Anaconda Mining Announces Significant Increase to the Mineral Resources at the Goldboro Gold Project

2021-02-22

TSXV - TSX Venture Exchange · Gold · Copper · Cobalt · Silver · Lead · Molybdenum · Arsenic · Antimony · Rare Earth Elements · Zinc · Canada

TORONTO, ON / ACCESSWIRE / February 22, 2021 /Anaconda Mining Inc. ("Anaconda" or the "Company") (TSX:ANX)(OTCQX:ANXGF) is pleased to announce an updated and significantly expanded Mineral Resource Estimate ("Mineral Resource") prepared in accordance with National Instrument 43-101 ("NI 43-101") for its 100% owned Goldboro Gold Project in Nova Scotia, Canada ("Goldboro", or the "Project")(Exhibit A). With an effective date of February 7, 2021, this updated Mineral Resource demonstrates the potential to meaningfully expand the scale of the Project, especially the surface mining potential from open pits(Exhibits A - E). The Mineral Resource will form the basis of the mine plan to be outlined in a Feasibility Study anticipated to be announced in Q4 2021.

Highlights of the Goldboro Gold Project Updated Mineral Resource

1,089,800 ounces of gold (11,880,000 tonnes at 2.86 grams per tonne ("g/t") gold) within two constrained open pits within the Measured and Indicated Mineral Resource categories, representing an increase in ounces of 1,361%; Overall, 1,946,100 ounces of gold (16,036,000 tonnes at an average grade of 3.78 g/t gold) within the Measured and Indicated Mineral Resource categories, representing a 179% increase in combined open pit and underground ounces; 798,100 ounces of gold (5,306,000 tonnes at 4.68 g/t gold) within the Inferred Mineral Resource category; a 16% increase in combined open pit and underground; Feasibility level metallurgical studies demonstrate an excellent average recovery of 96%for the open pit constrained Mineral Resource (see press release dated February 9, 2021). Continued growth potentialas the open pit shells only used Measured and Indicated Resources to create the open pit physical limits, strong opportunity exists for further conversion of Inferred Resources.

The significant increase in the size of the Mineral Resource at Goldboro represents a step-change for the economic potential of the Project, especially with over one million ounces of Measured and Indicated Resources within constrained open pits. Consequently, in addition to the ongoing Feasibility Study to be announced in Q4 2021, the Company has initiated a Preliminary Economic Assessment ("PEA") for Goldboro. The PEA will incorporate the updated Mineral Resource and feasibility work conducted to date, allowing the Company to demonstrate and discuss the economic potential of this significantly larger Project to all stakeholders.

"We are pleased to announce the significantly expanded Mineral Resource for the Goldboro Gold Project, which we believe is quickly transforming into a top-tier gold deposit. The expanded Mineral Resource is the culmination of nearly a year of effort that started with recognizing the massive potential of near-surface mineralization which is amenable to surface mining, which led to many months of updated geological modelling and incorporation of recent infill drilling campaigns, giving special attention to the broad zones of mineralization across a range of gold grades and their geological domains. With 1,089,800 ounces of Measured and Indicated Resources within constrained open pits, and metallurgical recoveries of 96% based on feasibility level studies, it is clear this Project is quickly developing into a sizeable gold deposit. We are excited to initiate a PEA for Goldboro, in parallel with the Feasibility Study, to demonstrate the economic potential of Goldboro and its ability to support the Company's growth strategy to become a 150,000 ounce per year gold producer."

~_Kevin Bullock, President and CEO, Anaconda Mining Inc._

Table 1summarizes the updated Mineral Resource and the comparative changes from the Previous Mineral Resource (as defined below).

