University of Wollongong Thesis Collections

University of Wollongong Thesis Collection

University of Wollongong Year

Regolith geochemical exploration in the

Girilambone District of New South Wales

Benjamin R. AckermanUniversity of Wollongong

Ackerman,Benjamin R, Regolith geochemical exploration in the Girilambone District ofNew South Wales, PhD thesis, School of Earth and Environmental Sciences, University ofWollongong, 2005. http://ro.uow.edu.au/theses/523

This paper is posted at Research Online.

http://ro.uow.edu.au/theses/523

NOTE

This online version of the thesis may have different page formatting and pagination from the paper copy held in the University of Wollongong Library.

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Chapter 4

91

CHAPTER FOUR – METHODS OF STUDY

4.1 Introduction to Sampling Methodology

The applications of exploration geochemistry are widespread and commonly multi-

disciplinary; for example, to identify various lithologies for geological mapping,

calibrating remote sensing imagery, determining the chemical response of alteration or

weathering, or elucidating the chemical signatures associated with mineralisation, to

name just a few. These applications vary considerably, although there are some

common features to all geochemical programs. It is the primary function of these

geochemical sampling programs to identify certain geochemical patterns which reflect

particular geological processes. This study is concerned with identifying the spatial

distribution of elements associated with ore formation, alteration and weathering of

copper sulfide deposits in the Girilambone District of New South Wales.

In the design and implementation of geochemical sampling programs, there are several

key concepts which should be addressed, these being sampling, sample processing and

chemical analysis. For all of these components there are numerous options available to

the geochemist. This chapter addresses the design, implementation and rationale of

sampling, chemical analysis and data analysis methodology undertaken to achieve the

objectives of the various geochemical programs of this study. Concepts which underpin

the methodologies referred to in its contents are largely presented in Chapter Two.

This study progressed in three phases which occurred chronologically as experimental

design, data acquisition and data analysis. The first stage of this process has previously

been identified in Chapter One. Table 4.1 identifies and summarises the basic steps

undertaken in the design and implementation of each geochemical survey. Initially

orientation studies were conducted to assess the viability of various sampling, sample

preparation and chemical analysis options. These orientation studies provide the basis

for the methodology which is introduced herein. Details of these studies are provided in

Appendix 1 and Appendix 7 which describe preliminary investigations of soil sample

preparation of various sample size fractions from Tritton soil geochemical sampling and

Larsens East profile studies, respectively. Data from these studies are incorporated in

later chapters in the corresponding sections.

Chapter 4

92

Table 4.1 The three phases of experimental design and implementation undertaken in this study.

All previously available geological and geochemical data were collected and reviewed

prior to field sampling. After consideration of the possible sampling media, sampling

density and sample size, a ‘sampling budget’ was created to determine the likely costs

and incidentals of the sampling programs at the proposed scale of investigation. For

each geochemical survey, possible sampling media were evaluated with the scientific

objectives of each survey in mind. Sampling density and sample size were proposed at a

scale considered appropriate to attain these objectives. Funding for the chemical

analyses by INAA and ICP-MS/AES was sought from the Australian Institute of

Nuclear Science and Engineering (AINSE) and the Society of Economic Geologists

(SEG) respectively. Table 4.2 outlines the funds awarded for completion of this study.

Field sampling and data collection were conducted at Tritton and Girilambone North

study sites and from various regional locations. Samples collected during the study were

transported to the University of Wollongong where they were prepared for

Phase Components 1. Identify scientific objective Surface geochemical expression of mineralisation

Dispersion characteristics of ore-related elements in regolith Regolith processes and products

2. Collect existing data Company data Remotely sensed data Previous studies

3. Sample media selection Available sampling media Scale of investigation Sampling density and sample size

4. Determine analysis methods Chemical analyses Physical analysis

5. Sample Budget Time and cost of field sampling, chemical analyses, quality assurance Chemical analyses Quality assurance

6. Field sampling Collection of samples in the field Sample Transport and storage Mapping, surveying

7. Sample preparation Sample reduction and splitting Prep of homogeneous samples Prep of samples for mineralogical analysis

8. Analyses Geochemical analysis - INAA, ICP-AES/MS Mineralogical analysis - XRD, petrographic analysis

9. Data Interpretation and analysis Data integrity Data storage and access Exploratory data analysis Multivariate data analysis Modeled investigations of data

10. Assess attainment of research objectives Draw conclusions Additonal sampling/analyses if required

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Chapter 4

93

mineralogical and petrographic analyses according to the various survey designs. The

majority of sample preparation for chemical analyses requiring a homogenised pulp

sample was conducted at the CSIRO Department of Exploration and Mining Sample

Preparation Laboratories, North Ryde. Following data acquisition, data were interpreted

by various exploratory data analysis and multivariate data analysis techniques.

Following these procedures, each geochemical survey was assessed to determine if

research objectives had been met.

Analysis method codes referred to throughout this study are summarised in Appendix 2.

Corresponding lab, analysis methods, descriptions and standard detection limits for each

analysis are indicated.

Table 4.2 Research funding received for various aspects of the present program of study.

4.2 Existing Data

Data were collected from several sources, including previous studies (Gilligan et al.,

1994; Pahlow, 1995; Gibson, 1998) and remotely sensed data (e.g. air photos, digital

elevation model (DEM), magnetics). Several decades of mineral exploration and mining

activity in the Girilambone district by various companies and research bodies has

amounted to a vast array of geological and geochemical information. In particular, Nord

Pacific Limited (Nord) allowed access to extensive company databases from current and

previous exploration, resource delineation, feasibility studies and mining activities.

Numerical data were stored in Microsoft Access (Access) databases and spatial data

were incorporated into a GIS using ESRI ArcGIS 9.0 software for each study area.

