NATIONAL UNIVERSITY OF ENGINEERING
FACULTY OF MINING, METALLURGICAL AND GEOLOGICAL
ENGINEERING
ECONOMIC EVALUATION OF THE KORAIDA PROJECT
PRESENTED BY:
Avalos Saravia, Edson Lenon
Calle Canchari, Williams Sairy
Escalante Yucra, Alexander Steven
Mallqui Belito, Percy Jersson
Palomino Gonzales, Luisa Lorena
Valenzuela Espinoza, Yackelyn
Vasquez, Salazar Andres
Lima – Perú
2021
1
Index
1.
ABSTRACT
14
2.
INTRODUCTION
15
3.
DESCRIPTION AND LOCATION OF THE PROPERTY
16
4.
ACCESSIBILITY, CLIMATE, LOCAL RESOURCES, INFRASTRUCTURE AND
PHYSIOGRAPHY.
5.
WEATHER
18
6.
HISTORY
19
7.
GEOLOGICAL FRAMEWORK AND MINERALIZATION
19
8.
TYPE OF DEPOSIT
20
9.
EXPLORATION
21
10.
DRILLING
22
11.
SAFETY,PREPARATION AND ANALYSIS OF SAMPLES
22
12.
MINERAL PROCESSING AND METALLURGICAL TEST
24
13.
TRANSPORTATION AND COMMERCIALIZATION OF CONCENTRATED
24
14.
ESTIMATION OF MINERAL RESOURCES
25
14.1.
Database
25
14.2.
Geological interpretation and modeling.
26
14.3.
Exploratory Data Analysis (EDA)
27
14.3.1. Descriptive statistics
2
17
28
14.3.1.1. Descriptive statistics of the data for lithology 1.
28
14.3.1.2. Descriptive statistics of the data for lithology 2.
29
14.3.1.3. Descriptive statistics of the data for lithology 3.
30
14.3.1.4. Descriptive statistics of the data for lithology 4.
31
14.3.1.5. Descriptive statistics of the data for lithology 5.
32
14.3.2. Correlation between metals
14.3.2.1. Lithology 1-Post
33
14.3.2.2. Lithology 2-Oxides
34
14.3.2.3.
Lithology 3-Mixed Sulfides
34
14.3.2.4. Lithology 4-Primary sulfides
34
14.3.2.5.
35
14.4.
Lithology 5-Sedimentary
Top cut analysis
35
14.4.1. Capping of Ag grades (gr/t)
35
14.4.2. Capping of Pb grade (%)
36
14.4.3. Capping of Zn grades (%)
36
14.5.
Compositing
37
14.6.
Variography
41
14.7.
Block Model
45
14.8.
Estimating plan
46
15.
3
33
ESTIMATION OF MINING RESERVES
47
15.1.
Pit optimization
47
15.2.
Pit by Pit
49
15.3.
Cut off
52
16.
Mine Design
16.1.
Mineral Reserves
62
16.2.
Mining Method
62
16.2.1. Production rate and sizing
62
16.2.2. Pre-stripping
62
16.2.3. Mining production and processing program
63
16.2.4. Waste management.
64
16.3.
Work system
16.3.1. Work regime at the Koraida mine
16.4.
66
66
Unitary Blasting Operation
67
16.4.1. Perforation mesh design
67
16.4.2. Diameter calculation
67
16.4.2.1. Calculation of the Burden
69
16.4.2.2. Calculation of Spacing
70
16.4.2.3. Calculation of sub Drilling
70
16.4.2.4. Perforation mesh simulation
70
16.1.
4
55
Calculation of equipment numbers
74
17.
16.1.1. Drilling Calculation
74
16.1.2. Calculation of hydraulic shovels
75
16.1.3. Truck Calculation
78
RECOVERY METHODS
80
17.1.
18.
PROJECT INFRASTRUCTURE
82
82
18.1.
Transport, Access and Roads
83
18.2.
Service Facilities
83
18.3.
Administrative Facilities
84
18.4.
Water management
84
18.5.
Power Source
85
18.6.
Waste and Tailings Management Facilities
85
19.
MARKET AND CONTRACT STUDIES
86
20.
ENVIRONMENTAL STUDIES, SOCIAL IMPACT AND PERMITS
87
20.1.
ENVIRONMENTAL OBLIGATIONS
87
20.2.
ENVIRONMENTAL PERMITS
87
21.
5
Water consumption
CAPITAL AND OPERATING COSTS
88
21.1.
Mining operation costs
88
21.2.
Plant operating costs
88
21.3.
Process Plant Labor
89
21.4.
Energy Costs
89
21.5.
Reagent Costs
90
21.6.
Maintenance Cost
90
21.7.
G&A Costs
91
21.8.
Cost of transportation and storage of concentrate
91
21.9.
Recovery and Closure cost
91
21.10.
Opex summary
92
21.11.
Capex Mine
92
21.12.
Capex Processing plant
92
21.13.
Capex Infraestructure
93
21.14.
Capex indirect
93
21.15.
Capex Others
93
ECONOMIC ANALYSIS
94
22.
22.1.
6
SENSITIVITY ANALYSIS
23.
RISK ANALYSIS
24.
INTERPRETION AND CONCLUSIONS
96
99
103
Figure Index
Figure 1.1 Koraida Project .................................................................................................... 15
Figure 3.1 Location of the Koraida Project. ........................................................................ 17
Figure 7.1. Regional Geology Map. ...................................................................................... 20
Figure 8.1 Koraida Proyect Deposit ..................................................................................... 20
Figure 10.1. Drilling drills ..................................................................................................... 22
Figure 11.1. Drilling samples ................................................................................................ 23
Figure 14.2.1. Plan view of wireframes. ............................................................................... 26
Figure 14.2.2. Longitudinal view of wireframes. ................................................................. 27
Figure 14.5.1. Cumulative Probabilty Plot Assayinterval. ................................................. 38
Figure 14.5.3. Q-Q Plot of 2.5-meter composite Ag. ........................................................... 40
Figure 14.5.2. Q-Q Plot of 3-meter composite Ag. ............................................................. 41
Figure 14.6.1. Spherical variogram and experimental variogram for Ag in lithology 3. 42
Figure 14.6.2. Spherical variogram and experimental variogram for Ag in lithology4. . 42
Figure 14.6.3. Spherical variogram and experimental variogram for Pb in lithology 3. 43
Figure 14.6.4. Spherical variogram and experimental variogram for Pb in lithology 4. 43
Figure 14.6.6. Spherical variogram and experimental variogram for Zn in lithology 4. 44
Figure 14.7.1. Plan view of the block model representing lithology. ................................. 45
Figure 14.8.1. Plan view of resources. ................................................................................. 47
Figure 15.2.1 Pit by Pit analysis ............................................................................................ 52
7
Table 16.1. Pit 64 .................................................................................................................... 58
Table 16.3. Geometric Parameters. ...................................................................................... 59
Figure 16.1. Ramp width. ...................................................................................................... 60
Figure 16.2. Main components of the project. ..................................................................... 61
Figure 16.3. Cross section of the largest well and topography. ......................................... 61
Figure 16.2.3.1. Preliminary production schedule... ........................................................... 64
Figure 16.2.4.1. Annual production plan. ............................................................................ 65
Figure 16.2.4.2. Trucks per years ......................................................................................... 66
Figura 16.4.2.1.1. Graph of Lithology Vs Compressive Resistance ................................. 69
Figura 16.2.4.1. Blast Energy Distribution .......................................................................... 73
Figure 16.5.1. Volume per hole ............................................................................................. 74
Figure 16.1.2.1. No. Hydraulic shovel model CAT 6040 ..................................................... 75
Figure 16.1.2.2. No. Plan view of the pit ............................................................................... 76
Figure 16.1.3.1.CAT 785D Model Truck.............................................................................. 78
Figure17.1. Floushet of the mill ............................................................................................ 81
Figure 21.1.1. NPV Sensitivity Analysis ............................................................................... 96
Figure 21.1.2. IRR Sensitivity Analysis ................................................................................ 97
Figure 23.1. Probabilities. ...................................................................................................... 99
Figure 23.2. NPV risk 8 ....................................................................................................... 100
Figure 23.3. NPV risk 10%. ................................................................................................ 100
8
Figure 23.4. NPV risk 12%. ................................................................................................ 101
Figure 23.5. IRR risk. .......................................................................................................... 102
Figure 23.6. NPV probability.ad NPV................................................................................ 102
9
Table Index
Table 14.1.1. Project limits and block dimensions. ............................................................ 25
Table 14.1.2. Koraida project database. .............................................................................. 26
Table 14.3.1. Descriptive statistics applied to data. ............................................................ 27
Table 14.3.2. Descriptive statistics applied to data. ............................................................ 27
Table 14.4.1.1. Capping Ag grade. ........................................................................................ 35
Table 14.4.1.2. Data capped to Ag grades for each lithology. ............................................ 36
Table 14.4.2.1. Capping Pb grade. ........................................................................................ 36
Table 14.4.2.2. Data capped to Pb grades for each lithology. ............................................ 36
Table 14.4.3.1. Capping Zn grade......................................................................................... 37
Table 14.4.3.2. Data capped to Zn grades for each lithology. ............................................ 37
Table 14.5.1. Average length of test intervals. ..................................................................... 37
Table 14.5.2. 2-meter composite............................................................................................ 38
Table 14.5.3. 2-meter composite............................................................................................ 38
.................................................................................................................................................. 39
Table 14.5.4. 2.5-meter composite. ....................................................................................... 39
Table 14.5.5. 2.5-meter composite. ....................................................................................... 39
.................................................................................................................................................. 40
Table 14.5.6. 3-meter composite............................................................................................ 40
Table 14.5.7. 3-meter composite............................................................................................ 40
10
Table 14.6.1. Angular parameters. ....................................................................................... 41
Table 14.6.2 Distance parameters. ........................................................................................ 41
Table 14.6.3. Data obtained from modeled theoretical variograms. ................................. 42
Table 14.6.4. Data obtained from modeled theoretical variograms. ................................ 43
Table 14.6.5. Data obtained from modeled theoretical variograms. ................................ 44
Table 14.8.1. Distances for grade interpolation. .................................................................. 46
Table 14.8.2 Resource categorization criteria. .................................................................... 46
Table 14.8.3. Mineral resources. ........................................................................................... 46
Table 15.3.1. Point Values ..................................................................................................... 55
Table 16.2. Operating Pit ...................................................................................................... 59
Table 16.4. Ramp width calculation. .................................................................................... 60
Table 16.5. Dump design parameters. .................................................................................. 61
Table 16.1.1. Proven and probable mineral reserves .......................................................... 62
Table 16.2.3.1. Preliminary production schedule given by the software .......................... 63
Table 16.2.4.1. Total truck per years .................................................................................... 65
Table 16.3.1.1. Work regime ................................................................................................. 66
Table 16.4.1.1. Project data for mesh design ...................................................................... 67
Table 16.4.2.1. Correction factors to estimate JSF y RQD. .............................................. 68
Table 21.1.1.Mining operation costs. .................................................................................... 88
Table 21.2.1. Plant operating costs. ..................................................................................... 88
11
Table 21.3.1. Process Plant Labor ........................................................................................ 89
Table 21.4.1. Energy Cost ...................................................................................................... 89
Table 21.5.1. Reagent costs. ................................................................................................... 90
Table 21.6.1. Maintenance Cost ............................................................................................ 90
Table 21.7.1. G&A costs. ....................................................................................................... 91
Table 21.8.1. Cost of transportation and storage of concentrate. ...................................... 91
Table 21.9.1. Recovery and closure cost. .............................................................................. 91
Table 21.10.1. Opex summary............................................................................................... 92
Table 21.11.1. Capex mine..................................................................................................... 92
Table 21.12.1. Capex Processing plant. ................................................................................ 92
Table 21.13.1. Capex Infraestructure on site ....................................................................... 93
Table 21.13.2. Capex Infraestructure off site ...................................................................... 93
Table 21.14.1. Capex Indirect ............................................................................................... 93
Table 21.15.1. Capex Others ................................................................................................. 93
Table 22.1. Economic Analysis for the Koraida Project .................................................... 95
Table 22.2. Net present value, internal rate of return and payback for the project ........ 96
Table 21.1.1. Sensitivity of the NPV and IRR to price changes. ........................................ 97
Table 21.1.2. Sensitivity of the NPV and IRR to the change in Capex. ............................. 97
Table 21.1.3. Sensitivity of the NPV and IRR to the change in the recovery of Ag. ........ 98
Table 21.1.4. Sensitivity of the NPV and IRR to the change in the recovery of Pb. ........ 98
12
Table 21.1.5. Sensitivity of the NPV and IRR to the change in the recovery of Zn. ........ 98
Table 21.1.6. Sensitivity of the NPV and IRR to the change in unit cost. ......................... 99
13
1. ABSTRACT
The present work aims to show a conceptual study of the Koraida mining project, in order to
analyze its viability.
Based on data provided by the teachers in charge of the course, data from exploration drills and
their subsequent analysis using the Mineplan software, with which we were able to perform
different types of calculations from the estimation and cubing of the reserve to its economic
evaluation.
The Ag, Pb and Zn project resources and reserves were estimated, resulting in a total of 187 Mt
of resources with a grade of 43.18 gpt Ag, 0.77% Pb and 0.46% Zn. Which for the calculation of
our reserves we define our cutoff grade (NSR cut off = 11.47 $ / t) resulting in 182Mt of proven +
probable exploitable reserves with an average grade of 43.58 gpt Ag, 0.82% Pb and 0.54% Zn.
From the resources and reserves model, the mining phases were defined according to the pit by
pit analysis, obtaining a final optimal pit marked by a minimum profitability, Pit Sell 50 in 4
phases. After that, the production plan was obtained with a plant capacity of 27,000 tons / day for
16 years. Finally, an economic analysis of the project was carried out, resulting in a NPV of 480
M US $ at a discount rate of 10% after taxes with an IRR of 27% and initial investment of 699.9
M US $.
Thus, the viability of the project is concluded with a return on investment period of 2.6 years,
for the assumptions considered in the evaluation of the project.
14
Figure 1.1 Koraida Project
2. INTRODUCTION
This report contemplates the technical-economic evaluation of the Koraida mining project at a
conceptual level, an area explored for many years and which is currently owned by the BCM
Mining Corporation. This project is classified within the large mining sector due to a prospective
production rate of 27,000 tpd, it is located at 5,200 meters above sea level in the province of
Carabaya, department of Puno, which consists of the exploitation of base metals such as Ag, Pb,
Zn during 16 years obtaining Pb concentrate and Zn concentrate as product. The general objective
of this evaluation process is to determine if the project presents reasonable expectations of
economic profitability, as well as to analyze the risk involved in the assumptions of our base case.
The specific objectives are to establish an adequate strategy to carry out the evaluation of the
project, to achieve an estimate of the resources that is as accurate as possible to reality even when
we do not have all the information on the deposit, to justify the costs incurred in the process and
the necessary investments, as well as defining the production schedule that can generate greater
value and sustain an attractive NPV of the project.
15
The main works and studies carried out to reduce the risk included: an update of the geometallurgical model referred to in the BCM report, studies of stability and characteristics of tailings
disposal, a legal review of the Peruvian tax regime, an update to the commercialization terms and
transportation of concentrates, development of alternative execution approaches and associated
capital costs, adjustment of operating plans and associated operating costs, an update of the project
schedule.
3. DESCRIPTION AND LOCATION OF THE PROPERTY
The Koraida project is an open-pit silver, lead and zinc mining project located in the
District of Koraida, Carabaya province of the Department of Puno, at an altitude that varies
between 4350 masl and 5200 masl. Koraida district, bordered on the south by the district of Nuñoa
(province of Melgar), on the north and west by the district of Checacupe (province of Canchis,
region of Cuzco) and on the east with the district of Macusani (province of Carabaya , Puno
region).
