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Panther Minerals Receives Satellite Imagery Survey Report Over The Fireweed Prospect, Boulder Creek Uranium Property, Alaska
VANCOUVER, BC, July 29, 2024 /CNW/ - Panther Minerals Inc. ("Panther Minerals" or the "Company") (CSE: PURR) (OTC: GLIOF) (FWB: 2BC) reports that it has receive
About this update from Panther Minerals Inc.
[{"type":"text","content":" VANCOUVER, BC, July 29, 2024 /CNW/ - Panther Minerals Inc. (\"Panther Minerals\" or the \"Company\") (CSE: PURR) (OTC: GLIOF) (FWB: 2BC) reports that it has received a report and multiple images from DIRT Exploration of Cape Town, South Africa, who conducted a long-wave infrared survey (\"LWIR\") and interpretation of high-resolution hyperspectral satellite imagery over the northern portion of the Boulder Creek uranium property, Alaska. The survey and report (Pendock, N. 2024, Mineral exploration in the Death Valley Basin, Seward Peninsula, Alaska, using Sentinel-2 visible near infrared (VNIR) and shortwave infrared (SWIR) satellite imagery; the \"DIRT Report\") was focused over the Fireweed uranium prospect (the \"Fireweed Prospect\") (see Company News Release, May 30th, 2024), where in 2007 twenty-one (21) rock samples by Triex Minerals Inc. (\"Triex\") returned from 0.14% to 0.81% U308. Background on the Fireweed Prospect The Fireweed Prospect was discovered in outcrop in 2006 by Triex, during the investigation of a strong radiometric anomaly from an airborne (helicopter) survey flown at 200-metre line spacing. The Fireweed mineralization is interpreted to be substantially different from that at the Boulder Creek deposit, which is hosted within Tertiary-aged sandstone units. Based on the data reviewed to date, and as indicated in the Triex reports, the size and strength of the anomalies (airborne radiometric, ground radiometric, rock sampling, and soil geochemistry) at the Fireweed Prospect is both larger and stronger than at the Boulder Creek deposit, and uranium mineralization is interpreted to be related with brick red hematite-silica alteration zones, hosted in intrusive rocks. Satellite Survey and AI LWIR analysis of various hyperspectral satellite images, through DIRT's proprietary processing, can map or identify, through reflectance spectroscopy against a set of known standards, mineral distribution over large areas covered by vegetation and shallow cover. The ground-penetrating nature of infrared radiation in the long-wave bands allows viewing of mineral spectra to shallow depths. The anomalous Triex rock samples were plotted and used to train a multivariate statistical classifier using machine learning to identify further exploration targets. DIRT reports, \"this application of AI to mineral exploration is becoming ...