29 August 2024
South32
Limited
(Incorporated in Australia under the Corporations Act
2001 (Cth))
(ACN 093
732 597)
ASX / LSE
/ JSE Share Code: S32; ADR: SOUHY
ISIN:
AU000000S320
south32.net
SIERRA GORDA COPPER MINE -
ORE RESERVE DECLARATION AND MINERAL RESOURCE
UPDATE
South32 Limited (ASX, LSE, JSE: S32; ADR: SOUHY)
(South32) reports the following in
relation to the Sierra Gorda copper mine:
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·
|
A
first time Ore Reserve estimate in accordance with the JORC Code
(2012)[1] guidelines at 782 million
tonnes, averaging 0.38% total copper, 0.020% total molybdenum and
0.06 g/t gold, at a total copper equivalent[2] grade of 0.44% (Table
A).
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|
·
|
An update to the Mineral Resource
estimate, to reflect the first time reporting of a 51 million tonne
sulphide stockpile averaging 0.28% total copper, 0.013% total
molybdenum and 0.05 g/t gold, at a total copper equivalent grade of
0.32% (Table B).
|
The first time Ore Reserve
represents an initial reserve life[3] of 16 years,
with significant growth potential expected to be unlocked as infill
drilling programs further test the Mineral Resource, which remains
open at depth.
Alongside our joint venture partner,
we continue to invest to grow future copper production from Sierra
Gorda, executing the capital efficient plant de-bottlenecking
project and progressing the feasibility study for the fourth
grinding line expansion to support an expected final investment
decision in H1 FY25. The fourth grinding line has the potential to
increase plant throughput by approximately 20% to
~58Mtpa[4], sustainably lifting copper
output and reducing Operating unit
costs.
Separately, an exploration drilling
campaign is underway at the priority Catabela Northeast copper
porphyry prospect, located approximately three kilometres from
Sierra Gorda's current operations.
We are also studying options to
unlock value from oxide material[5] that is
stockpiled at surface.
Full details of the Ore Reserve and
Mineral Resource updates are contained in this
announcement.
About Sierra Gorda
South32 acquired a 45% interest in
Sierra Gorda in February 2022 and has joint control alongside 55%
joint venture partner KGHM Polska Miedź.
Sierra Gorda is a large,
conventional, open pit copper mine located in the Antofagasta
region of northern Chile. Sierra Gorda benefits from high quality,
modern processing equipment, with significant historical capital
investment. The operation is serviced by established
infrastructure, including renewable power and a seawater pipeline,
with freight rail and a national highway connecting it to the ports
of Antofagasta and Angamos. The copper concentrate produced at the
operation is transported by truck and rail to the ports of
Antofagasta and Angamos for international export to end
markets.
Table A: Ore Reserve estimate for the Sierra Gorda deposit as
at 30 June 2024 in 100% terms1,2
|
Ore Type
|
Proved Ore
Reserves
|
Probable Ore
Reserves
|
Total Ore
Reserves
|
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
|
Sulphide
|
344
|
0.41
|
0.025
|
0.07
|
387
|
0.37
|
0.014
|
0.06
|
731
|
0.39
|
0.020
|
0.06
|
|
Stockpile
|
|
|
|
|
51
|
0.28
|
0.013
|
0.05
|
51
|
0.28
|
0.013
|
0.05
|
Million dry metric
tonnes3, % TCu- per cent total copper; % Mo- per cent
total molybdenum; g/t Au- grams/tonne of gold; Mt - Million
tonnes;
Notes:
1.
Cut-off grade: Net smelter return (NSR) of >0
US$/t. Input parameters for the NSR
calculation are based on long term price forecasts for copper,
molybdenum and gold; mining, haulage, processing, shipping,
handling and G&A charges. Metallurgical recovery assumptions
differ for geological domains with an average of 83% copper, 54%
for molybdenum and 47% for gold.
2. All
tonnes and grade information have been rounded to reflect the
relative uncertainty of the estimate, hence small differences may
be present in the totals.
3. All
volumes are reported as dry metric tonnes.
Table B: Mineral Resource estimate for the Sierra Gorda
Deposit as at 30 June 2024 in 100%
terms1,2
|
Ore Type
|
Measured Mineral
Resources
|
Indicated Mineral
Resources
|
Inferred Mineral
Resources
|
Total Mineral
Resources
|
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
Mt3
|
%
TCu
|
%
Mo
|
g/t
Au
|
|
Sulphide
|
377
|
0.40
|
0.025
|
0.07
|
534
|
0.34
|
0.013
|
0.06
|
906
|
0.37
|
0.013
|
0.06
|
1820
|
0.36
|
0.016
|
0.06
|
|
Stockpile4
|
|
|
|
|
51
|
0.28
|
0.013
|
0.05
|
|
|
|
|
51
|
0.28
|
0.013
|
0.05
|
Million dry metric
tonnes3, % TCu - per cent total copper; % Mo - per cent
total molybdenum; g/t Au - grams/tonne of gold;
Mt - Million tonnes;
Notes:
1.
Cut-off grade: NSR of >0 US$/t.
Input parameters for the NSR calculation are based
on long term price forecasts for copper, molybdenum and gold;
mining, haulage, processing, shipping, handling and G&A
charges. Metallurgical recovery assumptions differ for geological
domains with an average of 83% copper, 54% for molybdenum and 47%
for gold.
2.
All tonnes and grade information have been rounded
to reflect the relative uncertainty of the estimate, hence small
differences may be present in the totals.
3. All volumes are
reported as dry metric tonnes.
4. First time
reporting of sulphide stockpile Mineral Resource
estimate.
Competent Person Statement
The information in this announcement
that relates to Mineral Resource estimate for the Sierra Gorda
deposit, presented on a 100% basis, represents an estimate as at 30
June 2024 and is based on information compiled by Ian Glacken and
Omar Enrique Cortes Castro. Mr Glacken is a full-time employee of
Snowden Optiro and Mr Cortes is a full-time employee of Sierra
Gorda SCM. Mr Glacken is a Fellow and Mr Cortes is a Member of the
Australasian Institute of Mining and Metallurgy. Mr Glacken and Mr
Cortes each have sufficient experience relevant to the style of
mineralisation and type of deposit under consideration and to the
activities being undertaken, to qualify as Competent Persons as
defined in the 2012 Edition of the Australasian Code for Reporting
of Exploration Results, Mineral Resources and Ore Reserves (the
JORC Code). The Competent Persons consent to the inclusion in this
announcement of the matters based on their information in the form
and context in which it appears.
The information in this announcement
that relates to Ore Reserve estimate for the Sierra Gorda deposit,
presented on a 100% basis, represents an estimate as at 30 June
2024 and is based on information compiled by Paola Alejandra
Villagran Cardenas. Ms Villagran is a full-time employee of Sierra
Gorda SCM. Ms Villagran is a registered member of Chilean Mining
Commission (Recognised Professional Organisation as included in a
list posted on the ASX website). Ms Villagran has sufficient
experience relevant to the style of mineralisation and type of
deposit under consideration and to the activities being undertaken,
to qualify as Competent Person as defined in the 2012 Edition of
the Australasian Code for
Reporting of Exploration Results, Mineral Resources and Ore
Reserves (the JORC Code). Ms Villagran consents to the
inclusion in this announcement of the matters based on their
information in the form and context in which it appears.
About us
South32 is a globally diversified
mining and metals company. Our purpose is to make a difference by
developing natural resources, improving people's lives now and for
generations to come. We are trusted by our owners and partners to
realise the potential of their resources. We produce commodities
including bauxite, alumina, aluminium, copper, zinc, lead, silver,
nickel, manganese and metallurgical coal from our operations in
Australia, Southern Africa and South America. We also have a
portfolio of high-quality development projects and options, and
exploration prospects, consistent with our strategy to reshape our
portfolio towards commodities critical for a low-carbon
future.
Further information on South32 can
be found at www.south32.net.
Approved
for release to the market by Graham Kerr, Chief Executive
Officer
JSE Sponsor: The Standard Bank of South Africa Limited
29 August 2024
UPDATE OF MINERAL RESOURCE ESTIMATE
South32 confirms the first time
reporting of a sulphide stockpile Mineral Resource estimate for the
Sierra Gorda copper deposit as at 30 June 2024 (Table
B).
The estimate of Mineral Resource is
reported in accordance with the Australasian Code for Reporting of
Exploration Results, Mineral Resources and Ore Reserves, 2012
edition (JORC Code) and the Australian Securities Exchange Listing
(ASX) Rules. The breakdown of the estimate of Mineral Resources
into the specific JORC Code categories is contained in Table B.
This report summarises the information contained in the JORC Code
Table 1, which is included as Annexure 1.
