REG - Chaarat Gold Hlgs Ld - Kapan Mineral Resource Update
11/11/2022 08:15
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RNS Number : 0683G Chaarat Gold Holdings Ltd 11 November 2022
11 November 2022
Chaarat Gold Holdings Limited
("Chaarat" or "the Company")
Kapan Mineral Resource Update
Chaarat (AIM:CGH), the AIM-quoted gold mining Company with an operating mine
in Armenia, and assets at various stages of development in the Kyrgyz
Republic is pleased to announce the updated JORC Compliant Mineral Resource
Estimate ("MRE") for its Kapan polymetallic mine in the Republic of
Armenia. The full MRE report will be published on Chaarat`s website.
Highlights
· The 2022 constrained MRE contains 722 thousand gold equivalent ounces
("koz AuEq")(1) in the Measured & Indicated ("M&I") categories. This
compares to 584 koz AuEq M&I MRE reported in June 2021, reflecting a 25%
increase in MRE.
· M&I tonnes increased by 30% from 1.955 Mt to 2.602 Mt while
grade dropped by 5% from 9.1 g/t AuEq to 8.6 g/t AuEq.
· Mined Shape Optimization ("MSO") was performed on the mineral
inventory to apply constraining factors to the Mineral Resource.
The updated MRE will be used as the basis for the updated 2022 Ore Reserves
Estimate ("ORE"). As in prior years, Chaarat will employ the services of AMC
Consulting to review the 2022 MRE and develop a revised 2022 ORE.
(1) Gold equivalent ounces for the 2022 MRE is defined in Note 1 of Table 1.
Michael Fraser, Chief Executive Officer, commented:
"I am pleased to report the results of the 2022 Mineral Resource Estimate. The
new MRE shows a 25% increase in Measured and Indicated ounces compared to
2021. New drilling converted mineralization to M&I to replace depletion
during the period, and the improvements to the mining methods employed at
Kapan have enabled an increase to the resource."
UPDATED MRE STATEMENT
The following table summarizes the latest constrained 2022 MRE:
Class Mt AuEq (g/t) AuEq Metal (koz)
Measured 0.341 12.1 132
Indicated 2.261 8.1 590
M & I 2.602 8.6 722
Inferred 1.864 6.5 389
Table 1 Constrained Mineral Resources Estimate Sept 1,2022
Note 1:
· The effective date of the resource is 1st September 2022.
The Mineral Resources that are not Mineral Reserve do not demonstrate economic
viability. Numbers may not sum due to rounding.
· The gold equivalency (AuEq) formula is based on the
following metal prices: Au 1750 USD/oz; Ag 21.8 USD/oz; Cu 8300 USD/t; Zn 2950
USD/t
· The AuEq formula used is as follows: AuEq=
Au+Ag*21.8/1750+Cu*8300/1750*31.1035*100+Zn*2950/1750*31.1035*100
· Grade interpolation is done by Ordinary Kriging method.
· The applied MSO assumes a COG = 2.1g/t AuEq and minimum
mining widths of: 2.2m for the veins dipping < 70°; 1.8m for veins
dipping 70° - 80° and 1.2m for veins dipping 80°-90°
· Mineral Resources are with applied depletion and
inclusive of Ore Reserves.
· The resource estimate and classification are according
the JORC Code (2012) reporting code.
The previously reported June 2021 constrained MRE is shown below:
Class Mt AuEq (g/t) AuEq (koz)
Measured 0.238 12.3 94
Indicated 1.757 8.7 490
M & I 1.995 9.1 584
Inferred 3.497 6.9 775
Table 2 Constrained Mineral Resources Estimate June 1, 2021
Notes:
· The effective date of the resource is 1st June 2021. The
Mineral Resources that are not Mineral reserve do not demonstrate economic
viability. Numbers may not sum due to rounding.
· The gold equivalency formula is Au Eq = Au + (Ag g/t *
($25 / $1,700) + (Cu % * ($8,000 * 31.1035 / $1,700) / 100) + (Zn % * ($2,500
* 31.1035 / $1,700) / 100
· MSO applied assuming minimum width 2.2m; COG 2.0g/t Au
Eq
· Mineral Resources are with applied depletion and
inclusive of Ore Reserves.
· The resource estimate and classification are according
the JORC Code (2012) reporting code.
Mining depletion from June 1, 2021 to September 1, 2002, being the period
between the 2021 MRE and the 2022 MRE, was 0.232Mt containing 81 koz
AuEq. The results from the infill drilling program during 2021 and 2022
replaced depletion and added additional ounces to the MRE.
Modifying factors
Starting in 2021, Chaarat´s MRE is reported on a constrained basis by
applying modifying factors. Each vein in the resource model is run through MSO
software to determine the reasonable prospects for eventual economic
extraction on a vein-by-vein basis.
Table 3 below shows the main modifying factors applied to the model via the
use of the MSO software.