Table 1: Mineral Resource Statement for the Goldboro Gold Project with Comparison with Previous Mineral Resource

| Category | Tonnes* | Gold Grade* | Troy Ounces* | % Change in Tonnes | % Change in Ounces | | ('000) | (g/t) | from August 2019 | from August 2019 | | | | Measured | 7,521 | 3.58 | 866,200 | + 315% | + 240% | | Indicated | 8,515 | 3.95 | 1,079,900 | + 273% | + 143% | | Measured + Indicated | 16,036 | 3.78 | 1,946,100 | + 292% | + 179% | | Inferred | 5,306 | 4.68 | 798,100 | + 76% | + 16% |

_* Combined Open Pit and Underground Mineral Resources. Open Pit Mineral Resource based on a 0.44 g/t Au cut-off grade; Underground Mineral Resource based on 2.60 g/t Au cut-off grade._

Refer to the Company's technical report entitled "Anaconda Mining Inc., Goldboro Gold Project Resource Update Phase 2, Guysborough County, NS" with an effective date of October 31, 2019 and report filing date of December 18, 2019 ("Previous Mineral Resource").

Goldboro Gold Project - Mineral Resource Estimate The Mineral Resource, presented in Table 2, was prepared by Independent Qualified Person, Glen Kuntz, P. Geo. of Nordmin Engineering Ltd. ("Nordmin") of Thunder Bay, Ontario. The Mineral Resource is based on validated results of 635 surface and underground drill holes, for a total of 113,132.9 metres of diamond drilling that was completed between 1984 and the effective date of February 7, 2021. The Mineral Resource includes 45,408.7 metres of drilling conducted by Anaconda including 17,941.7 metres of diamond drilling in 121 holes since the Previous Mineral Resource estimate of August 21, 2019. Nine diamond drill holes totaling 1,001.9 metres were removed from the database due to inconsistent sample lengths.

Table 2: Mineral Resource Statement for the Goldboro Gold Project

| Resource Type | Gold Cut-off

(g/t) | Category | Tonnes

('000) | Gold Grade

(g/t) | Troy Ounces | | Open Pit | 0.44 | Measured | 6,137 | 2.73 | 538,500 | | Indicated | 5,743 | 2.99 | 551,300 | | | | Measured + Indicated | 11,880 | 2.86 | 1,089,900 | | | | Inferred | 1,580 | 1.75 | 89,000 | | | | Underground | 2.60 | Measured | 1,384 | 7.36 | 327,700 | | Indicated | 2,772 | 5.93 | 528,600 | | | | Measured + Indicated | 4,156 | 6.41 | 856,200 | | | | Inferred | 3,726 | 5.92 | 709,100 | | | | Combined* | 0.44/2.60 | Measured | 7,521 | 3.58 | 866,200 | | Indicated | 8,515 | 3.95 | 1,079,900 | | | | Measured + Indicated | 16,036 | 3.78 | 1,946,100 | | | | Inferred | 5,306 | 4.68 | 798,100 | | |

_* Combined Open Pit and Underground Mineral Resources; The Open Pit Mineral Resource is based on a 0.44 g/t gold cut-off grade, and the Underground Mineral Resource is based on 2.60 g/t gold cut-off grade._

Mineral Resource Estimate Notes

1. Mineral Resources were prepared in accordance with NI 43-101 and the CIM Definition Standards for Mineral Resources and Mineral Reserves (2014) and the CIM Estimation of Mineral Resources and Mineral Reserves Best Practice Guidelines (2019). Mineral Resources that are not mineral reserves do not have demonstrated economic viability. This estimate of MineralResources may be materially affected by environmental, permitting, legal, title, taxation, sociopolitical, marketing, or other relevant issues. 2. Open Pit Mineral Resources are reported at a cut-off grade of 0.44 g/t gold that is based on a gold price of CAD$2,000/oz (~US$1,550/oz) and a gold processing recovery factor of 96%. 3. Underground Mineral Resource is reported at a cut-off grade of 2.60 g/t gold that is based on a gold price of CAD$2,000/oz (~US$1,550/oz) and a gold processing recovery factor of 97%. 4. Assays were variably capped on a wireframe-by-wireframe basis (Table 5). 5. Specific gravity was applied using weighted averages to each individual wireframe. 6. Mineral Resource effective date February 7, 2021. 7. All figures are rounded to reflect the relative accuracy of the estimates and totals may not add correctly. 8. Excludes unclassified mineralization located within mined out areas. 9. Reported from within a mineralization envelope accounting for mineral continuity.