Geology and geological interpretation
The Sierra Gorda deposit is in the
plain of the intermediate valleys between the Cordillera de la
Costa and the source of the Cordillera de Los Andes. Exploration
and research identified three metallogenic belts from different
ages related to hydrothermal systems, with copper, molybdenum and
gold mineralisation. Most of the world-class copper porphyries that
exist in northern Chile are located within the three belts. Sierra
Gorda is located in the central belt.
Regionally, a sequence of Early
Cretaceous volcanic rocks that was intruded by a granitic complex
of Palaeocene age and a series of smaller younger intrusions have
served as host rock for numerous hydrothermal mineralisation
systems of copper, molybdenum and gold. The main structural systems
are defined by regional faults in north-south and northwest
directions, which control and serve as flow channels for systems of
alteration and economic mineralisation.
Drilling techniques
The Mineral Resource estimate for
the Sierra Gorda deposit was completed using a total of 403 diamond
drill holes (DD) (151,243m) with HQ (core diameter-63.5mm), 1,366
reverse circulation (RC) drill holes (261,147m) with a hole
diameter of 139.7mm and 366 holes with RC pre-collar to cover the
supergene zone, followed by diamond drilling (173,185m). Most of
the drill holes were orientated in the east-west direction, with
variable dips. A small number of holes were drilled in an
east-northeast direction and some of the shallower drill holes in
the active open pit area have a radial pattern.
The grade control model provides
input to the grade of the sulphide stockpile and is estimated using
samples from blast hole drilling. The spacing of blast hole
drilling is contingent on design of the blast. The average blast
hole pattern is 7m X 7m. All blast holes are sampled in the
operational areas and every second hole is sampled at the margin
beyond identified mineralisation.
Sampling and sub-sampling techniques
Logging data from 2,135 drill holes
were used for geological interpretation and assay results from
1,750 drill holes were used for Resource estimation.
Until 2021, drill half cores were
sampled at 2m intervals. Between 2021 and 2023, the practice was to
sample quarter core. Since August 2023, the sampling of half core
was re-initiated. For RC drilling, a 2m sample (up to 80kg) is
reduced to 10kg using three-stage splitting with a riffle splitter
before being sent to the laboratory. Historically, different
laboratories were used for sample preparation and chemical
analysis. Since 2018, GeoAssay in Antofagasta, an ISO 9001:2000
certified external laboratory, has been engaged for sample
preparation and chemical analysis. Preparation for both DD and RC
involves crushing to 90% passing 1.65mm. The crushed samples are
reduced using a riffle splitter to 1,000g and then pulverised to
95% passing 100µm. All logging was verified by geologists
throughout each drilling program and reviewed independently against
core photos or RC chips by an alternate geologist prior to
geological interpretation.
Blast hole samples were collected by
pushing tubes perpendicular to the blast cone. The tube is pushed
uniformly around the cone in eight locations to collect 15kg of
sample. The same laboratory, GeoAssay, and same procedure as
mentioned above was used for mechanical preparation and chemical
analysis of blast hole samples.
Sample analysis method
Samples of 1g taken from 1,000g pulp
were processed at the GeoAssay laboratory, where the samples were
digested in a mixture of nitric (95%) and hydrochloric (5%) acid
and the concentration of total molybdenum (Mo) and total copper
(TCu) was measured using Atomic Absorption Spectroscopy (AAS). A
30g to 50g charge was used to determine gold grade using the fire
assay method, followed by AAS. A range of certified reference
materials (CRMs) was routinely submitted to monitor assay accuracy,
with low failure rates within expected ranges for this deposit
style, demonstrating reliable laboratory accuracy.
Results of routinely submitted field
duplicates to monitor sample representativity, coarse crush
precision and laboratory pulp duplicates to monitor quality control
sample preparation homogeneity, and certified blank insertions to
detect cross-contamination were all within an acceptable range for
resource modelling.
Estimation methodology
Resource estimation was performed by
ordinary kriging interpolation for the three elements of economic
interest (TCu, Mo and Au). Search estimation criteria were
consistent with geostatistical models developed for each estimation
domain according to the appropriate geological controls. Validation
included statistical analysis, swath plots and visual inspection. A
discrete gaussian 'change of support' model was developed to
analyse the level of smoothing after comparison with the resource
model.
Specific gravity measurements from
drill cores were used as the basis for calculating average
densities for each estimation domain and oxidation style (i.e.
oxide, supergene and hypogene). Average specific gravities from all
samples from a domain were used for the domain tonnage conversion
factors when calculating tonnage for both mineralised and
non-mineralised material.
The grade control model is estimated
using inverse distance method with a power of two. Search criteria
use the surrounding samples to generate a local estimate. The ore
tracking system is then used where the parcel of ore moved from pit
to stockpile is assigned the grade of the respective block from the
grade control model.
Mineral Resource classification
A multi-criteria approach was used
to classify the Mineral Resource. The classification category
outcome from complete assessment is as below.
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·
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Measured Mineral Resources:
Applied to blocks where there is 90% confidence that the block
grade is within 15% on a quarterly tonnage parcel and the average
distance of the three nearest samples is less than
50m.
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·
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Indicated
Mineral Resources: Applied to blocks where there is a 90% chance
that the block grade is within 15% on an annual tonnage basis, the
slope of regression from ordinary kriging is greater than 0.6 and
the average distance of the three nearest samples is more than
50m.
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·
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Inferred
Mineral Resources: Blocks within the variogram range, but which
failed the above criteria.
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·
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Stockpile
Mineral Resource considers the uncertainty associated with material
mining, movement and tracking using equipment fitted with high
precision GPS (HPGPS). All stockpile Mineral Resource is classified
as Indicated Resource based on the above assessment.
|
Mining and metallurgical methods and
parameters
A pit optimisation (using the
Lerchs-Grossman algorithm) was completed to evaluate Reasonable
Prospects for Eventual Economic Extraction (RPEEE) for constraining
the resource boundary (both laterally and vertically) using the
parameters in the Life of Mine (LOM) Plan and joint venture (JV)
partner agreed price protocols.
Metallurgical recoveries were
derived based on current operational performance and test work. The
grade recovery curve was then derived from the inputs and has been
incorporated in the resource model for all paying elements (TCu, Mo
and Au). Metallurgical recovery assumptions differ between
geological and weathering domains and vary considerably. Average
process recovery for copper was 83%, for molybdenum was 54% and for
gold was 47%.
Cut-off grade
Sierra Gorda is a copper deposit
with molybdenum and gold which uses a NSR value as the grade
descriptor.
Input parameters for the NSR
calculation are based on long-term JV partner forecasts for Cu, Mo
and Au pricing, after considering all costs related to mining,
haulage, processing, shipping, handling and G&A
charges.
As all costs are included in the NSR
calculation, all blocks reporting a positive NSR value satisfied
the assessment of reasonable prospects for eventual economic
extraction and were reported as Mineral Resource.
Additional information is detailed
in Annexure 1.
ESTIMATE OF ORE RESERVE
South32 confirms the first time
reporting of an Ore Reserve estimate for the Sierra Gorda copper
deposit as at 30 June 2024 (Table A).
The Ore Reserve estimate is reported
in accordance with the Australasian Code for Reporting of
Exploration Results, Mineral Resources and Ore Reserves, 2012 (JORC
Code) and the Australian Securities Exchange Listing (ASX) Rules.
The breakdown of the estimate of Ore Reserves into the specific
JORC Code categories is contained in Table A. This report
summarises the information contained in the JORC Code Table 1,
which is included as Annexure 1.
Material and economic assumptions
Sierra Gorda is an open pit mine
that produced first ore in 2015. An annual review of the LOM plan
and production schedule is undertaken to confirm that the mine plan
is technically extractable and economically viable. Relevant
studies are undertaken to enable Mineral Resources to be converted
to Ore Reserves based on current operating methods &
practices.
Mining costs are calculated
primarily from first principles using detailed labour rate
calculations, equipment operating costs and actual expenditure for
materials and consumables. Processing costs account for plant
consumables and reagents, labour, power and maintenance materials
and tailings storage facilities (TSF) costs. General and
administrative (G&A) costs are based on current operating
structures. Permitting and environmental estimates are based on
current permitting timelines. Transportation charges have been
estimated using information on rail costs, export locations,
transload capabilities and transit time associated with moving
concentrate from site to port to market. Treatment and refining
charges are based on a long-term view of the refining costs and
commodity prices for copper and molybdenum concentrate. Applicable
royalties and property fees have been applied using current royalty
agreements.
Capital costs are based on the
expected future development of the mine, processing and sustaining
capital requirements. The costs have been accounted for in the
operation's valuation models. Other economic assumptions used for
the valuation reflect internal views of demand, supply, volume
forecasts and competitor analysis.
