Mineral Resource

Table 1: Combined Open Pit and Underground Mineral Resource Estimate, Copper Creek Project

    Grade Contained Metal
Category Tonnes (Mt) Cu Mo Ag CuEq Cu Mo Ag CuEq
    (%) (%) (g/t) (%) (Mlbs) (Mlbs) (Moz) (Mlbs)
Open Pit (OP)                  
Measured  38.9 0.68 0.010 1.8 0.72 584.2 8.7 2.2 614.6
Indicated  45.7 0.44 0.007 0.9 0.46 446.4 7.2 1.3 467.8
M&I  84.6 0.55 0.009 1.3 0.58 1,030.6 16.0 3.6 1,082.5
Inferred  29.3 0.35 0.004 0.8 0.36 224.6 2.9 0.8 233.0
Underground (UG)                  
Measured  26.1 0.50 0.012 1.5 0.54 288.7 7.0 1.3 312.7
Indicated  244.4 0.48 0.007 1.2 0.51 2,587.8 39.9 9.7 2,731.1
M&I  270.5 0.48 0.008 1.3 0.51 2,876.5 46.9 11.0 3,043.8
Inferred  45.6 0.41 0.009 0.9 0.44 410.3 9.2 1.3 440.5
Total (OP + UG)                  
Measured  65.1 0.61 0.011 1.7 0.65 872.9 15.7 3.5 927.3
Indicated  290.0 0.47 0.007 1.2 0.50 3,034.2 47.2 11.0 3,199.0
M&I  355.1 0.50 0.008 1.3 0.53 3,907.1 62.9 14.5 4,126.3
Inferred  75.0 0.38 0.007 0.8 0.41 634.9 12.0 2.0 673.5

This Mineral Resource Estimate is reported with an effective date of July 6, 2022.

  • Notes to Mineral Resource Table:
    • The Mineral Resources in this estimate were calculated using the CIM Standards on Mineral Resources and Reserves, Definitions and Guidelines (CIM, 2014) prepared by the CIM Standing Committee on Reserve Definitions and adopted by CIM Council.
    • All dollar amounts are presented in U.S. dollars.
    • Pit shell constrained resources with reasonable prospects for eventual economic extraction (“RPEEE”) are stated as contained within estimation domains above 0.23% CuEq cut-off grade. Pit shells are based on an assumed copper price of $3.80/lb, assumed molybdenum price of $13.00/lb, assumed silver price of $20.00/oz and overall slope angle of 47 degrees based on preliminary geotechnical data. Operating cost assumptions include mining cost of $2.25/tonne (“t”), processing cost of $7.95/t, General & Administrative (“G&A”) costs of $1.25/t, and Treatment Charges and Refining Charges (“TCRC”) and Freight costs of $6.50/t.
    • Underground constrained resources with RPEEE are stated as contained within estimation domains above 0.31% CuEq cut-off grade. Underground bulk mining footprints are based on an assumed copper price of $3.80/lb, assumed molybdenum price of $13.00/lb, assumed silver price of $20.00/oz, underground mining cost of $9.25/t, processing cost of $7.00/t, G&A costs of $1.25/t, and TCRC and Freight costs of $6.50/t.
    • Average bulk density assigned by domain: 2.33 g/cm3 for all near-surface breccias; 2.40 g/cm3 for the Mammoth breccia; 2.56 g/cm3 for the Keel breccia, porphyry mineralization and all other areas outside of breccias.
    • Variable metallurgical recovery by metal and domain are considered for CuEq, as follows: copper recovery of 92%, 85% and 60% within sulphide, transitional and oxide material, respectively; molybdenum recovery of 78% and 68% for sulphide and transitional material, respectively; silver recovery of 50% and 40% for sulphide and transitional material, respectively.
    • CuEq is calculated by domain based on the above variable recovery. For example, sulphide CuEq = [(Cu grade/100 *0.92 Cu recovery *2204.62 *3.8 Cu price) + (Mo grade/100 *0.78 Mo recovery *2204.62 *13 Mo price) + (Ag grade*0.50 Ag recovery*20 Ag price/31.10348)] / (0.92 Cu recovery *2204.62 *3.8)*100.
    • Mineral Resources are not Mineral Reserves and do not have demonstrated economic viability. There is no certainty that all or any part of the Mineral Resources will be converted into Mineral Reserves in the future. The estimate of Mineral Resources may be materially affected by environmental permitting, legal, title, taxation, sociopolitical, marketing or other relevant issues.
    • All quantities are rounded to the appropriate number of significant figures; consequently, sums may not add up due to rounding.

