Three stages of GoldSpot Discoveries AI
New BC project; Brazil drill targeting; gold in Ontario core Metal Tech News Weekly Edition – May 6, 2020
Last updated 6/27/2020 at 5:57am
From taking on a new gold exploration project in British Columbia's famed Golden Triangle to hitting gold with an artificial intelligence targeted drill hole in Ontario, it has been a busy week for GoldSpot Discoveries Corp.
On May 4, GoldSpot reported promising results from machine learning mapping on Manitou Gold Inc.'s Patents property, part of the larger Goudreau gold project in northeastern Ontario. One of the holes generated from this AI work, MTU-20-14, cut 0.5 meters of 12.8 grams per metric ton gold at a depth of 50 meters.
Patents is within a deformation zone immediately east of the Island Gold mine property and past producing Edwards and Cline mines.
There has been no previous drilling at Patents, but samples collected from the outcropping Reed vein has returned an average of 6.3 g/t gold over an average width of 1.3 meters.
GoldSpot focused its efforts on better defining known and identifying new deformation zones at Patents through a combination of geophysical, structural and lithological interpretations.
GoldSpot's geophysicists traced significant lineaments on Patents using publicly sourced data and its field mappers refined the outline of known deformation zones using the work from the 1990s as a starting point.
With glacial cover and dense forested areas locally limiting direct bedrock observation, GoldSpot's data scientists and geologists produced a model of strain intensity and direction using field mapping data and non-stationary numerical interpolation techniques. This work helped to generate the Patents targets tested by Manitou.
The first four holes drilled by Manitou, including MTU-20-14, led to the discovery of a wide mineralized shear zone with laminated shear-type quartz veins near the core.
"We are highly encouraged with our initial drilling of the Patents property, which resulted in the intersection of gold grades similar to those intersected at the Island Gold and Edwards mines immediately to the west of the property," Manitou Gold President and CEO Richard Murphy. "I look forward to the continued drilling at this property as work at adjacent mine properties suggest both gold grades and widths of mineralization can increase with depth."
GoldSpot said the major structure intersected at Patents is directly within a prospective zone highlighted by its AI mapping and conforms to its proprietary structural geology interpolation mapping techniques.
Murphy said Manitou is "eager to follow up on other areas of our properties interpreted as having high prospectivity through the GoldSpot process."
New BC project
Margaux Resources Ltd. is eager to see what the GoldSpot process can do with the extensive geoscience data that has been generated from decades of exploration and production on the Cassiar Gold project in northwestern British Columbia.
On May 4, Margaux said it is collaborating with GoldSpot to identify and assess high-quality near-mine and regional gold exploration targets at Cassiar, a 60,000-hectare (148,260 acres) property that hosts both lower grade bulk tonnage and high-grade vein occurrences across a 15-kilometer (nine miles) structural corridor.
The most advanced bulk tonnage target at Cassiar, Taurus, hosts 21.8 million metric tons of inferred resource averaging 1.43 grams per metric ton (1 million ounces) gold, using a cut-off grade of 0.7 g/t gold.
Table Mountain, a high-grade vein occurrence, hosts 21,470 metric tons of historical indicated resource averaging 18.02 g/t (13,650 oz) gold and 65,750 metric tons of inferred resource averaging 24.3 g/t (56,360 oz) gold, using a cut-off grade of 3 g/t gold.
In addition, roughly 350,000 oz of gold has been produced at Cassiar from 920,000 metric tons of hardrock material averaging 11.9 g/t gold. Most of this gold was mined from 1979 to 1997.
GoldSpot will use its geoscience and machine learning expertise to clean, unify and analyze exploration data from Cassiar to identify and assess targets for advancement during the 2020 exploration program.
Brazil drill targeting
GoldSpot's machine learning capabilities are also being used to find more gold on TriStar Gold Inc.'s Castelo de Sonhos project in Brazil.
A preliminary economic assessment completed for Castelo de Sonhos in 2018 outlines a mining operation that would produce 1.1 million oz of gold over 8.1 years, or roughly 130,000 oz annually.
Tristar is now utilizing GoldSpot's data-driven AI expertise to contribute information to the coming prefeasibility study for this prospective gold mine and delineate new targets outside the resource area.
"Their application of new technology should both accelerate and streamline our exploration programs," TriStar Gold President and CEO Nick Appleyard said upon signing the agreement with GoldSpot in November. "They will contribute significantly to the planned pre-feasibility study, but it is the unlocking of the potential value in the mostly unexplored parts of the CDS plateau and surroundings that is the real core of the work."
Towards this core objective, GoldSpot's team has generated multiple near surface drill targets for TriStar and has shifted its work toward identifying deeper targets at Castelo de Sonhos.
"Our geologists are currently evaluating the first round of these shallow open-pit targets in preparation for initial drill testing as soon as possible," said Appleyard. "Work on CDS deeper targets is ongoing and we anticipate it similarly generating multiple targets by the time work is completed in June."
More information on the use of machine learning for mineral exploration can be read at Mining exploration becomes smarter with AI in the Jan. 22 edition of Metal Tech News.