for

the demagnetization effect. The resulting TMI is found to

compare reasonably well with the observed TMI.

METHOD AND RESULTS

The 3D models are built by digitizing a central axis of each

body as a series of nodes from an observed TMI grid. Once

the first body has been digitized, the earth’s magnetic field

parameters at the given location are set along with default

parameters of depth to top, width, thickness, magnetic

susceptibility and number of layers. Each node along the line

is then individually edited for easting, northing, width, depth

to top, dip, dip direction, thickness and magnetic

susceptibility. Grid images and 2D profiles of the TMI, First

Vertical Gradient (1VG) and Total Gradient (TG) are viewed

on screen to aid the editing process. The modelled bodies

are illustrated in Figure 3.

Figure 3. Perspective view of 3D BIF models and

observed TMI map displayed as elevation.

Demagnetization is caused by the earth’s magnetic field

passing through a magnetic body, creating a charge build up

on each side of the body. The greater the susceptibility of the

body, the greater the charge build-up. These charges create a

‘self’ magnetic field or cross-component which opposes the

earth’s field. The resultant field rotates into the long axis of

the body causing both a decrease in the resultant amplitude of

the anomaly and an alteration of the asymmetric part of the

anomaly used to interpret dip. As BIF has a very high

magnetic susceptibility and is generally of the order of only

metres thick, the opposite charges are both high in amplitude

and close together. The BIF therefore incurs the

demagnetization effect. As demagnetization only affects the

cross component of the magnetic field in a thin sheet, the

effect is increased when the magnetic field cuts the body at a

high angle to the plane of the sheet.

In order to investigate the amplitude of the demagnetization

effect at Musselwhite, two 3D bodies are constructed as

shown in Figure 4 together with the calculated TMI.

Figure 4. Perspective view of synthetic models of equal

magnetic material with the calculated TMI displayed as

elevation. The ambient field is shown as a thin green cone

cutting the models at a high angle.

The ‘thin’ body to the west has a thickness of 10m and a

susceptibility of 1.5SI. The other ‘thick’ body to the east has

a thickness of 20m and a susceptibility of 0.75SI. Both

sheets have the same amount of magnetic material defined as

the product of magnetic susceptibility and thickness. The

thinner higher susceptibility sheet to the west produces a

smaller magnetic amplitude compared to the thicker lower

susceptibility body to the east. Although clearly present here,

the effect of demagnetization in the Musselwhite area is

subtle, and indicates that the amplitude changes present in

the aeromagnetic dataset cannot be explained by

demagnetization alone.

The study of the NIF and SIF in drill sections with respect to

anomalies seen on the TMI map has constrained the BIF

geometry in unexpected ways. Data from the eastern fold

limb between 9500N and 11280N shows that both BIF

packages contribute jointly to the sub-parallel magnetic

anomalies as a localised fold formation rather than each part

of the magnetic anomaly separately representing the NIF and

SIF (Figure 5).

E

EW

Figure 5. Schematic sectional view of NIF (yellow) and

SIF (red) interpretation from drill sections, beneath the

observed TMI profile in the eastern fold limb (~350m

across section).

Conversely on the western fold limb, the drilling data shows

that the NIF and SIF packages are individually contributing

to the two NNW trending linear anomalies (Figure 6).

Western

fold limb

Eastern

fold limb

SIF

NIF

E

E

W



-799.1

3311.1

7421.4

11531.6

15641.8

TMI (nT)8 000 8 500

8 000

8 500

9 000

9 500

10 000

10 500

11 000

11 500

12 000

Figure 6. Plan view of TMI (sunshaded from NE) of sub-

parallel western limb magnetic anomalies accounted for

by individual BIF packages.

When 3D bodies are constructed, the geometry of the BIF

units can account for the associated magnetic anomalies. At

11300N along the eastern fold limb, there is a decrease in

amplitude of the west side of the magnetic anomaly. This

can be accounted for by the localised fold hinge plunging to

depth, as opposed to a termination of the BIF unit (Figure 7).

-7 9 9.1

1 5 64 1 .8

TMI (n T)

8 7 0 0

1 0 5 0 0

1 1 0 0 0

1 1 5 0 0

1 2 0 0 0

Figure 7. Plan view of eastern fold limb in TMI map

(sunshaded from NE) decreasing sharply in amplitude on

the west side as localised fold plunges to depth.

At 12990N on the eastern fold limb, the BIF units turn

eastward and flatten in dip going northward, creating a

shallowly north dipping shape. The earth’s steeply dipping

magnetic field acting through the sides of the body, plus the

more subtle effect of demagnetization produce a dispersed

and lower amplitude ‘shoulder’ on the west side of the

anomaly (Figure 8). This anomaly had been previously

drilled as an alteration target, but little evidence of this was

intersected.

Calculated grid

Figure 8. Flexure and flattening of BIF (perspective view,

right) to the east creates a ‘shoulder’ in the TMI (left,

observed as contours, forward modelled in colour).

This feature is quite different to the structure further to the

south where the bodies are steeper and the earth’s magnetic

field is in a direction that is closer to the dip of the bodies

creating a more discrete magnetic high at the top of the body

such as in Figure 7.

An area of mineralisation known as the T-Antiform is

situated sub-parallel to the eastern fold limb on the west side

between 10000 and 12000N. Modelling the associated BIF

as a body plunging shallowly to depth here accounts for the

anomaly seen at 8840E, 8960N located in Figure 9.

Figure 9. TMI map (sunshaded from NE) at the T-

Antiform with surface projection of down plunge

mineralisation envelopes (black).

