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Mineral Resources Statement Measured + Indicated and Inferred - Manantiales

Classification

Tonnes

Grade

Contained Metal

(t)

(g/t Au)

(g/t Ag)

(g/t AuEq)

(oz Au)

(oz Ag)

(oz AuEq)

Open Pit

Measured

-

-

-

-

-

-

-

Indicated

21,017

4.85

27.82

5.19

3,275

18,798

3,509

M + I

21,017

4.85

27.82

5.19

3,275

18,798

3,509

Inferred

22,858

9.05

40.13

9.55

6,647

29,492

7,016

Underground

Measured

-

-

-

-

-

-

-

Indicated

8,612

4.37

12.29

4.53

1,211

3,404

1,254

M + I

8,612

4.37

12.29

4.53

1,211

3,404

1,254

Inferred

316,904

4.33

15.51

4.52

44,108

157,984

46,082

Mineral Resources Statement Measured + Indicated and Inferred - Mercado           

Classification

Tonnes

Grade

Contained Metal

(t)

(g/t Au)

(g/t Ag)

(g/t AuEq)

(oz Au)

(oz Ag)

(oz AuEq)

Open Pit

Measured

-

-

-

-

-

-

-

Indicated

141,963

1.77

116.68

3.23

8,097

532,557

14,754

M + I

141,963

1.77

116.68

3.23

8,097

532,557

14,754

Inferred

5,978

2.21

17.99

2.43

425

3,457

468

Underground

Measured

-

-

-

-

-

-

-

Indicated

28,518

1.49

157.89

3.46

1,363

144,768

3,173

M + I

28,518

1.49

157.89

3.46

1,363

144,768

3,173

Inferred

17,177

2.28

68.94

3.14

1,257

38,072

1,733

Mineral Resources Statement Measured + Indicated and Inferred - Julieta

Classification

Tonnes

Grade

Contained Metal

(t)

(g/t Au)

(g/t Ag)

(g/t AuEq)

(oz Au)

(oz Ag)

(oz AuEq)

Open Pit

Measured

-

-

-

-

-

-

-

Indicated

169,194

5.76

27.29

6.10

31,305

148,455

33,161

M + I

169,194

5.76

27.29

6.10

31,305

148,455

33,161

Inferred

90,397

11.82

20.18

12.07

34,347

58,661

35,080

Underground

Measured

-

-

-

-

-

-

-

Indicated

91,557

4.29

22.22

4.57

12,636

65,409

13,454

M + I

91,557

4.29

22.22

4.57

12,636

65,409

13,454

Inferred

23,047

5.11

24.44

5.42

3,788

18,108

4,014

Mineral Resources Statement Measured + Indicated and Inferred - B-Vein

Classification

Tonnes

Grade

Contained Metal

(t)

(g/t Au)

(g/t Ag)

(g/t AuEq)

(oz Au)

(oz Ag)

(oz AuEq)

Open Pit

Measured

15,600

3.89

92.39

5.04

1,949

46,338

2,528

Indicated

-

-

-

-

-

-

-

M + I

15,600

3.89

92.39

5.04

1,949

46,338

2,528

Inferred

-

-

-

-

-

-

-

Underground

Measured

15,600

3.89

92.39

5.04

1,949

46,338

2,528

Indicated

209,773

2.57

260.75

5.83

17,332

1,758,606

39,314

M + I

225,373

2.66

249.10

5.77

19,281

1,804,944

41,843

Inferred

121,885

2.59

221.93

5.36

10,141

869,679

21,012

Mineral Resources Statement Measured + Indicated and Inferred - Remaining Inca (2A + 2B + 2CD)

Classification   

Tonnes

Grade

     Contained Metal

(t)

(g/t Au)

(g/t Ag)

(g/t AuEq)

(oz Au)

(oz Ag)

(oz AuEq)

Open Pit

Measured

-

-

-

-

-

-

-

Indicated

-

-

-

-

-

-

-

M + I

-

-

-

-

-

-

-

Inferred

-

-

-

-

-

-

-

Underground

Measured

-

-

-

-

-

-

-

Indicated

8,231

2.63

179.76

4.88

697

47,571

1,292

M + I

8,231

2.63

179.76

4.88

697

47,571

1,292

Inferred

64,046

3.03

108.98

4.40

6,249

224,394

9,054

Mineral Resources Statement Measured + Indicated and Inferred - Stockpile

Classification

Tonnes

Grade

Contained Metal

(t)

(g/t Au)

(g/t Ag)

(g/t AuEq)

(oz Au)

(oz Ag)

(oz AuEq)

Open Pit

Measured

-

-

-

-

-

-

-

Indicated

374,003

1.26

74.18

2.19

15,151

891,975

26,301

M + I

374,003

1.26

74.18

2.19

15,151

891,975

26,301

Inferred

-

-

-

-

-

-

-

Underground

Measured

-

-

-

-

-

-

-

Indicated

-

-

-

-

-

-

-

M + I

-

-

-

-

-

-

-

Inferred

-

-

-

-

-

-

-

Criteria

JORC Code explanation

Commentary

Database integrity

• Measures taken to ensure that data has not been corrupted by, for example, transcription or keying errors, between its initial collection and its use for Mineral Resource estimation purposes.