Figures 4.1 and 4.2 depict site features of the Girilambone North and Tritton study area

respectively, including cultural features, drill collars, pit outlines and mine features.

Awards Received Title Value Reports

AINSE Award 2001 (01/031)

'Regolith processes and geochemistry of weathered ore deposits in the Girilambone District, NSW'

$10,000 http://www.ansto.gov.au/ainse/prorep2001/r_01_031.pdf

AINSE Award 2002 (02/023)

'Soil Geochemistry and Regolith Profile Analysis of the Tritton Copper Deposit, Girilambone District, New South Wales'

$7,650 http://www.ansto.gov.au/ainse/prorep2002/R_02_023.pdf

SEG - Hugh E. McKinstry Student Research Grant,

2002

‘Regolith Processes and Geochemistry of Weathered Ore Deposits in the Girilambone District, New South Wales, Australia’

US $2000 http://segweb.org/2002Grants.htm

Chapter 4

94

Figure 4.1 Girilambone North site features including drill hole collar positions and open pit

outlines. Sampling programs of the current study are indicated (AMG coordinates).

4.2.1 Nord Database - Girilambone North

Previous geochemical sampling programs at Girilambone North included RAB-drilling,

vacuum-drilling and soil sampling which pre-dated mining activities and are

summarised in Table 4.3. Soil sampling and vacuum drilling were conducted by Nord

and Straits exploration joint venture, while RAB drilling dates back to pre-Nord

ownership (1983) when Seltrust held these tenements.

Table 4.3 Surface geochemical programs conducted at Girilambone North.

Geochem. program No. samples Depth (m) Type Method codeRAB-drilling 1183 18-20 2 m composite D100

710 0-5 1 m composite D100

FAEX

503 <1 grab Regoleach

901 IC205Soil

Vacuum-drilling

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Sampling sectionsOpen cut pit outline

Chapter 4

95

Figure 4.2 Site features of the Tritton study area including drill hole collar positions, surface

projection of ore body and other site features (AMG coordinates).

Two RAB drilling programs were conducted on separate grids and orientations in the

Girilambone North exploration tenement. The first program contained 18 lines oriented

grid east-west (shown in blue in Figure 4.3) at 60 m spacings on lines 75-150 m apart

for 311 holes. The second RAB drilling program (shown in red in Figure 4.3) was

oriented on a north-east grid at 30 m spacings on lines 50 m apart for a total of 44 lines

and 871 samples. Two-metre composite samples were collected from 18-20 m depth.

Although the geochemical analysis method in the RAB programs is unknown, a ‘total’

digestion with AAS ‘finish’ was most likely the analysis method, which determined Cu

only for the first program and Co, Cu, Pb, Mn and Zn for the second program.

Vacuum drilling was conducted over 26 lines on a north-east grid at 50 m spacings on

lines 100-200 m apart. A total of 710 holes were sampled and the elements As, Co, Cu,

Au, Pb, Mo, Ni, and Zn determined by AAS after a perchloric acid digest. Figure 4.4

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Chapter 4

96

shows the orientation of vacuum drilling at Girilambone North in relation to other site

features.

Figure 4.3 RAB-drilling sampling programs, Girilambone North study area (AMG

coordinates).

Two soil sampling programs were conducted simultaneously by Nord and Straits

exploration joint venture at the Girilambone North site. The first determined soils on a

north east grid at 50-100 m spacings on lines 200 m apart utilising a proprietary partial

leach method, Regoleach, for determination of Sb, As, Ba, Bi, Ca, Co, Cu, Fe, Au, Pb,

Mg, Mn, Hg, Mo, Ni, K, Se, Ag, Na, Te, Sn, W, V and Zn. The second soil sampling

program analysed for Cu only after an Aqua Regia digest with ICP-AES finish (total

Cu). Sampling for this latter survey was at 50 m spacings for the same lines as the

aforementioned sampling program, although offset such that each Regoleach sample

was bound by a total Cu sample 25 m to the east and west on the sampling grid,

totalling 901 samples. In the vicinity of the delineated and now mined Girilambone

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Open cut pit outline

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0 200100 m

Chapter 4

97

North deposits, sampling lines collected soils at 50 m spacings and analyses by both

Regoleach and total Cu were obtained. Figure 4.5 shows the orientation of soil sampling

programs at Girilambone North and identifies samples analysed by Regoleach (green),

total Cu (yellow) and Regoleach and total Cu (orange) methods.

Figure 4.4 Vacuum-drilling program, Girilambone North study area (AMG coordinates).

Extensive drilling programs have been undertaken during exploration, resource

delineation and feasibility studies of the Girilambone North deposits. Table 4.4 shows

the extent of drilling for the Hartmans and Larsens East deposits, which combined

account for over 44000 m in total. Geochemical analyses of 1 m composite samples

were analysed by various methods (A102, A103, FA50, F614, H102, H109, M832, and

M821) which are detailed in Appendix 2. Figure 4.1 shows the position of drill collars of

the Girilambone North deposits.

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483500 484500 485500 48650065

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Open cut pit outline

") Vacuum sampling

0 1,000500 m

¯

Chapter 4

98

Figure 4.5 Soil sampling programs, Girilambone North (AMG coordinates).

Table 4.4 Hartmans and Larsens East drilling, Girilambone North.