It is in charge of the Canadian company Oso Mining, which will make an investment of
585 million dollars to obtain an annual production of 12 million ounces of silver. There will be
approximately 1500 workers. The useful life of Koraida is estimated to be 18 years.
16
Figure 3.1 Location of the Koraida Project.
Koraida
Koraida
4. ACCESSIBILITY, CLIMATE, LOCAL RESOURCES, INFRASTRUCTURE AND
PHYSIOGRAPHY.
Access to the project area is from Lima to Juliaca by air, then by land through the interoceanic
asphalt highway to Macusani; from this point, via an unpaved road, you reach the Koraida mining
project. The following table shows the access routes and the estimated times to reach the project.
ROUTE
Lima – Juliaca
Juliaca – Macusani
Macusani – Koraida
TIME IN HOURS
1.5
2.5
2.0
VIA
Aerial
Asphalt road
Asphalt road
The existing access to the project is mainly by an affirmed road from the city of
Macusani, which is easily reached from the city of Juliaca, which has an airport that receives
commercial airlines from Lima. This route typically takes 4.5 to 5 hours. From Juliaca, the route
generally heads north to the town of Azángaro on the Interoceanic Highway. At Macusani, the
route runs west and northwest 60 km from the mine, on an unpaved road.
17
Its neighboring communities are: Chacaconiza and Quelcaya.
5. WEATHER
The Koraida Project weather station is located in the vicinity of the proposed plant site. There
are almost eleven years of data available since the station was commissioned in December 2008.
The climate at the project site is characterized by an estimated average annual precipitation of
717.1 millimeters (mm), with the highest values being recorded between October and April (89%
of annual precipitation). Average annual evaporation was determined to be of the order of 810.4
mm, with the highest monthly evaporation rates in August (97.1 mm) and the lowest monthly
evaporation occurring in March (43.5 mm).
The monthly average temperature varies from 1.2 to 3.3 ° C. The monthly average minimum
temperature varies from -2.1 ° C to 1.5 ° C, while the monthly average maximum temperature
varies from 3.3 ° C at 4.8 ° C.
Average relative humidity ranges from 65 to 75%, with monthly averages ranging from a low
of 51% in July to a high of 83% in February.
Average annual wind speed is estimated at 2.2 m / s, with monthly averages ranging from 1.9
m / s in April to 2.4 m / s in July. The wind direction is generally from the southeast.
Limited comparison of site data can be made with other weather stations in the region. Regional
weather stations have relatively long data records. However, all available stations are at a
significant distance from the project and only general seasonal trends are correlated with the
weather station.
18
6. HISTORY
The company has all the surface rights linked to the area of the Koraida metallurgical mining
project, the same ones that have been acquired by the Public Deed of the Surface Right
Constitution Contract dated October 31, 2013 and in force to date, through which OSO MINING
SUCURSAL DEL PERÚ assigns to OSO MINING SAC, for a period of twenty-three (23) years,
all the surface rights of the properties for the purposes of carrying out and operating the Koraida
Metallurgical Mining Project, within which the rights are included. of superficial use of the
properties acquired from the Peasant Community of Quelcaya, the Peasant Community of
Chacaconiza and the Quechapata property, acquired from the Sanka family, duly ratified and
recognized by the Peasant Community of Chacaconiza.
The Canadian company Oso Mining obtained in June 2018 the mine construction permits,
granted by the Ministry of Energy and Mines, and water availability, granted by the Ministry of
Agriculture. His authorization to grant benefits is under evaluation at the ministry and he presents
14 observations.
As of April 30, 2021, the company has already started its early works but has not yet been able
to close the financing of 600 million.
7. GEOLOGICAL FRAMEWORK AND MINERALIZATION
Silver, lead and zinc will be extracted.
The Project area is supported by Tertiary volcanic rocks of the Quenamari Formation,
specifically a thick series of crystallolytic tuffs and andesite flows, which variably overlap
between the Lower Paleozoic and the Mesozoic metasediments of the Ambo and Tarma Groups.
The main zone of mineralization is the Chacacuzina Member of the Quenamari Formation. The
19
Chacacuzina is the youngest member of the Quenemari, and is composed of a sequence of crystallithic and crystal-vitric-lithic tuffs. Tuffs are extensively hydrothermally altered and generally
argillized to low-temperature clays, and exhibit variable faults, fractures, and gaps.
Figure 7.1. Regional Geology Map.
8. TYPE OF DEPOSIT
This mineralization is made up of an epithermal-type deposit with low sulphidation of silver,
lead and zinc hosted in stockworks, veins-breccias and fractures.
Figure 8.1 Koraida Proyect Deposit
20
The Ag-Pb-Zn polymetallic mineralization is typical of that developed in a raised crust
environment by rapid cooling of a hot hydrothermal fluid, derived predominantly from an intrusion
source that was in contact with cold wall rocks and remains at an unknown depth and an uncertain
metal grade. The important aspect of Koraida is that the lystric dilation faults concentrated
important sulphide ore fluids derived from intrusions, which were rapidly cooled to provide
economical polymetallic silver grades.
9. EXPLORATION
Oso mining began exploration activities at the Koraida property in 2005, initially under the
terms of an option agreement with Rio Tinto and since 2011, as sole proprietors. The first
exploration activities included surface geological mapping over the entire concession area (an area
of approximately 4.5 x 7 km), detailed lithological, alteration and structural mapping over the
deposit area at a scale of 1: 2500, excavation of trenches , terrestrial geophysical studies (induced
polarization and magnetism) and core drilling.
Since 2005, Oso mining has drilled 562 exploration wells at the Koraida Project, totaling
approximately 101,401 m. In 2019, six additional wells (a total of 906.0 m) were drilled in Koraida
to obtain material specifically for metallurgical test work. This additional core was also analyzed
for the presence of silver, lead, zinc and copper, and the results were added to the project database
to update the resource estimate.
21
10. DRILLING
Since 2005, 562 holes drilled in the Koraida project with a length total of 101401 meters
With a minimum spacing of 1200 meters with diamond drilling methods using LD250, the holes
are perpendicular to the mineralization, several holes were also made from the same point to reduce
the impact of the surface and obtain the necessary drilling coverage, in the case of lower grade
areas, the spacing was 25 meters.
Figure 10.1. Drilling drills
11. SAFETY,PREPARATION AND ANALYSIS OF SAMPLES
Diamond core samples are collected and placed in plastic boxes and weather-resistant cardboard
on the drilling rig by the drilling team and transported by vehicle to the Project camp, where the
core preparation facilities are located. BCM geologists photograph the core as it is received from
the rig and collect geotechnical (rock quality designation [RQD]) and core recovery information
before selecting sample intervals for the split. Test samples, usually 2 m in length, are selected by
the BCM geologist on site and divided using a manual core separator. Half of the sampled core is
22
returned to the box for the geological record, and the other half is packaged and labeled with a
blind sample number assigned by BCM.
BCM geologists collect channel samples from hand-dug trenches using a hammer and pointed
chisel. Trenches are dug by hand to remove overburden and expose a clean bedrock surface on the
trench floor.
BCM staff transport bagged core and trench samples from Cusco to Juliaca, where they are
transferred by bus for shipment to ALS-Chemex laboratories (ISL certified) in Arequipa, Peru.
Figure 11.1. Drilling samples
The samples are prepared in Arequipa and later sent to the ALS-Chemex laboratory in Lima for
analysis. The chain of custody is documented throughout the transportation process.
Samples are prepared according to the ALS-Chemex PREP-31 preparation code, which
involves following:
● The sample is dried at 110 ° to 120 ° C and crushed with a jaw and roller crusher to 70%
● 2mm (approximately # 10 mesh)
● a 250 g subsample is obtained using a riffle divider
● The division is sprayed with a ring and disk sprayer at 85% passing 75 microns (μm)
23
● Coarse rejects are returned to BCM
12. MINERAL PROCESSING AND METALLURGICAL TEST
The exploitation of the deposit will be carried out by the open pit method and the processing of
the minerals will be through conventional flotation, obtaining silver-lead and silver-zinc
concentrates.
In 2018 and 2019 additional metallurgical test work was performed on 12 samples from 9 wells
(6 of which were new, as described above) drilled in the East, Minas and Main wells to optimize
the known floatation test conditions, as well. as the crushing parameters. , scheme of reagents and
dehydration of concentrates and characteristics of tails. The selected samples reasonably cover the
entire ore deposit and include ore with some degree of oxidation and ore with low sulfur content.
The information obtained validated and improved the recovery formulas, providing additional
confidence in the Life of Mine production schedule. This test work confirmed that marketable
grade zinc and lead concentrates can be produced using the processing parameters selected for the
process plant design.
13. TRANSPORTATION AND COMMERCIALIZATION OF CONCENTRATED
Lead concentrate containing approximately 8% moisture will be transported in standard size,
sealed and lined containers from the plant to the container port in Matarani, approximately 632 km
from the site. An estimated 14 trucks per day of lead concentrate will be shipped during years 1-3
of the mine's life, after which shipments will be reduced to 10 trucks per day.
The zinc concentrate containing approximately 8% moisture will be shipped in bulk from the
site to the bulk container port in Matarani. Approximately 9 trucks of zinc per day will be shipped
24
during the first three years of the mine's life and about 5 trucks per day for the remainder of the
mine's life.
14. ESTIMATION OF MINERAL RESOURCES
Resource estimation is considered a continuous process that begins with the exploration and
compilation of information, then geological modeling and interpolation of grades is carried out.
Subsequently, the modifying factors of the JORC code (mining, metallurgical, environmental,
legal, economic, etc.) are considered for the estimation of reserves.
The main objective of these procedures is the adequate estimation of the grade and tonnage of
the blocks, which will depend on the quality, quantity and distribution of the samples and the
degree of continuity of the mineralization.
14.1.
Database
Drilling on the Koraida project has been under the control of BCM. All drilling was done by
diamond core methods that produced a 6.36 cm diameter (2.5 inch) HQ core.
The project coordinates are represented in Table 14.1.1.
Coordinate
East
North
Elevation
Minimum
313900
445000
3900
Maximum
317920
449500
5200
Block Size
15
15
10
Table 14.1.1. Project limits and block dimensions.
The database is made up of 343 diamond drill holes demarcated by the area where there is an
acceptable concentration of drill holes, with 24973 test intervals totaling 61076.36 meters drilled,
of which 24222, contain the important metals of the project (Ag, Pb, Zn). Table 14.2.2.
25
# DDH Input
Minimum perforated length
Maximum perforated length
Total meters drilled
343
18 metros
434.35 metros
61076.36 metros
Table 14.1.2. Koraida project database.
14.2.
Geological interpretation and modeling.
The Koraida deposit is best described as a low to intermediate sulphidation epithermal deposit
with silver, lead and zinc mineralization hosted in stock-works, veins and breccias.
The geological solids for this project were made based on the lithology encoded in the diamond
drill holes. With this we can deduce that the estimation domain will be by lithology associated
with mineralization limits.
Figure 14.2.1. Plan view of wireframes.
1
2
3
4
5
26
Post
Oxides
Mixed Sulphides
Primary Sulfides
Sedimentary
Figure 14.2.2. Longitudinal view of wireframes.
14.3.
Exploratory Data Analysis (EDA)
The statistics of the assays, histograms of metal grades, correlation graphs, distribution of
populations, measures of central tendency (mean, mode) or dispersion (standard deviation) are
made. A summary is shown in Tables 14.3.1 and 14.3.2.
Statistics
LITHO 1: LITHO 1:
LITHO 1: LITHO 2: LITHO 2: LITHO 2: LITHO 3: LITHO 3: LITHO 3:
AG
PB
ZN
AG
PB
ZN
AG
PB
ZN
Minimum
1.00
0.01
0.01
1.00
0.01
0.01
1.00
0.01
0.01
Maximum
26.00
0.27
0.59
923.00
3.51
5.46 5840.00
16.65
17.15
Mean
1.94
0.04
0.07
27.25
0.27
0.13
57.43
1.03
0.59
STD
2.87
0.05
0.08
36.07
0.28
0.27
107.26
1.14
1.16
CV
1.48
1.25
1.21
1.32
1.02
1.98
1.87
1.11
1.98
Table 14.3.1. Descriptive statistics applied to data.
Statistics
Minimum
Maximum
Mean
STD
CV
LITHO 4: LITHO
LITHO
LITHO
LITHO
LITHO
AG
4: PB
4: ZN
5: AG
5: PB
5: ZN
1.00
0.01
0.01
1.00
0.01
0.01
1245.00
7.77
7.23
148.00
1.36
1.78
10.21
0.18
0.30
2.27
0.03
0.12
23.48
0.33
0.47
5.15
0.07
0.17
2.3
1.77
1.55
2.27
2.24
1.41
Table 14.3.2. Descriptive statistics applied to data.
27
14.3.1. Descriptive statistics
Histograms to obtain descriptive statistics and analyze the variability of the laws, the presence
of populations and possible outliers.
14.3.1.1. Descriptive statistics of the data for lithology 1.
A. Statistical analysis for Ag
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
AG
88
1
26
1.94
8.26
2.87
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
PB
88
0.01
0.27
0.04
0.05
1.25
B. Statistical analysis for Pb
28
C. Statistical analysis for Zn
14.3.1.2.
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
ZN
88
0.01
0.59
0.07
0.08
1.21
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
AG
3711
1
923
27.25
36.07
1.32
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
PB
3711
0.01
3.51
0.27
0.28
1.02
Descriptive statistics of the data for lithology 2.
A. Statistical analysis for Ag
B. Statistical analysis for Pb
29
C. Statistical analysis for Zn
14.3.1.3.
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
ZN
3711
0.01
5.46
0.13
0.27
1.98
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
AG
10345
1
5840
57.43
107.26
1.87
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
PB
10345
0.01
16.65
1.03
1.14
1.11
Descriptive statistics of the data for lithology 3.
A. Statistical analysis for Ag
B. Statistical analysis for Pb
30
C. Statistical analysis for Zn
14.3.1.4.
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
ZN
10345
0.01
17.15
0.59
1.16
1.98
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
AG
8809
1
1245
10.21
23.48
2.3
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
PB
8809
0.01
7.77
0.18
0.33
1.77
Descriptive statistics of the data for lithology 4.
A. Statistical analysis for Ag
B. Statistical analysis for Pb
31
C. Statistical analysis for Zn
14.3.1.5.
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
ZN
8809
0.01
7.23
0.3
0.47
1.55
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
AG
1269
1
148
2.27
5.15
2.27
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
PB
1269
0.01
1.36
0.03
0.07
2.24
Descriptive statistics of the data for lithology 5.
A. Statistical analysis for Ag
B. Statistical analysis for Pb
32
C. Statistical analysis for Zn
Statistics
Assays
Minimum
Maximum
Mean
STD
CV
ZN
1269
0.01
1.78
0.12
0.17
1.41
14.3.2. Correlation between metals
A bivariate analysis is performed between the metals of importance, to understand the behavior
of the grade of one metal with respect to the grade of another metal. The Q-Q Plot is used.
14.3.2.1.
Lithology 1-Post
LITHO 1
AG-PB
AG-ZN
ZN-PB
33
COEF. CORRELATION
0.59
0.3
0.25
14.3.2.2.
Lithology 2-Oxides
LITHO 2
AG-PB
AG-ZN
ZN-PB
14.3.2.3.
34
0.38
-0.1
0.08
Lithology 3-Mixed Sulfides
LITHO 3
AG-PB
AG-ZN
ZN-PB
14.3.2.4.
COEF. CORRELATION
COEF. CORRELATION
Lithology 4-Primary sulfides
0.37
0.34
0.44
LITHO 4
AG-PB
AG-ZN
ZN-PB
14.3.2.5.
0.39
0.24
0.38
Lithology 5-Sedimentary
LITHO 5
AG-PB
AG-ZN
ZN-PB
14.4.