COG_AuEq_ppm 2.1 ppm
Metal prices See Notes 1
Ore body dip Minimum mining width (MSO)
80(o)-90(o) 1.2m
70(o)-80(o) 1.8m
< 70(o) 2.2m
Development overbreak 0%
Production Stope overbreak:
First mining sublevel 5%
Middle sublevel 10%
Bottom sublevel 15%
Table 3 MSO's COG, Minimal mining width and working over breaks percentage
Resource Estimation Assumptions and Methods
The MRE was constrained over the polymetallic veins of the deposit, using
wireframe solid models. The resource depletion zones were also encoded into
the resource model. Grade estimates are based on 1.0m composited assay data,
with applied top capping for all elements of interest. The interpolation of
the metal grades was undertaken via Datamine software using ordinary kriging
at parent blocks of 4x4x4m and minimal sub blocking of 0.1m. MSO software was
used to determine the reasonable prospects for eventual economic extraction.
The elements of interest interpolated in the resource model include gold,
silver, copper, zinc, lead and sulphur. Density estimation is based on a
sulphur regression formula. Full details can be found in the 2022 MRE report
which will be available on the Company's website.
Quality Assurance/Quality Control Procedures: Sampling Methodology and Quality
Control
Sampling comprises historical surface diamond and RC drilling, historical and
recent underground diamond drilling, and channel sampling. Core drill holes
were drilled along the full mineralization intersection, as normal to the
mineralization strike and dip as possible, predominantly at NQ diameter. The
maximum sampling interval was 1 metre, the minimum was 0.2 metres. In the
recent drilling campaigns entire core was collected as regular core samples.
Underground channel samples were chipped along the marked face with a
pneumatic hammer.
The samples were pre-processed and analysed at the on-site mine laboratory.
The laboratory conducts Fire Assay with atomic adsorption spectrometer ("AAS")
for gold (0.2 g/t-1000g/t), and atomic AAS for Ag (0.2 g/t -20000g/t), Cu
(0.005%-9.9%), Pb (0.005%-19.9%) and Zn (0.005%-29.9%). The laboratory is
accredited according to GOST ISO/IEC 17025-2019 standard. GOST refers to a set
of international technical standards maintained by the Euro-Asian Council for
Standardization, Metrology and Certification ("EASC"), a regional standards
organization operating under the auspices of the Commonwealth of Independent
States ("CIS"). Internal quality assurance and quality control ("QA/QC")
scheme includes certified reference materials ("CRM") and blank material.
Approximately 5% of the samples were sent to an accredited laboratory as a
part of mandatory Armenian state control. Kapan's on-site laboratory shows an
acceptable level of sample precision and accuracy for both diamond drilling
and channel sampling.
Geological Modelling Procedures
Ore wireframing is done via LeapFrog™ software, using all available drill
hole and channel data at 1.5 g/t AuEq as a base cut-off grade. The maximum
width of barren intervals, included in ore solid, is 2.0m and the minimal
interval width is 0.2m. Hard boundaries of the veins were used to outline the
ore bodies. In case of available barren contouring hole, the wireframe was
extrapolated on a half distance between the mineralized and barren holes, with
reducing the width accordingly.
In case the closest barren intercept has reasonable zone of increased grades,
these intercepts are used in the extrapolation process. In case of lack of
contouring barren drill hole, the ore wireframe is extrapolated in a half
distance between the last two holes, but not further than the half of the
average exploration drilling grid (grade control drilling is within average
grid of 20x20m).
This announcement contains inside information for the purposes of Article 7 of
Regulation (EU) 596/2014 (which forms part of domestic UK law pursuant to the
European Union (Withdrawal) Act 2018).
Enquiries
Chaarat Gold Holdings Limited +44 (0)20 7499 2612
Mike Fraser, Chief Executive Officer IR@chaarat.com (mailto:IR@chaarat.com)
Canaccord Genuity Limited (NOMAD and Joint Broker) +44 (0)20 7523 8000
Henry Fitzgerald-O'Connor
James Asensio
finnCap Limited (Joint Broker) +44 (0)20 7220 0500
Christopher Raggett
Panmure Gordon (UK) Limited (Joint Broker) +44 (0)20 7886 2500
John Prior
Hugh Rich
About Chaarat
Chaarat is a gold mining company which owns the Kapan operating mine in
Armenia as well as Tulkubash and Kyzyltash Gold Projects in the Kyrgyz
Republic. The Company has a clear strategy to build a leading emerging markets
gold company through organic growth and selective M&A.
Chaarat aims to create value for its shareholders, employees and communities
from its high-quality gold and mineral deposits by building relationships
based on trust and operating to the best environmental, social and employment
standards. Further information is available at www.chaarat.com/
(http://www.chaarat.com/) .
Competent Person- Mineral Resource Estimate
The information in this announcement that relates to exploration results is
based on and fairly represents information and supporting documentation
prepared by Dimitar Dimitrov, P. Geo, AIG member and a Competent Person as
defined in the 2012 edition of the JORC Code 'Australasian Code for Reporting
of Exploration Results, Mineral Resources and Ore Reserves' and is a Qualified
Person under the AIM Rules. Mr. Dimitar Dimitrov is a full-time employee of
the company. Mr. Dimitrov consents to the publication of this new release
dated November 11(th), 2022 by Chaarat. Mr. Dimitrov certified that this news
release fairly and accurately represents the information for which he is
responsible.