4.2.2 Nord Database – Tritton

Prior to the current study, soil geochemical surveys including total analyses and various

partial and selective leach methods, RAB and vacuum drilling had been conducted in

Pit Hole ID Description No. holes Drill metresHartmans HAD DDH - exploration 3 1281

HAGT geotech. drill hole 5 438

GAPQ PQ - metallurgical 2 224

HARC RC - resource definition 154 17185

Sub total 164 19128LED DDH - exploration 8 2472

LEGT geotech. drill hole 5 640

LEPQ PQ - metallurgical 3 332

LERC RC - resource definition 158 21528

Sub total 174 24972Total 338 44100

Larsens East

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485000 486000 487000 488000

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!( Regoleach!( Total Cu!( Total Cu & Regoleach

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!( Regoleach!( Total Cu!( Total Cu & Regoleach

Open cut pit outline

Chapter 4

99

the vicinity of the Tritton copper deposit. Table 4.5 summarises the surface geochemical

sampling programs conducted at this site. Figures 4.6, 4.7 and 4.8 depict the location of

these geochemical surveys in relation to the surface projection of mineralisation and site

features identified previously in Figure 4.2.

Table 4.5 Surface geochemical programs conducted at Tritton.

Figure 4.6 RAB-drilling sampling program, Tritton study area (AMG coordinates).

Pre-Nord exploration lease owners Seltrust conducted RAB drilling and geochemical

sampling for 898 holes over the Tritton and Budgerigar exploration tenements (then

Bonnie Dundee and Yarraman). Initially 703 holes were drilled on seven lines 480 m

apart oriented grid east-west and at 30 m spacings. Follow up drilling was conducted on

Geochem. Program No. samples Depth (m) Type Analysis Method RAB-drilling 898 1-5 1 m composite D100

Vacuum-drilling 922 1-4 1 m composite D100

FAEX

Soil 60 <1 grab Various - see table 4.6

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Chapter 4

100

lines 80 m apart and at 30 m spacings for 195 holes and was centred about the north

trending silicified ridge to the North of the delineated Tritton copper deposit. Figure 4.6

shows the location of RAB holes covering the Tritton and Budgerigar tenements. All

samples have been chemically analysed for Cu, Pb, Mn, Ni and Zn, with As also

determined for selected samples (n=49).

Vacuum drilling was conducted by Nord Resources in 1995 at 50 m spacings on lines

oriented grid east-west and 200 m apart for 922 samples. Figure 4.7 shows the locations

of vacuum sampling in relation to the known position of the Tritton copper deposit and

other site features. Samples were analysed for As, Co, Cu, Au, Pb, Mn, Mo, Ni, Ag and

Zn by several methods. Samples were taken as one-metre composite samples from one

to four metres depth below the surface level, and sampled the upper saprolite.

Figure 4.7 Vacuum-drilling sampling, Tritton study area (AMG coordinates).

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Chapter 4

101

Figure 4.8 shows the orientation and location of soil sample traverses from previous

geochemical exploration surveys. Soils were sampled from two northing lines of the

Nord mine grid, which is rotated 8o west of north. Soils were obtained from the

B-horizon at 50 m spacings on each traverse, and the less than 5 mm fraction retained

for analysis. Table 4.6 indicates the analysis type performed on each set of soil samples.

Figure 4.8 Soil sampling, Tritton study area. Sampling from the current study and Nord

exploration program indicated area (AMG coordinates).

Table 4.6 Soil geochemical surveys conducted at Tritton.

Drilling at Tritton has included exploration, resource development and mine feasibility

studies. Table 4.7 shows the extent of drilling at Tritton. Diamond drill holes were

drilled from Reverse Circulation (RC) pre-collared holes, thus RC drill metres are

considerably over represented in this table. In excess of 80,000 m of drilling has been

undertaken from these three programs combined (Tritton Resources Limited, 2003).

Line ID No. of samples Description Analysis Method Code29200N 30 <5 mm, B-horizon ALS, IC8M

29300N 30 <5 mm, B-horizon ALS, IC8M, IC588, PM224, PE10

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RoadOrebody surface projection

Budgerigar

0 500250 m

¯

Chapter 4

102

Geochemical analyses were conducted by various methods (F614, A102, A103, B665M,

M812, M821, M832) for the elements Sb, As, Bi, Cd, Au, Fe, Pb, Ni, Se, Ag, S and Zn.

Figure 4.2 shows the surface collar position of the Tritton prospect in relation to other

site features.

Table 4.7 Drilling programs conducted at Tritton.

4.3 Field Sampling

Field sampling was the first component of the data acquisition phase. Field work was

conducted at the Girilambone North and Tritton study sites, and at selected outcrop

exposures, road and railway cuttings throughout the region. Full access to the Nord

Resources Limited mining and exploration leases was granted for the purpose of field

work.

At each soil sampling location, details of the landscape position were recorded

including aspect, slope, relief, vegetation and nature of regolith materials (gravel, lag,

sediment etc.). In an effort to describe subtle changes in soil characteristics across soil

sampling traverses and trench profiles, texture, colour and pH were recorded in addition

to site attributes. Soils were described using the soil textural classifications system of

Northcote (1971) and wet and dry colours quoted using the Munsell colour chart

system. Soil pH was measured in the field initially using portable field pH meters and

then again in the laboratory with the same instrument after soaking one part sediment to

four parts distilled water and allowing soil solutions to equilibrate.

Company drill hole data including collar, survey, assay and lithology information were

integrated with geochemical, mineralogical and petrographic information obtained in

the present study. The combined data were extracted from drilling and geochemical

databases to log profile plotting software, WinLog version 3.14. This has enabled the

comparison of drill hole data with geochemistry for the purpose of interpretation and

Prospect Hole ID Description No. holes Drill metresTritton BDSRC DDH - exploration/resource 46 46701.41

BDS RC - exploration/resource 167 33630.82

BDSM metallurgical 17 4407

Total approx. 230 approx. 85000

Chapter 4

103

presentation. Appendix 3 holds detailed lithological logs of all drill holes from

Girilambone North and Tritton study areas sampled and analysed as part of the present

study.