• Data validation procedures used.

• Initial data collection was completed in MS Excel, visual review and inspections using formulas for errors were completed before import into Vulcan. For drill hole validation to check for issues such as overlapping intervals, missing intervals and intervals beyond hole depth. The validated data was protected and passed to a server workspace to preserve the integrity of the information in charge of the IT department and controlled by the corporate database administrator.

• All lab assay data was imported into the database and paired with sample data by sample ID.

• The final database was again validated in Vulcan for overlapping intervals, intervals beyond hole depth, non-consecutive intervals, missing intervals etc. A visual inspection of drill hole locations was completed.

Site visits

• Comment on any site visits undertaken by the Competent Person and the outcome of those visits.

• If no site visits have been undertaken indicate why this is the case.

• A site visit was undertaken by the Competent Person of this Technical Report between March 12^th to 14^th, 2024. The Competent Person has been on site, and can review drill holes from each deposit, and can develop a field visit to the location of each deposit, which ones were subject and matter of study in this report also.

Geological interpretation

• Confidence in (or conversely, the uncertainty of) the geological interpretation of the mineral deposit.

• Nature of the data used and of any assumptions made.

• The effect, if any, of alternative interpretations on Mineral Resource estimation.

• The use of geology in guiding and controlling Mineral Resource estimation.

• The factors affecting continuity both of grade and geology.

• Reasonable and well developed understanding of geology and morphology of the mineralization was stablished and it was done using geological constrain to identify the geological ore bodies using textures and metal contents, further works were developed to a better understanding of the mineralization based on the hangingwall and footwall geological features that commonly presents brecciation and low grade mineralization in the Casposo Dacite unit also, felsic and andesitic dikes cut the mineralisation which is possible to follow at different levels and sections. Outcrop of the main veins and subordinated structures are well exposed in surface and in oldest open pits and in the underground. Faulting is well identified and well understood of its actions in the main ore bodies at this time. Some faults may constrain the bounds of the mineralization and offset it vertically and horizontally in places.

Dimensions

• The extent and variability of the Mineral Resource expressed as length (along strike or otherwise), plan width, and depth below surface to the upper and lower limits of the Mineral Resource.

• Resource block model ranges from surface to approximately 600 m below surface over a strike length ranging of approximately 700 m to 1000 m and from width length from 400 to 550 m. Thickness of the structures are typically between 0.5 and 5 m.

• Block Size: Parent: 2.5mx2.5mx2.5m and sub- block 0.5mx0.5mx0.5m

Following tables indicate the Origin, Rotation and offset:

Estimation and modelling techniques

• The nature and appropriateness of the estimation technique(s) applied and key assumptions, including treatment of extreme grade values, domaining, interpolation parameters and maximum distance of extrapolation from data points. If a computer assisted estimation method was chosen include a description of computer software and parameters used.

• The availability of check estimates, previous estimates and/or mine production records and whether the Mineral Resource estimate takes appropriate account of such data.

• The assumptions made regarding recovery of by-products.

• Estimation of deleterious elements or other non-grade variables of economic significance (eg sulphur for acid mine drainage characterisation).

• In the case of block model interpolation, the block size in relation to the average sample spacing and the search employed.

• Any assumptions behind modelling of selective mining units.

• Any assumptions about correlation between variables.

• Description of how geological interpretation was used to control the resource estimates.

• Discussion of basis for using or not using grade cutting or capping.

• The process of validation, the checking process used, the comparison of model data to drill hole data, and use of reconciliation data if available.

• A detailed explanation of the estimation and modelling techniques is given in Section 14 of the technical report relating to this resource estimate. It is not practical to describe all aspects of the estimation in JORC Table 1.

• Estimation was completed using block modelling and ordinary kriging, these methods are considered appropriate. Top cutting and high-grade restrictions were applied by domains, hard boundary to constrain the main geology feature was applied to prevent smearing the high grades into the low-grade area.

• Vulcan software was used for 3D estimation and geological modelling.

• A Block model with the parent cell size

• A variable search geometry was used to follow the strike and dip variations of the deposit where it follows the geometry of the vein structures. A semi-parametric variography model was applied to the deposits.

• A univariate estimate was completed.

• Geology was used to separate the different geological and stationary domains named as:

  • MQV: Massive Quartz Vein

  • BX: Hydrothermal breccia

  • VLT: Veinlet

• Additional Kriging Parameters are as follows defining 5 passes.