Mining factors and assumptions
An optimised pit shell is developed
utilising appropriate mining, processing, metallurgical,
infrastructure, economic, legal and ESG factors complying with the
approved geo-mechanical configuration, such as inter-ramp angles,
inter-ramp height, and berm widths. The global net dilution factor
of 2.7% was used based on average dilution of 6.5% and mining
recovery of 96.2%.
The optimised pit is designed using
Whittle software; the operational pit is designed with Vulcan
Software; strategic planning is developed in the Minemax Software
and tactical planning is completed with SP2 software.
Open pit mining equipment used
include Komatsu 930E trucks, Caterpillar 7495 and P&H 4100 XPC
shovels, PC5500 hydraulic excavators. To support mining production,
CAT D11T & Komatsu D475-A bulldozers, Komatsu WD900-3-wheel
dozers and Komatsu GD825A motor graders.
Processing method and assumptions
The sulphide ore is crushed and
ground to 194µm. The ground ore is floated to produce copper and
molybdenum concentrate with a current throughput capacity of
135ktpd. Total payable copper, molybdenum and gold production from
2024 until 2040, the end of the project's reserve life, is
estimated at 2,360kt of copper, 691koz of gold and 79kt of
molybdenum, respectively.
Geo-metallurgical domains are
defined based on mineralogy, lithology and alteration. The recovery
formula for each geo-metallurgical domain is based on bond work
index (BWI) and grades of total copper, soluble copper, iron and
molybdenum. Metallurgical recovery was assessed based on current
operational performance and test works. Recovery curve was then
derived from the inputs and is incorporated in the resource model
for all paying elements (copper, molybdenum and gold). Recovery
formulae for copper and molybdenum are included in Annexure
1.
Material modifying factors
The Sierra Gorda community team
maintain relations with the nearby community to ensure operational
continuity. Meteorological variables and air quality are monitored
on an ongoing basis and blasting is done to ensure no more than 270
blasts are carried out each year.
The mining areas are within existing
mining leases with appropriate environmental studies and approvals
in place until 2035. It is planned to update the environmental
approval to extend the mine life beyond 2035. The approval process
is planned to start by 2030 to complete the required work in time
for approval through usual processes.
Estimation methodology
The Sierra Gorda Ore
Reserve was estimated considering all modifying
factors to define an optimised pit using a Lerchs-Grossmann
algorithm. In optimisation to derive a final pit shell, Inferred
Resources were deemed to add value. In developing final mine
designs and the production schedule to achieve the annual ore
production target (mill capacity) from Measured and Indicated
Resources as an input to the valuation model, Inferred Resources
have been deemed to be waste. This ensures appropriate definition
of the ultimate pit with consideration for resource uncertainty
related to Inferred Resources.
Cut-off parameters
Sierra Gorda uses an NSR value as
the grade descriptor. Input parameters for the NSR calculation are
based on long-term JV partner forecasts for copper, molybdenum and
gold pricing, after considering all costs related to mining,
haulage, processing, shipping, handling and G&A charges. As all
costs are included in the NSR calculation, all blocks reporting a
positive NSR value satisfied the assessment of reasonable prospects
for eventual economic extraction and were reported as Ore
Reserves.
Sensitivity analyses have been
completed on metal prices, metallurgical recoveries, mine operating
costs, capital costs and use of Inferred Mineral Resources to
understand the value drivers and impact on valuation. The valuation
remains robust under the tested conditions.
Ore
Reserve classification
The following criteria were used for
classification of Ore Reserves:
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·
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Sulphide and transition ore
processed by flotation with a NSR value greater than zero Value
attributed only from Measured and Indicated Mineral
Resources.
|
|
·
|
Use of
long-term base price and cost assumptions.
|
|
·
|
Ore Reserve
converted from a Measured Mineral Resource is reported as Proved
Ore Reserve.
|
|
·
|
Ore Reserve
converted from an Indicated Mineral Resource is reported as
Probable Ore Reserve.
|
The Competent Person considers that
the classification of Ore Reserve reflects the risks and
opportunities related to geological interpretation, level of study,
appropriate assessment of the mining and processing factors,
economic and infrastructure assumptions and environmental, social
and governmental considerations.
Annexure 1: JORC Code Table 1 - Mineral
Resource and Ore Reserve estimate for Sierra Gorda
deposit
The following tables provide a
summary of important assessment and reporting criteria used at the
Sierra Gorda deposit for the reporting of Mineral Resources and Ore
Reserves in accordance with the Table 1 checklist in the
Australasian Code for the
Reporting of Exploration Results, Mineral Resources and Ore
Reserves (The JORC
Code, 2012 Edition) on an 'if not, why not'
basis.
Section 1 Sampling Techniques and
Data
(Criteria in this section apply to
all succeeding sections.)
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Sampling techniques
|
·
The Mineral Resource estimate for the Sierra Gorda
copper deposit was completed using a total of 1,750 DD holes and RC
drill holes. A total of 2,135 drill holes were used for geological
interpretation.
·
A heterogeneity study, to determine the
appropriate sample size, was undertaken by Sierra Gorda SCM in
2014. The sample reduction and preparation are in line with the
study.
·
A quarter of the RC sample volume and quarter or
half cores from diamond drilling were processed and analysed for
every twentieth sample (duplicate) to assess sample
representativity. The analytical results were within +/- 10% for
more than 98% of the samples for 2,022 drilling results.
·
Samples from DD and RC drilling were collected at
2m intervals. For RC drilling, the samples collected from 2m
intervals (up to 80kg) were reduced by riffle splitter to 10kg and
sent to the laboratory. Blast hole samples are collected by pushing
tubes perpendicular to the blast cone. The tube is pushed uniformly
around the cone in 8 locations to collect ~15kg of
sample.
·
At the laboratory, 10kg samples were crushed to
90% passing 1.65mm. The crushed samples were reduced to 1,000g
using a lineal cutter (CRC, Crushing Robotic Cell) and the 1,000g
samples were pulverised to 95% passing 100µm. For DD, prior to
2021, half cores were used for sub-sampling for chemical analysis.
Since 2021, only quarter cores have been used; the other quarter is
used for geo-metallurgical assessment. Between 2021 and 2023, the
practice was to sample quarter core. Since August 2023, the
sampling of half core was re-initiated. Half and quarter DD core
samples from 2m intervals (approx. 3kg to 4kg) were crushed to 90%
passing 1.65mm. The crushed samples were reduced to 1,000g using a
riffle splitter and then pulverised to 95% passing 100µm. Finally,
1g pulp samples were subjected to chemical analysis using acid
digestion (nitric acid at 95% concentration and hydrochloric acid)
followed by Atomic Absorption Spectroscopy (AAS). A 30g to 50g
charge was used to determine gold (Au) grade using the fire assay
method, followed by AAS. The same laboratory (GeoAssay) and same
procedure is used for preparation and chemical analysis of blast
hole samples.
|
|
Drilling techniques
|
·
A total of 403 DD holes (151,243m) with HQ core
(hole diameter of 63.5mm), 1,366 RC drill holes (261,147m) with a
hole diameter of 139.7mm and 366 holes with RC pre-collar to cover
the supergene zone, followed by diamond drilling (173,185m) have
been included in the reported resource estimation (Figure
3).
·
The spacing of blast hole drilling is contingent
on design of the blast. The average blast hole pattern is 7m X 7m.
All blast holes are sampled in the operational areas and every
second hole is sampled at the margin.
|
|
Drill sample recovery
|
·
Core recovery was measured for each 3m run at the
drill site for all DD holes. The average recovery exceeded
95%.
·
The recovery of RC drilling was determined by
weighing a sample and comparing it with the theoretical weight
determined from the hole diameter. The average recovery for all RC
drilling was more than 93%.
·
Recovery drops when drilling encounter fault
zones. Recovery was therefore maximised by managing speed of
rotation and optimising drilling fluid density.
·
Given that the overall recovery was very high,
correlation analysis between core recovery and grade was not
performed.
|
|
Logging
|
·
All DD cores were logged for lithology,
alteration, mineralisation, veins and structures. Selected drill
holes were logged for geotechnical data, which includes rock
quality designation (RQD), fracture frequency (FF), type of fault
and fill. Representative RC chips were collected from each RC drill
interval in a sample tray and were logged for lithology, alteration
and mineralisation.
·
The geological parameters required for developing
a geology and mineralisation model are pre-defined in the logging
software. For consistency, the pre-defined codes are used for
logging when entering information in the centralised
database.
·
Geological logging is both qualitative and
quantitative in nature. The quantitative assessment reflected the
prediction of the occurrence and abundance of
mineralisation.
·
The DD cores were photographed in their
entirety.
·
The geological description has the appropriate
level of detail to properly support the development of a geology
and mineralisation model.
|
|
Sub-sampling techniques and sample
preparation
|
·
The sampling interval of 2m was based on the
nature of mineralisation and method of mining. No formal study was
completed to support the sampling interval.