COEF. CORRELATION
COEF. CORRELATION
0.74
0.40
0.43
Top cut analysis
The criteria assumed are:
•
The percentage of fines loss when applying Capping should not be greater than 2%.
•
The amount of capped data should not be greater than 2% of the number of samples.
14.4.1. Capping of Ag grades (gr/t)
LITHO
1-5
GRADE
CAPPING
3250
2500
2250
1750
1250
# DATA
CAPPED
1
2
3
6
8
# DATA
24222
MEAN
32.54
MEAN
STD
CV
32.3
32.2
32.1
31.87
31.76
66.52
64.47
62.57
59.07
57.76
2.06
2
1.95
1.85
1.82
STD
76.27
CV
2.4
MIN MAX
1
1
1
1
1
2580
2450
1950
1410
1245
MIN
1
%∆
DATA
0.004%
0.008%
0.012%
0.025%
0.033%
Table 14.4.1.1. Capping Ag grade.
35
MAX
5840
%∆ MEAN
0.74%
1.04%
1.35%
2.06%
2.40%
%∆ LOSS
FINE
-0.74%
-1.06%
-1.37%
-2.10%
-2.46%
Statistics
LITHO 1: LITHO 2: LITHO 3: LITHO 4: LITHO 5:
AG
AG
AG
AG
AG
88
3711
10345
8809
1269
1
1
1
1
1
26
923
1950
1245
148
1.94
27.25
56.95
10.21
2.27
2.87
36.07
90.24
23.48
5.15
1.48
1.32
1.58
2.3
2.27
Valid Data
Minimum
Maximum
Mean
STD
CV
Table 14.4.1.2. Data capped to Ag grades for each lithology.
14.4.2. Capping of Pb grade (%)
GRADE
CAPPING
16.5
15
14
13
LITHO
# DATA
MEAN
STD
CV
MIN
MAX
1-5
24222
0.551
0.89
1.61
1
16.65
# DATA
CAPPED
1
2
3
4
MEAN
STD
CV
MIN
MAX
%∆ DATA
%∆ MEAN
0.551
0.55
0.549
0.549
0.88
0.87
0.87
0.86
1.6
1.59
1.58
1.58
0.01
0.01
0.01
0.01
15.55
14.4
13.25
12.7
0.004%
0.008%
0.012%
0.017%
0.00%
0.18%
0.36%
0.36%
Table 14.4.2.1. Capping Pb grade.
Capping is therefore not performed:
Statistics
Valid Data
Minimum
Maximum
Mean
STD
CV
LITHO 1: LITHO 2: LITHO 3: LITHO 4: LITHO 5:
PB
PB
PB
PB
PB
88
3711
10345
8809
1269
0.01
0.01
0.01
0.01
0.01
0.27
3.51
16.65
7.77
1.36
0.04
0.27
1.03
0.18
0.03
0.05
0.28
1.14
0.33
0.07
1.25
1.02
1.11
1.77
2.24
Table 14.4.2.2. Data capped to Pb grades for each lithology.
14.4.3. Capping of Zn grades (%)
LITHO
1-5
36
# DATA
24222
MEAN
0.39
STD CV MIN MAX
0.84 2.16 0.01 17.15
%∆ LOSS
FINE
0.00%
-0.18%
-0.36%
-0.36%
GRADE
CAPPING
17
12
11.5
# DATA
CAPPED
1
2
6
MEAN
0.39
0.39
0.38
STD
CV
MIN
MAX
%∆
DATA
0.83 2.147 0.01 13.75 0.004%
0.826 2.139 0.01 11.95 0.008%
0.812 2.115 0.01 11.45 0.025%
%∆ MEAN
0.00%
0.26%
0.78%
%∆ LOSS
FINE
0.00%
-0.26%
-0.78%
Table 14.4.3.1. Capping Zn grade.
Capping is therefore not performed:
Statistics
Valid Data
Minimum
Maximum
Mean
STD
CV
LITHO 1: LITHO 2: LITHO 3: LITHO 4: LITHO 5:
ZN
ZN
ZN
ZN
ZN
88
3711
10345
8809
1269
0.01
0.01
0.01
0.01
0.01
0.59
5.46
17.15
7.23
1.78
0.07
0.13
0.59
0.30
0.12
0.08
0.27
1.16
0.47
0.17
1.21
1.98
1.98
1.55
1.41
Table 14.4.3.2. Data capped to Zn grades for each lithology.
14.5.
Compositing
When compositing, it must be considered that the size of the composite must be larger than the
average of the length of the assay intervals; the compositing should not change the average grade
of the assays, maximum by 5%; and the compositing should not change the sum of the metal
content (length x grade), maximum by 5%.
ASSAY INTERVAL
MEAN
CV
STD
MIN
MAX
2.43
2.69
6.54
0.05
163.81
Table 14.5.1. Average length of test intervals.
37
Figure 14.5.1. Cumulative Probabilty Plot Assayinterval.
Statistics
LITHO 1:
AG
Data
88
Minimum
1
Maximum
26
Mean
1.94
STD
2.87
CV
1.48
LITHO 1:
PB
88
0.01
0.27
0.04
0.05
1.25
LITHO 1: LITHO 2: LITHO 2: LITHO 2: LITHO 3: LITHO 3: LITHO 3:
ZN
AG
PB
ZN
AG
PB
ZN
88
3711
3711
3711
10345
10345
10345
0.01
1
0.01
0.01
1
0.01
0.01
0.59
923
3.51
5.46
1950
16.65
17.15
0.07
27.25
0.27
0.13
56.95
1.03
0.59
0.08
36.07
0.28
0.27
90.24
1.14
1.16
1.21
1.32
1.02
1.98
1.58
1.11
1.98
Table 14.5.2. 2-meter composite.
Statistics
LITHO 4:
AG
Data
8809
Minimum
1
Maximum
1245
Mean
10.21
STD
23.48
CV
2.3
LITHO
4: PB
8809
0.01
7.77
0.18
0.33
1.77
LITHO
4: ZN
8809
0.01
7.23
0.3
0.47
1.55
LITHO
5: AG
1269
1
148
2.27
5.15
2.27
Table 14.5.3. 2-meter composite
38
LITHO
5: PB
1269
0.01
1.36
0.03
0.07
2.24
LITHO
5: ZN
1269
0.01
1.78
0.12
0.17
1.41
Figure 14.5.2. Q-Q Plot of 2-meter composite Ag.
Statistics
LITHO 1:
AG
Data
111
Minimum
1
Maximum
26
Mean
5.48
STD
8.83
CV
1.61
LITHO 1:
PB
111
0.01
0.27
0.07
0.09
1.26
LITHO 1: LITHO 2: LITHO 2: LITHO 2: LITHO 3: LITHO 3: LITHO 3:
ZN
AG
PB
ZN
AG
PB
ZN
111
3767
3767
3767
10371
10371
10371
0.01
1
0.01
0.01
1
0.01
0.01
0.59
923
3.51
5.46
1950
16.65
17.15
0.09
27.27
0.27
0.13
56.97
1.03
0.59
0.09
34.96
0.27
0.27
89.23
1.13
1.15
1.01
1.28
0.99
1.98
1.57
1.1
1.96
Table 14.5.4. 2.5-meter composite.
Statistics
LITHO 4:
AG
Data
8878
Minimum
1
Maximum
1245
Mean
10.19
STD
23.4
CV
2.3
LITHO
4: PB
8878
0.01
7.77
0.18
0.32
1.77
LITHO
4: ZN
8878
0.01
7.23
0.3
0.47
1.54
LITHO
5: AG
1339
1
148
2.25
5.03
2.23
LITHO
5: PB
1339
0.01
1.36
0.03
0.07
2.21
Table 14.5.5. 2.5-meter composite.
39
LITHO
5: ZN
1339
0.01
1.78
0.12
0.17
1.41
Figure 14.5.3. Q-Q Plot of 2.5-meter composite Ag.
Statistics
LITHO 1:
AG
Data
94
Minimum
1
Maximum
26
Mean
5.4
STD
8.71
CV
1.61
LITHO 1:
PB
94
0.01
0.27
0.07
0.09
1.27
LITHO 1: LITHO 2: LITHO 2: LITHO 2: LITHO 3: LITHO 3: LITHO 3:
ZN
AG
PB
ZN
AG
PB
ZN
94
3102
3102
3102
8415
8415
8415
0.01
1
0.01
0.01
1
0.01
0.01
0.45
747
3.4
4.37
1716.2
11.18
10.92
0.09
27.19
0.27
0.14
56.78
1.03
0.59
0.08
32.72
0.25
0.25
79.82
1.03
1.08
0.97
1.2
0.91
1.86
1.41
1
1.82
Table 14.5.6. 3-meter composite.
Statistics
LITHO 4:
AG
Data
7231
Minimum
1
Maximum
1245
Mean
10.25
STD
23.04
CV
2.25
LITHO
4: PB
7231
0.01
7.22
0.18
0.29
1.58
LITHO
4: ZN
7231
0.01
6.74
0.3
0.42
1.39
LITHO
5: AG
1132
1
118.8
2.21
4.35
1.96
Table 14.5.7. 3-meter composite.
40
LITHO
5: PB
1132
0.01
1.09
0.03
0.06
1.96
LITHO
5: ZN
1132
0.01
1.32
0.11
0.15
1.31
Figure 14.5.2. Q-Q Plot of 3-meter composite Ag.
Considering the amount of data, the variation of averages and the graphs with respect to the
tests, the compost length to be chosen is 2 meters.
14.6.
Variography
PARAMETERS
HORIZONTAL VERTICAL
ANGLE BEGINNING
0°
0°
ANGLE INCREMENT
15°
15°
WINDOWING ANGLE
7.5°
7.5°
NUMBER OF ANGLES
18
7
Table 14.6.1. Angular parameters.
PARÁMETROS
LAG DISTANCE
NUMBER OF LAGS
LAG DISTANCE TOLERANCE
30
8
0
Table 14.6.2 Distance parameters.
Experimental variograms are obtained from the 2-meter composited data, including the
parameters in Tables 14.6.1 and 14.6.2.
41
Variograms for Ag
AG
LITHO
3
4
NUGGET
562.79
381.16
SILL
9605.8
704.76
RANGE
60.149
59.281
AZIMUTH DIP
75
15
255
45
Table 14.6.3. Data obtained from modeled theoretical variograms.
Figure 14.6.1. Spherical variogram and experimental variogram for Ag in lithology 3.
Figure 14.6.2. Spherical variogram and experimental variogram for Ag in lithology4.
42
Variograms for Pb
PB
LITHO
3
4
NUGGET
0.1819
0.03293
SILL
1.3022
0.07232
RANGE
63.516
59.247
AZIMUTH
135
75
DIP
0
75
Table 14.6.4. Data obtained from modeled theoretical variograms.
Figure 14.6.3. Spherical variogram and experimental variogram for Pb in lithology 3.
Figure 14.6.4. Spherical variogram and experimental variogram for Pb in lithology 4.
43
Variograms for Zn
ZN
LITHO
3
4
NUGGET
0.6735
0.1479
SILL
1.3042
0.2091
RANGE
59.667
58.729
AZIMUTH
75
255
DIP
0
45
Table 14.6.5. Data obtained from modeled theoretical variograms.
Figure 14.6.5. Spherical variogram and experimental variogram for Zn in lithology 3.
Figure 14.6.6. Spherical variogram and experimental variogram for Zn in lithology 4.
44
By modeling these variograms, we obtain an average range of 60 meters, which will be useful
for resource estimation.
14.7.
Block Model
The block model is the discretization of the geological solid obtained in the modeling. The
dimensions of the block used in the model is 15x15x10 meters.
1
2
3
4
5
Post
Oxides
Mixed Sulphides
Primary Sulfides
Sedimentary
Figure 14.7.1. Plan view of the block model representing lithology.
45
14.8.
Estimating plan
The estimation was made by inverse of the distance because Kriging was not appropriate since
the geological model is not so consistent. The average range of the variograms in lithologies 3 and
4 of 60 meters is considered. The estimation was made considering that each block will be
estimated by geological domain.
SEARCH DISTANCE MODEL X
SEARCH DISTANCE MODEL Y
SEARCH DISTANCE MODEL Z
MAX 3D DISTANCE
MIN # COMPOSITES
MAX # COMPOSITES
MEASURED
30
30
15
30
6
15
INDICATED
60
60
15
60
4
15
INFERRED
90
90
15
90
1
15
Table 14.8.1. Distances for grade interpolation.
Categorization criteria
Categorization was based on ranges of average estimation distances and range of number of
composites to define measured, indicated, and inferred resources.
CATEGORÍA
AVERAGE DISTANCE
# COMPOSITES
CAT
MEASURED
MIN
MAX
0
30
6
15
1
INDICATED
MIN
MAX
0
60
4
15
2
INFERRED
MIN
MAX
0
90
1
15
3
Table 14.8.2 Resource categorization criteria.
Declaration of mineral resources
Based on the parameters used in our estimation, we obtain a tonnage of 187.661 million
measured + inferred resources.
Ton (000)
Measured
Indicated
M+I
Inferred
46
Ag gpt
Pb%
92,416
48.31
0.83
95,245
38.20
0.71
187,661
43.18
0.77
46,694
32.63
0.61
Table 14.8.3. Mineral resources.
Zn%
0.51
0.41
0.46
0.33
Figure 14.8.1. Plan view of resources.
15. ESTIMATION OF MINING RESERVES
15.1.
Pit optimization
The analysis by the Lerchs Grossman algorithm was performed using the Minesight software.
The Net Smelter Return (NSR) and the values of each block calculated in the software were used.
The NSR includes income payable less costs to sell, including treatment and refining expenses.
The values of the block consider the operating costs of extraction, processing and general and
administrative expenses. In addition, metal prices, average cost of inputs, a recovery model by
rock type, with a constant slope angle of 45 ° are used to produce a theoretical maximum pit
containing the highest possible net economic value. For our present evaluation of the project at the
conceptual level, we have considered the following optimization parameters.
47
PRECIOS
METAL
LOM
UNIDAD
Pb
0.9
$/lb
Zn
1.15
$/lb
Ag
22
$/Oz
Mining Cost ore
Mining Cost waste
Processing
G&A Cost
Unit Operating cost
1.84 $/t mined
1.5 $/t mined
9.25 $/t processed
1.88 $/t processed
Production
Mix
Sulfide
Metal
Silver
Lead
Zinc
Silver
Lead
Zinc
Recovery
68.00%
90.00%
87.00%
66.00%
88.00%
85.00%
Likewise, the commercial terms were defined
Treatment factors
Lead Concentrate
48
Payable Pb
95%
3.00%
Payable Ag
95%
1.61
Treatment Charge
Refining Charge Ag
Trucking and port
Shipping
Moisture
111.5
0.8
70.96
66.75
7%
$/dmt
$/payable oz
$/wmt
$/wmt
Zinc Concentrate
Payable Zn
Price participation above $
Price participation below $
Payable Ag
Treatment Charge
85%
2400.00
2400.00
70%
231.3
8%
0.10
-0.30
3
$/dmt
oz/dmt
$/dmt
dmt
oz/dmt
Refining Charge
Trucking and port
Shipping
Moisture
Penalties copper + lead (per 1% over 4%)
0%
59
62.28
8%
1.00
$/wmt
$/wmt
$/dmt
Being the characteristics of the concentrates:
Metal Recoveries
Concentrate
Lead Recovery
Zinc Recovery
Silver Recovery
Lead concéntrate
74.6%
13.0%
61.0%
Zinc concéntrate
3.5%
73.2%
6.1%
Concentrate characteristics
Element
Lead
Zinc
Silver
Lead concentrate
51.00%
6.82%
2154.38 g/t
Zinc concentrate
3.29%
52.8%
296.03 g/t
This provides us with the following graph, which describes the amount of ore and waste to be
extracted in each pit generated, with their respective net value. Carrying out the pit by pit analysis,
we define the mining phases.