Input Parameters for Mineral Resource Calculation

Open Pit For the open pit Mineral Resource (Table 2 and Exhibit A), a pit limit analysis was undertaken using the Lerchs-Grossmann ("LG") algorithm in Geovia's Whittle™ 4.7 software to determine physical limits for a pit shell constrained Mineral Resource. The parameters used to generate a pit shell are shown in Table 3.

Table 3: Physical Pit Limit Analysis Parameters

5.00$/tminedRock

0.02$/t per 10 m for depths between 100 - 200 m

0.03$/t per 10 m for depths +200 m | | Process Cost

includes assumptions for Milling, G&A, tailings, rehabilitation | 24.50$/tprocessed | | Selling Cost

Exchange Rate 1US$: 1.3C$

2,000 C$/t.oz.(rounded) | | Process Recovery | Based on Grade - Recovery Curve

(Block Grade -(0.0262*LN (Block Grade)+0.0712))/Block Grade*100-0.083

The milling cut-off grade is used to classify the material contained within the pit shell limits as open pit resource material. This break-even cut-off grade is calculated to cover the Process and Selling Costs using the parameters listed in Table 3. The open pit Mineral Resource cut-off grade is estimated to be 0.44 g/t gold. For resource cut-off calculation purposes, a mining recovery of 100% and 0% mining dilution were applied.

Underground For the underground Mineral Resource (Table 2), the parameters used to calculate the cut-off grade are shown in Table 4. The underground Mineral Resource cut-off grade is estimated to be 2.60 g/t gold. For resource cut-off calculation purposes, a mining recovery of 100% and 0% mining dilution were applied.

Table 4: Underground Mineral Resource Cut-off Grade Parameters

includes assumptions for operating waste development, surface rehandle | 96.25$/tprocessed | | Process Cost

includes assumptions for Milling, G&A, tailings, indirect costs | 44.30$/tprocessed | | Underground Support Cost

Includes assumptions for sustaining underground capital, infill diamond drilling | 22.50$/tprocessed | | Selling Cost

Exchange Rate 1US$: 1.3CA$

Geological Domaining Nordmin, through an interactive process with Anaconda, undertook a full re-examination of the mineralogical, lithological, structural, and geochemical correlations influencing the higher-grade and lower-grade gold areas within the Project. Gold mineralization at the Project occurs in both quartz veins and within the argillite that hosts the veins and within the rocks adjacent to the modelled argillites and quartz veins, including both lesser argillite with greywacke. Disseminated, euhedral arsenopyrite is pervasively associated with gold mineralization. It is commonly observed within the host rock and is usually present in mineralized quartz veins. Wall rock generally contains more pyrrhotite and arsenopyrite than directly associated quartz veins.

The Deposit consists of three domains referred to as the Boston Richardson ("BR"), East Goldbrook ("EG"), and West Goldbrook ("WG") Gold Systems (Exhibit A). The WG Gold System is separated from the BR Gold System by a north trending, near vertical fault with tens of metres of apparent offset. The EG Gold System is separated from the BR Gold System by a thick greywacke sequence or marker unit. Stratigraphic younging is from west to east with the anticlinal fold plunging shallowly to the east.

From a modelling perspective, each of the Deposit Gold Systems was separated into its own domain. Each domain was further subdomained into High-Grade Mineralized "Belts" and Low-Grade Mineralized Zones.