  • Interpolation was conducted at the parent and sub-block scale

  • Discretization 4x4x4

  • Negative weights were not set to zero

  • Maximum of 1 composite and minimum of 2 or 1 composites per drill hole to estimate

  • Maximum of 6, 4, 2 or 1 composite per search.

  • Search Radius:

                           Pass 1: 16 x 0.5 x 16 m
                             Pass 2: 32 x 0.5 x 32 m
                             Pass 3: 64 x 1.0 x 64 m
                             Pass 4: 80 x 1.0 x 80 m
                             Pass 5: 120 x 2.0 x 120 m.

• The model was validated by visual inspection of input and output data as well as statistical validation using boundary analysis and declustered mean comparison.

Moisture

• Whether the tonnages are estimated on a dry basis or with natural moisture, and the method of determination of the moisture content.

• Bulk density Is based on dry values

Cut-off parameters

• The basis of the adopted cut-off grade(s) or quality parameters applied.

• Austral will process the material exploited in their own plant facility and all the mineral deposits are in the vicinity of the plant, with a maximum distance of 5 km.

• A cutoff grade is based on both metals and the definition of income is based on gold equivalent (AuEq). Prices used were USD $2,000 per oz gold and USD $20 per oz silver. Recoveries were applied according to the deposits (see chapter 13).

• Open pit cut-off was defined as 1.5 gpt AuEq and Underground cut-off was defined as 2.0 gpt AuEq (for further details, see section 14.12).

Mining factors or assumptions

• Assumptions made regarding possible mining methods, minimum mining dimensions and internal (or, if applicable, external) mining dilution. It is always necessary as part of the process of determining reasonable prospects for eventual economic extraction to consider potential mining methods, but the assumptions made regarding mining methods and parameters when estimating Mineral Resources may not always be rigorous. Where this is the case, this should be reported with an explanation of the basis of the mining assumptions made.

• A Reasonable Prospectus to be exploited was based on open pit and underground optimizations.

• Optimizations were developed assuming USD $2,000 per oz gold and USD $20 per oz silver.

• Pit shell and Stope optimizer was used to develop the open pit and underground mining respectively.

• Further details are provided in section 14.12.

Metallurgical factors or assumptions

• The basis for assumptions or predictions regarding metallurgical amenability. It is always necessary as part of the process of determining reasonable prospects for eventual economic extraction to consider potential metallurgical methods, but the assumptions regarding metallurgical treatment processes and parameters made when reporting Mineral Resources may not always be rigorous. Where this is the case, this should be reported with an explanation of the basis of the metallurgical assumptions made.

• No Metallurgical recovery assumptions have been applied using mineral processing records from the Casposo plant between 2010 to 2019, particularly used to process Casposo open pit and underground ore.

• Several metallurgical tests were performed on each structure of this MRE, and was calculated their own particular recovery for each one:

  • Manantiales Open Pit: Au: 93%, Ag: 80%

  • Manantiales Underground: Au: 93%, Ag: 75%

  • Julieta: Au: 87%, Ag: 90%

  • Mercado: Au: 93%, Ag: 91%

  • B-Vein: Au: 89.6%, Ag: 87.4%

Environmental factors or assumptions

• Assumptions made regarding possible waste and process residue disposal options. It is always necessary as part of the process of determining reasonable prospects for eventual economic extraction to consider the potential environmental impacts of the mining and processing operation. While at this stage the determination of potential environmental impacts, particularly for a greenfield project, may not always be well advanced, the status of early consideration of these potential environmental impacts should be reported. Where these aspects have not been considered this should be reported with an explanation of the environmental assumptions made.

• No detailed Environmental Studies, Permitting and Social or Community Impact have been undertaken as part of this study. However, Casposo Mine is a mine complex that operated until 2019, all environmental care was carried out, even when the operation is in the state of care and maintenance and once operations can restart, all environmental care and compliance required by the legislation of the province of San Juan and the Republic of Argentina demand.

Bulk density

• Whether assumed or determined. If assumed, the basis for the assumptions. If determined, the method used, whether wet or dry, the frequency of the measurements, the nature, size and representativeness of the samples.

• The bulk density for bulk material must have been measured by methods that adequately account for void spaces (vugs, porosity, etc), moisture and differences between rock and alteration zones within the deposit.

• Discuss assumptions for bulk density estimates used in the evaluation process of the different materials.

• A comprehensive program of systematic bulk density measurement was implemented and developed by AGL and Bulk density, a compilation of 310 samples was provided detailed by rock type and was assigned an average value for each one, were calculated an accumulated and average values and both shows coherent values.

• For the MRE was assumed as 2.5 ton/m3 based on the information provided and defined by the mine planning department. Due to the mineralization styles mainly bearing in veins, hydrothermal breccias, stockworks and veinlets, it is recommended to have intensified measurements in the mineralized units.

