Unlock stock picks and a broker-level newsfeed that powers Wall Street. Upgrade Now
Greenridge Exploration Pinpoints High Priority Uranium Targets with KorrAI’s Advanced Analysis at its Nut Lake Project

In This Article:

Greenridge Exploration Inc.
Greenridge Exploration Inc.

VANCOUVER, British Columbia, Dec. 16, 2024 (GLOBE NEWSWIRE) -- Greenridge Exploration Inc. (“Greenridge” or the “Company”) (CSE: GXP | OTC: GXPLF | FRA: HW3), is pleased to announce the successful implementation of KorrAI Technologies Inc.'s ("KorrAI") advanced analysis at the Company's Nut Lake Project (the "Project"). KorrAI’s hyperspectral imaging and AI-driven analysis continue to play a critical role in enhancing the efficiency and precision of future exploration efforts, leading to actionable targets and advancing Greenridge’s objectives. The Company received significant outcomes, which were achieved through this innovative program with KorrAI (the "Program"). The 2024 exploration program included seventeen (17) sample locations that showed readings greater than 30,000 cps, with six (6) sample locations registering off-scale radioactivity (Please see News Release dated September 17, 2024).

Russell Starr, Chief Executive Officer of the Company, commented, “The team continues to integrate KorrAI data with existing datasets to validate high-priority Uranium targets. The 2024 ground exploration results will be used to add an additional layer of analysis to confirm targets for future work programs.”

Key Outcomes of the Collaboration

The geospatial datasets delivered by KorrAI, including iron oxide mapping and AI/ML-driven prospectivity models, were instrumental in validating Greenridge’s exploration targets. Outcrop predictions generated by KorrAI’s Convolutional Neural Network (“CNN”) models identified clean, vegetation-free outcrops, summarized using a hotspot analysis technique to produce an intuitive heat-map (Please see Figure 2). The heat-map revealed significantly higher concentrations of predicted outcrops on the eastern half of the Property and notable clusters inland on the western half. These key findings will allow future exploration programs to allocate resources more effectively.

Detailed Results

KorrAI’s CNN models identified numerous vegetation-free outcrops, summarized in a heat-map highlighting clusters across the Property (Please see Figure 1). While the heatmap indicates the presence of outcrops, it does not assess their quality regarding lichen cover, sediments, boulders, or uranium prospectivity.

Heat-map of AI predicted outcrops across the Nut Lake Project, overlain by previously known uranium showings
Heat-map of AI predicted outcrops across the Nut Lake Project, overlain by previously known uranium showings


Figure 1 - Heat-map of AI predicted outcrops across the Nut Lake Project, overlain by previously known uranium showings

Fe-Oxide Target Prioritization

Within the predicted outcrops, Fe-oxide targets were determined using band ratio analysis (Please see red targets in Figure 2). Outcrops were statistically analysed for maximum, minimum, mean, and standard deviation values of Fe-oxide bands. Targets were prioritized as high or medium priority based on desirable characteristics such as high mean values, high maximum values, and low standard deviation. This analysis identified 564 Fe-oxide targets, with 120 deemed high-priority, correlating with hematite alteration associated with uranium mineralization models.