In 2020, Anaconda completed 121 infill drill holes (17,941.7 m) across these three domains and within approximately the top 225 m of surface. Nordmin utilized these infill drill holes and reviewed the lithological, structural, spatial mineralization controls and grade variances within the Project. The review concluded that each domain required extensive remodeling of the tightly folded higher-grade mineralized belts and the creation of a new lower-grade mineralized zone that encapsulates the mineralized belts. Previously, the significance of the lower-grade zones was not correctly understood and not included within previous resource estimates. The combination of higher-grade mineralized belts and lower-grade mineralized zones supports the estimation of grade between the higher-grade belts and therefore can be applied to support various surface and underground mining methods.

Detailed wireframing was completed based on plan-oriented sections to mirror likely mining patterns based on the geometry of the Deposit. Special attention was given to consistent smoothing of the wireframe linework to mimic the underlying geological controls on mineralization, including geological bedding, regularly dipping north and south limbs of the large-scale anticlinal fold geometry and down the plunge of the anticline. Historical workings of three underground mines, which traced the outline of the fold geometry down the fold plunge and along anticlinal limbs coincident with gold mineralization, were also used to orient wireframes. Previously, wireframes were created between 10 m to 25 m cross-sections and joined section to section resulting in irregular geometries and plunge lines not representative of the underlying geology. All wireframes are independent of each other without overlap across wireframes or across domains.

Explicit modelling was used to create the Mineral Resource, which allows for mineralization to better reflect the Deposit geology and associated geochemistry. Nordmin's opinion is that the explicit modelling approach minimizes risks compared to using implicit modelling for the Project.

Compositing Compositing of assays is a technique used to give each sample a relatively equal length to reduce the potential for bias due to uneven sample lengths; it prevents the potential loss of sample data and reduces the potential for grade bias due to the possible creation of short and potentially high-grade composites that are generally formed along the zone contacts when using a fixed length.

The raw assay data was manually "flagged" to intersecting belts and low-grade zones. Each belt and low-grade zone's flagged assays were statistically analyzed to define appropriate capping, modelling procedures, and parameters. Nordmin reviewed the previous historical estimate capping method and determined the global 80 g/t gold cap was not representative of the gold distribution for the entire Deposit. Therefore, the assays were variably capped to prevent excessive high-grade from skewing the estimation in each wireframe (Table 5). The overall difference between an 80 g/t gold cap and a variable cap is less than 2% over the entire Deposit.

Table 5: Assay Capping on a Wireframe-By-Wireframe Basis

| West Goldbrook | Boston Richardson | East Goldbrook | | | | | | | | Belt | Type | Au Cap (g/t) | Belt | Type | Au Cap (g/t) | Belt | Type | Au Cap (g/t) | | 1 | DDH | No cap | 1 | Chip | 100 | 1 | DDH | No cap | | 2 | DDH | 80 | DDH | 75 | 2 | DDH | No cap | | | 3a | DDH | No cap | 2 | Chip | 95 | 3 | DDH | 120 | | 3b | DDH | No cap | DDH | 70 | 4 | DDH | 50 | | | 4 | DDH | No cap | 3 | Chip | 95 | 4a | DDH | No cap | | 5 | DDH | No cap | DDH | No cap | 4b | DDH | 120 | | | 5a | DDH | 100 | 3a | DDH | 210 | 5 | DDH | 120 | | 5b | DDH | No cap | 4 | DDH | 40 | 5a | DDH | 80 | | 6 | DDH | No cap | 4a | DDH | No cap | 6 | DDH | 120 | | 6a | DDH | 50 | 5 | DDH | 120 | 7 | DDH | 30 | | 6b | DDH | No cap | 5a | DDH | 120 | 8 | DDH | 56 | | 7 | DDH | No cap | 6 | DDH | 120 | 9 | DDH | 120 | | 8 | DDH | 70 | 7 | DDH | 75 | 10 | DDH | No cap | | 9 | DDH | No cap | 8 | DDH | 55 | 10a | DDH | No cap | | 10 | DDH | No cap | 9 | DDH | No cap | 11 | DDH | 120 | | 11 | DDH | No cap | 10 | DDH | 60 | 11a | DDH | No cap | | Low Grade | DDH | No Cap | 11 | DDH | 100 | 12 | DDH | 120 | | | | | 12 | DDH | No cap | 12a | DDH | No cap | | | | | 13 | DDH | No cap | 13 | DDH | 50 | | | | | Low Grade | DDH | No cap | 13a | DDH | No cap | | | | | | | | 14 | DDH | 50 | | | | | | | | 14a | DDH | 120 | | | | | | | | 15 | DDH | 80 | | | | | | | | 15a | DDH | No cap | | | | | | | | 15b | DDH | No cap | | | | | | | | 16 | DDH | 120 | | | | | | | | 17 | DDH | 40 | | | | | | | | 18 | DDH | 80 | | | | | | | | 19 | DDH | 80 | | | | | | | | 20 | DDH | 80 | | | | | | | | 21 | DDH | No cap | | | | | | | | 22 | DDH | 80 | | | | | | | | 23 | DDH | 80 | | | | | | | | 24 | DDH | No cap | | | | | | | | 25 | DDH | 80 | | | | | | | | Marker | DDH | No Cap | | | | | | | | Low Grade | DDH | 5 |

