African Gold Group Announces Mineral Reserve for its Kobada Gold Project

African Gold Group, Inc. (“AGG” or the “Company”) is pleased to announce an updated Mineral Reserve Estimate for its Kobada Gold Project (the “Project” or “Kobada”). The reserve estimate is an update to the reserve disclosed in the National Instrument 43-101 Standards of Disclosure for Mineral Projects (“NI 43-101”) report titled “NI 43-101 Technical Report on Kobada Gold Project in Mali” with an effective date of June 17, 2020 (the “2020 DFS”), and will be the basis for the updated feasibility study (expected to be delivered before mid-October 2021) (the “2021 DFS”).

Highlights from the reserve update include:

• Proven and Probable Mineral Reserves increased by 66% for a total of 1,252,522 ounces of gold; an increase of 497,772 ounces from the previous reserve estimate in the 2020 DFS.
• Growth highlights significant upside potential at Kobada, with the updated mineral reserve estimates expected to increase already attractive economics.
• Life of mine (“LOM”) has increased to 16 years, with the potential to deliver average production of 100,000 ounces of gold per annum for the first 10 years.
• Inclusion of sulphides within new pit shells, opens the potential for a substantial sulphide resource below the oxides.
• Optimised pit shell and mine plan to deliver optimal free cash flow.

Danny Callow, CEO of African Gold Group, commented:

“We are delighted to announce these results from our upcoming 2021 DFS at the Kobada Gold Project in Mali. With the inclusion of significant exploration drilling within our oxides and fresh rock, we have achieved a massive 66% increase in delivered gold ounces and now have an asset that can deliver an average of 100,000 ounces of gold per annum for the first 10 years, with a mine life of 16 years. Furthermore, the introduction of sulphides into the mine plan opens the possibility for a substantial sulphide resource below the oxides as the Project develops.

As well as the material increase in reserve, these results have demonstrated that there is clearly significant upside potential at Kobada in the short-term. With more than 50 km of shear zones yet to explore, as well as an additional estimate of more than 280,000 inferred ounces within the new pit shell that requires minimal drilling to convert into measured and indicated resource.

We have spoken at length about the upside potential of the Kobada asset, and the delivery of 1.25 million ounces of reserves from 3.1 million ounces of measured, indicated and inferred resources is a validation of the quality of the Kobada Gold Project. Based upon just these near-term convertible ounces, there remains the potential to further increase the measured and indicated resources and thereby increase shareholder value.”

Pit Optimisation Parameters

Open-pit optimisation was conducted on the deposit to determine the economic limits of the pit. The optimisation was conducted during the initial stage of the Project using initial cost, the gold sale prices, and pit and plant operating parameters.

The pit optimisation was conducted using GEOVIA Whittle™ software to provide guidance as to the economic pit limit of the Kobada deposit. The optimiser operates on a net present value (“NPV”) calculation for all the blocks in the model, which is the revenue from the sales of products less the operating cost. The principal aspects to consider for a NPV estimation are as follows:

• Product Tonnage = Mineralised Tonnage × Recovery × Grade of Feed/Gold Grade

• Revenue = Product Tonnage × Sales Price
• Net Value = Revenue – (Mining Cost + Processing Cost + Transportation Cost + General and Administration (“G&A”) Cost)

The optimiser software establishes the pit limits where the revenue from the ore and the waste stripping costs, balance each other. The result is that the sum of all the blocks contained within this optimal pit shell will report the optimal economic value, if the pit is smaller, some value is left in the ground, and if the pit is bigger, some value is “destroyed” due to the additional stripping.

Once this pit shell is generated, it is used as a guide to design the engineered pit incorporating berms, benches, and haulages roads. This engineered pit is used for the development of the Mine Schedule, to determine the ore quantity and grades mined for each period of the LOM.

Table 1 highlights the pit optimisation parameters used in the 2021 DFS of the Kobada Project.

Description	Unit	Value
Mining Cost (Laterite and Saprolite)	US$/t	2.50
Mining Cost (Transition and Sulphide)	US$/t	3.00
Processing Cost (Laterite and Saprolite)*	US$/t	9.41
Processing Cost (Transition)*	US$/t	12.64
Processing Cost (Sulphide)*	US$/t	15.08
Mining Recovery	%	95.0
Mining Dilution	%	5.0
Process Recovery (Laterite and Saprolite)	%	96.5
Process Recovery (Transition)	%	90.5
Process Recovery (Sulphide)	%	95.4
Gold Price	US$/oz	1 610
Refining Cost	US$/oz	7.59
Royalties	%	3.0
Overall Pit Slope	Degrees	40
*     This cost includes the G&A and tailings costs.

Table 1: Pit Optimisation Parameters

Mining Dilution and Recovery

Within all mining operations it is not possible to accurately separate the mineralised and waste material from one another due to the scale and the use of the drilling and blasting equipment.