·
All DD cores for every 2m interval were
longitudinally cut into equal halves. One half of each core was
further sub-divided into two equal quarters; one to be used for
chemical analysis and the other for geo-metallurgical testing. The
other half was stored in the core library. The approximate weight
of a 2m quarter core sample is between 3kg and 4kg. The whole
quarter core samples were sent to an external laboratory for
processing and chemical analysis. Since August 2023, half core was
used for sampling.
·
Until 2021, DD cores were cut into two equal parts
at intervals of 2m, with one half used for chemical analysis and
the other stored in the core library.
·
A 2m RC interval weighs approximately 80kg.
Samples are reduced to 10kg using a riffle splitter and sent to an
external laboratory for processing.
·
Different laboratories have been used from time to
time for preparation and chemical analysis of drill samples. Chemex
was used in 2004 and in 2005 Acme and Andes Analytical Assay Ltda
were used. Between 2006 and 2010 Andes prepared and analysed all
drilling samples. Between 2010 and 2018, SGS (Société Génerale de
Surveillance), AAA, (Andes Analytical Assay) and ALS (Laboratory
Group) were used for sample preparation and analysis. Since 2018,
GeoAssay has been engaged to do the preparation and chemical
analysis of drilling samples. All laboratories used to date are ISO
9001:2000 certified.
·
Sample reduction and preparation for chemical
analysis is summarised below.
o RC
samples are weighted to confirm the weight received and then dried
in an oven at 105oC (+5oC) for approximately 6 to 10 hours. For
RC drilling, a 2m sample (up to 80kg) is reduced to 10kg with a
riffle splitter and sent to the laboratory. At the laboratory, the
10kg samples are crushed to 90% passing 1.65mm and reduced to
1,000g using a lineal cutter (crushing robotic cell (CRC)). The
1,000g samples are pulverised to 95% passing 100µm.
o Core
samples: For DD, prior to 2021, half cores were used for sample
preparation and chemical analysis. Between 2021 and 2023, the
practice was to sample quarter core. Since August 2023, the
sampling of half core was re-initiated. Half core samples from 2m
intervals (approx. 3kg to 4kg) are crushed to 90 passing 1.65mm.
The samples are then dried in an oven at 105oC
(+5oC) for approximately 6 to 10
hours. The crushed samples are reduced to 1,000g using a riffle
splitter and then pulverised to 95% passing 100µm.
o The
pulverised samples are passed through a rotary divider to obtain
three pulps of 200g each. One of the portions is used for chemical
analysis by AAS and the remaining two are stored as duplicates for
future reference.
o At
the secondary crushing stage, the laboratory inserts 5% duplicates
and reports on them in each report as part of its internal quality
control process. The duplicate samples are processed and analysed.
The results show that 98% of the duplicate samples are within 10%
of the original samples. Sierra Gorda SCM (SGSCM) does not keep a
formal account of the results.
·
Sub-sampling and sample preparation techniques are
adequate for the declaration of Mineral Resources.
|
|
Quality of assay data and laboratory tests
|
·
A 1g pulp sample is digested using nitric acid and
hydrochloric acid and thereafter quantified using AAS. This is
considered appropriate for the type of mineralisation. The method
is used to determine TCu and Mo percentages. A 30g to 50g charge is
used to determine gold grade using the fire assay method followed
by AAS.
·
Samples are analysed in batches of 25. A batch
contains 20 samples, two certified reference material (CRM), one
pulp duplicate, one field duplicate and one blank
sample.
·
The analytical laboratory manages an internal
quality control protocol that is performed on each batch analysed.
The protocol includes analysis of three control samples one each of
CRM, duplicate samples and blank samples per batch. The results
from the laboratory's internal control samples are reported on each
certificate of analysis delivered.
·
An analytical accuracy assessment is performed by
the SGSCM team in accordance with the 'Westgard' control rules
(control/reject/warning). A maximum of 30% relative error (RE) is
accepted for the sample duplicate, a maximum of 20% RE for the
laboratory duplicate and a maximum of 10% RE for the pulp
duplicate. The acceptance limit for contamination is the equivalent
of five times the lower detection limit (5 LDD) reported by the
chemical analysis laboratory for the method and analyte of
interest.
·
All QA/QC samples submitted by SGSCM are reviewed
immediately on receipt of analytical results. Quality control
standards are essentially defined for TCu and Mo. No significant
bias in the data has been identified from the QA/QC
results.
·
Currently, duplicate pulp samples are not sent to
another independent laboratory (check or umpire analysis) to assess
whether there is procedural bias at GeoAssay, the primary
laboratory.
·
The Competent Persons consider that the nature and
quality of the chemical analysis and laboratory procedures are
appropriate to support estimation of the mineralisation grades of
the Sierra Gorda deposit (Figure 5).
|
|
Verification of sampling and assaying
|
·
All logging and chemical analysis is peer reviewed
to confirm the geology (using core photographs) and mineralisation
match with the analytical outcome. Once verification is complete,
the data is authorised for inclusion in the central
database.
·
Drill holes have not been twinned due to the
disseminated nature of mineralisation and the low 'nugget' effect.
The assessment is confirmed on review of semi-variogram models and
provides confidence in the predictability of drilling results over
short and long ranges.
·
The logging is performed on digital tablets, which
are loaded as CSV files directly to the database. The results of
chemical analyses are digitally recorded (in CSV files) and
uploaded to a database in the SQL server.
·
SGSCM has procedures in place for periodic back up
of all information, including storing periodic backup
offsite.
·
No adjustment has been made to the analytical
data. For estimation purposes, values reported as less than the
detection limit by the laboratory were assigned a value of half of
the detection limit.
|
|
Location of data points
|
·
The mining concessions allow mining exploitation
and exploration in Chile and are regulated by the Mining Code,
which establishes the UTM coordinate system in Datum PSAD56 to be
used as the official coordinate system. The local coordinate system
developed by the mine is linked to the official coordinate system.
The location of drill hole collars is surveyed by the survey
department, using Trimble R12i equipment (global navigation
satellite system), with a real-time kinematic accuracy of 8mm
(horizontal) and 15mm (vertical).
·
Geodetic satellite positioning equipment (GPS)
(TOPCON brand - GR3 model, double frequency, with accuracy of 5 mm)
is used for geographical location and planimetry. A Total Topcon
Station model 7501 is used to determine surface distances and an
electronic LEICA level, model DNA3, is used to define precision
elevations in the mining area.
·
Downhole surveys are performed with a gyroscope
(model STO Gyro Master). The measurement is taken at downhole
intervals between 20m and 50m from the end of the hole. The company
conducting the downhole survey (Datawell) provides the data for
each hole, which is then lodged in the database. SGSCM is in the
process of preparing a procedure to validate all survey and depth
information.
·
Surveying procedures and practices are adequate
and can be used for mine planning purposes.
|
|
Data spacing and distribution
|
·
No exploration results are reported.
·
Due to the variable orientations of the drill
holes, data spacing may vary with depth. In general, drill hole
collars are spaced between 50m and 100m. Infill drilling is spaced
between 30m and 60m (Figure 3).
·
The scheduling of twin drilling will be considered
by the Project team during future campaigns.
·
All samples are composited to 8m along the drill
hole. The composite length is appropriate for panel grade
estimation with a block height of 16m.
·
Drill spacing is considered sufficient by the
Competent Persons to establish geological and grade continuity
necessary to support a reliable resource estimate.
|
|
Orientation of data in relation to geological
structure
|
·
Most of the drill holes are orientated in the
east-west direction, with variable dip. However, there are also a
small number of east-northeast orientated drill holes, and some of
the shallower drill holes in the active open pit area have a radial
pattern.
·
The general orientation of mineralisation within
the hypogene zone is sub-vertical, with a north-northeast
orientation in plan view. The drill holes are planned with an
orientation that allows lateral recognition of the main body, to
enable edge variability to be controlled. Within the mineralised
body drilling confirms the mineralised zones and provides
reasonable confidence in defining the mineralisation
·
Even though the mineralisation is structurally
controlled, the structures radiate in all directions, which means
that drill cores are not generally oriented.
|
|
Sample security
|
·
Each sample generated is assigned a number by an
automated numbering system which allows traceability at all stages
of the process.
·
The samples are sent to the GeoAssay laboratory in
Antofagasta for preparation and chemical analysis according to a
defined procedure as described above. Transport is adequate to
maintain the integrity and safety of the samples. The results are
received and are verified for storage in a custom SQL server
database.
·
The SQL database has user-level security and there
are periodic backups of the server according to SGSCM
procedure.