Glossary of Technical Terms
"Ag"
chemical
symbol for silver
"Au" chemical symbol for gold
"AuEq" the value of a tonne of mineralised material calculated by summing the value
of each contained payable metal and expressing it as an equivalent gold
content at a given set of metals prices
the chemical symbol for copper
"Cu"
"cut-off" the lowest grade value that is included in a Resource statement. It must
comply with JORC requirement 19: "reasonable prospects for eventual economic
extraction" the lowest grade, or quality, of mineralised material that
qualifies as economically mineable and available in a given deposit. It may be
defined on the basis of economic evaluation, or on physical or chemical
attributes that define an acceptable product specification
"g/t" grammes per tonne, equivalent to parts per million
"Inferred Resource" that part of a Mineral Resource for which tonnage, grade and mineral content
can be estimated with a low level of confidence. It is inferred from
geological evidence and assumed but not verified geological and/or grade
continuity. It is based on information gathered through appropriate techniques
from locations such as outcrops, trenches, pits, workings and drill holes
which may be limited or of uncertain quality and reliability
"Indicated Resource" that part of a Mineral Resource for which tonnage, densities, shape, physical
characteristics, grade and mineral content can be estimated with a reasonable
level of confidence. It is based on exploration, sampling and testing
information gathered through appropriate techniques from locations such as
outcrops, trenches, pits, workings and drill holes. The locations are too
widely or inappropriately spaced to confirm geological and/or grade continuity
but are spaced closely enough for continuity to be assumed
"JORC" The Australasian Joint Ore Reserves Committee Code for Reporting of
Exploration Results, Mineral Resources and Ore Reserves 2012 (the "JORC Code"
or "the Code"). The Code sets out minimum standards, recommendations and
guidelines for Public Reporting in Australasia of Exploration Results, Mineral
Resources and Ore Reserves
"koz" thousand troy ounces of gold
"Measured Resource" that part of a Mineral Resource for which tonnage, densities, shape, physical
characteristics, grade and mineral content can be estimated with a high level
of confidence. It is based on detailed and reliable exploration, sampling and
testing information gathered through appropriate techniques from locations
such as outcrops, trenches, pits, workings and drill holes. The locations are
spaced closely enough to confirm geological and grade continuity
"Mineral Resource" a concentration or occurrence of material of intrinsic economic interest in or
on the Earth's crust in such form, quality and quantity that there are
reasonable prospects for eventual economic extraction. The location, quantity,
grade, geological characteristics and continuity of a Mineral Resource are
known, estimated or interpreted from specific geological evidence and
knowledge. Mineral Resources are sub-divided, in order of increasing
geological confidence, into Inferred, Indicated and Measured categories when
reporting under JORC
"Mt" million tonnes
"oz" troy ounce (= 31.103477 grammes)
"Pb" the chemical symbol for lead
"t" tonne (= 1 million grammes)
"Zn" the chemical symbol for zinc
12.0 JORC Code, 2012 Edition - Table 1 report
Section 1 Sampling Techniques and Data
Criteria JORC Code explanation Commentary
Sampling techniques Nature and quality of sampling (e.g., cut channels, random chips, or specific Sampling comprises historical surface drilling, historical and current
specialized industry standard measurement tools appropriate to the minerals underground drilling, and channel sampling.
under investigation, such as down hole gamma sondes, or handheld XRF
instruments, etc.). These examples should not be taken as limiting the broad Predominantly diamond drilling, and channel cut from the face, with a chisel
meaning of sampling. saw, according to a marked channel boundary.
Include reference to measures taken to ensure sample representativity and the Core was drilled along the full mineralization intersection, as normal to the
appropriate calibration of any measurement tools or systems used. mineralization strike as possible.
Aspects of the determination of mineralization that are Material to the Public Channel rock chips are providing representative data collection of the sampled
Report. face.
In cases where 'industry standard' work has been done this would be relatively All sampling practices are meeting the industry standards.
simple (e.g., 'reverse circulation drilling was used to obtain 1 m samples
from which 3 kg was pulverized to produce a 30 g charge for fire assay'). In
other cases, more explanation may be required, such as where there is coarse
gold that has inherent sampling problems. Unusual commodities or
mineralization types (eg submarine nodules) may warrant disclosure of detailed
information.
Drilling techniques Drill type (e.g., core, reverse circulation, open-hole hammer, rotary air DH sampling: approximately 717 000 samples (1024km).
blast, auger, Bangka, sonic, etc.) and details (e.g., core diameter, triple or
standard tube, depth of diamond tails, face-sampling bit, or other type, Channel sampling: approx. 122 000 samples (123.1 km).
whether core is oriented and if so, by what method, etc.)
Total sampling: approx. 840 000 samples (1147km).
Core is predominantly HQ and NQ diameter, singe barrel drilled.
Channel samples are chipped along the marked face with a pneumatic hammer and
collected by the sampler in one-meter intervals. All channel samples are taken
from south to north, in a horizontal fashion, rather than perpendicular to the
mineralized dip angle. The results from the channel sampling are used for
grade control, modelling, mine design, resource estimation, and for mine
reconciliation data.