Therefore, to account for this, a mining recovery of 95% and a mining dilution of 5% is applied.

The original sub-blocked model has been re-blocked to 5.0 m × 5.0 m × 5.0 m block with sub-block of 5.0 m x 5.0 m x 2.5 m in the X, Y and Z directions, respectively to enable the use of HxGN MinePlan™ 3D software.

This regularisation process induced an external dilution because a portion of each regularised block contained some waste material on the edge of the mineralised zones. As highlighted in Table 2 the total dilution induced by the regularisation process has been estimated at 2.3% for ore. An additional 3% dilution factor has been applied to the reserves to achieve the 5% dilution target.

Block Model	Total Ore	Gold
Tonnes	Grade	Oz
Original Sub-Blocked	67.46	0.86	1 875 779
Regularised (5 m x 5 m x 5 m) with sub-block (5m x 5m x 2.5m)	69.01	0.84	1 857 077
Difference	+2.3 %	−2.3 %	−1.0 %

Table 2: Dilution Induced by Regularisation

Final Pit Results

The optimal open-pit mining limits were established using GEOVIA Whittle™, which uses the Lerchs-Grossmann algorithm for pit optimisation. The results of the pit optimisation evaluation conducted on the deposit for varying revenue factors are summarised in Table 3 and Figure 1.

Mining optimisation was conducted over the geological model produced by Minxcon geologists. The NPV sensitivity analysis was used as the main criterion to select the optimal pit in the optimisation software, together with a range of nested pit shells generated, so that the most economically viable pit is selected.  

Notably the NPV in this optimisation summary does not consider the capital costs and is used only as a guide for shell selection and the determination of the mining shapes.

As part of the optimisation process, a stockpiling strategy has been defined to feed the process plant with the higher-grade material at the start of the operation and stockpile the lower-grade material to be processed in the later years. The goal, therefore, was to optimise the pit for the high-grade ore and process the low-grade ore contained inside the pit at the end of the LOM.

The results are highlighted in Table 3 and Figure 1.

Table 3: Pit Optimisation Evaluation

Figure 1: Project Evaluator Optimisation Results

Sensitivities

During the optimisation process, additional sensitivity runs were examined to determine the sensitivity of the resource to certain parameters. The following main parameters were changed as part of the sensitivity runs:

• Gold price ranges: from US$1,450/oz to US$1,750/oz

Table 4 shows the results of the sensitivity runs.

Description	NPV (%)	Tonnes of Ore (%)	Grade (%)	Contained Gold (%)
Selling Price
US$1,450/oz	83	96	103	100
US$1,500/oz	91	98	101	100
US$1,550/oz	94	99	101	100
US$1,610/oz (base case)	100	100	100	100
US$1,650/oz	104	101	99	100
US$1,700/oz	110	102	99	100
US$1,750/oz	115	102	98	100
Mine OPEX
Mine OPEX −10 %	103	100	100	100
Mine OPEX (base case)	100	100	100	100
Mine OPEX +10 %	97	100	100	100
Process OPEX
Process OPEX −10 %	104	103	98	101
Process OPEX (base case)	100	100	100	100
Process OPEX +10 %	96	97	102	99

Table 4: Results from Sensitivity Runs

This result shows that the Kobada resources are relatively robust to withstand changes in the optimisation parameters; therefore, even if the commodity price fluctuates or if the physical or cost parameters change, the defined engineered pit will not vary drastically.

Cut-off Grade (“COG”)

The COG is used to determine whether the material being mined will generate a profit after the mining, processing, and administrative costs have been paid. Material that is mined below the COG is sent to the waste dump. The COG has been calculated using the following formula:

COG = Gold Grade x ((Mining Cost + Process Cost + G&A)/(Sales Price x Mill Recovery))

The marginal COG has been defined as the total ore cost excluding mining costs, but including a rehandling cost divided by the net recovered gold price.

The total marginal ore, as defined above (with a grade higher than the marginal COG), approximates to 19.8 Mt at an average grade of 0.46 g/t. This material will be stored in a designated area (low-grade stockpiles), lifted, and processed at the end of the LOM.

Material	COG (g/t of Au)
Direct Feed to Mill	Marginal COG
Laterite	0.6	0.35
Saprolite	0.6	0.35
Transition	0.6	0.35
Sulphide	0.6	0.35

Table 5: Cut-Off Grade

The COG used to determine if the material will be fed directly to the mill has been calculated to maximise the gold production for the first five years of the LOM and reach an average of 100 koz/a of gold production, given the mill throughput constraint of 3 Mt/a of material.

Figure 2 shows a grade tonnage curve of the in-pit material prior to applying any dilution and mining recovery parameters. When using a 0.6 g/t COG and a throughput of 3 Mt/a of mill feed material, a target of 100 koz/a of gold production can be reached.