·
Half cores are kept in a safe place before being
processed. After sampling, crushed cores and duplicate samples are
stored in a dedicated facility with controlled access.
|
|
Audits or reviews
|
·
Between 6 and 10 March 2023, Snowden Optiro was
commissioned by South32 to conduct an independent audit of the
Mineral Resource estimate. The review identified a requirement to
collect additional density data and minor improvements to QA/QC
processes. Soon after the audit, SGSCM have put processes in place
to measure density at site.
|
Section 2 Reporting of Exploration
Results
(Criteria listed in the preceding
section also apply to this section.)
|
|
|
|
Mineral tenement and land tenure status
|
·
SGSCM is owned by KGHM Polska Miedź SA (55%) and
South32 Ltd (45%).
·
The Sierra Gorda deposit is backed by mining
tenure, granted through 249 mining concessions. Exploration of
minerals is allowed across the effective area covered by the mining
concessions, which is a total of 17,560.99 hectares. The Mining
Code, which regulates mining concession activity in Chile,
establishes that mining concessions grant the right to explore and
exploit metallic and non-metallic mineral substances. The
concessions are perpetual and are maintained indefinitely through
the annual payment of the mining patent to the General Treasury of
the Republic of Chile. Until the date of verification, their
validity extends until 28 February 2025 (Figure 1). Seven mining
easements have also been established, which grant the right to
occupy the surface and establish infrastructure necessary for the
extraction and processing of minerals, covering a total area of
33,748.94 hectares and including the water pipeline. A
corresponding payment has been made for the mining easements and
renewal of two of them will take place on 31 December 2024, with
the remaining five to be renewed before 5 January 2025. The annual
payment of the mining easement keeps the right to occupy surface
land belonging to the State of Chile in force. Currently, there are
five mining easements granted for an indefinite term, while the
remaining two have definite expiry dates:
a) Rol 2837-2013 expires 22 March
2034; and
b) Rol 3123-2010 expires 12 July
2025.
For the latter easement, the renewal
process has already been initiated.
·
Operations are carried out in compliance with the
regulations and payments established to guarantee the viability and
continuity of mining activities.
·
Royalties Law 20,026 of 2005, modified by Law
20,469 of 2010, establishes the regime under which mining companies
must pay a royalty to the State of Chile, with variable rates on
their mining operating income of from 5% to 34.5%, progressive by
sections as mining operating margin increases.
|
|
Exploration done by other parties
|
·
The historical drilling of the Sierra Gorda
deposit began in 1966 with the first surveys by ITT, Cimma Mines
and Chevron. The companies drilled 108 drill holes (95RC-13DD)
before 1987. Between 1991 and 1996, Outokumpu began the first
formal exploration campaign, completing 238 drill holes
(109RC-48DD-81 mixed). Between 1997 and 2003, RTZ drilled 61 holes
(53RC-8DD). Two companies, Teck-Cominco and SOQUIMICH, drilled 61
holes (44RC-8DD-17 mixed) between 1997 and 2011 on the Pampa Lina
property. In parallel, Quadra drilled 1,069 holes between 2004 and
2012. Finally, SGSCM drilled 589 holes between 2013 and
2022.
|
|
Geology
|
·
The Sierra Gorda deposit is located in the plain
of the Intermediate Depression or the Intermediate Valleys located
between the Cordillera de la Costa and the headwaters of the
Cordillera de Los Andes.
·
Exploration and research associated with Andean
metallogenesis identified three metallogenic belts from different
ages related to hydrothermal systems, with copper, molybdenum and
gold mineralisation, between 20° and 27° south latitude.
Metallogenic belts are differentiated by an area to the west
located in the coastal zone of Cretaceous age (130Ma), a central
zone of Paleocene-Early Eocene age (66Ma to 55Ma) and an eastern
belt of Upper Oligocene age (42Ma to 31Ma). All the world-class
copper porphyry deposits that exist in northern Chile are located
at the source of the Cordillera de Domeyko and its continuation to
the north.
·
Sierra Gorda is located in the Palaeocene-Early
Eocene metallogenic belt, located at the western edge of the
Domeyko range in the second region of northern Chile.
·
Regionally, a sequence of Early Cretaceous
volcanic rocks that was intruded by a granitic complex of
Palaeocene age and a series of smaller, younger intrusions, have
served as host rocks for numerous hydrothermal mineralisation
systems of copper, molybdenum and gold (Figure 2).
·
The main structural systems are defined by
regional faults of north-south and northwest direction, which
control and serve as conduits for fluid for alteration of the host
rock and for deposition of economic mineralisation.
·
Figure 4 shows a cross section of the chalcopyrite
mineralisation main body and drilling information used for the
modelling and estimation processes.
|
|
Drill hole information
|
·
Exploration results are not reported as part of
the Mineral Resource estimate.
·
Figure 3 shows the collar location of the drilling
information used to develop the Mineral Resource
estimate.
·
A metal equivalent has been used for reporting the
Mineral Resource estimate.
|
|
Data aggregation methods
|
·
Data is not aggregated, other than being
composited to 8m using a length weighted average for geostatistical
analysis and estimation.
·
The composite length of 8m is considered
appropriate based on the nature of mineralisation and the method of
mining (including bench height).
|
|
Relationship between mineralisation widths and intercept
lengths
|
·
The main ore body is vertical and the dominant
drilling orientation is east-west, with variable dips (vertical to
65°) depending on the location of the drill hole collar. Where
mineralisation is disseminated or stockwork in nature, drilling
also uses a variety of dip angles (vertical to 65°).
|
|
Diagrams
|
·
Relevant maps and sections are appended to this
document.
|
|
Balanced reporting
|
·
Exploration results are not specifically reported
as part of the Mineral Resource estimate.
|
|
Other substantive exploration data
|
·
SGSCM is currently conducting a geological survey
(lithology, alteration and structural system) of the entire mining
property and geophysics studies (IP-MIMDAS and
magnetometry).
|
|
Further work
|
·
SGSCM is completing annual infill drilling
programs to improve confidence in the Mineral Resource estimate
within the Catabela Pit and to identify potential extensions to the
deposit. In parallel, exploration is ongoing outside the existing
pit shell to assess the continuity of mineralisation laterally,
with emphasis on known structural trends and other potential
satellite deposits.
|
Section 3 Estimation and Reporting
of Mineral Resources
(Criteria listed in section 1 and
where relevant in section 2, also apply to this
section.)
|
|
|
|
Database integrity
|
·
The analytical results, once received, are
verified and stored in a custom SQL server database. Since the
start of mining in 2014, data on collars, downhole surveys,
geological logging and analytical results have been loaded from CSV
files as it becomes available. The upload process includes
validation checks for consistency, including assessment of
anomalous values.
·
As part of updating the geological model, all
records are reviewed by experienced geologists against core photos
in the context of the surrounding geological
interpretation.
·
Measures are taken to ensure that data has not
been modified, for example, due to transcription or typing errors,
between initial collection and use for Mineral Resource estimation
purposes. The process of validation is repeated
annually.
|
|
Site visits
|
·
Mr Ian Glacken from Snowden Optiro visited the
Sierra Gorda mine from 1 to 6 March 2023 and reviewed geology and
mineralisation in drill cores. Mr Glacken visited the open pit, the
active DD site and the core logging facility. Discussions on site
included review of QA/QC information, geological model, domain
definition, database procedures, Mineral Resource modelling and
model validation. Review of the GeoAssay laboratory in La Negra,
Antofagasta was also completed.
·
Mr Omar Cortes, an employee of SGSCM, regularly
visits all facilities and reviews all informing data and conducts
regular assessments to ensure that relevant procedures are followed
when collecting, assessing and interpreting data.
·
The findings of site visits indicate that data and
procedures are of sufficient quality for Mineral Resource
estimation and reporting.
|
|
Geological interpretation
|
·
The geological model has been developed using
lithology, mineralisation and alteration. Leapfrog software is used
in developing 3-D volumes for geology and
mineralisation.
·
The interpretation criteria considered for the
lithological units is based on the conceptual model of the deposit,
which considers a volcanic sequence (Quebrada Mala Formation,
Maastrichtian; 73Ma to 65Ma), which is in contact with the Sierra
Gorda intrusive complex (71Ma to 65Ma). Both units host porphyry
bodies (Figure 2).
·
The alteration considers the interpretation of
four main units (biotite, propylitic, sericite quartz and
argillic), with biotite alteration being dominant. Biotite
alteration is mainly characterised by pervasive replacement of
mafic minerals by secondary biotite. The propylitic alteration is
located in the periphery of the deposit. The sericite quartz
alteration corresponds to the main hydrothermal alteration,
presenting a wide spatial distribution affecting intrusives,
volcanic rocks and intra-mineral porphyries. The argillic
alteration is identified in the most supergene zone of the deposit
and has a close genetic relationship with the secondary processes
of sulphide leaching.