The samples are contoured along all major lithological breaks.
Drill sample recovery Method of recording and assessing core and chip sample recoveries and results The core recovery is assessed by regular measurements of each drill run and
assessed. generally excess 95 %. Core recovery is based on recovered core length vs
drill run length, and RC material is assessed by the recovered weights.
Measures taken to maximize sample recovery and ensure representative nature of
the samples. There does not appear to be a relationship bias between grade and length, or
sample weight or recovery.
Whether a relationship exists between sample recovery and grade and whether
sample bias may have occurred due to preferential loss/gain of fine/coarse The average grade of the channel samples is higher compared to the drilling.
material. This is primarily attributed to the frequency of channel samples in high grade
open areas of the mine, compared to drilling
Logging Whether core and chip samples have been geologically and geotechnically logged Once the hole is finished, the core is transported to the core storage area
to a level of detail to support appropriate Mineral Resource estimation, for logging. The core trays are plastic, and are covered with a plastic cover
mining studies and metallurgical studies. as well, to prevent core losses or extra moving.
Whether logging is qualitative or quantitative in nature. Core (or costean, The key procedures are including core recovery measuring; sample interval
channel, etc) photography. marking; geological and geotechnical logging; photo documentation; sampling
and later destruction of non-mineralized part.
The total length and percentage of the relevant intersections logged.
Core logging is including lithology; alteration; mineralization; structures;
obtaining geotechnical data for assess RMR and Q-index.
Sampling is primarily based on the visible mineralization, and minimum 2
meters are taken from either side of the sampled interval.
The maximum sampling interval is 1 meter, the minimum is 0.2m
Once the sampling intervals are outlined, currently a full core diameter is
used for assaying. Areas with non-visible mineralization, outside of the
expected mineralization zone are not sampled.
In absence of visible mineralization, but in areas where mineralization
interception is expected the material is sampled depending on the field
geologist's decision, considering all the available information.
The collection of geological data is meeting the industrial standards.
The core logging protocol keeps a high standard, and the involved geologists
have sufficient knowledge for Shahumyan mineralization system.
Sub-sampling techniques and sample preparation If core, whether cut or sawn and whether quarter, half or all core taken. Prior to July 2017 core was halved with a diamond saw and half was sent for
analysis and the other half was retained. Since then, the whole core is
If non-core, whether riffled, tube sampled, rotary split, etc and whether processed and only the pulps are retained for future analysis.
sampled wet or dry.
The laboratory prepares samples according to industry standard of drying
For all sample types, the nature, quality, and appropriateness of the sample crushing, pulverizing, splitting and analysis.
preparation technique.
All samples are analysed in the local Kapan's mine laboratory
Quality control procedures adopted for all sub-sampling stages to maximise
representativity of samples. The laboratory is providing Fire Assay with AAS for gold (0.2 g/t-1000g/t),
and AAS for Ag (0.2 g/t -20000g/t), Cu (0.005%-9.9%), Pb (0.005%-19.9%) and Zn
Measures taken to ensure that the sampling is representative of the in situ (0.005%-29.9%).
material collected, including for instance results for field
duplicate/second-half sampling.
Whether sample sizes are appropriate to the grain size of the material being
sampled.
Quality of assay data and laboratory tests The nature, quality and appropriateness of the assaying and laboratory The assaying is meeting the industry standards and it is suitable to support
procedures used and whether the technique is considered partial or total. Mineral Resource estimate.
For geophysical tools, spectrometers, handheld XRF instruments, etc, the The current QA/QC scheme is including blank samples and certified reference
parameters used in determining the analysis including instrument make and material (CRM). As core is no longer halved, no field duplicates are assessed,
model, reading times, calibrations factors applied and their derivation, etc. and historically these results were no good due to highly variable nature of
mineralization.
Nature of quality control procedures adopted (eg standards, blanks,
duplicates, external laboratory checks) and whether acceptable levels of QA/QC achieves acceptable levels of accuracy and precision.
accuracy (ie lack of bias) and precision have been established.
Verification of sampling and assaying The verification of significant intersections by either independent or Yearly, in each quarter, between 3 and 5 percent of the pulps are sent to
alternative company personnel. Yerevan state laboratory for reference the results.
The use of twinned holes. A twin analysis has been conducted during 2017-2018 by local geology team for
channel and diamond drilling (DD) holes and shows potential bias that could be
Documentation of primary data, data entry procedures, data verification, data attributed to highly variable nature of mineralization
storage (physical and electronic) protocols.
Discuss any adjustment to assay data.
Location of data points Accuracy and quality of surveys used to locate drill holes (collar and Grid system is Pulkovo 1942 /Gauss -Kruger zone 8, ( with reduced first 2
down-hole surveys), trenches, mine workings and other locations used in digits in the BM and wireframes encoding).
Mineral Resource estimation.
Survey is completed underground, with high precision tools which meets the
Specification of the grid system used. industrial standards: Leica TS16 (3'' accuracy), Ranger Explorer II R2231,
IMMN_32A.