The mineralization is in the northerly plunging magnetized

BIF. The near-surface part of the BIF up plunge has a strong

magnetic response, but the main body of the BIF down

plunge has a subtle response and can’t be readily recognised

N

Mine Grid North

Mine Grid North

Observed

Localised

fold plunges

to depth

Mine Grid North

Mineralisation

exists down

plunge

T-Antiform

Magnetic

anomaly

Forward modelled



in the TMI map. Figure 10 shows a section view of the T-

Antiform model with the observed and forward modelled

TMI. The models are simplistic so the forward calculation

does not account for the BIF in full, hence the slight

discrepancies between observed and forward modelled TMI.

The association between mineralisation at depth and the TMI

anomaly had not been previously recognised at Musselwhite.

Figure 10. Model of T-Antiform in section view with

observed and forward modelled TMI maps displayed as

elevation

Similarly, a feature known as Billet (8480E, 6700N in Figure

2) to the west of the western fold limb shows an up plunge

anomaly that can also be produced by a shallowly north

plunging body (Figure 11). Again the models are simplistic

here creating slight discrepancies between the observed and

modelled TMI. However, a drill hole intersecting the top of

a BIF matches well to the top of the modelled body here,

increasing confidence in the models.

Figure 11. Model of Billet feature in section view with the

observed and forward modelled TMI maps displayed as

elevation

At Musselwhite we should be aware of other areas like Billet

where mineralization may lie in the down plunge extent of

high amplitude magnetic anomalies (Figure 12). This has

implications for exploration targeting of mineralisation since

we need to infer the plunge of the body and then drill down

plunge and across the body. The source of a magnetic

anomaly needs to be considered rather than the anomaly itself

which can be misleading.

-799.1

1941.1

4681.2

7421.4

10161.5

12901.6

15641.8

TMI (nT)5 000

5 000

7 500

7 500

10 000

10 000

7 500 7 500

10 000 10 000

12 500 12 500

15 000 15 000

Figure 12. Arrows point to areas of interest for potential

down plunge mineralization on the TMI map.

The magnetic BIF on the eastern fold limb has been modelled

using geometrical parameters from reliable drilling

information. The steep decrease in magnetic amplitude to the

east was difficult to replicate using these relatively well-

defined parameters, suggesting that there may be a

component of remnant magnetisation or that the in-situ

magnetic susceptibility is higher that those determined from

samples.

In the north east, changes in the character of the magnetic

anomaly around the fold nose area (10000E, 15000N)

suggest the presence of faults. Models created as bodies

separated by the faults can account for the associated TMI

anomalies (Figure 13).

Figure 13. NNW trending faults at fold nose (modeled,

left, perspective view) can account for breaks in the TMI

map (right, plan view with NE sunshading).

It is possible that some destruction of magnetite could occur

in the faults. It is not likely that this would be associated

with sulfidization as the faults are not in the direction of

regional strain at the time of mineralization which is aligned

with the overall trend of the T-Antiform body.

CONCLUSIONS

In the Musselwhite area, the interpretation of some well-

drilled zones have been validated by modelling the BIF. In

-7 9 9.1

1 5 64 1 .8

TMI (n T)

9 0 0 0 9 5 0 0 1 0 0 0 0 1 0 5 0 0 1 1 0 0 0

1 3 5 0 0

1 4 0 0 0

1 4 5 0 0

1 5 0 0 0

1 5 5 0 0

1 6 0 0 0

Mine Grid North

Mine Grid

North

Observed TMI

Forward modelled TMI

S N



many places, poorly understood magnetic anomalies have

been accounted for by building representative 3D bodies,

often with simple geometry. The effect of demagnetization

at Musselwhite was found to be subtle and therefore not

solely responsible for sharp and subtle dispersed changes in

amplitude that are seen in the TMI.

Down plunge areas are identified as targets of interest. The

T-Antiform example highlights the importance of defining

and considering plunge and plunge azimuth. The modelling

results emphasize that highly magnetic bodies may not cause

a magnetic anomaly directly above them in the TMI, and that

a plunging geometry can interact with the earth’s field in a

way that is not immediately intuitive.

ACKNOWLEDGMENTS

I wish to acknowledge the code developed by Colin T

Barnett of BWG Mining, and the MAGNET code

subsequently developed by Kieran Logan of Logantek Pty

Ltd which incorporated subroutines modified from program

ANDOR written by John Coggon of Mines Geophysical

Services. John Paine of Scientific Computing and

Applications used the MAGNET code to create the WinDisp

BIF Builder in 2004. I also wish to acknowledge Peter

Kowalczyk of Barrick Gold for his encouragement and

support in carrying out this work.

REFERENCES

Anderson, C.G. and Logan, K.J., 1992. The History and

Current Status of the Osborne Cu and Au Deposit, Mt Isa.

Exploration Geophysics, Vol. 23, Nos. 1 /2:1-8.

Barnett, C. T., 1976, Theoretical modeling of the magnetic

and gravitational fields of an arbitrarily shaped three-

dimensional body: Geophysics, 41, 1353-1364.

Coggon, J.,H. 1976. Magnetic and gravity anomalies of

polyhedra: Geoexploration 14, 93-105.

Druecker, M. D., and Gay, S.P., Jr., 1987, Mafic dyke

swarms associated with Mesozoic rifting in eastern Paraguay,

South America, in Halls, H.C., and Fahrig, W.F., eds., Mafic

dyke swarms: Geological Association of Canada Special

Paper 34, p. 187-193.

Grant, F.S. and West, G.F., 1965, Interpretation theory in

applied geophysics: McGraw-Hill Book Company, Inc., New

York and London..

Logan, K.J. and Angus, R., 1997, An iterative method to

calculate self-demagnetisation for 3D magnetic bodies, with

application to the Osborne copper gold deposit: 12th

Australian Society Exploration Geophysics Conference

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