Figure 1: Reasonable prospects for eventual economic extraction (RPEEE) pit shells used to constrain the open pit MRE, and grade distribution above 0.2% CuEq grade

Figure 2: Reasonable prospects for eventual economic extraction (RPEEE) underground shapes used to constrain the underground MRE, and grade distribution above 0.2% CuEq grade

Sensitivity Analysis

The results of grade sensitivity analysis are presented below to illustrate the continuity of the grade estimates at various cut-off increments and the sensitivity of the potentially minable resource to changes in cut-off grade. The reader is cautioned that figures in the following tables should not be misconstrued as Mineral Resource or confused with the Mineral Resource Statement reported above. These figures are only presented to show the sensitivitity of the block model estimated grades and tonnnages to the selection of cut-off grade. The sensitivity analysis for Measured and Indicated blocks have been separated from Inferred blocks for reporting. Combined material type (oxide, mixed, and sulphide) sensitivity results by classification category for the open pit Mineral Resource are shown in Figure 3 and Table 2.

The grade-tonnage data presented below for open pit sensitivity reports tonnes and grade of the pit constrained mineral resource at various cut-off increments.

Figure 3: Grade-tonnage curves for Open Pit Measured & Indicated and Inferred Mineral Resources

Notes: See Notes to Mineral Resources Table (above) for the calculation of copper equivalency.

Table 2: Grade-tonnage for Open Pit Measured & Indicated Mineral Resource

Open Pit Mineral Resources
Measured and Indicated Inferred
Cut-off Grade (CuEq %) Tonnes (Mt) CuEq Grade (CuEq %) Contained Metal (CuEq Mlb) Tonnes (Mt) CuEq Grade (CuEq %) Contained Metal (CuEq Mlb)
0.10 153.0 0.39 1,315.7 60.8 0.25 332.9
0.20 94.1 0.54 1,127.6 32.9 0.34 249.8
0.23 84.6 0.58 1,082.5 29.3 0.36 233.0
0.30 63.4 0.69 958.7 14.5 0.46 146.7
0.40 44.3 0.83 813.3 6.9 0.59 89.7
0.50 32.6 0.97 697.5 3.4 0.75 55.2
0.60 24.7 1.11 603.0 2.0 0.89 38.5

The underground resource has been constrained using commercial software packages to define the potential mineable limits (i.e. footprint volumes) applicable to the resource using defined economic assumptions. Multiple footprint volumes were optimized at different costs to approximate sensitivity of the resource to changes in CuEq cut-off grade. As bulk underground mining is not selective, all material within each of the underground block cave footprints are reported. Sensitivity results by classification category for the underground resource are shown in Table 3.

Table 3: Grade-tonnage for Underground Measured & Indicated and Inferred Mineral Resource

Underground Mineral Resources
Measured and Indicated Inferred
Cut-off Grade (CuEq %) Tonnes (Mt) CuEq Grade (CuEq %) Contained Metal (CuEq Mlb) Tonnes (Mt) CuEq Grade (CuEq %) Contained Metal (CuEq Mlb)
0.20 737.8 0.37 5,981.9 618.5 0.28 3,802.2
0.31 270.5 0.51 3,043.8 45.6 0.44 440.5
0.40 148.4 0.61 1,987.7 3.6 0.50 42.3
0.50 57.0 0.78 976.4 1.4 0.71 21.0

Estimation Methodology

Sixteen individual breccias were modeled in Leapfrog Geo™ software (version 2021.2.4) by Faraday and verified as suitable estimation domains by SRK. Fourteen of these breccias contained mineralization above cut-off grade and were included in the MRE. Samples were analyzed for potential outlier capping by metal on a global basis and no top cuts were applied. Historical sample collection was in imperial units and averaged 3.05 m per sample. Raw assay samples were averaged into 6.10 m composites broken on breccia domain boundaries with residual lengths up to 3.05 m added to the previous interval. Certain historical drill holes were selectively sampled within the breccias during previous drilling campaigns and any unsampled intervals were ignored during primary compositing.