Quality and adequacy of topographic control.
The available digital elevation model of the area topography is used in the
Mineral Resource estimation process (surveyed via GPS by expatriate and local
surveyors in 2013)
Data spacing and distribution Data spacing for reporting of Exploration Results. Along the drive advancing, a channel sampling is taken every blast.
Whether the data spacing, and distribution is sufficient to establish the Typically, the space between two blasts is 4 -6m
degree of geological and grade continuity appropriate for the Mineral Resource
and Ore Reserve estimation procedure(s) and classifications applied. The grade control drilling net is 20 X 20 m, adjusted to denser grid, where
required
Whether sample compositing has been applied.
The geostatistical analysis and trial blast unit drilling data have shown that
thicker data spacing, and distribution do not add any sufficient value in
accuracy of geological and grade continuity.
As majority of samples have 1m in length, the 1m composite is being applied.
Orientation of data in relation to geological structure Whether the orientation of sampling achieves unbiased sampling of possible Geometry is derived and interpreted from underground mapping and sampling.
structures and the extent to which this is known, considering the deposit True thickness is calculated from apparent thickness, during the
type. interpretation.
If the relationship between the drilling orientation and the orientation of No bias has been introduced through the geometry of the sampling and
key mineralised structures is considered to have introduced a sampling bias, subsequent geological interpretation
this should be assessed and reported if material.
Sample security The measures taken to ensure sample security. The mine process plant and laboratory are sufficiently secured, with security
guards and entry, requiring personal ID cards
Audits or reviews The results of any audits or reviews of sampling techniques and data. Independent reviews have considered the sampling process to meet industry best
practices: NI 43-101 Technical Report in 2014 (Galen White - QP, Julian
Bennett- QP, Simon Meik - QP) and Global Report (Galen White - QP) in 2018 by
CSA, report by AMC (Alan Turner, Bryan Pullman) in 2019. At 2021 AMC
consulting completed a high-level review of MRE 21.
Section 3 Estimation and Reporting of Mineral Resources
(Criteria listed in section 1, and where relevant in section 2, also apply to
this section.)
Criteria JORC Code explanation Commentary
Database integrity Measures taken to ensure that data has not been corrupted by, for example, Data is logged and digitized by trained geologists.
transcription or keying errors, between its initial collection and its use for
Mineral Resource estimation purposes. The used software is providing several stages of cross validation, initial
through the logging process, second when the logging data is imported to main
Data validation procedures used. database platform (acQuire) and one more time prior the Mineral Resource
estimation.
Site visits Comment on any site visits undertaken by the Competent Person and the outcome The last site visit of competent person (Dimitar Dimitrov) for the Mineral
of those visits. Resource was from 17th to 28th of May 2022
If no site visits have been undertaken indicate why this is the case. Mr.Dimitar Dimitrov P. Geo, AIG member and a Competent Person as defined in
the 2012 edition of the JORC Code 'Australasian Code for Reporting of
Exploration Results, Mineral Resources and Ore Reserves', is a SVP
-Exploration of Chaarat Gold Holdings, and full-time employee of the company.
Geological interpretation Confidence in (or conversely, the uncertainty of) the geological Based on lithological evidence (drill core logging and underground mapping
interpretation of the mineral deposit. data) the veins and veinlets are being interpreted.
Nature of the data used and of any assumptions made. The Mineral Resource is controlled by hard boundaries of the interpreted
geological structures, including faults and post mineralization barren dykes.
The effect, if any, of alternative interpretations on Mineral Resource
estimation. The geological continuity is reasonable, but grade variability is high, often
within the mineralized structure.
The use of geology in guiding and controlling Mineral Resource estimation.
The factors affecting continuity both of grade and geology.
Dimensions The extent and variability of the Mineral Resource expressed as length (along The Resource includes a series of E-W striking orebodies (veins), dipping from
strike or otherwise), plan width, and depth below surface to the upper and 45(o) to 90(o) (mainly in South direction). Vein strike lengths reach up to
lower limits of the Mineral Resource. 0.5km, and the true thickness ranges from several cm to 2m.
The Resources goes near the surface (~950masl) to average of 500 - 600 m asl
deep.
Further mineralization potential exists below 600msal, and to the flanks of
current Resource, explored historically.
Estimation and modelling techniques The nature and appropriateness of the estimation technique(s) applied and key The Mineral Resource estimation was completed in Datamine Studio by Kapan's
assumptions, including treatment of extreme grade values, domaining, geological department
interpolation parameters and maximum distance of extrapolation from data
points. If a computer assisted estimation method was chosen include a The wireframes were prepared in Leapfrog Geo
description of computer software and parameters used.
The grades were interpolated by Ordinary Kriging
The availability of check estimates, previous estimates and/or mine production
records and whether the Mineral Resource estimate takes appropriate account of Top-cuts were applied for each vein (based on statistical analysis).
such data.
The search radii were defined by variogram modelling of veins
The assumptions made regarding recovery of by-products.
The estimate was constrained into the hard boundary of the mineralization
Estimation of deleterious elements or other non-grade variables of economic interpretation
significance (eg sulphur for acid mine drainage characterisation).
