AI Case Study
Jerrit Canyon Gold identifies high prospectability areas using Goldspot Discoveries' machine learning geological model
Jerritt Canyon enlisted Goldspot Discoveries for a proof of concept study to determine which areas had the highest promise for prospecting at its site, which it did by creating a geological model based on historic and mining data.
Mining And Metals
From GlobeNewsWire: "The Jerritt Canyon project, majority owned by Sprott Mining Inc., through Jerritt Canyon Gold LLC, a private mid-tier gold producer in Northern Nevada has asked Goldspot to assess a significant amount of data in order to assist with continued exploration. Goldspot consolidated over 30 years of historical remote sensing, mining, and exploration data into one comprehensive and functional geological model. Goldspot Artificial Intelligence was then able to use this geological model to identify correlations in the data layers of existing and historically mined deposits."
The POC is moving onto its final phase where, according to GlobeNewsWire, "Jerritt has agreed to commence the first 1,000-meters of a 5,000-meter drill program as soon as logistically possible", indicating success thus far.
"Goldspot has developed a machine‐learning algorithm capable of significantly improving mineral exploration targeting. The Goldspot Algorithm is proven to mitigate investment risk and increase the efficiency and success rate of exploration in data‐rich environments." (GlobeNewsWire)
According to Goldspot's website, "Goldspot Discoveries is revolutionizing the mineral exploration business by utilizing machine learning to target on a regional and localized scale: Mineral deposits form for a reason. Machine learning links this "reason" to available geoscience data to determine the relationship. With that "relationship" we can predict likelihood of mineralization in new exploration regions".
"[H]istorical remote sensing, mining, and exploration data" (GlobeNewsWire).