15.2.
Pit by Pit
This provides us with the following graph, which describes the amount of ore and waste to be
extracted in each pit generated, with their respective net value. Performing the pit by pit analysis
we define the mining phases.
Cut
Tonnes
Ag
Pb
Zn
NSR
VPT
PIT05-PIT06
11,610
250.83
2.39
3.77
126.80
119.46
PIT06-PIT07
44,064
177.68
1.81
2.89
125.11
117.95
PIT07-PIT08
57,888
160.09
1.42
1.68
123.42
115.18
PIT08-PIT09
319,680
119.11
1.56
0.78
93.01
85.10
PIT09-PIT10
2,503,440
66.47
0.79
0.88
63.14
57.07
PIT10-PIT11
5,194,206
66.66
0.76
0.75
60.78
53.89
49
SR
0.1
0.5
0.8
ORE (000 t)
WASTE (000 t)
10.80
0.81
Ingresos
(MU$$)
1.37
40
15.44
73
40.93
245
Egresos
(MU$$)
-0.08
Valor Neto
(MU$$)
1.29
5.05
-0.31
4.74
9.05
-0.62
8.43
187.81
25.12
-2.21
22.92
1,242
1,694.95
88.03
-10.51
77.52
3,691
4,439.61
236.93
-31.53
205.40
0.9
1.5
1.1
PIT11-PIT12
1,879,146
PIT12-PIT13
1,449,792
63.28
1.00
0.61
57.90
50.68
PIT13-PIT14
4,022,784
51.82
0.85
0.43
46.58
39.46
PIT14-PIT15
1,675,674
43.47
0.72
0.78
50.48
43.21
PIT15-PIT16
3,808,296
38.28
0.66
0.39
38.00
32.16
PIT16-PIT17
2,393,820
36.99
0.51
0.37
30.72
26.34
PIT17-PIT18
2,030,184
41.32
0.82
0.45
39.07
32.67
PIT18-PIT19
4,033,476
30.96
0.82
0.46
36.53
30.01
PIT19-PIT20
45,593,768
PIT20-PIT21
11,313,432
29.97
0.66
0.22
29.62
23.07
PIT21-PIT22
5,594,184
26.56
0.61
0.40
28.37
21.64
PIT22-PIT23
4,391,604
24.38
0.54
0.31
26.19
20.00
PIT23-PIT24
3,774,276
28.91
0.63
0.47
31.32
23.42
PIT24-PIT25
3,845,124
25.43
0.59
0.32
26.04
19.35
PIT25-PIT26
17,170,759
22.04
0.46
0.25
19.32
13.64
PIT26-PIT27
8,237,484
30.41
0.55
0.31
27.36
19.08
PIT27-PIT28
9,764,388
PIT28-PIT29
8,966,700
22.99
0.49
0.20
23.06
16.12
PIT29-PIT30
23,137,921
24.86
0.48
0.22
24.05
16.48
PIT30-PIT31
9,024,750
22.34
0.49
0.22
21.90
14.45
PIT31-PIT32
3,970,188
27.62
0.52
0.20
24.64
16.41
PIT32-PIT33
13,491,631
19.16
0.37
0.21
18.83
11.84
PIT33-PIT34
5,733,180
17.88
0.41
0.55
24.82
15.56
PIT34-PIT35
5,243,886
16.27
0.36
0.27
18.26
11.49
PIT35-PIT36
7,625,718
PIT36-PIT37
5,585,598
17.50
0.36
0.24
17.11
10.59
PIT37-PIT38
3,766,554
16.98
0.35
0.27
17.34
10.40
PIT38-PIT39
9,300,312
16.01
0.32
0.16
15.59
9.05
PIT39-PIT40
7,762,932
PIT40-PIT41
17,650,549
15.12
0.28
0.13
11.80
6.64
PIT41-PIT42
3,660,930
13.79
0.32
0.23
15.55
8.64
PIT42-PIT43
2,213,136
13.95
0.29
0.34
18.00
9.44
PIT43-PIT44
8,243,478
PIT44-PIT45
5,085,234
15.35
0.26
0.22
13.05
6.81
PIT45-PIT46
4,205,466
10.45
0.32
0.24
13.16
7.04
PIT46-PIT47
5,309,982
14.16
0.27
0.33
13.07
6.63
PIT47-PIT48
3,788,370
PIT48-PIT49
6,215,778
11.06
0.30
0.20
12.81
6.06
PIT49-PIT50
7,543,476
11.04
0.23
0.13
10.03
4.76
PIT50-PIT51
7,038,900
13.44
0.26
0.20
12.29
5.49
PIT51-PIT52
6,858,918
50
66.70
0.97
0.70
63.17
55.95
4,645
5,365.49
297.14
-39.80
257.34
5,372
6,087.91
339.26
-46.14
293.12
7,338
8,145.09
430.81
-63.21
367.60
8,184
8,974.10
473.55
-70.61
402.94
1.0
1.0
1.0
1.0
9,637
11,329.79
528.75
-82.63
446.12
10,474
12,886.61
554.47
-88.63
465.83
11,586
13,804.40
597.93
-97.13
500.80
13,527
15,896.57
668.85
-112.92
555.93
27,994
47,023.80
1,017.98
-234.46
783.52
33,011
53,320.63
1,166.55
-276.76
889.79
35,618
56,307.42
1,240.53
-298.80
941.73
37,490
58,827.01
1,289.56
-314.18
975.38
39,720
60,371.08
1,359.41
-334.12
1,025.30
41,611
62,325.78
1,408.64
-349.70
1,058.95
47,815
73,291.93
1,528.49
-401.33
1,127.15
52,303
77,042.02
1,651.26
-444.11
1,207.15
57,817
81,291.82
1,789.63
-497.03
1,292.60
61,974
86,101.71
1,885.49
-533.11
1,352.38
73,892
97,321.83
2,172.15
-640.24
1,531.91
78,506
101,732.06
2,273.23
-681.24
1,591.99
80,889
103,319.82
2,331.93
-703.22
1,628.71
87,126
110,574.45
2,449.36
-757.71
1,691.66
90,878
112,555.12
2,542.51
-795.44
1,747.06
93,268
115,409.40
2,586.13
-815.90
1,770.24
96,678
119,625.50
2,643.53
-844.56
1,798.98
99,167
122,721.70
2,686.13
-865.44
1,820.69
100,900
124,754.85
2,716.19
-880.53
1,835.66
104,837
130,118.57
2,777.57
-914.33
1,863.24
109,510
133,208.93
2,872.00
-962.43
1,909.58
114,964
145,405.48
2,936.35
-1,008.84
1,927.51
116,638
147,392.41
2,962.37
-1,023.37
1,939.00
117,815
148,428.35
2,983.56
-1,035.00
1,948.56
121,972
152,514.85
3,048.83
-1,071.77
1,977.06
123,854
155,718.19
3,073.39
-1,088.32
1,985.07
125,532
158,245.49
3,095.47
-1,102.38
1,993.09
127,796
161,291.26
3,125.05
-1,121.51
2,003.54
129,088
163,787.89
3,139.70
-1,132.36
2,007.34
131,691
167,400.87
3,173.04
-1,155.35
2,017.69
133,932
172,703.35
3,195.52
-1,175.12
2,020.40
136,810
176,864.05
3,230.90
-1,200.93
2,029.97
139,608
180,924.25
3,264.73
-1,226.35
2,038.38
1.6
1.9
0.8
1.1
26.32
0.34
0.26
24.13
18.96
2.2
1.3
1.1
1.3
0.7
1.0
1.8
0.8
24.31
0.56
0.45
25.09
16.65
0.8
1.2
0.9
1.0
0.7
1.2
0.5
1.2
13.09
0.33
0.26
16.84
10.28
1.2
1.2
1.2
1.4
14.76
0.38
0.39
20.21
10.91
0.7
2.2
1.2
0.9
15.26
0.33
0.20
15.70
8.33
1.0
1.7
1.5
1.3
11.89
0.26
0.20
11.34
5.84
1.9
1.4
2.4
1.4
13.09
0.30
0.17
12.09
5.18
1.5
PIT52-PIT53
2,525,310
PIT53-PIT54
10,707,066
9.94
0.20
0.11
9.10
3.98
PIT54-PIT55
9,405,072
9.77
0.25
0.36
13.96
5.05
PIT55-PIT56
2,142,666
13.18
0.34
0.26
13.57
5.64
PIT56-PIT57
4,646,646
10.07
0.24
0.13
9.38
3.70
PIT57-PIT58
2,971,728
14.31
0.25
0.19
10.48
4.08
PIT58-PIT59
2,369,034
12.76
0.28
0.29
13.51
5.10
PIT59-PIT60
4,818,582
10.00
0.17
0.15
9.91
3.74
PIT60-PIT61
4,827,762
PIT61-PIT62
3,222,558
11.10
0.27
0.30
13.74
4.56
PIT62-PIT63
3,150,306
13.71
0.31
0.26
12.77
4.32
PIT63-PIT64
1,082,916
14.44
0.37
0.42
13.60
4.77
PIT64-PIT65
4,517,586
8.96
0.16
0.13
8.41
2.82
PIT65-PIT66
3,236,544
12.07
0.26
0.21
12.19
4.07
PIT66-PIT67
24,471,937
7.52
0.10
0.03
5.58
1.86
PIT67-PIT68
3,882,816
9.10
0.22
0.15
9.62
2.92
PIT68-PIT69
2,341,224
PIT69-PIT70
2,874,690
8.51
0.20
0.17
9.29
2.58
PIT70-PIT71
2,031,318
8.55
0.15
0.16
8.52
2.30
PIT71-PIT72
2,449,440
9.65
0.25
0.33
10.78
2.95
PIT72-PIT73
3,792,042
9.73
0.20
0.11
8.11
2.07
PIT73-PIT74
3,378,078
9.34
0.15
0.13
7.55
1.85
PIT74-PIT75
1,379,970
8.72
0.18
0.22
10.91
2.46
PIT75-PIT76
3,679,128
7.28
0.13
0.15
7.84
1.69
PIT76-PIT77
7,613,298
PIT77-PIT78
7,602,876
9.32
0.15
0.18
8.07
1.60
PIT78-PIT79
2,146,662
7.97
0.16
0.18
8.23
1.69
PIT79-PIT80
3,490,452
7.57
0.16
0.18
7.84
1.45
PIT80-PIT81
4,096,008
PIT81-PIT82
3,870,180
9.40
0.21
0.14
6.62
1.16
PIT82-PIT83
3,296,322
9.35
0.18
0.08
7.04
1.19
PIT83-PIT84
1,146,096
9.32
0.19
0.28
11.67
1.80
PIT84-PIT85
3,412,530
PIT85-PIT86
3,918,780
9.67
0.12
0.13
5.91
0.78
PIT86-PIT87
2,563,650
9.40
0.16
0.22
10.94
1.21
PIT87-PIT88
2,121,660
7.20
0.17
0.29
11.04
1.26
PIT88-PIT89
4,197,042
PIT89-PIT90
2,119,230
9.13
0.17
0.19
7.48
0.75
PIT90-PIT91
453,600
10.35
0.22
0.20
11.42
1.07
PIT91-PIT92
4,413,960
10.95
0.15
0.13
8.41
0.54
PIT92-PIT93
3,863,376
51
12.98
0.29
0.34
16.01
6.93
141,172
181,886.32
3,289.76
-1,241.99
2,047.77
144,313
189,451.93
3,318.36
-1,269.42
2,048.94
149,373
193,797.21
3,388.99
-1,321.00
2,067.99
150,480
194,832.87
3,404.01
-1,331.33
2,072.68
151,948
198,011.10
3,417.79
-1,344.44
2,073.35
153,089
199,842.13
3,429.75
-1,354.49
2,075.26
154,369
200,931.04
3,447.05
-1,366.88
2,080.16
156,142
203,977.23
3,464.61
-1,382.39
2,082.22
157,764
207,182.83
3,478.86
-1,396.08
2,082.78
159,559
208,609.89
3,503.53
-1,414.70
2,088.82
161,282
210,037.60
3,525.53
-1,431.41
2,094.12
161,930
210,472.51
3,534.34
-1,437.78
2,096.56
163,393
213,526.70
3,546.64
-1,450.54
2,096.10
165,197
214,959.64
3,568.62
-1,467.32
2,101.30
169,862
234,765.98
3,594.65
-1,514.37
2,080.28
171,445
237,066.60
3,609.88
-1,528.43
2,081.45
172,217
238,635.62
3,616.38
-1,535.40
2,080.98
173,345
240,381.71
3,626.86
-1,545.59
2,081.27
174,080
241,678.63
3,633.12
-1,552.11
2,081.01
175,343
242,864.47
3,646.74
-1,563.78
2,082.96
176,699
245,301.11
3,657.73
-1,575.63
2,082.11
177,757
247,620.79
3,665.73
-1,585.14
2,080.59
178,459
248,298.76
3,673.39
-1,592.09
2,081.30
179,690
250,746.69
3,683.05
-1,603.33
2,079.71
182,941
255,109.19
3,713.24
-1,634.27
2,078.97
185,677
259,976.64
3,735.32
-1,659.27
2,076.06
186,514
261,286.30
3,742.22
-1,666.70
2,075.51
187,804
263,486.15
3,752.34
-1,678.26
2,074.08
189,035
266,350.96
3,760.78
-1,689.55
2,071.24
190,207
269,049.34
3,768.54
-1,699.99
2,068.54
191,363
271,190.06
3,776.68
-1,709.97
2,066.71
192,103
271,596.36
3,785.31
-1,717.88
2,067.43
193,102
274,009.89
3,791.48
-1,726.73
2,064.75
194,144
276,886.47
3,797.63
-1,736.38
2,061.25
195,526
278,067.72
3,812.76
-1,751.61
2,061.14
196,833
278,882.58
3,827.19
-1,765.62
2,061.56
198,129
281,783.62
3,835.78
-1,777.69
2,058.09
198,950
283,082.05
3,841.92
-1,785.16
2,056.76
199,258
283,227.85
3,845.43
-1,788.56
2,056.87
200,797
286,102.81
3,858.38
-1,805.00
2,053.38
202,271
288,491.99
3,868.81
-1,818.22
2,050.59
0.6
2.4
0.9
0.9
2.2
1.6
0.9
1.7
9.78
0.22
0.13
8.78
3.30
2.0
0.8
0.8
0.7
2.1
0.8
4.2
1.5
9.31
0.17
0.14
8.42
2.44
2.0
1.5
1.8
0.9
1.8
2.2
1.0
2.0
11.96
0.19
0.19
9.29
1.78
1.3
1.8
1.6
1.7
8.15
0.14
0.08
6.86
1.18
2.3
2.3
1.9
0.5
7.30
0.12
0.12
6.17
0.94
2.4
2.8
0.9
0.6
8.35
0.11
0.11
6.63
0.68
2.2
1.6
0.5
1.9
6.14
0.12
0.17
7.07
0.54
1.6
PIT93-PIT94
5,197,122
6.22
0.09
0.16
6.38
0.39
PIT94-PIT95
604,476
9.05
0.14
0.24
9.71
0.59
PIT95-PIT96
4,583,682
6.69
0.11
0.10
5.11
0.26
PIT96-PIT97
4,041,522
7.47
0.13
0.20
7.12
0.23
PIT97-PIT98
1,873,314
8.56
0.11
0.08
5.73
0.19
PIT98-PIT99
943,758
8.43
0.15
0.18
8.47
0.19
PIT99-PT100
1,901,502
5.47
0.09
0.20
6.47
0.08
PT100-PT101
1,378,944
10.45
0.16
0.27
8.25
0.04
203,875
292,085.31
3,879.05
-1,833.23
2,045.82
204,242
292,322.59
3,882.62
-1,836.93
2,045.68
205,451
295,696.67
3,888.80
-1,847.86
2,040.94
206,677
298,512.39
3,897.53
-1,860.52
2,037.00
207,271
299,791.70
3,900.93
-1,865.73
2,035.20
207,757
300,249.46
3,905.05
-1,870.45
2,034.60
208,362
301,546.16
3,908.96
-1,876.26
2,032.70
208,934
302,352.71
3,913.68
-1,882.17
2,031.51
2.2
0.6
2.8
2.3
2.2
0.9
2.1
1.4
600,000.00
2,500.00
500,000.00
2,000.00
400,000.00
1,500.00
300,000.00
1,000.00
200,000.00
500.00
100,000.00
0.00
PIT05-PIT06
PIT08-PIT09
PIT11-PIT12
PIT14-PIT15
PIT17-PIT18
PIT20-PIT21
PIT23-PIT24
PIT26-PIT27
PIT29-PIT30
PIT32-PIT33
PIT35-PIT36
PIT38-PIT39
PIT41-PIT42
PIT44-PIT45
PIT47-PIT48
PIT50-PIT51
PIT53-PIT54
PIT56-PIT57
PIT59-PIT60
PIT62-PIT63
PIT65-PIT66
PIT68-PIT69
PIT71-PIT72
PIT74-PIT75
PIT77-PIT78
PIT80-PIT81
PIT83-PIT84
PIT86-PIT87
PIT89-PIT90
PIT92-PIT93
PIT95-PIT96
PIT98-PIT99
0.00
Figure 15.2.1 Pit by Pit analysis
15.3.