·
Copper mineralisation is defined on the basis of
consideration of the following criteria.
o A
hypogene zone is defined, which corresponds to the mineralisation
of primary sulphides formed by the zones of primary pyrite and
primary chalcopyrite.
o The
supergene zone is formed by a process of rebalancing from hypogenic
(hydrothermal) mineralogy to oxidising conditions near the earth's
surface. The supergene event has generated three zones; leached,
oxides and secondary enrichment.
·
Hypogene sulphide mineralisation forms most of the
mineralisation, both in terms of volume and metal content. Hypogene
copper sulphides consist predominantly of chalcopyrite.
·
Visual checks were made in 3D, plan and section
views and interpretation anomalies were reviewed and modified as
appropriate.
·
The geology is well understood due to the long
history of exploration and mining in the area and alternate
interpretations were therefore not considered.
|
|
Dimensions
|
·
The morphology and extent of the Mineral Resource
of the Sierra Gorda deposit is a sub-vertical body with a diameter
varying between 1,600m and 2,000m. Currently, the mineralised
system has been extended to a depth of 1,800m.
·
The stockpile resource covers an area of over
260ha and is located adjacent to the Catabela pit.
|
|
Estimation and modelling techniques
|
·
Mineralisation domains were developed for each
element of economic interest (TCu, Mo and Au). Seven copper
domains, six molybdenum domains and three gold domains were defined
based on mineral composition, alteration, lithology and grade
cut-off. The domains were validated by exploratory data analysis
(EDA).
·
Outlier assessment resulted in capping of
high-grade values. Probability plots were generated to identify
outliers. Composited data for Mo and Au were capped, while no
capping was applied to TCu data.
·
Datamine's Supervisor Software was used for EDA,
variography, Quantitative Kriging Neighbourhood Analysis (QKNA) and
validation of the resource model. Maptek's Vulcan software was used
for resource estimation and reporting.
·
QKNA was used to optimise estimation block size
and search neighbourhood (i.e., minimum and maximum samples, number
of samples per drill hole, octant definition). The parameters
reviewed in the optimisation process were the slope of regression
and kriging efficiency. A parent block size of 15m in the X
direction by 15m in the Y direction by 16m in the Z direction was
used for estimation. No sub-blocking was considered due to the bulk
scale of mining.
·
Ordinary kriging was used as the estimation
method, with search ellipses defined as the full range of the
respective variogram model. Three estimation passes were used by
varying the minimum number of samples, with the first search
representing the outcome from QKNA. The minimum number of
samples was reduced in subsequent passes, indicating reduced
confidence in the remaining two passes of estimation. Finally, a
fourth pass was defined for estimation by considering ten times the
original search ellipse to identify potential for future
exploration, using current understanding of the behaviour of
mineralisation.
·
Kriging efficiency and slope of regression were
recorded for each estimation run and for each element, to quantify
estimation confidence.
·
The estimate was validated by:
o visual comparison of the block model with informing data in
vertical sections and plans (Figure 6).
o scatter plots to compare estimated block with the nearest
neighbour estimate.
o swath plots in three orthogonal directions (X, Y and Z) with a
defined window to compare estimation with informing composited data
(Figure 7).
o a
discrete Gaussian change of support assessment to assess the level
of smoothing and potential under- or over-estimation of
grade.
o comparison of the Mineral Resource estimate with a previous
estimate which used a different estimation method and
reconciliation with production data, indicating a reasonable
correlation on a global and local scale.
·
Metallurgical recovery was derived for each block
using the metallurgical recovery curve generated from metallurgical
test work at different grade intervals (Tables 3 &
4).
·
No deleterious elements were considered for
estimation.
·
Correlation between different grade elements was
not considered in the estimation process. A correlation study will
be completed, and the outcome of the study will be implemented in
the next resource update.
·
The grade control model, used as an input to
stockpile grades, has been estimated using inverse distance method
with a power of two. Search criteria include the surrounding
samples to generate a local estimate. The ore tracking system is
then used where the parcel of ore moved from pit to stockpile is
assigned the grade of the respective block. The volume is assigned
to the stockpile material based on the ore tracking system. The
stockpiles are classified into four categories, namely low, medium
and high grade based on TCu grades, and the transitional material
is stored separately.
|
|
Moisture
|
·
Based on experience of neighbouring deposits and
preliminary assessment of drill cores, the moisture content appears
to be minimal.
·
To date, the laboratory does not record sample
weights before or after drying. A moisture study will be completed
to verify the moisture content and to validate the dry bulk density
assumption.
|
|
Cut-off parameters
|
·
The Mineral Resource is defined by calculating a
NSR (US$/tonne) and considering revenue using the JV partner agreed
price protocol after accounting for metallurgical recovery and
deducting mining, processing, transportation and G&A costs. The
NSR formula is provided below.
NSR (US$/t) = (Cu Price-Freight Cu
Conc.) (US$/lb) * Tcu * RecCu * (2205 * lb/t)
+ (Mo Price - Freight Mo
Conc.) (US$/lb) * Mo * RecMo * (2205 *
lb/t)
+ (Au Price - Freight Au
Conc.) (US$/Oz) * Au * RecAu / (31.1035gm /
Oz)
- ((Process +
G&A) (US$/t) - (Mining (US$/t))
t - tonnes
Cu Conc. - copper in
concentrate
RecCu - metallurgical recovery of
copper
Mo Conc. - molybdenum in
concentrate
RecMo- metallurgical recovery of
molybdenum
Au Conc. = gold in
concentrate
|
|
Mining factors or assumptions
|
·
A pit optimisation (using the Lerchs-Grossman
algorithm) was completed to determine RPEEE for defining the
optimised resource boundary (both laterally and vertically) using
the parameters in the LOM Plan and JV agreed price protocol.
Measured, Indicated and Inferred Resources were all considered as
value contributors in the optimisation process.
|
|
Metallurgical factors or assumptions
|
·
Metallurgical recovery was assessed based on
current operational performance and test work. The grade recovery
curve was then derived from the inputs and is incorporated in the
resource model for all paying elements (Tcu, Mo and Au).
|
|
Environmental factors or assumptions
|
·
SGSCM follows a strict guideline of mitigating
environmental risks inherent to operations. Some aspects considered
in developing the strategic plan include energy and water
efficiency, waste reduction, emissions reduction, control of
particulate matter and promoting recycling and reuse of materials.
There are defined targets which will result in minimising
environmental impacts on the operation and within the
community.
·
The tailings disposal has appropriate permits in
place.
·
The waste dumps are designed to ensure slope
stability.
|
|
Bulk density
|
·
A total of 6,407 density measurements were
completed by collecting samples from diamond drill cores. Outlier
values (<2.1t/m3 and >3.3t/m3) were
removed before deriving average values for each lithology and
alteration zone. No major variation is observed in density within
each lithology.
·
Samples of 15cm to 20cm in size are selected from
drill cores for density measurement. The sample is dried and coated
with paraffin. Density is calculated by weighing the sample in air
with and without paraffin and in water with paraffin, assuming the
specific gravity of water to be 1 t/m3. Average density
is assigned per lithology in the resource model.
·
Density in the stockpile resource is assigned as
1.8t/m3 based on the average density of broken rock
typical of this type of deposit.
|
|
Classification
|
·
A multi-criteria approach was used to classify the
Mineral Resource. Initially an assessment of confidence was
completed using the '90:15' method, in which the first number
demonstrates confidence and the second number provides accuracy
(e.g. a Measured Resource is defined using +/-15% accuracy with 90%
confidence over a quarterly production volume). A second phase of
assessment was conducted to consider the impacts of data quality,
data density and geological uncertainty. Consequently, a
combination of modelling criteria was used to refine the
classification scheme, including the estimation pass, equivalent
sample distance of the closest three samples and the slope of
regression. The classification category outcome from complete
assessment is as below.
o Measured: applied to blocks where there is 90% confidence that
the block grade is within 15% on a quarterly tonnage parcel and the
average distance of the three nearest samples is less than
50m.
o Indicated: applied to blocks where there is a 90% chance that
the block grade is within 15% on an annual tonnage basis, the slope
of regression is greater than 0.6 and the average distance of the
three nearest samples is more than 50m.
o Inferred: blocks within the variogram range, but which failed
the above criteria.
·
Classification of the stockpile Mineral Resource
considers the uncertainty associated with material mining, movement
and tracking using equipment fitted with HPGPS (high precision
GPS). All stockpile Mineral Resource is classified as Indicated
based on the above assessment.
·
The Competent Person is satisfied that the Mineral
Resource classification (Figure 8) reflects the geological
interpretation and the constraints of the deposit.
|
|
Audits or reviews
|
·
In March 2023, Snowden Optiro was commissioned by
South32 to conduct an audit of the Mineral Resource estimate. The
audit did not identify any major shortcomings, and it was concluded
that, in general terms, the process of generating the resource
model has followed industry standards and the supporting
documentation is adequate.