Parent cell dimensions are 4m*4m*4m, with minimum sub-celling dimensions
In the case of block model interpolation, the block size in relation to the 0.1m*0.1m*0.1m
average sample spacing and the search employed.
The composite length is 1m
Any assumptions behind modelling of selective mining units.
The validation methods currently show high level of correspondence between
Any assumptions about correlation between variables. resource model and the actual data, and are done via visual inspection,
preparation of Q-Q and swath plots.
Description of how the geological interpretation was used to control the
resource estimates. Comparison with previous Mineral Resource estimates
Discussion of basis for using or not using grade cutting or capping. Reconciliation that includes comparing forecasted data and measurements in
different phases of mining process
The process of validation, the checking process used, the comparison of model
data to drill hole data, and use of reconciliation data if available.
Mineral Inventory (depleted) up to 09-2022:
Class Mt SG (g/cm(3) ) AuEq (g/t) AuEq (koz)
Meas 0.646 2.75 8.9 185
Ind 5.627 2.76 5.3 958
M& I 6.273 2.76 5.7 1 143
Inf 6.790 2.78 4.5 975
Total 13.063 2.77 5.0 2 118
AuEq=AU+AG*21.8/1750+CU*8300*31.1035/175000+ZN*2950*31.1035/17500
Moisture Whether the tonnages are estimated on a dry basis or with natural moisture, Tonnage is reported on dry basis
and the method of determination of the moisture content.
Cut-off parameters The basis of the adopted cut-off grade(s) or quality parameters applied.
The Reasonable Prospects for Eventual Economic Extraction of the Mineral
Inventory was conducted via Mine Shape Optimization (MSO) run. Cut-off grade
of 2.1 g/t AuEq was applied.
Mining factors or assumptions Assumptions made regarding possible mining methods, minimum mining dimensions The Resource model is based on geology.
and internal (or, if applicable, external) mining dilution. It is always
necessary as part of the process of determining reasonable prospects for The reasonable prospects for eventual economic extraction were achieved by
eventual economic extraction to consider potential mining methods, but the running Mineable Stope Optimization (MSO) and reported is Resource is
assumptions made regarding mining methods and parameters when estimating constrained by the MSO. The MSO parameters are in accordance with the
Mineral Resources may not always be rigorous. Where this is the case, this selective mining method planned to be implemented.
should be reported with an explanation of the basis of the mining assumptions
made.
COG_AuEq_ppm 2.1 ppm
Used AuEq_formula AUEQV=AU+AG/80+CU/0.6779+ZN/1.9072
Ore body dip MMU (MSO)
80(o)-90(o) 1.2m
70(o)-80(o) 1.8m
< 70(o) 2.2m
Development overbreak 0%
Production Stope overbreak:
First mining sublevel 5%
Middle sublevel 10%
Bottom sublevel 15%
Kapan's 2022 Mineral Resource is:
Class Mt SG (g/cm3 ) AuEq (g/t) AuEq (koz)
Meas 0.341 2.76 12.1 132
Ind 2.261 2.77 8.1 590
M& I 2.602 2.77 8.6 722
Inf 1.864 2.77 6.5 389
AuEq=AU+AG*21.8/1750+CU*8300*31.1035/175000+ZN*2950*31.1035/17500
Metallurgical factors or assumptions The basis for assumptions or predictions regarding metallurgical amenability. The metal recovery data is as follows:
It is always necessary as part of the process of determining reasonable
Process recovery Units 2017 2018 2019 2020 2021
prospects for eventual economic extraction to consider potential metallurgical Au recovery (all con) % 83.6 76.2 79.7 73.1 75.5
methods, but the assumptions regarding metallurgical treatment processes and Ag recovery (all con) % 83 80.9 82.4 82.2 82.5
parameters made when reporting Mineral Resources may not always be rigorous. Cu recovery (Cu con) % 86.4 83.6 86.4 87 85.2
Where this is the case, this should be reported with an explanation of the Zn recovery (Zn con) % 81.9 77.4 80.2 76.4 71.1
basis of the metallurgical assumptions made.
Extraction of Au at refining % 91
Extraction of Ag at refining % 84
Extraction of Cu at refining % 94
Extraction of Zn at refining % 85
Metal recovery is not directly applied in the reported Resource.
Environmental factors or assumptions Assumptions made regarding possible waste and process residue disposal There are no known factors which may inhibit the extraction of the Resource
options. It is always necessary as part of the process of determining
reasonable prospects for eventual economic extraction to consider the
potential environmental impacts of the mining and processing operation. While
at this stage the determination of potential environmental impacts,
particularly for a greenfields project, may not always be well advanced, the
status of early consideration of these potential environmental impacts should
be reported. Where these aspects have not been considered this should be
reported with an explanation of the environmental assumptions made.
Bulk density Whether assumed or determined. If assumed, the basis for the assumptions. If Currently the density estimation is using polynomial regression model based on
determined, the method used, whether wet or dry, the frequency of the modelled sulphur grade:
measurements, the nature, size and representativeness of the samples.