The raw sample data was found to have a moderately consistent range of sample lengths. Samples captured within all zones were composited to 1.0 m regular intervals based on the observed modal distribution of sample lengths, supporting a 2.0 m x 2.0 m x 2.0 m (Northing x Easting x Elevation) block model with three sub-blocking levels (Northing = 0.25 m x Easting = 0.25 m x variable elevation). An option to use a slightly variable composite length was chosen to allow for backstitching shorter composites located along the edges of the composited interval. All composite samples were generated within each high-grade mineralized belt and lower-grade mineralized zones. There are no overlaps along boundaries. The composite samples were statistically validated to ensure no material loss of data or change to each sample population's mean grade.

Block Model Resource Estimation A series of upfront test modelling was completed to define an estimation methodology to meet the following criteria:

Representative of the deposit geology, structural models and geological controls on mineralization. Accounts for the variability of grade, orientation, and continuity of mineralization. Controls the smoothing (grade spreading) of grades and the influence of outliers. Accounts for most of the mineralization. Is robust and repeatable within the domains. Supports multiple high-grade belts and low-grade zones.

Multiple test scenarios were evaluated to determine the optimum processes and parameters to achieve the stated criteria. Each scenario incorporated nearest neighbour, inverse distance squared, inverse distance cubed, and ordinary kriging interpolation methods.

All test scenarios were evaluated based on global statistical comparisons, visual comparisons of composite samples versus block grades, and overall smoothing assessment. Based on the testing results, it was determined that the draft and final resource estimation methodology would constrain the mineralization by using hard wireframe boundaries to control the spread of high-grade and low-grade mineralization. Ordinary kriging was selected as the most representative interpolation method.

Search Strategy and Estimation Zonal controls were used to constrain the grade estimates to each wireframe. These controls prevented the samples from individual wireframes from influencing others' block grades, acting as a "hard boundary" between the wireframes.

The search orientation strategy determined to be most representative of the mineralization at the Deposit was to use a combination of an overall search ellipsoid for each domain and to allow dynamic anisotropy in the estimation process. Dynamic anisotropy is a search adjustment applied to estimation, which considers local variation of the wireframe orientation. The dynamic anisotropy approach was applied to the three Gold Systems and adjusts the search ellipsoid on a block-to-block basis controlled by the orientation for all mineralized wireframes. Nordmin's opinion is that dynamic anisotropy allows for a much more accurate estimation of grade and mineralization due to the tightly folded nature of mineralized belts and lower-grade mineralized zones.

Earlier from Magna Terra Minerals Inc.

IIROC Trading Halt - ANX 2021-02-22
Metals & Mining Investor Conference Presentations Now Available for On-Demand Viewing 2021-02-22
Global Metals & Mining Live Virtual Investor Conference February 16th, 17th, 18th 2021-02-12