Cut off
To estimate the reserves of the project we are based on economic criteria defined by the cutoff
law. Due to the polymetallic deposit, the proposed cut-off grade is ($ / t), which is determined as
follows:
𝑁𝑆𝑅𝑐 = (𝑀𝑜 + 𝑃𝑜 + 𝑂𝑜 ) − (𝑀𝑤 + 𝑃𝑤 + 𝑂𝑤 )
Where:
52
Mo: Mining cost per metric ton of ore
Po: Processing cost per metric ton processed
Oo: General cost per metric ton processed
Mw: Mining cost per metric ton of waste
According to the parameters considered, we obtain the cut-off NSR = 11.47 $ / t
Metallurgical balance
Producto
Cabeza
Concentrado de Pb
Concentrado de Zn
TMS
270,605
2216.63
1613.17
%Pb
0.56%
51.00%
3.29%
Grade
%Zn
0.43%
6.82%
52.80%
Ag (g/t)
28.93
2154.38
296.03
%Pb
100%
74.60%
3.50%
Recovery
%Zn
100%
13.00%
73.20%
LEAD CONCENTRATE
Grade Pb
Grade Ag
Payable Metals
Pb: 95% (md 3u)
Ag: 95% (md 1.61 oz/dmt)
Total payable
Deductions
Treatment charge
Refining charge Ag
Concentrate transportation
Total deductions
Concentrate value
Concentration ratio
53
51.00%
69.26
oz/t
952.40
1,447.63
2,400.03
$/dmt
$/dmt
$/dmt
111.50
52.64
147.35
311.49
$/dmt
$/dmt
$/dmt
$/dmt
2,088.54
122.08
$/dmt
%Ag
100%
61.00%
6.10%
ZINC CONCENTRATE
Grade Zn
Grade Ag
Grade Pb
52.80%
9.52
3.29%
Payable Metals
Zn: 85% (md 8u)
Ag: 70% (md 3.0 oz/dmt)
Total payable
oz/t
1,135.82
143.39
1,279.21
$/dmt
$/dmt
$/dmt
Deductions
Treatment charge
Price participation
Refining charge Ag
Concentrate transportation
Total deductions
231.30
13.53
0.00
130.98
375.81
$/dmt
Concentrate value
Concentration ratio
903.39
167.75
$/dmt
$/dmt
$/dmt
$/dmt
LEAD CONCENTRATE
Pb contribution
Ag contribution
694
1,395
$/TM cc
$/TM cc
Value in Pb points (1%)
Water point value (1 oz)
10.14
12.29
$/ 1% Pb
$/ 1oz Ag
Pb contribution
Ag contribution
760
143.4
$/TM cc
$/TM
Zn Point Value (1%)
Ag Point Value (1 oz)
10.54
0.92
$/1% Zn
$/ 1oz Ag
ZINC CONCENTRATE
54
POINT VALUES SUMMARY
Pb
Zn
Ag
10.14
10.54
13.22
$/ 1% Pb
$/ 1% Zn
$/ 1oz Ag
Table 15.3.1. Point Values
16. Mine Design
For the operation of the pit, we proceed to incorporate the access roads to each of the bench of
the phases, this process is called operational phase design. For this, the mining equipment must
have been previously selected. These roads constitute the route for transporting ore and waste rock
from the active extraction areas to the upper Edge of the pit.
The operational design is affected by the current trend of deeper mines, which increases the
transport distance; and economies of scale, which affect team size. The possible effects of both
factors are decrease in the useful life of trucks and their tires, loss of productivity, poor driving
quality, and excessive generation of airborne dust. These aforementioned effects translate into high
maintenance costs (of equipment and roads) and loss of safety in the operation.
An open pit mine requires coordinating the execution of its daily productive activities with the
execution of construction activities and access ramps, which must satisfy the following restrictions
(Vásquez, Galdames, & LeFeaux, 2007; Atkinson, 1992):.
•
Allow free, safe and timely access to a specific area, in accordance with the production
schedule. This task is not so simple, especially in conditions in which various activities
are carried out in the same sector, so its planning should generate the least negative
impact on the rest of the operation.
55
•
Comply with the geometric restrictions of the equipment and transport activities, in
order to guarantee that the equipment that circulates on the ramps does so in safe
conditions for its operation and avoiding its premature deterioration.
•
Comply with the geomechanical restrictions of the sector since it must be exempt from
any risk of instability in the mine.
•
Allow the extraction of all material related to the sector.
•
Allow parallel activities to be carried out with complete safety.
A good design of the geometry of a ramp must comply with all the geometric specifications
imposed by geotechnics and, in addition, deliver the greatest possible economic benefit
(Thompson R. 2011), contained in the reserves of the pit design with ramp. This geometric
arrangement must consider: the economic scenario with which the optimal final pit is evaluated,
the equipment that transits the ramp, the mining plan, the pit area, and the deposit area.
For the selection of phases, the 100-pit run was made, of which Pit 20,31,42 and 64 were
chosen.
56
Ilustration 1: Original topography
Ilustration 2:Pit 20
57
Ilustration 3:Pit 31
Ilustration 4:Pit 42
Ilustration 5::Pit 64
Pit 64 was taken as the final pit, which gave us as a result.
The following tons.
PITS
Pit 64
Ore
182857229
Waste
189545075
S.R
1.04
Ag (gr/tm)
43.58
Pb %
0.82
Zn %
0.54
Table 16.1. Pit 64
Starting with Pit 20,31,42 and 64, the design of the phases was made as shown below in the
illustration.
Illustration 6: Horizontal view of the phases.
58
.
Illustration 7: Phase 01 (Pit 20)
Ilustration 9: Phase 03 (Pit 42)
PITS
OPERATING PIT
Ore
185,302,352
Waste
218,097,411
Illustration 8: Phase 02 (Pit 31)
Ilustration 10: Phase 04 (PIT 64)
S.R
1.18
Ag (gr/tm)
41.96
Pb %
0.79
Table 16.2. Operating Pit
The geometric components of the mining slope are presented in the following table:
PIT
Slope Angle
Bench Angle
Berm
Bench Height
45°
70°
6.1 meters
10 meters
Table 16.3. Geometric Parameters.
59
Zn %
0.52
For the design of the ramp, the following considerations are taken, adding that the slope of the
ramp is 12%, obtaining a design ramp width of 29 meters.
Description
Tire height
Truck width
Bench height
Angle of repose
Sidewalk width
Passable width
Ditch
Ramp width-Theoretical
Ramp width - Design
A
B
C
D
E
F
G
H
I
Truck
3.06 m
7.05 m
2.30 m
37°
6.09 m
21.15 m
0.6 m
28.44 m
29 m
Table 16.4. Ramp width calculation.
Figure 16.1. Ramp width.
60
Figure 16.2. Main components of the project.
In the Figure 16.2., a plan view of the main components of the project..
Dump
Slope angle
Bench angle
Berm
bench height
33°
50°
7 meters
10 meters
Table 16.5. Dump design parameters.
Figure 16.3. Cross section of the largest well and topography.
61
16.1.
Mineral Reserves
The mineral reserves of the project consider only categories of measured and indicated
resources, which have been converted to the categories of proven and probable reserves,
respectively. Mineral Reserves are defined as the material that will be fed to the process plant in
the mine plan already described and have proven to be economically viable.
Reserves
Proven
Probables
Proven + Probable
Tons
91,611,919
91,245,200
182,857,119
Ag (gr/tm)
48.20
38.94
43.58
Pb%
0.84
0.80
0.82
Zn%
0.53
0.55
0.54
NSR $/t
34.80
34.34
34.57
Table 16.1.1. Proven and probable mineral reserves
16.2.
Mining Method
16.2.1. Production rate and sizing
Determine the preliminary production rate, in a range of 9000 kt / year and 13000 kt / year.
Initially we opted for 10,280 kt / year with a daily production of 27,000 tons / day, according to
the stripping ratio that the final pit showed in the calculations of 1.04, we obtain an approximate
of the necessary waste removal of 16,700 kt / year.
Thus, defining our preliminary capabilities:
Reserves
Proven
Probables
Proven + Probable
Tons
91,611,919
91,245,200
182,857,119
Ag (gr/tm)
48.20
38.94
43.58
16.2.2. Pre-stripping
A 28 Mt clearing will be carried out during one year before the start of the operation, to allow
the sustainability of the mine.
62
16.2.3. Mining production and processing program
The mine's production schedule was developed to meet extraction and processing limitations,
focusing on maximizing the net present value (NPV) of the project.
Developing a variable cutoff grade strategy (NSR $ / t), while extracting the highest-grade
phases to maximize the overall NPV is what was sought.
The preliminary production schedule is shown below..
Table 16.2.3.1. Preliminary production schedule given by the software
As we noted, we obtain the high grades at the beginning of the operation, which will give us a
greater margin with respect to the costs per metal. However, this preliminary plan must be adjusted
63
with the objective of having relatively constant rates of production, a better management of the
business that implies low risks.
Figure 16.2.3.1. Preliminary production schedule...
16.2.4. Waste management.
As shown in the previous chapter, it is necessary to propose strategies for smoothing the waste
tonnage. The clearing cannot be extended into the future, but it can be brought to the present. This
balancing occurs by group of years with the consideration of the beginning of contiguous phases.
Finally, after a detailed review we will obtain the following graph respecting certain restrictions
with one year of pre-stripping.
64
ADJUSTED PRODUCTION
35000000
30000000
TONS
25000000
20000000
15000000
10000000
5000000
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17
YEAR
MILL
WASTE
TOTAL TONNAGE
Figure 16.2.4.1. Annual production plan.
Required production
PRODUCTIVIDAD CARGUIO
YEAR
WASTE
MILL
TPD MILL
0
28,483,187
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
20,123,925
13,945,673
13,915,478
15,155,055
17,045,376
12,695,640
12,666,010
10,718,190
10,756,404
10,749,854
10,769,387
9,074,279
9,242,599
9,242,101
8,002,116
5,512,080
11,661,570
11,564,478
11,610,026
11,539,863
11,641,841
11,511,660
11,566,474
11,635,477
11,581,254
11,590,548
11,562,832
11,540,253
11,571,104
11,571,968
11,599,002
11,554,005
0
32,393
32,124
32,250
32,055
32,338
31,977
32,129
32,321
32,170
32,196
32,119
32,056
32,142
32,144
32,219
32,094
Total Cycle.
Loadinghauling
Truck
productivity (ton
/ hr)
14.46
423.48
423.48
423.48
423.48
384.68
384.68
384.68
384.68
295.05
295.05
295.05
295.05
295.05
303.30
303.30
303.30
303.30
14.46
14.46
14.46
15.92
15.92
15.92
15.92
20.75
20.75
20.75
20.75
20.75
20.19
20.19
20.19
20.19
Table 16.2.4.1. Total truck per years
65
N ° OF TRUCKS
MILL
N ° OF
TRUCKS
WASTE
0.00
10.00
3.93
3.90
3.92
4.29
4.32
4.28
4.30
5.63
5.61
5.61
5.60
5.59
5.45
5.45
5.46
5.44
7.07
7.10
7.08
7.71
8.68
8.72
8.70
7.37
7.39
7.39
7.40
7.41
7.55
7.55
6.54
4.50
TOTAL
10
11
11
11
12
13
13
13
13
13
13
13
13
13
13
12
10
Figure 16.2.4.2. Trucks per years
16.3.
Work system
16.3.1. Work regime at the Koraida mine
The work system will be as follows:
The mine will be carried out with benches 10 meters high. Operations will be worked in 2 shifts
of 12 hours per day, 365 days a year. 3 crews of workers will be used. There will be a day watch,
a night watch and a rest group. Each group will be given in groups of 14 days (7 day and 7 night)
and 7 days off. 14x7 system.
Description
Hours per day
Changing of the guard
Foods
Blasting
Unit
H/day
H/day
H/day
H/day
Table 16.3.1.1. Work regime
66
Time
24
1
2
0.5
16.4.
Unitary Blasting Operation
16.4.1. Perforation mesh design
Koraida project data
Bench Height
10 m
Annual production
33000 Ton
Rock tensile strength
509.85 Kg/cm2
Rock mass density
2.4 Ton/m3
Table 16.4.1.1. Project data for mesh design
To determine the diameter of the hole, the model in the Enaex Manual will be used.
𝐷=
𝐻
(𝑝𝑢𝑙𝑔)
𝑘
Where:
D= Drill Diameter (in.)
H= Bench Height (m)
k= Constant <1.2 – 1.7>
16.4.2. Diameter calculation
𝐷=
10
= 5.88 𝑖𝑛 = 6 𝑖𝑛
1.7
𝐷 = 152 𝑚𝑚
For the design of the perforation mesh, the mathematical model of PEARSE will be used.
𝑅=𝐵=
Where:
R= Critical Radio.
B= Burden (m).
67
𝐾𝑣 𝐷 𝑃2
√
1000 𝑆𝑡𝑑
D= Hole diameter (m).
P2=Detonation pressure of the explosive charge (psi).
Std=Resistance to dynamic stress of the Rock (psi).
K= Volability Factor.
𝐾𝑣 = 1.96 − 0.27 ∗ 𝐿𝑛(𝐸𝑅𝑄𝐷)
ERQD = Equivalent Rock Quality Index (%).
ERQD = RQD x JSF
RQD: Rock Quality Designation.
JSF: Joint Strenght Correction Factor.
Table 16.4.2.1. Correction factors to estimate JSF y RQD.
Rock quality estimation
JSF
RQD (%)
Competent
1.0
75-90
Fair
0.9
50-75
Poor
0.8
25-50
Very Poor
0.7
0-25
Source: J. López Practical manual for rock drilling and blasting.
Calculation de Kv
𝐸𝑅𝑄𝐷 = 85 𝑥 1
𝐸𝑅𝑄𝐷 = 85
𝐾𝑣 = 1.96 − 0.27 ∗ 𝐿𝑛(63)
𝐾𝑣 = 0.76
68
16.4.2.1. Calculation of the Burden
Figura 16.4.2.1.1. Graph of Lithology Vs Compressive Resistance
Lithology vs Resistance to Simple Compression (UCS), González de Vallejo, 2002
(1,2,3,5,6,7); Hoek & Brown, 1997 (4); Kahraman, 2001 (9); CONAMA (8); Chau & Wong, 1996.
A compressive resistance of 120 Mpa is obtained according to the table.