If S >= 19.8 %, Density == exp [0.2587x + 0.4835], for x = ln (S grades)
The bulk density for bulk material must have been measured by methods that
adequately account for void spaces (vugs, porosity, etc), moisture and If S > 1 and S <19.8%, Density == exp [0.0114169x6 - 0.0891652x5 +
differences between rock and alteration zones within the deposit. 0.26951043x4 + 0.38060004x3 + 0.23832052x2 + 0.0052027x + 0.9070334], for x =
ln (S grades)
Discuss assumptions for bulk density estimates used in the evaluation process
of the different materials. If S<1, Density = 2.65 g/cm3
In dykes Density = 2.65 g/cm3
This approach is considered as slightly conservative scenario for density
assessment.
Classification The basis for the classification of the Mineral Resources into varying The model is classified according to the quantity and quality of the data.
confidence categories.
The Measured Mineral Resource category was assigned to portions of the ore
Whether appropriate account has been taken of all relevant factors (ie bodies in the following cases:
relative confidence in tonnage/grade estimations, reliability of input data,
confidence in continuity of geology and metal values, quality, quantity and In the areas of current mine development workings, informed by both channel
distribution of the data). sampling data and drilling data and where the data spacing is less than 20x20
m.
Whether the result appropriately reflects the Competent Person's view of the
deposit.
The Indicated category was assigned to the portions of the ore bodies in the
following cases:
- In the areas with the exploration grid spacing up to
20×20 m, provided there was enough confidence in the continuity of the ore
body mineralization between the drill holes.
- In the areas of extrapolation to up to 30 m distance
from the last sublevel drift in down-dip/up-dip direction of the ore body,
provided there was enough confidence in the continuity of its mineralization.
The intersections of extrapolation areas by exploration drill holes are not
required in this case.
- In the areas of extrapolation to up to 30 m distance
from the last sublevel drift in the downdip /up-dip direction of the ore body.
In case of any doubts in continuity of this ore body mineralization, the
exploration grid spacing of not more than 20-30 m is required to classify the
mineralization as an Indicated Mineral Resource.
The Inferred category was assigned to the portions of the ore bodies if they
could not be classified as an Indicated Mineral Resource.
Audits or reviews The results of any audits or reviews of Mineral Resource estimates. No external audits or reviews were conducted for MRE 2022
Discussion of relative accuracy/ confidence Where appropriate a statement of the relative accuracy and confidence level in The effective date of the Resource is 01.09.2022
the Mineral Resource estimate using an approach or procedure deemed
appropriate by the Competent Person. For example, the application of Model estimates were checked by QQ plots, swath plots, and by comparing the
statistical or geostatistical procedures to quantify the relative accuracy of volumes of the wireframes and the block model, statistically and visually.
the resource within stated confidence limits, or, if such an approach is not
deemed appropriate, a qualitative discussion of the factors that could affect
the relative accuracy and confidence of the estimate.
The statement should specify whether it relates to global or local estimates,
and, if local, state the relevant tonnages, which should be relevant to
technical and economic evaluation. Documentation should include assumptions
made and the procedures used.
These statements of relative accuracy and confidence of the estimate should be
compared with production data, where available.
AuEq=AU+AG*21.8/1750+CU*8300*31.1035/175000+ZN*2950*31.1035/17500
Moisture
Whether the tonnages are estimated on a dry basis or with natural moisture,
and the method of determination of the moisture content.
Tonnage is reported on dry basis
Cut-off parameters
The basis of the adopted cut-off grade(s) or quality parameters applied.
The Reasonable Prospects for Eventual Economic Extraction of the Mineral
Inventory was conducted via Mine Shape Optimization (MSO) run. Cut-off grade
of 2.1 g/t AuEq was applied.
Mining factors or assumptions
Assumptions made regarding possible mining methods, minimum mining dimensions
and internal (or, if applicable, external) mining dilution. It is always
necessary as part of the process of determining reasonable prospects for
eventual economic extraction to consider potential mining methods, but the
assumptions made regarding mining methods and parameters when estimating
Mineral Resources may not always be rigorous. Where this is the case, this
should be reported with an explanation of the basis of the mining assumptions
made.
The Resource model is based on geology.
The reasonable prospects for eventual economic extraction were achieved by
running Mineable Stope Optimization (MSO) and reported is Resource is
constrained by the MSO. The MSO parameters are in accordance with the
selective mining method planned to be implemented.
COG_AuEq_ppm 2.1 ppm
Used AuEq_formula AUEQV=AU+AG/80+CU/0.6779+ZN/1.9072
Ore body dip MMU (MSO)
80(o)-90(o) 1.2m
70(o)-80(o) 1.8m
< 70(o) 2.2m
Development overbreak 0%
Production Stope overbreak:
First mining sublevel 5%
Middle sublevel 10%
Bottom sublevel 15%
Kapan's 2022 Mineral Resource is:
Class Mt SG (g/cm3 ) AuEq (g/t) AuEq (koz)
Meas 0.341 2.76 12.1 132
Ind 2.261 2.77 8.1 590
M & I 2.602 2.77 8.6 722
Inf 1.864 2.77 6.5 389
AuEq=AU+AG*21.8/1750+CU*8300*31.1035/175000+ZN*2950*31.1035/17500
Metallurgical factors or assumptions
The basis for assumptions or predictions regarding metallurgical amenability.