Sample positions were recorded by Global Positioning System (GPS) and Electronic

Distance Measurement Total Station (EDM) survey equipment. GPS positions were

post-time differentially corrected against base station data collected from a known

position for the duration of sampling. Similarly, EDM surveys were sighted back to a

known position to convert data into a standard coordinate system. A trig station at

Tritton was used as the known reference position and survey stations at Girilambone

North.

All spatial data are quoted in metric units, and have been converted to the Australian

Map Grid (AMG) coordinate system using the AGD 1984 datum (Zone 55), including

all local mine grids. GPS positions were recorded in the WGS 84 datum and

subsequently converted to AMG coordinates. Data processing was facilitated using

Trimble Pathfinder Office software and ArcGIS. All elevations coordinates have been

converted to metres above sea level (RL) for all data in this study. Thus, all spatial data

are represented by easting (AMG), northing (AMG) and RL (m). Each sample was

given a separate sample identification number with the prefix ‘BRA’ and a four digit

suffix e.g. BRA0001. After collection, all samples were stored in zip-lock plastic bags

and clearly labelled with indelible ink. Handwritten paper tags were added to each

sample bag to aid identification if the external label were to become unreadable. A

sample catalogue was created in Access which documents sample identification, sample

location, coordinates (x,y,z), sample type and where necessary Nord sampling

identification details. Survey data and descriptive fields of each sampling location were

input to the database as well as geochemical, mineralogical or other data which

followed. The sample identification number formed the primary key for database

queries, joins and relates in various Access databases created within this study.

4.3.1 Girilambone North

Investigations at the Girilambone North mine include sampling from the Larsens East

and Hartmans open cut mines. Rock chip samples from RC drill programs and diamond

drilling programs of Nord and Straits exploration and mine development were collected

Chapter 4

104

as part of this investigation as well as pit wall samples of the present investigation.

Table 4.8 summarises the sample types collected and analysed from Girilambone North.

Table 4.8 Girilambone North drilling samples.

4.3.1.1 Larsens East Samples were collected from retained RC drill chip samples from section 2550N. Figure

4.1 shows the orientation of this section in plan view with respect to the Larsens pit

extent and Figure 4.9, the sample locations in cross section. A total of 91 samples were

collected and analysed by INAA, 35 of these samples form the orientation study which

also analysed for an additional 20 elements by ICP-MS/AES by method I104. Details of

the Larsens profile orientation study are provided in Appendix 7.

4.3.1.2 Hartmans

The Hartmans long-section profile incorporates samples from ten RC drill holes from

surface level to depths of up to 142 m. The profile is shown in plan view in Figure 4.10,

which samples the economic extent of the Hartmans ore body. Figure 4.11 depicts the

sampling of this program through the upper weathered profile, supergene enriched

copper ore body and primary sulfide zones. Samples were obtained from retained drill

cuttings and sample pulps.

Pit Hole Id east north rl dip az. tot. depth weath. depth from (m) to (m) nHARC011 485135.3 6545923.0 220.6 90 113 92 0 106 21HARC005 485175.8 6545861.7 222.5 90 101 approx. 100 0 96 17HARC034 485233.8 6545808.0 224.5 90 101 96 0 96 15HARC039 485259.2 6545765.5 225.9 90 101 95 0 96 15HARC044 485263.6 6545709.4 228.2 90 83 >83 0 83 14HARC064 485255.1 6545675.4 230.0 90 102 >102 0 100 19HARC065 485268.0 6545653.8 231.5 90 102 >102 0 100 21HARC080 485280.9 6545632.4 232.7 90 130 112 0 121 28HARC084 485294.0 6545611.4 233.5 90 150 97 0 141 23HARC090 485327.8 6545602.2 231.7 90 150 96 0 142 23

196LERC006 485605.4 6545332.0 220.4 60 240 173 121 25 143 22LERC007 485563.5 6545306.0 221.2 60 240 138 112 0 90 22LERC071 485545.6 6545296.0 221.8 60 240 110 >110 0 47 15LERC103 485631.1 6545345.0 219.9 60 240 198 106 77 130 8LERC118 485584.2 6545320.0 220.8 60 240 150 118 24 143 24

91287

Lars

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Survey (AMG) SamplingDepth (m)

Har

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Chapter 4

105

Figure 4.9 Larsens East section 22550N, Girilambone North. Orientation study and additional

sampling indicated. All measurements are in metres.

Figure 4.10 Collar position of Hartmans long-section in plan view, Girilambone North (AMG

coordinates).

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Chapter 4

106

Figure 4.11 Hartmans long-section, Girilambone North. All measurements are in metres.

4.3.2 Tritton

After close examination of Nord drill sections and existing geochemical drilling

database, RC drill cuttings, metallurgical drill hole sample pulps and diamond drill core

from previous surveys were obtained. A total of 210 samples from 20 drill holes were

collected to sample various lithologies, mineralisation and the weathered profile.

Table 4.9 summarises the sample types collected and analysed from the various Tritton

drilling programs. Figure 4.12 shows the location of sampled Tritton drill collars in plan

view. With the exception of drill holes for metallurgical testing (prefix BDSM), the

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Orebody surface projection

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0 200100 m

Figure 4.12 Sampled drill hole collar locations, Tritton study area (AMG coordinates).

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RL

(m)

Chapter 4

107

orientation of sampled drill holes were inclined to the east and from drill holes on an

irregular drill pattern. Thus, the sampling density was insufficient to allow merging of

drill holes to create a two dimensional profile as observed with near surface deposits at

Girilambone North. Hence, drill hole features are represented as individual drill hole

logs rather than in section (see Appendix 3).

Table 4.9 Tritton drilling sampled drill holes.