Calculation of the tensile strength of the rock.
𝑆𝑡𝑑 =
Where:
Std: rock tensile strength.
RC: Compressive resistance (kg/cm2)
69
𝑅𝑐 − 280 𝑘𝑔
( 2)
21
𝑐𝑚
𝑆𝑡𝑑 =
1223.66 − 280
𝑘𝑔
= 45 2
21
𝑐𝑚
The detonation pressure of the Anfo-Heavy is 91774.459 kg / cm2 according to Famesa
technical data sheet.
𝑅=𝐵=
𝑅=𝐵=
𝐾𝑣 𝐷 𝑃2
√
1000 𝑆𝑡𝑑
0.76 ∗ 152 91 774.459
√
1000
45
𝑅 = 𝐵 ≈ 5.22 𝑚
16.4.2.2. Calculation of Spacing
For wells with a large diameter D> 175 mm the relationship will be: S=1.1*B
For wells with a small diameter D <175 mm the relationship will be: S=1.5*B
𝑆 = 1.5𝑥𝐵
𝑆 = 1.5𝑥6.5 = 9.75𝑚
16.4.2.3. Calculation of sub Drilling
𝑆𝑢𝑏 𝐷𝑟𝑖𝑙𝑙𝑖𝑛𝑔 = 𝑆𝐷 = 0.3𝑥𝐵
𝑆𝐷 = 0.3𝑥6.5𝑚
𝑆𝐷 = 1.95 ≈ 2𝑚
16.4.2.4. Perforation mesh simulation
● Design parameters
Burden (B)
Spacing (E)
Taco(T)
About drilling (J)
Drilling length (Lp)
Loading length (Lc)
70
5.22
6.01
3.60
2.00
12.00
8.40
● Charge factor
The load factor is calculated according to the following formula
h=10 m
𝐹. 𝐶 =
𝑘𝑔 𝑑𝑒 𝐸𝑥𝑝𝑙𝑜𝑠𝑖𝑣𝑜𝑠
𝑇𝑜𝑛𝑒𝑙𝑎𝑑𝑎𝑠 𝑉𝑜𝑙𝑎𝑑𝑎
(0.152)2 ∗ 𝜋
𝐾𝑔
) ∗ (1230 3 )
4
𝑚
𝑡𝑜𝑛
10 ∗ 5.2 ∗ 6 ∗ (2.4 3 )
𝑚
8.4 ∗ (
𝐹. 𝐶 =
𝐹. 𝐶 = 0.25
● Simulation en JK Simblast
71
𝐾𝑔 𝑑𝑒 𝑒𝑥𝑝𝑙𝑜𝑠𝑖𝑣𝑜
𝑇𝑜𝑛 𝑑𝑒 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙
Location of bank 5080 to design and export data from MINEPLAN to JK Simblast
Production Drills
72
Pre Cut Drills
Figura 16.2.4.1. Blast Energy Distribution
The PPV was 8.5mm / s, being accepted under the international blasting regulations according
to the USBM- EEUU
73
16.1.
Calculation of equipment numbers
16.1.1. Drilling Calculation
Figure 16.5.1. Volume per hole
PRODUCCION REQUERIDA
Densidad(ton/m3)
2.4
mineral (ton/mes)
858,143
S.R
1.6
desmonte (ton/mes)
1,405,222
total(mineral+ desmonte)
2,263,365
DRILL PARAMETERS
Drill Diameter (in)
6.0
Burden B(m)
5.2
Spacing E (m)
6.0
Bench height (m)
10.0
Over perforation (m)
2.0
DRILL PRODUCTION
ton/drill
904
m perf/drill
12
ton/ m perf
75
NEED FOR DRILLS
drills/month
2,505
m perf/ month
30,061
drill precorte (m perf/month)
6,012
20
total m perf/month
36,073
RENDIMIENTO DE PERFORADORAS
Veloc drill (m perf/h)
40.0
hrs/g day
10.0
74
g/day
day/month
Mechanical availability (%)
Mechanical use (%)
m perf/month
REQUIRED PRODUCTION
AÑO
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
MILL
WASTE
TOTAL
TONNAGE
TDM
11,609,811
11,527,622
11,516,809
11,557,857
11,578,887
11,578,438
11,507,340
11,555,882
11,603,786
11,527,142
11,492,530
11,581,731
11,492,900
11,578,599
11,565,070
11,484,055
12,800,000
12,812,784
13,220,000
13,790,000
12,790,000
12,790,000
12,930,000
12,790,000
12,840,000
12,870,000
12,800,000
12,930,000
12,930,000
12,930,000
12,930,000
11,110,711
24,409,811
24,340,406
24,736,809
25,347,857
24,368,887
24,368,438
24,437,340
24,345,882
24,443,786
24,397,142
24,292,530
24,511,731
24,422,900
24,508,599
24,495,070
22,594,766
2,034,151
2,028,367
2,061,401
2,112,321
2,030,741
2,030,703
2,036,445
2,028,824
2,036,982
2,033,095
2,024,378
2,042,644
2,035,242
2,042,383
2,041,256
1,882,897
2.0
30.0
0.9
0.8
15,300.0
NECESIDAD DE PERFORADORAS
m
pre
total m Number of
drill /
drills
perf/mont corte(m perforated
month
h
perf/mont /month
2,251
27,016
5,403
32,420
2.00
2,245
26,940
5,388
32,327
2.00
2,282
27,378
5,476
32,854
2.00
2,338
28,055
5,611
33,665
2.00
2,248
26,971
5,394
32,365
2.00
2,248
26,971
5,394
32,365
2.00
2,254
27,047
5,409
32,456
2.00
2,245
26,946
5,389
32,335
2.00
2,254
27,054
5,411
32,465
2.00
2,250
27,002
5,400
32,403
2.00
2,241
26,887
5,377
32,264
2.00
2,261
27,129
5,426
32,555
2.00
2,253
27,031
5,406
32,437
2.00
2,260
27,126
5,425
32,551
2.00
2,259
27,111
5,422
32,533
2.00
2,084
25,008
5,002
30,009
2.00
N° perf
3
16.1.2. Calculation of hydraulic shovels
Figure 16.1.2.1. No. Hydraulic shovel model CAT 6040
75
Figure 16.1.2.2. No. Plan view of the pit
MATERIAL CHARACTERISTICS
Insitu density (ton/m3)
2.4
Loose density (ton/m3)
1.96
Swell factor (%)
30.0
TONS PER PASS
Shovel capacity (m3)
22
Shovel capacity (yd3)
28.8
Bank factor (lb/BYC)
4,046.3
Factor
0.8
Loose factor (lb/LCY)
3,112.5
Fill factor of the shovel (%)
0.95
Ton/pass
38.6
MATERIAL CHARACTERISTICS
Insitu density (ton/m3)
2.4
Loose density (ton/m3)
1.96
Swell factor (%)
30.0
TONS PER PASS
Shovel capacity (m3)
8
Shovel capacity (yd3)
10.5
Bank factor (lb/BYC)
4,046.3
Factor
0.8
Loose factor (lb/LCY)
3,112.5
Fill factor of the shovel (%)
0.95
Ton/pass
14.0
𝑇𝑜𝑛
𝑙𝑏/𝐿𝐶𝑌
= 𝐶𝑎𝑝. 𝑆𝑢𝑒𝑙𝑡𝑎(𝑦𝑑3) ∗ 𝑓𝑖𝑙𝑙 𝑓𝑎𝑐𝑡𝑜𝑟 ∗ 𝑀𝑒𝑐ℎ𝑎𝑛𝑖𝑐𝑎𝑙 𝑠ℎ𝑜𝑣𝑒𝑙 ∗
𝑝𝑎𝑠𝑒
2205
76
𝑆ℎ𝑜𝑣𝑒𝑙 𝑐𝑦𝑐𝑙𝑒 =
𝑃𝑎𝑦𝑙𝑜𝑎𝑑(𝑡𝑛) ∗ 𝐶ℎ𝑎𝑟𝑔𝑒 𝑓𝑎𝑐𝑡𝑜𝑟 ∗ 2205 ∗ 60
𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑠ℎ𝑜𝑣𝑒𝑙 ∗ 𝐹. 𝐿𝐿 ∗ 𝑙𝑏/𝐿𝐶𝑌
𝑆ℎ𝑜𝑣𝑒𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 =
60
𝑇𝑜𝑛
∗ 𝑁° 𝑝𝑎𝑠𝑠 ∗
𝑆ℎ𝑜𝑣𝑒𝑙 𝑐𝑦𝑐𝑙𝑒
𝑝𝑎𝑠𝑠
REQUIRED PRODUCTION
YEAR
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
77
MILL
WASTE
TOTAL
TONNAGE
0
11,609,811
11,527,622
11,516,809
11,557,857
11,578,887
11,578,438
11,507,340
11,555,882
11,603,786
11,527,142
11,492,530
11,581,731
11,492,900
11,578,599
11,565,070
11,484,055
24,397,007
12,800,000
12,812,784
13,220,000
13,790,000
12,790,000
12,790,000
12,930,000
12,790,000
12,840,000
12,870,000
12,800,000
12,930,000
12,930,000
12,930,000
12,930,000
11,110,711
24,397,007
24,409,811
24,340,406
24,736,809
25,347,857
24,368,887
24,368,438
24,437,340
24,345,882
24,443,786
24,397,142
24,292,530
24,511,731
24,422,900
24,508,599
24,495,070
22,594,766
TPD
30% TPD
100%
30%
66,841
66,876
66,686
67,772
69,446
66,764
66,763
66,952
66,701
66,969
66,841
66,555
67,155
66,912
67,147
67,110
61,903
20,052
20,063
20,006
20,332
20,834
20,029
20,029
20,085
20,010
20,091
20,052
19,966
20,147
20,074
20,144
20,133
18,571
Number
of
hydraulic
drills
1.83
1.83
1.83
1.86
1.90
1.83
1.83
1.84
1.83
1.84
1.83
1.82
1.84
1.83
1.84
1.84
1.70
2
Number
of front
loader
0.98
0.98
0.98
0.99
1.02
0.98
0.98
0.98
0.98
0.98
0.98
0.97
0.98
0.98
0.98
0.98
0.91
1
16.1.3. Truck Calculation
Figure 16.1.3.1.CAT 785D Model Truck
TONS PER PASS
Payload (ton)
Charge factor (%)
140.00
0.90
Round trip time of the mill
1th phase
From
To
Velocity (km/hr) Distance Time(s) Time(s)
Frente 1
rampa1
10
118
0.708
0.679
Rampa
exit-pit
15
930
3.72
1.640
Exit-pit
rampa2
25
477
1.1448
4.242
Rampa2
Superficie
15
233
0.932
2.915
Superficie
Mill
25
1148
2.7552
0.965
Mill
superficie
30
1148
2.296
0.346
Superficie
rampa2
15
233
0.932
Rampa2
exit-pit
30
477
0.954
Exit-pit
rampa-vicer
30
930
1.86
Rampa1
frente n
10
118
0.708
10.787
From
Frente 2
Rampa1
Exit-pit
Rampa2
Superface
78
2th phase
Time(s)
1.018
2.600
3.972
2.730
1.383
0.544
12.246
3th phase
Time(s)
0.912
1.828
1.200
2.600
3.972
2.730
1.383
0.894
1.075
0.487
17.081
4th phase
Time(s)
0.691
3.720
1.431
0.932
3.444
2.367
0.583
1.060
1.938
0.352
16.517
Round trip time of the waste
1th phase 2th phase 3th phase 4th phase
To
Velocity (km/hr) Distance Time(s) Time(s)
Time(s)
Time(s)
0
rampa1
0
25
118
0.679
1.018
0.912
0.691
exit-pit
12
15
930
1.640
2.600
1.828
3.720
rampa2
0
25
477
4.713
4.158
1.200
1.431
Superface
12
15
233
3.239
3.868
2.600
0.932
Rampa
2
25
4854
0.965
2.015
4.158
4.851
botadero
Rampa
botadero
Waste
12
15
2132
Waste
Rampa
botadero
12
30
Superface
2
rampa2
exit-pit
Rampa1
frente 2
12
0
12
0
Rampa
botadero
Superface
Rampa2
Exit-pit
Rampa1
0.346
2.858
5.800
8.528
2132
1.383
2.990
4.396
30
4854
0.544
2.858
3.334
30
30
30
30
233
477
930
118
18.442
1.383
0.894
1.075
0.487
26.185
0.583
1.060
1.938
0.352
31.815
11.582
CARGUIO PRODUCTIVITY
Shovel cycle (min)
Turn time and discharge (min)
Positioning time (min)
Mechanical availability (%)
Mechanical use (%)
REQUIRED PRODUCTION
YEAR
MILL
TPD
0
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
11,661,570
11,564,478
11,610,026
11,539,863
11,641,841
11,511,660
11,566,474
11,635,477
11,581,254
11,590,548
11,562,832
11,540,253
11,571,104
11,571,968
11,599,002
11,554,005
79
CARGO PRODUCTIVITY
Total loadcarry cycle
14.46
32,393
32,124
32,250
32,055
32,338
31,977
32,129
32,321
32,170
32,196
32,119
32,056
32,142
32,144
32,219
32,094
2.07
1.3
0.3
0.9
0.9
14.46
14.46
14.46
15.92
15.92
15.92
15.92
20.75
20.75
20.75
20.75
20.75
20.19
20.19
20.19
20.19
NUMBER NUMBER
OF TRUCKS OF TRUCKS
Truck
MILL
WASTE
productivity
(ton / hr)
0.00
10.00
423.48
423.48
3.93
7.07
423.48
3.90
7.10
423.48
3.92
7.08
384.68
4.29
7.71
384.68
4.32
8.68
384.68
4.28
8.72
384.68
4.30
8.70
295.05
5.63
7.37
295.05
5.61
7.39
295.05
5.61
7.39
295.05
5.60
7.40
295.05
5.59
7.41
303.30
5.45
7.55
303.30
5.45
7.55
303.30
5.46
6.54
303.30
5.44
4.50
TOTAL
10
11
11
11
12
13
13
13
13
13
13
13
13
13
13
12
10
Equipment
Trucks
Shovel
Drill
Drill Rock
Front loader
Motor grader
Excavator
Water truck
Compactor
Bulldozer
Generator group
Equipment Summary
Model
Unit Price
Life (Hrs)
785 D
$ 2,695,000
60,000
6040 fs
$ 23,585,000
120,000
MD6250
$ 5,378,000
70,000
Roc L8
$ 965,679
40,000
972 L
$ 2,809,000
70,000
CAT 18
$ 1,662,000
45,000
CAT 374
$ 295,000
60,000
Volvo FMX
$ 1,072,000
80,000
CAT CS76
$ 115,000
45,000
CAT D11
$ 2,205,971
45,000
Lighting Tower
$ 132,000
45,000
Quantity
13
2
2
1
1
1
1
2
2
1
2
17. RECOVERY METHODS
A profitable plant has been designed to process ore from Koraida at a rate of 27,000 t / d. This
was achieved by minimizing the footprint, maximizing performance and taking advantage of
Topography.
The extracted ore will be crushed by a single rotary crusher before two stages of grinding in a
semi-autogenous mill (SAG) and ball mill. Lead and zinc-containing ores will be recovered in a
sequential two-stage flotation and crushing circuit.
Recovery
80
Lead
Zinc
75%
69%
PBD MAIN PLANT
ROM
ESPESADOR
Water Recovery
PRIMARY CRUSHER
FILTRADO
PRIMARY
SCREEN
SECONDARY CRUSHER
Pb-Ag Concentrate
CONDITIONER I
HIDROCYCLONE
O/F
21
H2O
11
U/F
STOCK PILE
Zn ROUGHER
20
ZN SCAVANGER
BALL MILL
19
SAG MILL
PUMP
Tails
Zn CLEANER
tail
O/Z
SECONDARY
SCREEN
U/Z
22
18
Pb/Ag BULK
ROUGHER
23
17
O/Z
CONDITIONER V
PEBBLES CRUSHER
ESPESADOR
Ag/Pb BULK
SCAVANGER
CONDITIONER IV
FILTRADO
16
tail
CONDITIONER III
Figure17.1. Floushet of the mill
81
Water Recovery
Zn Concentrate
17.1.