The estimation was constrained within discrete breccia domains interpreted by Faraday based on geological logging and assay grades. Grade estimation was based on parent block dimensions of 20 m in X-Y-Z and sub-blocked along the domain boundaries to 1 m in X-Y-Z. The sub-blocked resource models and block grade estimates were created using Leapfrog Edge™ software (version 2021.2.4).

The resource was estimated for copper, molybdenum and silver using inverse distance weighting cubed and considering hard boundaries at the breccia unit outer contacts. The grade estimation evaluated all parent blocks with centroids within the estimation domains and sub-blocks are coded based on the parent block centroid. Estimation outside of the defined breccia units, within the deeper porphyry-style mineralization and “halo” zones around the near-surface breccias, considered a 5 m soft boundary with the breccia units. Bulk density was scripted by general domain, based on analysis of specific gravity measurements collected by Faraday and previous project operators.

A two-pass search was used to optimize block estimation, so that well-informed blocks are interpolated using a tighter search ellipse than less informed blocks. The estimation search neighborhood was defined for individual breccia units based on the copper data population, as the key economic variable. Estimation parameters for the minor elements were identical to copper. To assess the impact of missing data, additional copper variables were estimated using null and nominal assignments for unsampled data in separate composited data sets. Un-estimated blocks outside of the search neighborhood were scripted with null values equal to one-half of the lower limit of detection.

The selection criteria used for search ellipsoid size, number of samples and other conditions are derived based on data spacing to ensure appropriate interpolation, as well as visual and statistical evaluation, during iterative trial estimation runs. Across all breccias, the estimation is informed by an average of nine composites from at least two drill holes with average sample distance of 49 m, although this varies for individual estimation domains. Outside of the breccias, the estimation is informed by an average of 11 composites at average sample distance of 134 m.

Limited historical mining has occurred at Copper Creek, mainly in the Old Reliable and Childs-Aldwinkle breccias. Block grades were depleted in the model according to available records of historical mining, which have inherent limitations.

For Mineral Resource classification a confidence variable was defined as follows:

  • Class 1 reflects the highest confidence in grade and potential measured classification. These blocks were estimated with seven or more composites in three or more drill holes. The average distance to samples is 40 m or less within breccia domains and 60 m outside.
  • Class 2 reflects potential indicated classification. Blocks are estimated with four or more composites from two or more drill holes. The average distance to samples is 80 m or less within breccia domains and 100 m outside.
  • Class 3 reflects potential inferred classification. Blocks are estimated with two or more composites from at least one drill hole. The average distance to samples is 200 m or less.
  • Class 4 delineates blocks within the modelled estimation domains that are not classified as Mineral Resources. These areas of the model may have exploration potential.

Qualified Persons

The scientific and technical information contained in this Mineral Resource Estimate pertaining to Copper Creek has been reviewed and approved by the following qualified persons under NI 43-101:

  • Geology and Mineral Resources: Berkley Tracy, PG, CPG, P.Geo, SRK Principal Consultant;
  • Geology: Dr. Thomas Bissig, P.Geo., Faraday's Vice President of Exploration; and
  • Mining: Zach Allwright, P.Eng., Faraday’s Vice President of Projects and Evaluations.

The qualified persons have verified the information disclosed herein, including the sampling, preparation, security and analytical procedures underlying such information, and are not aware of any significant risks and uncertainties that could be expected to affect the reliability or confidence in the information discussed herein.

For the complete Mineral Resource Estimate details see the Company’s news releases or the Faraday Copper Corp. SEDAR profile

Refer to the “Cautionary Statement Regarding Mineral Reserve and Resource Estimates” in our Disclosure.

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