Two soil survey lines (Line 1 & Line 2) were conducted by the present study in

conjunction with Nord, whereby C-horizon soils from two lines oriented north-east

traversing the up plunge extension of known mineralisation of the Tritton copper

deposit (Figure 4.8). Samples were taken at approximately 42 m spacings on each line

for a total traverse distance of 1503 m and 21 samples per line. Chemical analyses for

the elements Sb, As, Co, Cu, Au, Pb, Ni, Ag and Zn were undertaken by methods

PM205 and IC205 following Aqua Regia digest. Additional sampling was undertaken

as part of the current study which extended the sampling of C-horizon soils to 2500 m

centred about the known position of mineralisation. Sample spacing was maintained at

the extremities of previous sampling and increased to 84 m and greater further from

known position of mineralisation. Nord sampling line 29300N was re-sampled at the C-

Type Hole ID east north rl dip azimuth tot. depth weath. depth from (m) to (m) n

BDS012 473484.1 6526500.4 266.2 80 262 426 68 226 227 1

BDS014W 473518.4 6526606.6 265.1 80 262 360 - 283 355 2

BDS018W 473622.5 6526620.8 263.9 80 262 379 - 350 351 1

BDS020 473420.0 6526593.4 267.6 68 262 353 106 326 327 1

BDS023 473546.6 6526408.2 270.0 80 262 585 69 542 543 1

BDS042 473609.2 6526672.1 263.6 85 262 612 59 493 494 1

BDS052A 473670.6 6526627.4 263.3 85 262 642 65 578 579 1

BDS084 473593.4 6526640.7 264.0 85 262 425 50 329 392 3

BDS085 473810.3 6526697.7 261.3 85 262 858 83 468 469 1

BDS085N1 473810.3 6526697.7 261.3 85 262 756 - 511 512 1

BDS091 473704.9 6526732.4 262.1 85 262 708 70 694 695 1

BDS093 473699.7 6526429.7 265.9 85 262 651 68 558 559 1

BDS121 473614.0 6526669.5 263.5 85 262 570 98 456 470 2

BDS003 473080.3 6526496.6 275.9 80 262 184 127 0 171 22

BDS007 473428.4 6526544.0 267.2 80 262 390 73 20 71 19

BDS126 473618.5 6526620.1 263.9 85 282 576 58 115 176 13

BDSM001 473370.7 6526595.4 268.6 90 270 111 0 262.7 52

BDSM005 473372.9 6526615.5 268.3 90 259 129 0 259 42

BDSRC002 473153.5 6526707.8 270.6 60 262 168 122 0 162 21

BDSRC004 473054.5 6526694.8 274.3 60 262 120 >120 0 120 24210

DD

H c

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RC

chi

ps

SamplingSurvey (AMG) Depth (m)

Chapter 4

108

horizon at the site of previous investigations for comparison of these studies with the

current soil sampling program. All additional sampling (n=107) undertaken in this study

were prepared as <63 µm and <2 mm fractions and analysed by INAA. Figure 4.8

shows the location of soil sampling sites sampled during the course of this study.

Positions of proposed soil sampling were created in a GIS and the converted to

‘waypoints’, which were subsequently located in the field using a GPS unit. Samples

were taken from as close to the waypoint as practically possible. At each location a

detailed log was taken of the sampling site including site aspect, relief, soil

characteristics (type, colour, matrix), lithology, presence/absence of quartz/lithic lag and

moisture.

4.3.3 Regional investigations

Regional field work involved inspection of various rock outcrops and regolith-landform

features of the Girilambone district. This included bedrock exposures in railway cuttings

of the now inoperative Nyngan-Bourke line, Radio Hill, Hermidale, Coolabah, Byrock

and respective access roads. A number of Nord exploration sites e.g. Wilga tank, Avoca

Tank, and historic mine sites e.g. Budgerigar, were also visited.

4.4 Structural Mapping

Structural mapping was conducted in conjunction with C. Fergusson of the University

of Wollongong. Due to the lack of adequate outcrop exposure of the Girilambone Group

rocks, mapping was confined mainly to Hartmans and Larsens pits of Girilambone

North mine and the Murrawombie pit of the Girilambone mine. Structural features were

mapped at these locations and positioned with a handheld GPS. Other locations

including outcrop exposures around Girilambone, Coolabah and Tottenham were

mapped by C. Fergusson. This mapping and other investigations forms the focus of

Fergusson et al. (2005).

4.5 Regolith-Landform Mapping

Regolith-landform mapping was conducted at the Tritton study area at a scale of

1:25000 to assist with the design and interpretation of surface geochemical

investigations. Unfortunately, mining of the Girilambone North deposits precluded

production of a regolith-landform map in this study area. Several steps in the

compilation of this map included remote assignment of landform units, field checking,

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regolith-landform unit assignment and cartographic presentation of the map using

ArcGIS software. Much of the work of this kind has been pioneered by workers of CRC

LEME and this methodology is largely that of Pain et al. (1991; in press). For

consistency with these workers, regolith-landform (RLU) codes referred to in this text

are those of Pain et al. (1991; in press) and RGB colour fills are those proposed by CRC

LEME workers.

All available spatial data were incorporated into an ArcGIS project and registered to a

common datum (AGD 84, Zone 55). Landform units were identified primarily from

interpretation of 1:50,000 air photo stereo pairs in conjunction with a detailed digital

elevation model (DEM) supplied by Nord Resources Limited. Other data were available

for the area including radiometric, magnetic and Landsat images, although at the desired

scale of investigation, these data proved too coarse to extract remote information of

worth. Various surfaces to model slope, elevation and aspect were created from

interpolation (kriging) of the detailed DTM using the 3D Analyst extension in ArcGIS.

Drainages were mapped remotely from air photo interpretation and in the field with

GPS. These surfaces and drainage features were subsequently used to identify likely

landform units remotely and divide the study area into prospect-scale drainages.

Landform unit polygons were then digitised ‘on screen’ and checked in the field during

subsequent site visits.