Water consumption
To reduce water consumption, the tailings from the flotation circuits will be thickened in
high compression thickeners before filtration in conventional pressure filters. The filtered tailings
will be disposed of along with the extracted waste to produce a stable waste deposit.
18. PROJECT INFRASTRUCTURE
The location of the Koraida Project site is remote, high altitude and 42 km from the
interoceanic highway. The closest urban area is Macusani with a population of approximately
12,700 people (2017 Census). The infrastructure to be developed for the project includes access to
the site, access routes, process buildings and related facilities, water supply, power supply,
communication and storage systems.
The work related to the infrastructure carried out after the 2017 report presented by the
company in charge is presented below:
- Additional geotechnical investigations, adding 9 wells, 28 test wells and 31 Light
Dynamic Penetration Tests (LDPT).
- Better access from the camp to the processing plant.
- Quarry study, locating the appropriate aggregates for concrete near the process plant.
- Review and optimization of the project and the footprints of the plant.
- Optimized access for mining vehicles (haul roads).
82
18.1.
Transport, Access and Roads
Building access has low interference and requires minimal CAPEX investment due to alignment
and location. There is minimal impact on local residents as there are no communities located along
the route. Access will also be available if needed during operations and can be used to receive
supplies and deliver the lead and zinc concentrates to the Port of Matarani or other ports via trucks
that connect to Peru's public highway system.
Another access road (a new 44 km road designed by GMI included in the Report), has a
government investment budget for construction approved for 2021 and will be available for
operations assuming funds are released and construction is completed as planned.
18.2.
Service Facilities
The mine service facilities will be located primarily in the Mining Infrastructure Area
(MIA) adjacent to the processing plant. The facilities include:
• Truck workshop
• Laundry and associated repair facilities
• Mine offices
• Deposit
• Fleet management system (dispatch)
• Explosives storage facility.
The explosives storage facility will be located in a remote area adjacent to the mine for
safety and security purposes.
83
18.3.
Administrative Facilities
Administrative facilities include the following buildings:
• Building of the entrance door of the process plant
• Administration building.
• Warehouse building
• First aid building
• Reagent storage building.
The administration facilities are located near the process plant and will contain the offices for
the local administration and management staff. The process plant entrance gate is located at the
entrance to the site near the contact and non-contact water ponds.
There will be a small administrative building in the accommodation camp for the management
of the camp, as well as the main medical post.
18.4.
Water management
Surface and groundwater will be used to provide the water needed for the project. Surface water
(runoff and current flow) and groundwater (from well dehydration) will come from the watershed
that houses the project.
The project is classified as contact water or non-contact water. Contact water is defined as water
that has had contact with any area disturbed by the project where water quality could be degraded
by acid rock drainage (ARD) or other water contaminants. Non-contact water is defined as water
that has not had contact with the process components or any area that has been disturbed. Contact
water and non-contact water will be managed and transported separately.
84
Ultimately, it will be stored in a water storage pond that has two separate compartments, one
for each circuit. The contact water that has been stored will be consumed as a preferential process
for the plant. This water cannot be discharged to the environment during operations. A part of the
non-contact water stored in the pond will be used to supplement the demand for process water
during dry seasons. Non-contact water that is not used will be discharged, if necessary, to the
Quebrada Chacaconiza. The project must discharge a fixed amount of non-contact water
downstream as part of the ITS and environmental impact study.
18.5.
Power Source
A 138 kV power transmission line is required to supply power to the Koraida Project. A new
electrical substation (the Antapata substation, currently under construction) will connect with
transmission lines L-1010 and L-1051 (San Gabán II - Azángaro) as a source of energy.
The 138 kV electric transmission line will be built to connect the Antapata substation to the
main substation that will be built near the main process buildings of the Project. The transmission
line will be 29.4 km long.
The transmission line route uses the route already provided by the access road to the Project.
Rights of way for the power line have been agreed with local communities, but have not yet been
purchased from individual land owners.
18.6.
Waste and Tailings Management Facilities
The main mine waste and filtered tailings deposit is used for the disposal of mining waste and
filtered tailings in a common deposit, the size of which has been designed for the quantities
considered in the mine plan. The height could be increased to give more capacity in the future if
85
necessary. In total, 79% of the waste to be extracted is classified as non-acid generating. The coarrangement will use a 25 meter thick layer of non-acid-generating material on the base and outer
shell to encapsulate the acid-generating potential.
Initially, a base platform will be built using mine waste from the pre-stripping stages of the
mine. This facility and the mine shafts are designed to minimize and mitigate the formation of acid
rock drainage (ARD), which is a natural process that arises from the oxidation of sulphide
minerals. This risk is present in the waste rock, tailings and walls of the Koraida pits.
Co-disposition during the rainy season will take place in the upstream area of the reservoir.
During the dry season, co-disposal will be carried out in the downstream area. The upstream
zone will also be used to place filtered tailings with a humidity greater than 17% w / w or mining
waste with high clay content. A detailed disposal plan has been prepared monthly for the first two
years and year after year during the life of the mine. If times during operations occur when mine
waste is not available in sufficient quantities for co-disposal, the tailings will be placed in the
upstream zone.
Filtered tailings and mining waste will be placed in the same location to form layers with a
maximum thickness of 2 meters. The arrangement will be made from upstream to downstream in
order to facilitate water management.
19. MARKET AND CONTRACT STUDIES
The company prepared an analysis of market prices and market conditions for lead and zinc.
This included a review of current and anticipated treatment and smelter and / or refinery refining
charges and penalties, costs associated with handling concentrates, and shipping costs to potential
customers. All information was obtained from public and subscription-based sources, quotes
86
collected from the market, and BLB experience. The information provided was used as a guide to
develop all payments and expenses associated with the sale of Koraida concentrates.
20. ENVIRONMENTAL STUDIES, SOCIAL IMPACT AND PERMITS
20.1.
ENVIRONMENTAL OBLIGATIONS
An Environmental and Social Impact Assessment (ESIA) is required to initiate mining
activities. The Ministry of Energy and Natural Resources approved this document in 2013. They
approved the ESIA based on the Feasibility Study prepared in 2011, the closure plan approved in
April 2015 and in 2016, the Ministry of Energy and Mines approved the modification of the ESIA
based on the Optimized and Final Feasibility Study prepared by 2015.
It is expected that the design and operational improvements incorporated in this Technical
Report will allow requiring only a modification to the existing approved ESIA, without the need
for additional modifications.
20.2.
ENVIRONMENTAL PERMITS
In order to conduct exploration in Peru, 3 permits are required:
1. A principal permit or affidavit. Issued by the Ministry of Energy and Mines and can be
a Category B for less than 20 drill holes, or a Category C for more than 20 drill holes.
BCM received its Category C permit on March 1, 2006.
2. A surface use permit. This is obtained from local indigenous people, as acreage is
divided into small local villages for grazing or farming. The nearest villages of Quelcaya
and Chacaconiza have granted surface permits to BCM based on signatures of most of
87
the villagers in each village, a lease agreement for it and an exploration camp has been
established with the villages.
3. A water use permit. Water rights for exploration are obtained from the local Technical
Administration Office.
21. CAPITAL AND OPERATING COSTS
For the cost parameters in the present study, we have considered those of the BCM 2019 report.
21.1.
Mining operation costs
Cost Item
Direct Cost
Indirect Cost
Technical Services (BCM)
Total
LOM Cost( $M)
443.1
123.7
27.6
594.4
LOM Average Cost($/t)
2.39
0.67
0.15
3.21
Table 21.1.1.Mining operation costs.
21.2.
Plant operating costs
Cost Item
Operating and maintenance costs
Overhead transmission line BOOT
contract and power costs
Reagents
Wear parts and consumables
Tailing’s disposal
Maintenance parts and services
Mobile equipment
Laboratory
Water pumping
Total
LOM Cost( $M)
89.2
344.5
LOM Average Cost($/t)
0.48
1.86
340.5
238.7
224.6
100.5
37.0
13.3
2.8
1,391
1.84
1.29
1.21
0.54
0.20
0.07
0.02
7.51
Table 21.2.1. Plant operating costs.
88
21.3.
Process Plant Labor
Department
Number of Personal
Mill operations
62
Total Labour
($M/y)
2555
Mill maintenance
Total
62
124
3387
5942
Table 21.3.1. Process Plant Labor
21.4.
Energy Costs
Uses
Prices
Open
Regulated
Billing
Open
Regulated
Concept
Power
Energy
Concept
Power
Energy
Principal tariff
Secondary tariff
Rural Electrification
Social inclusion energy
fund
Concept
Power
Energy
Sub Total
Principal tariff
Secondary tariff
Rural Electrification
Social inclusion energy
fund
Sub Total
Total $ M )not including IGV)
Table 21.4.1. Energy Cost
89
Units
MW
MWh
Value
588
426,043
$ / Kw - month
$ / MWh
$ / Kw - month
$ / MWh
$ / MWh
$ / MWh
6.2
28
10.79
0.65
2.55
1.95
$M
$M
$M
$M
$M
$M
$M
2.7
11.9
14.7
4.75
0.275
1.09
0.75
$M
6.86
21.5
21.5.
Reagent Costs
Reagents
Consumption
Kg / t
Sodium isoprul Xanthate
Unit Rate
Average kg / y
$ / kg
Average $ M/y
0.04
369,553
2.037
1.16
3.5
32,335,871
0.127
6.31
0.05
461,941
2.867
2.03
0.015
138,582
3.507
0.746
Sodium cyanide
0.02
184,776
2.267
0.643
Copper sulphate
0.3
2,771,646
1.917
8.15
Sodium hydroxide
0.01
92,388
0.657
0.093
Sodium sulphite
0.15
1,385,823
0.615
1.31
Zinc sulphate
0.62
5,728,069
0.817
7.18
Flocculant
0.02
184,776
3.317
0.94
Antiscalent
0.005
46,194
2.387
0.169
Lime (calcium oxide)
Methuy isobutyl
Pb promoter
Water treatment reagent
6.1
Total
34.831
Table 21.5.1. Reagent costs.
21.6.
Maintenance Cost
Item
Consumption
Kg / t
Primary crusher liners
SAG mill liners
SAG mill balls
Ball mill liners
Ball mill balls
Lead regrind mill liners
Zinc regrind mill liners
Lead regrind mill balls
Zinc regrind mill balls
Filter cloths
Total
0.008
0.050
0.238
0.030
0.690
0.005
0.005
0.010
0.010
Average kg / y
73,911
461,941
2,198,839
277,165
6,374,786
46,194
46,194
92,388
92,388
Table 21.6.1. Maintenance Cost
90
Unit Rate
$/
Average $ M/y
kg
4.600
0.340
3.600
1.663
1.346
2.959
3.600
0.998
1.128
7.191
5.600
0.259
5.600
0.259
1.137
0.105
1.137
0.105
2.033
15.9
21.7.
G&A Costs
Cost Item
Salaries and benefits
Camp operations
Camp leasing/renal
Insurance
Travel
Community development
Other
Total
LOM Cost ($M)
96.8
58.1
33.8
15.2
8.99
21.2
26.7
261
LOM Cost ($/t)
0.52
0.31
0.18
0.08
0.05
0.11
0.14
1.41
Table 21.7.1. G&A costs.
21.8.
Cost of transportation and storage of concentrate
Cost Item
Concentrate treatment charges
Silver refining charges
transportation
Total
LOM Cost ($M)
431
109
344
883
Table 21.8.1. Cost of transportation and storage of concentrate.
21.9.
Recovery and Closure cost
Item
Progressive closure (years 1-15)
Final closure (years 16-18)
Post-closure (years 19-23)
Total
Cost ($M)
Table 21.9.1. Recovery and closure cost.
91
24.91
21.97
0.96
47.83
21.10.
Opex summary
Cost Item
Mining
Process Plant
General and Administrative
TOTAL
LOM ROM (Mt)
Average LOM Operating Cost
LOM Cost ($M)
594
1,391
261
2,246
139
$ 16.20 /t
Table 21.10.1. Opex summary.
21.11.
Capex Mine
Area Description
Mining
Mining facilities
Mining phase 2
Total $
TOTAL ($ M)
30.5
0.9
36.6
68.0
Table 21.11.1. Capex mine
21.12.
Capex Processing plant
Area Description
Primary crushing
Stockpile and reclaim
Gringing and classification
Flotation and regrind
Concentrate thickening and filtration
Tailings thickening
Tailing filtration and stockpile
Reagents
Utilities, services and plant common
Total $
TOTAL ($ M)
9.3
8.2
46.9
59.6
17.3
9.1
66.3
8.8
8.8
234.3
Table 21.12.1. Capex Processing plant.
92
21.13.
Capex Infraestructure
Area Description
Bulk earthworks
Infrastructure buildings
HV substation and distribution
Control system and communications
Sewage
Tailings and waste dump
Total $
TOTAL ($ M)
22.4
8.7
9.3
6.7
0.4
10.7
58.2
Table 21.13.1. Capex Infraestructure on site
Area Description
Main Access road
Accommodation village
Total $
TOTAL ($ M)
18.4
7.1
25.5
Table 21.13.2. Capex Infraestructure off site
21.14.
Capex indirect
Area Description
Temporary construction facilities and
utilities
Construction support
Contractor commissioning assistance
Quarry and aggregate production
Total $
TOTAL ($ M)
18.5
1.5
0.6
0.3
20.9
Table 21.14.1. Capex Indirect
21.15.
Capex Others
Area Description
First fills
Spares
Total $
TOTAL ($ M)
3.2
0.6
3.8
Table 21.15.1. Capex Others
93
22. ECONOMIC ANALYSIS
For the economic analysis, we used the mine production, the capital and operating costs, and
the smelter treatment factors from the data summarized in previous sections.
The economic analysis presents the net present value (NPV), payback period (Payback) and the
internal rate of return (IRR) for the project.
94
Table 22.1. Economic Analysis for the Koraida Project
Parameter
Units
Mine Production
Ore
Pb grade
Zn grade
Ag grade
Waste
Total
Total/Average
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
000 t
%
%
oz/t
000 t
000 t
185,302
0.78
0.52
1.35
218,097
374,917
28,483
28,483
11,662
1.19
0.71
2.68
20,124
31,785
11,564
1.08
0.77
2.68
13,946
25,510
11,610
0.96
0.54
2.00
13,915
25,526
11,540
0.92
0.13
1.72
15,155
26,695
11,642
0.90
0.33
1.71
17,045
28,687
11,512
0.90
0.69
1.21
12,696
24,207
11,566
0.78
0.86
0.94
12,666
24,232
11,635
0.70
0.47
1.09
10,718
22,354
11,581
0.72
0.56
1.10
10,756
22,338
11,591
0.60
0.61
0.93
10,750
22,340
11,563
0.67
0.59
0.93
10,769
22,332
11,540
0.62
0.36
1.00
9,074
20,615
11,571
0.74
0.41
1.08
9,243
20,814
11,572
0.58
0.56
0.70
9,242
20,814
11,599
0.54
0.42
0.89
8,002
19,601
11,554
0.64
0.34
0.89
5,512
17,066
Mill production
Lead Concentrate
Pb Recovery
Ag Recovery
Pb grade in Conc.