Figure 2: Grade Tonnage Curve

Mineral Reserve Estimate

The Mineral Reserves for the Project are estimated at 45.0 Mt of Proved and Probable Mineral Reserves at a grade of 0.87 g/t Au based on the marginal cut-off grades of 0.35 g/t. To access these reserves, 157.9 Mt of waste rock will need to be removed.  This results in a stripping ratio of 3.5 to 1 (waste/ore).

Table 6 highlights the open pit Mineral Reserves for the Project.

Category	Material	Ore (kt)	Grade (g/t)	In Situ Ounces (koz)	Recovered Ounces (koz)
Proven	Laterite	336	0.87	8.3	8.0
Saprolite	12,276	0.90	331.8	320.1
Transition	1,776	0.90	47.4	42.9
Sulphide	5,870	0.94	140.4	133.9
Subtotal	20,259	0.91	527.8	504.9
Probable	Laterite	1,288	0.85	36.1	34.8
Saprolite	16,015	0. 88	465.6	449.3
Transition	1,975	0.87	57.2	51.8
Sulphide	5,492	0.84	165.9	158.2
Subtotal	24,770	0.87	724.7	694.1
Total Proven and Probable	Laterite	1,624	0.85	44.4	42.8
Saprolite	28,291	0.88	797.3	769.4
Transition	3,752	0.87	104.6	94.6
Sulphide	11,362	0.84	306.3	292.2
Total	45,029	0.87	1,252.5	1,199.0
Notes:1. The effective date of the Mineral Reserve Estimate is 24 September 2021.2. Mineral Reserves are reported in accordance with the CIM guidelines.3. A marginal COG of 0.35 g/t Au for all material is applied.4. Mineral Reserves were estimated at a gold price of US$1,610/oz and include modifying factors related to miningcosts, dilution and recovery, process recoveries and costs, G&A costs, and royalties.5. Figures have been rounded to an appropriate level of precision for the reporting of Mineral Reserves.6. Due to rounding, some columns or rows might not add up exactly as shown.7. The Mineral Reserves are stated as dry tonnes processed at the crusher. All figures are in metric tonnes.8. The in situ and recovered ounces are in troy ounces.

Table 6: Kobada Mineral Reserve Estimate

Inferred resources have been excluded from the mineral reserve estimate. Table 7 shows the total amount of inferred resources included inside the ultimate pit limit.

Category	Material	Ore (kt)	Grade (g/t)	In Situ Ounces (koz)
Inferred	Laterite	1,109	0.97	34.6
Saprolite	5,914	0.97	184.9
Transition	544	0.93	16.3
Sulphide	1,492	0.94	45.0
Total	9,059	0.96	280.9
Notes:1. Inferred Resources are excluded from the Mineral Reserves estimate.2. A marginal COG of 0.35 g/t Au for all material is applied.3. Figures have been rounded to an appropriate level of precision.4. Due to rounding, some columns or rows might not add up exactly as shown.5. Inferred resources within the ultimate pit limit shown above are in-situ tonnes with no mining recovery and dilution applied.8. In situ ounces are in troy ounces.

Table 7: Kobada Inferred Resources Inside the Ultimate Pit Plan

These resources can be drilled by an in-fill drilling program, similar to the Phase 4 drill program completed in January 2021. It is highly probable that this will increase the size of the measured and indicated resource, and therefore conversion to reserves within the optimized pit shell. It is recommended that this drilling is prioritized prior to the start of production to increase the ounces available for processing.

Optimised Mine Plan

The mine plan has been optimised for targeted mining tonnes of 20 million tonnes per annum ore and waste, with a flow through of 3 million tonnes of feed to the mill, generating 100,000 ounces of finished gold. There is further opportunity for additional optimisation, especially following further drilling of inferred ounces within the ultimate pit shell, which could add additional gold ounces without increasing the amount of waste material.

The optimised mine plan is presented in Table 8, with the mill delivered tonnes shown in Figure 3 and total material movement shown in Figure 4.

TOTAL
Year	t	g/t	Oz	Rec Oz
Pre-Prod	0	0	0	0
11	1,377,348	1.18	52,122	50,298
2	2,996,931	1.10	106,157	102,441
3	3,006,964	1.09	105,819	102,083
4	2,906,190	1.10	102,603	98,789
5	2,929,603	1.09	102,769	98,698
6	2,963,738	1.12	106,688	102,519
7	2,960,975	1.12	106,988	101,801
8	3,029,853	0.92	89,575	84,434
9	2,995,620	1.16	111,326	106,239
10	3,058,838	1.05	103,015	98,099
11	2,957,078	0.66	62,289	59,701
12	2,997,514	0.46	44,707	43,139
13	2,918,084	0.45	42,452	40,967
14	3,030,887	0.45	44,451	41,963
15	3,040,896	0.46	45,082	42,660
16	1,858,313	0.44	26,471	25,210
Total	45,028,831	0.87	1,252,522	1,199,041

Table 8: Optimised Mining Schedule

Figure 3: Mill Schedule and Delivered Ounces