It is always necessary as part of the process of determining reasonable
prospects for eventual economic extraction to consider potential metallurgical
methods, but the assumptions regarding metallurgical treatment processes and
parameters made when reporting Mineral Resources may not always be rigorous.
Where this is the case, this should be reported with an explanation of the
basis of the metallurgical assumptions made.
The metal recovery data is as follows:
Process recovery Units 2017 2018 2019 2020 2021
Au recovery (all con) % 83.6 76.2 79.7 73.1 75.5
Ag recovery (all con) % 83 80.9 82.4 82.2 82.5
Cu recovery (Cu con) % 86.4 83.6 86.4 87 85.2
Zn recovery (Zn con) % 81.9 77.4 80.2 76.4 71.1
Extraction of Au at refining % 91
Extraction of Ag at refining % 84
Extraction of Cu at refining % 94
Extraction of Zn at refining % 85
Metal recovery is not directly applied in the reported Resource.
Environmental factors or assumptions
Assumptions made regarding possible waste and process residue disposal
options. It is always necessary as part of the process of determining
reasonable prospects for eventual economic extraction to consider the
potential environmental impacts of the mining and processing operation. While
at this stage the determination of potential environmental impacts,
particularly for a greenfields project, may not always be well advanced, the
status of early consideration of these potential environmental impacts should
be reported. Where these aspects have not been considered this should be
reported with an explanation of the environmental assumptions made.
There are no known factors which may inhibit the extraction of the Resource
Bulk density
Whether assumed or determined. If assumed, the basis for the assumptions. If
determined, the method used, whether wet or dry, the frequency of the
measurements, the nature, size and representativeness of the samples.
The bulk density for bulk material must have been measured by methods that
adequately account for void spaces (vugs, porosity, etc), moisture and
differences between rock and alteration zones within the deposit.
Discuss assumptions for bulk density estimates used in the evaluation process
of the different materials.
Currently the density estimation is using polynomial regression model based on
modelled sulphur grade:
If S >= 19.8 %, Density == exp [0.2587x + 0.4835], for x = ln (S grades)
If S > 1 and S <19.8%, Density == exp [0.0114169x6 - 0.0891652x5 +
0.26951043x4 + 0.38060004x3 + 0.23832052x2 + 0.0052027x + 0.9070334], for x =
ln (S grades)
If S<1, Density = 2.65 g/cm3
In dykes Density = 2.65 g/cm3
This approach is considered as slightly conservative scenario for density
assessment.
Classification
The basis for the classification of the Mineral Resources into varying
confidence categories.
Whether appropriate account has been taken of all relevant factors (ie
relative confidence in tonnage/grade estimations, reliability of input data,
confidence in continuity of geology and metal values, quality, quantity and
distribution of the data).
Whether the result appropriately reflects the Competent Person's view of the
deposit.
The model is classified according to the quantity and quality of the data.
The Measured Mineral Resource category was assigned to portions of the ore
bodies in the following cases:
In the areas of current mine development workings, informed by both channel
sampling data and drilling data and where the data spacing is less than 20x20
m.
The Indicated category was assigned to the portions of the ore bodies in the
following cases:
- In the areas with the exploration grid spacing up to
20×20 m, provided there was enough confidence in the continuity of the ore
body mineralization between the drill holes.
- In the areas of extrapolation to up to 30 m distance
from the last sublevel drift in down-dip/up-dip direction of the ore body,
provided there was enough confidence in the continuity of its mineralization.
The intersections of extrapolation areas by exploration drill holes are not
required in this case.
- In the areas of extrapolation to up to 30 m distance
from the last sublevel drift in the downdip /up-dip direction of the ore body.
In case of any doubts in continuity of this ore body mineralization, the
exploration grid spacing of not more than 20-30 m is required to classify the
mineralization as an Indicated Mineral Resource.
The Inferred category was assigned to the portions of the ore bodies if they
could not be classified as an Indicated Mineral Resource.
Audits or reviews
The results of any audits or reviews of Mineral Resource estimates.
No external audits or reviews were conducted for MRE 2022
Discussion of relative accuracy/ confidence
Where appropriate a statement of the relative accuracy and confidence level in
the Mineral Resource estimate using an approach or procedure deemed
appropriate by the Competent Person. For example, the application of
statistical or geostatistical procedures to quantify the relative accuracy of
the resource within stated confidence limits, or, if such an approach is not
deemed appropriate, a qualitative discussion of the factors that could affect
the relative accuracy and confidence of the estimate.
The statement should specify whether it relates to global or local estimates,
and, if local, state the relevant tonnages, which should be relevant to
technical and economic evaluation. Documentation should include assumptions
made and the procedures used.
These statements of relative accuracy and confidence of the estimate should be
compared with production data, where available.
The effective date of the Resource is 01.09.2022
Model estimates were checked by QQ plots, swath plots, and by comparing the
volumes of the wireframes and the block model, statistically and visually.
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