Concentrate
Pb Fines Produced
Ag Fines Produced
Concentrate Moisture
Concentrate Delivered
Payable Pb Production
Payable Ag Production
%
%
%
000 dmt
000 dmt
000 oz
%
000 wmt
000 dmt
000 oz
74.6
61.0
51.0
2,125
1,084
152,330
7.0
2,262
1,020
144,714
74.6
61.0
51.0
203
104
19,064
7.0
216
97
18,111
74.6
61.0
51.0
183
93
18,906
7.0
195
88
17,960
74.6
61.0
51.0
163
83
14,164
7.0
174
78
13,456
74.6
61.0
51.0
155
79
12,108
7.0
165
75
11,502
74.6
61.0
51.0
153
78
12,144
7.0
163
74
11,536
74.6
61.0
51.0
152
77
8,497
7.0
161
73
8,072
74.6
61.0
51.0
132
67
6,632
7.0
140
63
6,301
74.6
61.0
51.0
119
61
7,736
7.0
127
57
7,350
74.6
61.0
51.0
122
62
7,771
7.0
130
59
7,382
74.6
61.0
51.0
102
52
6,575
7.0
108
49
6,247
74.6
61.0
51.0
113
58
6,560
7.0
121
54
6,232
74.6
61.0
51.0
105
53
7,040
7.0
111
50
6,688
74.6
61.0
51.0
125
64
7,623
7.0
133
60
7,242
74.6
61.0
51.0
98
50
4,941
7.0
105
47
4,694
74.6
61.0
51.0
92
47
6,297
7.0
98
44
5,982
74.6
61.0
51.0
108
55
6,273
7.0
115
52
5,959
Zinc Concentrate
Zn Recovery
Ag Recovery
Zn grade in Conc.
Concentrate
Zn Fines Produced
Ag Fines Produced
Concentrate Moisture
Concentrate Delivered
Payable Zn Production
Payable Ag Production
%
%
%
dmt
dmt
oz
%
000 wmt
000 dmt
000 oz
73.2
6.1
52.8
1,341
708
15,233
8.0
1,441
601
10,663
73.2
6.1
52.8
115
61
1,906
8.0
123
51
1,335
73.2
6.1
52.8
123
65
1,891
8.0
133
55
1,323
73.2
6.1
52.8
87
46
1,416
8.0
93
39
991
73.2
6.1
52.8
21
11
1,211
8.0
22
9
848
73.2
6.1
52.8
53
28
1,214
8.0
57
24
850
73.2
6.1
52.8
110
58
850
8.0
118
49
595
73.2
6.1
52.8
138
73
663
8.0
148
62
464
73.2
6.1
52.8
76
40
774
8.0
81
34
542
73.2
6.1
52.8
90
47
777
8.0
97
40
544
73.2
6.1
52.8
98
52
658
8.0
105
44
460
73.2
6.1
52.8
95
50
656
8.0
102
42
459
73.2
6.1
52.8
58
30
704
8.0
62
26
493
73.2
6.1
52.8
66
35
762
8.0
71
29
534
73.2
6.1
52.8
90
47
494
8.0
97
40
346
73.2
6.1
52.8
68
36
630
8.0
73
30
441
73.2
6.1
52.8
54
29
627
8.0
59
24
439
Net Smelter Return
Lead Concentrate
Pb Sales
000 US$
Ag Sales
000 US$
Total Sales
000 US$
Ag Refining Cost
000 US$
Refining & Smelting Cost
000 US$
Total Refining & Smelting Cost
000 US$
Concentrate Transportation US$/wmt
Total Conc. Transportation 000 US$
2,023,653
3,183,704
5,207,357
115,771
236,915
352,687
137.71
311,524
193,326
398,445
591,771
14,489
22,633
37,122
137.71
29,761
173,995
395,127
569,122
14,368
20,370
34,738
137.71
26,785
155,271
296,032
451,304
10,765
18,178
28,943
137.71
23,903
147,902
253,049
400,952
9,202
17,315
26,517
137.71
22,768
145,966
253,801
399,767
9,229
17,089
26,318
137.71
22,470
144,333
177,582
321,916
6,458
16,898
23,355
137.71
22,219
125,685
138,613
264,298
5,040
14,714
19,755
137.71
19,348
113,467
161,691
275,158
5,880
13,284
19,164
137.71
17,467
116,165
162,414
278,579
5,906
13,600
19,506
137.71
17,883
96,882
137,424
234,306
4,997
11,342
16,339
137.71
14,914
107,926
137,096
245,021
4,985
12,635
17,621
137.71
16,614
99,677
147,127
246,803
5,350
11,669
17,020
137.71
15,344
119,287
159,322
278,608
5,794
13,965
19,759
137.71
18,363
93,502
103,272
196,774
3,755
10,947
14,702
137.71
14,394
87,257
131,609
218,866
4,786
10,215
15,001
137.71
13,432
103,015
131,099
234,113
4,767
12,060
16,827
137.71
15,858
Zinc Concentrate
Zn Sales
000 US$
Ag Sales
000 US$
Total Sales
000 US$
Refining & Smelting Cost
000 US$
Total Refining & Smelting Cost
000 US$
Concentrate Transportation US$/wmt
Total Conc. Transportation 000 US$
1,522,875
234,589
1,757,464
310,120
310,120
121.28
174,739
130,377
29,359
159,736
26,550
26,550
121.28
14,960
140,218
29,115
169,333
28,554
28,554
121.28
16,089
98,722
21,813
120,535
20,104
20,104
121.28
11,328
23,623
18,646
42,269
4,811
4,811
121.28
2,711
60,495
18,701
79,197
12,319
12,319
121.28
6,941
125,076
13,085
138,161
25,471
25,471
121.28
14,352
156,634
10,214
166,848
31,897
31,897
121.28
17,973
86,113
11,914
98,027
17,536
17,536
121.28
9,881
102,125
11,967
114,092
20,797
20,797
121.28
11,718
111,332
10,126
121,458
22,672
22,672
121.28
12,775
107,424
10,102
117,526
21,876
21,876
121.28
12,326
65,419
10,841
76,260
13,322
13,322
121.28
7,506
74,704
11,739
86,444
15,213
15,213
121.28
8,572
102,043
7,609
109,652
20,780
20,780
121.28
11,709
76,711
9,698
86,408
15,621
15,621
121.28
8,802
61,858
9,660
71,518
12,597
12,597
121.28
7,098
NSR
643,114
55
632,288
55
487,561
42
386,414
33
410,915
35
374,680
33
342,173
30
309,137
27
322,768
28
289,064
25
294,110
25
269,871
23
303,146
26
244,841
21.2
252,418
21.8
253,251
21.9
21,457
30,186
107,870
21,924
181,436
21,279
20,919
106,971
21,741
170,910
21,362
20,873
107,393
21,827
171,455
21,233
22,733
106,744
21,695
172,405
21,421
25,568
107,687
21,887
176,563
21,181
19,043
106,483
21,642
168,350
21,282
18,999
106,990
21,745
169,016
21,409
16,077
107,628
21,875
166,989
21,310
16,135
107,127
21,773
166,343
21,327
16,125
107,213
21,790
166,454
21,276
16,154
106,956
21,738
166,124
21,234
13,611
106,747
21,696
163,289
21,291
13,864
107,033
21,754
163,941
21,292
13,863
107,041
21,755
163,952
21,342
12,003
107,291
21,806
162,442
21,259
8,268
106,875
21,722
158,124
461,677
461,378
316,106
214,009
234,352
206,331
173,157
142,148
156,424
122,610
127,986
106,583
139,204
80,890
89,975
95,128
000 US$
US$/t. ore
5,815,751
Operating Costs
Mine Cost Ore
Mine Cost Waste
Process Cost
G&A Cost
Total Operating Costs
000 US$
000 US$
000 US$
000 US$
000 US$
340,956
284,421
1,714,047
348,368
2,687,793
EBITDA
000 US$
3,127,958
42,725
Capital Costs
Mining
Process plant
Infraestructure
Engineering
Owner's costs
Contingency
Initial Capex
Sustaining Capex
Closure & Reclamation
000 US$
000 US$
000 US$
000 US$
000 US$
000 US$
000 US$
000 US$
000 US$
169,576
234,000
108,500
60,000
65,300
51,500
688,876
30,585
47,830
169,576
234,000
108,500
60,000
65,300
51,500
688,876
Cash Flow Before Taxes
000 US$
2,300,449
(688,876)
Taxation
Total DD&A
OSINERGMIN (0.14%)
OEFA (0.10%)
Operating Margin
Mining Royalty
Special Tax (IEM)
Worker's Participation (8%)
Taxable Income
Total Taxes (29.5%)
Net Income
000 US$
000 US$
000 US$
%
000 US$
000 US$
000 US$
000 US$
000 US$
000 US$
716,766
8,142
5,816
115,695
105,141
174,112
2,002,286
590,675
1,411,612
Cash Flow After Taxes
000 US$
1,361,087
95
169,576
95451.679
(688,876)
2,695
9,680
1,000
6,635
462
2,695
4,610
5,420
11,940
22,970
458,982
(229,894)
1
451,698
221,805
0.51
315,106
536,911
-
206,912
743,823
-
231,657
975,479
-
205,724
1,181,203
-
173,157
1,354,360
-
137,601
1,491,961
-
3,940
607
156,424
1,648,385
-
122,003
1,770,388
-
127,986
1,898,374
-
102,036
2,000,410
-
139,204
2,139,614
-
76,280
2,215,894
-
84,555
2,300,449
-
83,188
2,383,637
-
(22,970)
2,360,667
109,245
900
643
61
21,005
17,974
24,953
286,956
84,652
202,304
109,245
885
632
62
21,355
18,156
24,888
286,216
84,434
201,783
110,213
683
488
55
12,930
11,532
14,421
165,839
48,923
116,917
110,313
541
386
48
7,667
7,228
7,030
80,843
23,849
56,994
111,246
575
411
49
8,502
7,971
8,452
97,195
28,672
68,522
31,070
525
375
45
6,857
6,683
12,866
147,955
43,647
104,308
31,070
479
342
40
5,164
5,294
10,465
120,344
35,501
84,842
31,070
433
309
38
4,040
4,239
8,165
93,892
27,698
66,194
31,464
452
323
40
4,628
4,762
9,184
105,612
31,156
74,457
30,925
405
289
34
3,558
3,481
6,716
77,236
22,785
54,451
1,856
412
294
35
3,625
3,674
9,450
108,675
32,059
76,616
1,856
378
270
33
3,231
2,971
7,830
90,047
26,564
63,483
1,282
424
303
38
3,960
4,154
10,326
118,755
35,033
83,722
1,182
343
245
26
3,064
2,054
5,920
68,082
20,084
47,998
788
353
252
29
3,053
2,384
6,652
76,493
22,565
53,927
3,940
355
253
31
3,056
2,583
6,795
78,146
23,053
55,093
308,854
301,348
226,130
160,210
177,073
134,771
115,912
92,717
105,921
84,769
78,472
60,792
85,004
44,570
49,295
47,093
607
3,940
607
607
(22,970)
The net present value, the internal rate of return and the payback for the economic analysis for
the Koraida project are summarized in the next table.
Parameter
Pre-Tax
After Tax
NPV @8%
1,141 M US$
578 M US$
NPV @10%
995 M US$
480 M US$
NPV @12%
870 M US$
395 M US$
NPV @15%
713 M US$
288 M US$
IRR
46%
27%
Payback
1.7 years
2.6 years
Table 22.2. Net present value, internal rate of return and payback for the project
22.1.
SENSITIVITY ANALYSIS
The following sensitivity analysis of the following variables has been carried out: Price, Capex,
Unit cost and the recovery of Ag, Zn, Pb.
For this, the base values will be varied between -30% to + 30%.
From the calculations carried out, the variation of the IRR and the NPV will be obtained and it
is shown in the following graphs.
SENSITIVITY ANALYSIS VPN
Figure 21.1.1. NPV Sensitivity Analysis
96
SENSITIVITY ANALYSIS IRR
Figure 21.1.2. IRR Sensitivity Analysis
From the graphs, it is observed that the blue curve that indicates the price variable has a greater
slope than the others, this means that it is the most sensitive variable and causes the greatest change
in the NPV and the IRR.
The tables of the results for each variable are shown below.
Precios
30%
20%
10%
0%
-10%
-20%
-30%
VPN
1,118,663
907,272
694,660
480,147
262,961
39,855
-212,850
IRR
47%
41%
34%
27%
20%
12%
-4%
Table 21.1.1. Sensitivity of the NPV and IRR to price changes.
Capex
30%
20%
10%
0%
-10%
-20%
-30%
VPN
270,177
340,167
410,157
480,147
550,137
620,127
690,117
IRR
18%
20%
24%
27%
32%
38%
46%
Table 21.1.2. Sensitivity of the NPV and IRR to the change in Capex.
97
Ag Recovery
30%
20%
10%
0%
-10%
-20%
-30%
VPN
783,342
682,662
581,595
480,147
378,150
273,247
166,232
TIR
37%
34%
31%
27%
24%
20%
17%
Table 21.1.3. Sensitivity of the NPV and IRR to the change in the recovery of Ag.
Pb Recovery
30%
20%
10%
0%
-10%
-20%
-30%
VPN
621,254
574,276
527,270
480,147
432,958
385,655
338,265
TIR
32%
30%
29%
27%
26%
24%
23%
Table 21.1.4. Sensitivity of the NPV and IRR to the change in the recovery of Pb.
Zn Recovery
30%
20%
10%
0%
-10%
-20%
-30%
VPN
570,814
541,880
511,901
480,147
448,379
416,499
384,567
TIR
30%
29%
28%
27%
27%
26%
25%
Table 21.1.5. Sensitivity of the NPV and IRR to the change in the recovery of Zn.
98
Unit Cost
VPN
TIR
30%
242,473
20%
20%
322,721
23%
10%
401,824
25%
0%
480,147
27%
-10%
557,071
30%
-20%
632,700
31%
-30%
707,133
33%
Table 21.1.6. Sensitivity of the NPV and IRR to the change in unit cost.
This leads us to have a greater focus on the price since it significantly impacts the NPV and the
IRR, a risk analysis must always be carried out according to future market conditions.
23. RISK ANALYSIS
It is a systematic process that plans, identifies, analyzes, responds and controls the risks of a
project. This process is a study of the causes of possible threats and probable unwanted events, as
well as the damages and consequences that these may produce,
The present study was carried out with the crystal ball program to quantify the probability that
the project fails, obtaining the following results for NPV and IRR.
A normal distribution was defined for the NSR ($ / t), which is marked by prices, a triangular
distribution for unit costs (opex), and a uniform distribution for investments (capex).
Figure 23.1. Probabilities.
99
The following results were obtained for the NPV and TIR
Figure 23.2. NPV risk 8
Figure 23.3. NPV risk 10%.
100
Figure 23.4. NPV risk 12%.
NPV
Probability
NPV @8%
48.53%
NPV @10%
47.48%
NPV @12%
47.95%
In all cases, obtaining a NPV greater than or equal to those calculated is more than 47% on average.
The probability of obtaining an IRR of 57% or more is 57.14%.
101
Figure 23.5. IRR risk.
For a certainty of 90%, a NPV of 493,251 M US $ would be achieved. Which we can consider
to be an acceptable value to invest in the project.
Figure 23.6. NPV probability.ad NPV.
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24. INTERPRETION AND CONCLUSIONS
•
The estimated resource tonnage exceeds 181 million with an average Ag grade of 43 gr
/ t, Pb 0.77% and Zn 0.46%. The lithologies of importance are mixed and primary
sulphides. The estimation method used was the inverse of distance, using a range of 60
meters as a reference, based on the variograms obtained from the important lithologies.
•
• A capping was carried out for silver taking into consideration the variation of data and
loss of fines, since there are 3 outliers of Ag grade greater than 2000 gr / t that influenced
the average Ag grade in mixed sulfides.
•
The mine's production schedule develop allows the investment to be recovered in the
third year of operation.
•
Regarding the sensitivity analysis, there was a greater focus on the price because it
significantly impacts the NPV and the IRR, but despite this, a risk analysis must always
be carried out according to future market conditions.
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