Detailed regolith descriptions were recorded for selected sites across the study area

thought to be representative of each regolith-landform unit and the location of each

captured with GPS. In addition, survey traverses were made over the study area,

specifically for the purpose of characterising surface regolith features and creating a

basic model for the study area. These traverses were surveyed in the field using standard

EDM survey equipment which allowed accurate determination of elevation not readily

achievable by GPS survey methods. At each survey point shallow pits were dug and

short hand auger holes drilled for closer inspection of the soil profile and surface

material. These traverses were subsequently tied into the site GIS framework. Figure 4.2

shows the position of regolith profile traverses, which were focussed about a low-lying

silicified ridge (<9 m relief) in the centre of the Tritton study area.

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To further characterise the regolith at various locations in the study area, two trench

profiles were excavated to expose the soil profile to a depth of up to 1.2 m. Bulk

samples were obtained at 10 cm increments from the surface level which subsequently

enabled investigations of soil morphology, particle size distribution in the profile and

soil mineralogy. Figure 4.2 also indicates the position of these trenches.

4.6 Sample Preparation

Sample preparation was conducted at the University of Wollongong School of Earth and

Environmental Sciences ‘Crushing Lab’, and ‘Wet Sediment Lab’, and at the CSIRO

Department of Exploration and Mining Sample Preparation Laboratories in North Ryde.

Where possible, every effort was made to minimise the potential for cross-

contamination of samples and introduction of external contaminants during sample

preparation. All material to come in contact with the samples including sieves,

containers, spatulas and scooping utensils, were thoroughly washed and dried prior to

contact with the specimens. In between each sample, bench tops, utensils and equipment

were washed and dried and sub samples packaged, labelled and stored prior to handling

the next sample.

Drying of samples was conducted at room temperature in positive pressure fume

cupboards in large high density plastic containers. Splitting and sieving were conducted

in the ‘Crushing Lab’, with a dust extraction unit in operation to remove fine airborne

particles derived from sample preparation and dust in general. Sieving was undertaken

with the use of plastic sieves with nylon mesh for wet sieving and stainless steel

Endecott ring sieves with stainless steel mesh for dry sieving. In each instance, the

sieves were washed in warm water and air dried between samples.

The majority of samples required pulverising to obtain homogeneous samples for

chemical analysis by ICP-AES and ICP-MS. Although it was not necessary to provide a

pulverised and homogenous sample for INAA, it was desirable to provide a

homogenous sample for each analysis type to allow collation of all geochemical data at

a later stage. Thus, samples were split in a stainless steel riffle splitter following

pulverisation to obtain equivalent sample aliquots for the various chemical analyses.

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The Sample Preparation Laboratory enabled rapid pulverisation of rock chip, drill core

and soil samples by ring grinding in a dust free and clean environment. Prior to the

processing of each sample, the mill was cleaned using the method of Evans et al.

(2003), whereby grinding mills were cleaned with compressed air propelled glass beads

in a sand blaster. In this way, a clean metal surface free of residue from previous

samples, corrosion or possible contaminants was obtained. Rock chip and soil samples

were milled in a manganese steel mill for various depending on the material. After

crushing, samples were split and stored in plastic vials. Depending on the density of the

material, this allowed for aliquots of 10-25 g of homogenised sample per vial.

For INAA, the required sample size was approximately 10 g of pulverised sample,

although as little as 4 g could be analysed and an acceptable analysis still obtained (D.

Garnett, personal communication). Chemical analysis by ICP-AES and ICP-MS

required approximately 2 g of pulverised and homogenous sample.

The following is a brief description of the preparation methods used for the various

sampling media. A discussion of these methods and the potential for contamination

follows in Chapter Seven.

4.6.1 Soil samples

In the present study, three sample preparation methods A, B and C were trialled on 10

samples to determine the method most likely to yield meaningful and reproducible

results. Each of these methods was trialled for the same 10 samples, and the results

compared. Samples were analysed by INAA to determine the merit of each method. In

addition, samples were examined by binocular microscope at each stage of preparation

to observe the physical changes in each sample aliquot as the procedure progressed, and

mineralogy determined by XRD of selected samples. The results of this orientation

study are provided and discussed in Appendix 1, wherein the method found to allow

representative and reproducible sampling of bulk soils as determined by the orientation

study is detailed. This method was performed for all soil samples from the sampling

traverses 29300N, Line 1 and Line 2 overlying the Tritton copper deposit.

Soils were prepared by method B (Appendix 1, excluding 180 µm sieve) to obtain a

<2 mm and <63 µm fraction (Figure 4.13). The 2 kg bulk soil samples were transferred

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to large plastic containers and air dried in a positive pressure fume cupboard. Once

dried, samples were then split by ‘cone and quartering’ using the method of van Loon &

Barefoot (1989), each time combining the first and third quarter until approximately

400 g of sample was obtained for sample preparation. Samples were passed through

2 mm and 63 µm sieves with stainless steel rings and stainless steel mesh. Oversize

fractions for each sieve were ground gently using a glass mortar and pestle to

disaggregate agglomerations of undersize particles. Each fraction was passed through its

respective lower bounding sieve until no more material passed through the 63 µm sieve.

Oversize material of size greater than 2 mm was discarded. The fractions were split and

stored in plastic zip lock bags. Approximately 30 g of split sample for each fraction

were ground to less than approximately 10 µm using a small diameter manganese steel

mill. Mill-time was generally in the order of 15-30 seconds, and longer for samples with

abundant clay material.

Figure 4.13 Soil sample preparation flow chart. After Method B, Appendix 1.