·
The audit identified possibility of further
sub-domaining of Mo and Au domains and also suggested to implement
more robust validation processes.
|
|
Discussion of relative accuracy/confidence
|
·
An assessment of confidence was conducted using a
conditional simulation study. For each domain at the block
dimension (15m X 15m X 16m), 70 realisations were generated for TCu
grades and were validated against the sample information. The
realisations were re-blocked to reflect quarterly and annual
production tonnage. The block dimensions were oriented to be
laterally extensive, to mimic the mining technique at Sierra Gorda.
A default average density for sulphide material was applied. The
90% confidence interval was compared to the mean grade of the
realisations to derive accuracy +/-15%.
o annual tonnage assumption - 47Mt
o quarterly tonnage assumption - 12Mt
·
The Competent Person is satisfied that the
accuracy and confidence of Mineral Resource estimation is well
established and reasonable for the deposit.
|
Section 4: Estimation and reporting
of Ore Reserves
(Criteria listed in section 1; and
where relevant in section 2 and 3; also apply to this
section.)
|
|
|
|
Mineral Resource estimate for conversion to Ore
Reserves
|
· The
Ore Reserve estimation is based on the estimate of Mineral Resource
included in this announcement. The Mineral Resource estimate input
to the Ore Reserve estimate was updated as at 30 June 2024 as per
Table B of this announcement.
· Mineral Resources are inclusive of Ore Reserves. The location
map with mining lease boundary is provided in Figure 1.
|
|
Site visits
|
· The
Competent Person, Ms Paola Alejandra
Villagran Cardenas, is a full-time employee
of Sierra Gorda SCM (SGSCM) and works as Technical Services Manager
at the mine. The Competent Person regularly visits all facilities
at the mine and processing plant. The Competent Person is
responsible for the long-term plan and reviewing all informing data
and conducts regular assessments to ensure that relevant procedures
for estimation of Ore Reserves are followed.
|
|
Study status
|
· SGSCM,
an open pit mine with an onsite processing facility, has been in
commercial production since 2015 following completion of a
feasibility study. An annual assessment is undertaken to review all
modifying factors and update the LOM Plan to ensure that the
updated plan continues to be technically achievable and
economically viable.
|
|
Cut-off parameters
|
· SGSCM
is a polymetallic deposit which uses an equivalent NSR as grade
descriptor to determine the value of each block. The NSR considers
the remaining gross value after deducting all costs related to
mining, processing, transporting and refining.
· Copper, molybdenum, and gold are elements of economic
interest.
· The
cut-off strategy at SGSCM considers all costs when calculating the
remaining value (NSR). An NSR cut-off grade greater than US$
0/tonne is therefore considered economic. The NSR formula (US$/t)
is provided in Section 3 (Estimation and Reporting of Mineral
Resources) of this report under cut-off parameters.
|
|
Mining factors or assumptions
|
· Open
pit mining is appropriate for the geometry of the deposit and style
of mineralisation. An optimised pit shell is developed using
appropriate mining, processing, metallurgical, infrastructure,
economic, legal and ESG factors. The main considerations when
designing the final pit include:
o Maximising recovery of economically extractable ore and
minimising increase in waste material.
o Location of key infrastructure, such as processing plant,
waste dumps and stockpiles.
o Mitigating risks in areas in the pit affected by structures
(faults).
o Complying with the approved geo-mechanical configuration, such
as inter-ramp angles, inter-ramp height, and berm widths. The
Design parameters are shown in Table 1.
· The
optimised pit is designed using Whittle software. The operational
pit is designed with Vulcan software. Strategic planning is
developed in Minemax Software. Tactical planning is completed with
SP2 software.
· Pit
design parameters including minimum mining width are provided in
Table 2.
· The
global net dilution of 2.7% was considered based on average
dilution of 6.5% and mining recovery of 96.2%.
· In
optimisation to derive a final pit shell, Inferred Resources were
deemed to add value. In developing final mine designs and the
production schedule to achieve the annual ore production target
(mill capacity) from Measured and Indicated resources as an input
to the valuation model, Inferred Resources have been deemed to be
waste.
· Open
pit mining equipment used includes Komatsu 930E trucks, Caterpillar
7495 and P&H Shovels and PC5500 hydraulic excavators. Equipment
to support mining production includes CAT D11T and Komatsu D475-A
bulldozers, Komatsu WD900-3-wheel dozers and Komatsu GD825A motor
graders.
· A
vertical section of the ore body with the final designed pit is
included in Figure 9.
· The
quality and quantity of ore sent to stockpile is tracked. Regular
surveys are conducted, and the quantity is reconciled on monthly
basis. Most of the ore in the stockpile is scheduled to be
processed towards the end of mine life.
|
|
Metallurgical factors or assumptions
|
· SGSCM
has a crushing and grinding circuit followed by two stage
floatation to develop a copper and a molybdenum concentrate. The
copper concentrate contains gold and silver.
· SGSCM
has developed a geo-metallurgical model which enabled development
of metallurgical parameters for designing and sizing the
concentrator, the ability to understand the ore characteristics and
the metallurgical response and behaviour of the concentrator when
in operation through the life of the deposit. Geo-metallurgical
sampling is reviewed for representativity on a periodic basis to
confirm the recovery models for copper and molybdenum.
· Samples are logged by a team of geologists from a geological
and metallurgical perspective (lithology, alteration, mineralogy,
RQD, etc.). The samples are sent to a laboratory for chemical
analysis and, in many cases, half of the core, is sent for
metallurgical testing. Metallurgical and mineralogical
characteristics of the samples, such as hardness, metallurgical
recovery in flotation, settling and filtration characteristics are
measured. The parameters were used in the initial design and sizing
of the concentrator and for assumption in the ongoing
operation.
· SGSCM
has defined several geo-metallurgical domains or UGM's (Figure 10)
based on mineralogy, lithology and alteration, which were the basis
for the construction of the geo-metallurgical models. A minor
revision to the original geo-metallurgical model developed in 2018
was completed in 2021 following completion of 2021-2022
geo-metallurgical sampling campaign.
· The
identification of the main geological factors controlling hardness
and copper and molybdenum recoveries was an important scope for
SGSCM. It was concluded that:
o The
main factors controlling copper recovery are lithology and
alteration, followed by mineralogy (mineral zone).
o Lithology, alteration and mineralogy (mineral zone) are not
always important factors in molybdenum recovery.
o The
principal factor controlling hardness (bond work index) is the
lithology.
o The
geo-metallurgical domains defined for SGSCM are defined by sulphide
mineralogy and rock type. Alteration is not considered an important
control variable. For all previous analysis in geo-metallurgical
models the original domains were used with modification as
required.
· There
are no material deleterious elements to copper or molybdenum
recovery.
· The
generation of the LOM model for estimating the overall
metallurgical recovery of copper and molybdenum is based on
multivariate modelling.
· Information used for fitting the LOM metallurgical recovery
model corresponds to scaling simulation information obtained from
laboratory results. The Integrated geo-metallurgical Simulator
(IGS) model, obtained in the geo-metallurgical program incorporates
the following independent variables for multiple linear
regression:
o Geo-metallurgical unit of the sample.
o Head
grades: TCu, Mo, Fe, CuS.
o Solubility ratio: TCu/CuS.
o Ratio: Fe/TCu.
Where TCu- total copper grade; Fe-
total iron grade; Mo- total molybdenum grade; CuS- soluble copper
grade.
· All
the information used for developing the multiple linear regression
which corresponds to the selection of independent variables is
considered in the current block model.
· The
copper recovery formula is provided in Table 3 and the molybdenum
recovery formula is included in Table 4.
|
|
Environmental factors or assumptions
|
· The
mining areas are within existing mining leases which have
appropriate environmental studies and approvals in
place.
· After
the Antofagasta Environmental Assessment Commission approved the
environmental impact study for "Updating of the tailings deposit
and associated facilities" project, SGSCM has been working to
address all the actions to comply with the requirements laid out by
the commission.
· SGSCM
has environmental permits that allow it to operate until 2035. It
is planned to update the environmental approval to extend the mine
life beyond 2035. The approval process is planned to start by 2030
to complete the required work in time for approval in
2035.
|
|
Infrastructure
|
· SGSCM
is a mature operation with all major infrastructure required for
ongoing operations at planned production levels in
place.
· The
following key infrastructure and supply agreements are in
place:
o Electric power supply: SGSCM has a contract in place to be
supplied with 100% renewable electric power until December 2039.
The contract covers both the current and projected capacity of
SGSCM.
o Seawater supply: SGSCM has a seawater supply contract with
ENGIE, which ensures a flow of 1,500 litres per second from the
Mejillones 1 and 2 thermal power plants until 2034. ENGIE is
currently managing the change of the seawater supply point in its
facilities with an objective to provide a longer-term supply
proposal.
|
|
Costs
|
· Capital costs are reviewed periodically for operation,
maintenance, and general & administrative (G&A). While the
capital expenditure for G&A is defined for a period of two
years, the operation and maintenance team provide input for the
life of operation. Five strategic pillars underpin project
design:
o green copper;
o business as usual;
o excellence and growth;
o unique culture; and
o compliance and risks.
