Augustus Minerals (ASX:AUG)

AI Defines 18 New Gold Targets at Music Well

Augustus Minerals (ASX: AUG; “Augustus” or the “Company”) is pleased to announce the results from the application of Artificial Intelligence (AI) algorithms to generate and predict gold targets within the Company’s Music Well project.

SensOre consultants have applied artificial intelligence (AI), machine learning (ML) and other processing techniques using both public and proprietary datasets over the Music Well Project.

  • Cutting edge AI/ML algorithms targeting areas with minimal outcrop or under cover.
  • Integration of geological, geochemical and geophysical data sets into the AI process to define digital mineralisation fingerprints and generate AI-enhanced gold discovery predictions.
  • The AI SensOre study concluded that “Application of ML algorithms were found to model +1m oz Au potential with a high degree of predictability, and a total of 18 targets were identified within the Music Well project”:
    • Target 1 has the highest priority and is in the central north of the project with a strike length of 8km.
    • Target 1 trends NNW parallel to the general geological fabric as well as being intersected by several WNW trending cross structures.
    • Target 2 is located 4km east of the Wonder Deeps mine of Northern Star and is adjacent to a parallel WNW trending structure hosting Vault Minerals Great Western mine.
    • Target 2 is 1.4km in strike and 800m wide.
    • No historic drilling has been recorded at any of the target areas, highlighting the underexplored nature of the Music Well project.
  • Next Steps
       
    • Geological mapping and sampling over these new targets are scheduled for the next two weeks to gain further insight into the new targets.
    • Results from the January rock chip sampling program are expected shortly.

Andrew Ford, GM Exploration

“The work by SensOre has focussed our attention from areas of outcrop, toward regional targets which are obscured in many cases by thin cover and sheetwash. By applying groundbreaking technologies such as artificial intelligence has enabled the rapid prioritization of multiple targets. The definition of targets reflecting a specific geophysical and geochemical response which also focuses on key mineralised structural trends provides encouragement as to the robust nature of the targeting process”.

Augustus MineralsFigure1: Regional Tenement Packages and Gold Projects

Background:

Augustus Minerals Limited (ASX: AUG) holds the exploration licenses and applications comprising the Music Well Gold Project (“Project”) located 35km north of Leonora in the Leonora/Laverton Greenstone Belt of Western Australia.

Music Well comprises ten exploration licences covering an area of 1,345km2, making the Project one of the largest exploration packages in the region (Figures 1 and 2).

The outstanding gold endowment of the Leonora-Laverton District of >28M ounces3 is illustrated by the numerous operating gold mines including the Darlot Gold Mine (~12km to the north), the King of the Hills Mine (~20km to the west), the Leonora Gold Camp (~30km to the southwest), and the Thunderbox Gold Mine (~20km to the west).

AI Enhanced Gold Exploration

The Company commenced a gold targeting exercise with SensOre_X Pty Ltd (SensOre) in November 2024, using their Artificial Intelligence (AI) and Machine Learning (ML) technologies to allow predictive analytics to generate targets for discovery of gold systems at the Music Well project.

SensOre is an industry leading technology services provider of AI/ML applications to the minerals exploration and mining industry. SensOre’s technologies have been developed over many years and involve the application of new computer assisted statistical approaches and ML techniques across the mineral cycle to provide the next generation of exploration discoveries. SensOre aims to become the top global minerals targeting company through deployment of big data, AI/ML technologies and geoscience expertise.

The Company committed to this new technological approach to gold exploration at Music Well to reinforce the existing generative exploration undertaken by the Company and deliver new “out of the box” targets for gold mineralisation over the project area, which has minimal historic exploration and limited outcrop.

In addition, the Company has inherited a large and impressive database of geological, geochemical, and geophysical information since acquiring Music Well Gold Mines Pty Ltd in late 2024. Having a variety of good quality datasets is considered a key attribute for the application of the AI/ML technology to accelerate the discovery process. The data layers used in the AI/ML processing include results from 2,478 Ultra fine fraction soil samples, 18,042 soil samples and 155 rock chip samples, in addition to detailed aeromagnetic and gravity data.

The Music Well project is contained within an area of influence (AOI) where a “data cube” was constructed covering the four 100k scale regional map sheets containing 80m x 80m cells. This data cube contains 1,440,000 cells x 1,618 variables where the AI/ML technology was applied.

Figure 2: SensOre geophysical predictions identifying multiple intrusion types and an area of probable mafic/ultramafic rocks in the SE of the project

The application of the machine learning approach applied by SensOre to the database of geochemical, geological and geophysical information compiled over the Company’s AOI has demonstrated the highly gold prospective nature of the Music Well project. Application of the machine learning algorithms modelled the probability of gold systems within the AOI and more specifically the Music Well project. This required 107 variables for discrimination that were applied to the 80m by 80m cells within the AOI.

Click here for the full ASX Release

This article includes content from Augustus Minerals, licensed for the purpose of publishing on Investing News Australia. This article does not constitute financial product advice. It is your responsibility to perform proper due diligence before acting upon any information provided here. Please refer to our full disclaimer here.



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