4.6.2 Drill chips

Drill chips were split in a large stainless steel riffle splitter and where possible, 25% of

the sample was retained for later inspection, petrographic or chemical analysis should

the need arise. In some instances, the sample size did not permit retention of any

original sample as there would not have been enough for chemical analysis. In some

cases the decreased sample size was unavoidable due to poor recovery of sample during

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reverse circulation drilling. Following splitting, drill chips were simply air dried and

pulverised to obtain a homogeneous pulp. Pulverised samples were then split and

packaged in sample vials for later chemical analysis. Pulverising time varied from 30

seconds to 90 seconds for the small diameter ring mill depending on the relative

hardness of the material. Average pulverising time for the majority of samples was in

the order of 45 seconds.

4.6.3 Drill core

Diamond drill core samples were washed and allowed to air-dry prior to preparation. A

small length of core was then crushed into manageable pieces of no more than 10 mm in

diameter by use of a hydraulic press. This sample was then spit and pulverised by ring

grinding to a fine powder in a large diameter manganese steel mill. Milling duration was

generally in the order of 10 to 20 seconds. Samples were then split and packaged in 6

dram vials for chemical analysis, excess samples was stored in small plastic zip lock

bags for later use.

4.7 Mineralogical Determination

The mineralogy of selected samples was determined by X-ray diffraction (XRD) and

petrographic analysis.

4.7.1 X-Ray diffraction

Samples of greater than 10 mm in diameter were crushed to size in a hydraulic press and

then pulverised in a large diameter Cr-steel mill in the Crushing Lab. Pulverising time

was generally quite short to avoid fine pulverising and significant damage to mineral

components’ crystal lattice. XRD traces were determined by a Phillips PW1130/90

powered by an air cooled Spellman DF3 high voltage power supply. Diffractograms

were produced from 4o-70o at 0.2o increments at 2o per minute (D. Carrie, personal

communication). Qualitative analysis and interpretation of XRD traces was facilitated

by µPDSM and Traces software and quantitative analysis by Siroquant version 2

software.

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4.7.2 Petrographic analysis

Samples for petrographic analysis were made according to the method of Allman and

Lawrence (1972). Samples were sectioned and impregnated prior to mounting. Mounted

slabs were ground to approximately 30 µm, as determined by the interference colours of

component quartz grains in each sample. Glass slides were then examined under a

transmitted light microscope.

4.8 Particle Size Analysis

Soil samples obtained from selected trenches from the Tritton study area were subjected

to particle size analysis. This was conducted at the University of Wollongong using the

Malvern Mastersizer 2000. Bulk samples were split and a small representative sample

sieved to obtain the less than 2 mm fraction. A portion of this was then passed through

the particle size analyser. Ultrasonics were used to disaggregate soils prior to analysis,

with a moderate pump speed.

4.9 Incorporating Data into GIS Frameworks

All spatial data were entered into a GIS framework, using ArcGIS version 9.0 software.

ArcGIS projects were set up for the Tritton prospect and Girilambone North

Girilambone Mine site, incorporating all cadastral data available from Nord Resources

Limited, air photos and data points collected in the field by GPS and survey stations.

ArcGIS projects for Hartmans long-section, Hartmans pit wall sampling and Larsens

East cross section were produced by plotting the easting or northing as the ‘x’

coordinate depending on the orientation of the survey, and RL as the ‘y’ coordinate for

each data point. In this way, sections can be represented in plan view and subsequently

modelled.

4.10 Analytical Precision and Data Integrity

To test analytical precision of INAA and ICP-AES/MS geochemical analyses, replicate

samples of a carefully homogenised bulk sample from Hartmans pit wall survey were

analysed by INAA. Approximately 2 kg of sample from Hartmans pit (BRA0604 –

Hartmans pit, wall rock) was pulverised and homogenised in a large Mn-steel ring mill.

This sample was then riffle split and sub-sampled to obtain approximate 10 g aliquots

for submission with analysis batches. Replicate samples were randomly placed in each

analysis batch at the rate of at least 1 in every 50 submitted samples.

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The results of replicate analyses are included in Appendix 4. These tests show analytical

precision is within acceptable limits for the INAA and ICP-MS/AES methods used (see

Chapter 2). Furthermore, the commercial labs used for determining geochemical

analyses in this study regularly participated in interlaboratory cross-checks which tests

their precision against other laboratories and insert their own reference samples (D.

Garnett, personal communication) and sub-sample duplicates to monitor analytical

precision. The combined efforts of these procedures have ensured a reliable and

reproducible determination of geochemical data within the acceptable limitations of

analytical instrumentation.

4.11 Data Analysis, Interpretation and Presentation

Data analysis followed a three-stage process of preliminary, exploratory and modelled

data analysis. Largely the methods of data presentation and analysis follows that of

Lawie (1997), Grunsky (1998) and Davis (2002), the details of which are provided in

Chapter 2. The application of these methods and various aspects of geochemical data

analysis are discussed in later chapters.

Geochemical data were divided into discrete data sets according to the various

geochemical sampling programs of current and previous investigations. Each data set

was transformed into a standard format within an Access database and subject to

various exploratory data analysis approaches. Data analysis, interpretation and

presentation were facilitated by the following statistical and data visualisation software

packages: Microsoft Access; ArcGIS; JMP; Microsoft Excel; SPSS and Surfer. Except

where otherwise stated, elemental abundances are measured in part per million (ppm).

Selected elements for some analyses are quoted in weight percent (%) or parts per

billion (ppb). All distance measurements are those of the metric system. For

determination of pH, units quoted are pH units which reflect the negative log to the base

10 of the hydronium ion concentration.

Prior to data analysis, all geochemical data were processed according to a predefined set

of conditions to achieve a uniform data set free of missing or erroneous data. Univariate

data distributions were inspected spatially and in conjunction with other data series,

prior to investigation of the combined multivariate data. The high dimensionality of

multi-element data sets was reduced by cluster analysis and principal component

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analysis, which aided recognition of natural structures and chemical associations in the

data sets. Spatial reference information was then added and the data plotted with respect

to other samples in the geochemical sampling program. Thus all data were treated in a

similar fashion according to the following methods.