· The
capital expenditure for TSFs is aligned to the Mine Metal
Plan.
· Deferred stripping is updated according to the Mine Metal
Plan.
· The
operational costs have been modelled using XERAS 2.5 software and
with consideration for correlation with productive indicators from
the main business units.
· The
operational areas provide their assumptions which correspond to the
main cost indicators such as maintenance plans and strategies,
consumption rates and external services.
· Mining
costs are calculated primarily from first principles using detailed
labour rate calculations, equipment operating costs and actual
expenditure for materials and consumables.
· Processing costs account for plant consumables and reagents,
labour, power and maintenance materials and TSF costs.
· G&A costs are based on current operating structures.
Permitting and environmental estimates are based on current
permitting timelines.
· Transportation charges have been estimated using information
on rail costs, export locations, transload capabilities and transit
time associated with moving concentrate from site to port to
market.
· Treatment and refining charges used for valuation are based on
a long-term view of the refining costs and commodity prices for
copper and molybdenum concentrate.
· Applicable royalties and property fees have been applied using
current royalty agreements.
|
|
Revenue factors
|
· The
LOM Plan provides the mining and processing physicals such as
volume, tonnes and grades to support valuation.
· Sales
strategy is the responsibility of the JV partners in conjunction
with operation, finance and logistics areas. The sales strategy is
designed to ensure expected results for the JV partners.
· Revenue is calculated by applying forecast metal prices and
foreign exchange rates to the scheduled payable metal. Metal
payabilities are based on contracted payability terms, typical for
copper and molybdenum concentrate markets. Payability terms will
not be detailed as the information is commercially
sensitive.
· The
long-term price protocol reflects view of demand, supply, volume
forecasts and competitor analysis.
· Every
commodity produced by SGSCM has its own revenue, even though gold
and silver are included in the copper concentrate. As copper
concentrate is not the final product, the treatment and refinery
costs (TC/RC) are incorporated into revenues estimation by
subtracting the value from the initial revenue.
|
|
Market assessment
|
· Currently, the main product from SGSCM is copper concentrate
with an average concentrate grade of 23.1% of fine copper for
calendar year 2023 (based on actual value) and a LOM average
content of 24.6%.
· Gold
and silver are by-product in the copper concentrate. Molybdenum
concentrate is roasted to convert to molybdenum oxide and
marketed.
· SGSCM
clients include smelters and traders, both local and foreign. Since
the copper concentrate forms part of a process prior to converting
the raw material, the conversion, treatment, and refinery costs are
included in the process of negotiation with each client. Depending
on the market being commercialised, the costs incurred, will be
values that will be assigned as reductions in revenue from copper
concentrate sales.
· Sales
strategies and customer diversification are generated by JV
partners and managed by KGHM marketing department.
|
|
Economic
|
· Economic inputs are described in the cost, revenue, and
metallurgical factors sections of this report.
· Net
present value (NPV) determination includes all relevant cost,
price, taxes and royalty inputs.
· Sensitivity analyses have been completed on metal prices,
metallurgical recoveries, mine operating costs, growth capital
costs and use of Inferred Mineral Resources to understand the value
drivers and impact on valuation. The valuation remains robust
under the tested conditions.
|
|
Social
|
· General Counsel, Sustainability and Corporate Affairs identify
critical issues for the operation including eventual environmental
and social risks and establishes action plans and maintain relation
with each interest group.
· The
community team maintain relations with the nearby community to
ensure operational continuity.
|
|
Other
|
· Meteorological variables and air quality are pivotal to the
Company's environmental management. To that end, all variables are
monitored on an ongoing basis and blasts are done according to a
blasting protocol that is regulated to ensure no more than 270
blasts are carried out each year.
· Ensuring a permanent dialogue with the community, including
open communication channels and feedback processes, is one of the
requirements for SGSCM to maintain its operational
licence.
· The
main monitoring and control activities pertaining to air quality,
including exhaustive maintenance of the SGSCM's air quality
monitoring network, are aimed at controlling the level of annual
PM10 emissions.
|
|
Classification
|
The following criteria were used
when reporting Ore Reserves:
· Value
attributed from only Measured and Indicated Resources.
· Ore
Reserve converted from Measured Mineral Resource is reported as
Proved Ore Reserve
· Ore
Reserve converted from Indicated Mineral Resource is reported as
Probable Ore Reserve.
· Sulphide and transition ore processed by flotation with a NSR
value greater than or equal to zero.
· Use of
long-term commodity price and cost assumptions.
· Cut-off calculated considering value contribution from
recovery of copper, molybdenum, and gold.
· Reserves must be within the mine phase designs developed from
the optimised pit shell.
|
|
Audits or reviews
|
· In
March 2023, an independent consulting firm was commissioned by
South32 to review the planning process leading into Ore Reserve
estimation. The planning process was found to be appropriate
for estimation of Ore Reserves. Minor gaps identified relate to
sensitivity assessment of technical and economic assumptions and
having a clear path to extend the environmental approval to extend
the life of operation beyond 2035. These gaps have been resolved or
actions put in place to the satisfaction of the auditor.
|
|
Discussion of relative accuracy/ confidence
|
· Ore
Reserve estimation techniques are robust and well understood. The
estimates are global with a local estimation plan achieved through
grade control drilling during execution.
· Sensitivity assessment was completed to validate the use of
appropriate modifying factors and their impact. This included
varying cost and price when deriving the NPV for the
operation.
· Regular reconciliation is performed, and actions are taken to
address material deviations.
· Sufficient studies, reviews, and audits have been conducted
both internally and externally to confirm the modifying factors
used.
· The
Competent Person has determined that the relative accuracy and
confidence in the Ore Reserve estimate is appropriate to declare a
reserve.
|
Figure 1: Sierra Gorda SCM location map with tenement
boundary
Figure 2: Regional geology map
Figure 3: Distribution of drill holes used in the resource
estimation
Figure 4: Distribution of drill holes and the chalcopyrite
mineralisation zone
Figure 5. Precision analysis of assay results for TCu (%) and
Mo (%)
Figure 6: Vertical Section comparing estimation with drilling
for TCu (%) at Northing (Y) = 4471210m
Figure 7: Swath Plots for Mo (%), TCu (%) and Au (g/t): in
three orthogonal directions
Figure 8: Mineral Resource classification with drilling at
Northing (Y) = 4471445m at NSR>US$0/t
Figure 9: Vertical section (Northing = 4471500m) with the
designed ultimate pit (red) and topography
(1 July 2024) (Blocks coloured on total copper
grade)
Figure 10: Geo-metallurgical domains considering lithology,
mineralisation and alteration.
Table 1: Geo-mechanical pit design
parameters
|
Material type
|
B (m)
|
hB (m)
|
αb
(°)
|
αIR(°)
|
|
Gravel
|
13.2
|
16
|
70°
|
40°
|
|
Oxide
|
9.1
|
16
|
70°
|
47°
|
|
Transition αIR=50°
|
10.6
|
16
|
80°
|
50°
|
|
Transition αIR=52°
|
9.7
|
16
|
80°
|
52°
|
|
Sulphide
|
8.8
|
16
|
80°
|
54°
|
B (m): berm; hB (m): bench height; αb (°):
bench phase angle; αIR(°): inter-ramp angle
Table 2: Pit design parameters
|
Parameters
|
Unit
|
Value
|
|
Bench height
|
(m)
|
16
|
|
Berm
|
(m)
|
>8.8 and <13.2
|
|
Bench face angle
|
(°)
|
>70 and <80
|
|
Minimum phase width
|
(m)
|
100
|
|
Ramp width
|
(m)
|
40
|
|
Ramp slope
|
(%)
|
10
|
|
Decouplings
|
(m)
|
25
|
|
Maximum inter-ramp height
|
(m)
|
192
|
|
Phase connection angle
|
(°)
|
< 35
|
Table 3: Global copper recovery models
|
UGM
|
Global Copper Recovery
Models
|
|
830
|
|
|
834
|
|
|
840
|
|
TCu%- grade of total copper; Fe%-
grade of total iron; Mo%- grade of total molybdenum; CuS%- grade of
soluble copper; BWI- Bond Work Index; P80= 174µm
Table 4: Global molybdenum recovery models
|
UGM
|
Models for Global Mo
Recovery
|
|
830
|
|
|
834
|
|
|
840
|
|
TCu%- grade of total copper; Fe%-
grade of total iron; Mo%- grade of total molybdenum; CuS%- grade of
soluble copper; BWI- Bond Work Index; P80= 174µm