• As the amount of information taken in waste units is at a sufficient level, it is recommended to continue with this program by intensifying the measurements in mineralized units rather than waste rocks. Only 7 measurements were taken on the veins, or any type of mineralised rock types and the Competent Person agreed with the definition to use a constant value of 2.5 ton/m3 for all rock types.

Classification

• The basis for the classification of the Mineral Resources into varying confidence categories.

• Whether appropriate account has been taken of all relevant factors (ie relative confidence in tonnage/grade estimations, reliability of input data, confidence in continuity of geology and metal values, quality, quantity and distribution of the data).

• Whether the result appropriately reflects the Competent Person's view of the deposit.

• Classification of Mineral Resources at Casposo uses a criterion based on the risk associated to the distribution of the information as follows:

- Confidence in the Au and Ag estimate.
  - Reasonable prospects for eventual economic extraction.

• Assessment of confidence in the estimate of grades included guidelines as outlined in JORC (2012).

- Drill data quality and quantity
  - Geological interpretation and mineralised domaining.
  - The spatial continuity of mineralisation.

• The more quantitative criteria relating to these guidelines include data density or grid pattern and the kriging search distances used.

• The overall confidence in the geological and mineralised interpretation and domaining is considered high, due in part to the existing mine opening and surface mapping undertaken by Austral Gold staff.

• The spatial continuity of mineralisation has shown itself to be consistent in all the geological and stationary domains and the data into those, are geostatistical coherent and valid.

• The risk assessment was properly addressed using several sources of information to configurate a drill grid pattern that can assure a risk level according with AGL expectations:

-  A benchmarking study was carried out to compare similar Epithermal Low Sulphidation deposits in well-known mines like El Penon, Cerro Bayo and Amancaya in Chile, Cerro Vanguardia, some structures in Cerro Moro and Cerro Negro in Argentina, and Mercedes in Mexico. Most cases are between 20 m to 35 m arrangement and the variability of the gold and silver distributions are key to defining a minor or major drill pattern.
-  Key information was the pattern that was used in the past by AGL an previous owner in Casposo Mine. As stated by the AGL geology team, reliable reconciliations were obtained when was used a 25 m drill hole pattern to declare and define a resource as indicated.

• Finally, this information, the benchmarking inputs and the expert criteria of the Competent Person were relevant to define the same drill grid pattern 25 m x 25 m to define indicated resources for Manantiales, Julieta, Mercado and B-Vein deposits.

• Formal studies of the optimal grid distance is fully recommended to develop in all of these new deposits in the Casposo Mine, the main goal is to determine the optimal distance between drill holes to ensure the desired level of confidence and error for a year of ore production which is around 400Kton/year according the AGL expectations.

Audits or reviews

• The results of any audits or reviews of Mineral Resource estimates.

• In 2016 RPA developed a comprehensive review of the mineral resource estimate covering all the areas of the mine developing a deep analysis of the entire Casposo mine which in the opinion of the Competent Person is coherent and appropriate.

Discussion of relative accuracy
/ confidence

• Where appropriate a statement of the relative accuracy and confidence level in the Mineral Resource estimate using an approach or procedure deemed appropriate by the Competent Person. For example, the application of statistical or geostatistical procedures to quantify the relative accuracy of the resource within stated confidence limits, or, if such an approach is not deemed appropriate, a qualitative discussion of the factors that could affect the relative accuracy and confidence of the estimate.

• The statement should specify whether it relates to global or local estimates, and, if local, state the relevant tonnages, which should be relevant to technical and economic evaluation. Documentation should include assumptions made and the procedures used.

• These statements of relative accuracy and confidence of the estimate should be compared with production data, where available.

• A statistical measure of uncertainty is appropriate at this time.

• The highest risk factor ascertaining the accuracy of the estimate is the interpretation of the mineralized volume and therefore the tonnage of the estimate.

• The accuracy of the drill hole collars and digital terrain model over the historic pit area, as well as the data in the historic pit area are key factors the measure this uncertainty.

• A qualitative estimate of uncertainty is of the order +/-15 global contained resource tonnes and metal. This is considered by the competent person to be well within the acceptable limits of the indicated resource.

• Higher-grade assays are also a risk factor, although it should be noted that in relative terms the uncertainty on these high assay values, are mitigated based on the use of thresholds to define the top-cuts and the spatial influence of them avoiding smearing extreme values.

• A local estimate has been completed, only tonnages which have a reasonable prospect of economic extraction have been reported as Resources as stipulated by the JORC 2012 code. All Resources are considered relevant to technical and economic evaluation. The use of differential GPS collar surveys mitigates the uncertainty on the location of input data samples and therefore the accuracy of the local estimate.