4.11.1 Detection limits and missing data

Analytical responses below the detectable limit were indicated as the negative sign of

ascribed instrument detection limit. For each analyte element, geochemical data below

the specified detectable limit was substituted with a value half that of the specified

detection limit (see Appendix 2 for analyte detection limits). Missing data arose from the

inclusion of additional elements between batches of chemical analyses e.g. Cd, Hg, Tb

and Sn by INAA. Similarly, missing data were substituted for half the value of the

detection limit. With the exception of soil geochemical survey line-profile analyses and

geochemical (proportional symbol) maps, analyte element data series which contained

greater than 25 % of either missing or below the detectable limit data were excluded

from further analysis.

4.11.2 Preliminary data analysis

The initial stages of data analysis involved investigation of data distributions,

preparation of summary statistical tables and identification of statistical outliers. This

was largely performed on a univariate basis, which considers the distribution of

individual elements.

All geochemical data are presented by analyte element in a summary table by data set.

Summary statistics for each data set include the following parameters: maximum;

minimum; mean; median; range; standard deviation; variance; skewness; kurtosis;

sample population size above instrument detection limit (count); the values for the 1, 2,

5, 10, 25, 50, 75, 90, 95, 98 and 99th percentile and inter-quartile range (IQR). Analysis

details including method, lab and detection limits are also included in data set summary

tables.

Threshold values for anomalism (statistical outliers) of data series were determined by

visual inspection of normal probability plots and data distributions (frequency

histograms). Summary tables for each data set include details of estimated anomaly

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thresholds. In line-profile analysis, background thresholds are defined as the 50th

percentile.

Univariate data analysis includes visualisation of data series as a frequency histogram

and normal probability plots. In the instance of soil traverse data or drill hole depth

profiles, line-profile plots of analyte concentration versus distance along the traverse or

drill hole were plotted, respectively. Input data for line-profile (time-series) plots

included all analyte elements, regardless of proportion missing or below the detection

limits of instrumental analysis.

Geochemical data were also represented spatially as univariate geochemical maps,

which plot the occurrence of geochemical elements for surface geochemical

investigations, drill hole surveys and pit wall sampling. In these plots natural divisions

identified from normal probability plots (Q-Q plots) in the data set were determined by

analysis of univariate data distributions and category data plotted with proportional

symbols to represent the geochemical response at each sampling location. The use of

proportional symbols for plotting geochemical response was used for multi-element

representations of various data sets.

4.11.3 Exploratory data analysis and modelled investigations of multivariate data

The next stage of data analysis was used to explore the relationships between two or

more variables and the spatial significance of these relationships. For several methods

discussed herein, an assumption of their use is attainment of a normal or Gaussian

distribution. In methods where this was required, data were transformed by the Box-Cox

transformation [x’=(xλ-1)/λ] method of Box & Cox (1964), described previously in

Chapter Two. Prior to transformation, anomalous, missing and below detection limit

data were excluded from the data set and the Box-Cox transformation parameter (λ)

assessed manually for each variable using the Geostatistical Analysis package of

ArcGIS software. Experimental values of λ (-2< λ <2) were trialled to obtain an

approximately normal distribution (skew.=0, kurt.=3, mean=median). Excluded data

values were then returned to the data set and transformed using the pre-determined λ

value.

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Measures of bivariate association were determined by the correlation coefficient. Levels

of significance of the correlation coefficient were determined by the two tailed

significance test described by Davis (2002). Levels of correlation coefficient

significance were determined using the method of Gravetter (2004), which compares

significant correlation scores with tabulated probability values (ρ) at a selected

confidence intervals (0.001<α<0.10). In this method, absolute values of the test

correlation coefficient in excess of the predefined ρ values were considered significant.

Multi-variate data analysis methods were employed to reduce the dimensionality of the

multi-variate data and categorise variables and samples into statistically significant

groups. Principal Component Analysis (PCA) was performed on normally distributed

data sets (following transformation if required) and based on the covariance matrix

(where variables were in comparable measurement units). Where variance differences

between variables under investigation were large e.g. Fe (%) and Sb (ppm), PCA was

based on the correlations matrix following standardisation of (normally transformed)

variables in the data set.

An iterative approach was adopted for categorising geochemical data and samples

which involved a two-step Cluster Analysis followed by Discriminant Analysis (DA) of

the cluster solution. Cluster analysis was conducted on standardised raw data using the

method of Perera (2001) which first determines the number of clusters by means of

hierarchical cluster analysis (standardised data, Ward method, squared Euclidean

distance). Once the number of clusters was determined, non-hierarchical K-means

cluster analysis, which requires apriori knowledge as to the number of expected

categories, was applied. The cluster solution was then tested using discriminant

analysis, which examines the predicted group membership and the probability that each

sample is successfully assigned based on the input variables. The relative contribution

of each variable was determined following discrimination based on the number of

identified clusters. In the event of a variable contributing a negligible weighting to the

observed multi-variate variance, non-contributing variables were removed and the

process (beginning at hierarchical clustering) was repeated. Similarly, outliers were

identified by plotting the discriminant function, and where extreme, removed from the

data set. In this way, consecutive iterations were able to eliminate non-contributing

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variables and identify anomalous samples in the population and at the same time

identify contributing variables to geochemical variance of the system under

investigation.

Geochemical associations were explored further by the creation of indices to represent

various geological processes, which were subsequently plotted spatially as geochemical

maps. The final stage of data analysis involved modelling geochemical data spatially, to

represent the geochemical associations identified in the data sets. Spatial representation

of multi-element data was largely facilitated by ArcGIS.