Toronto, Ontario–(Newsfile Corp. – May 4, 2020) – GoldSpot Discoveries Corp. (TSXV: SPOT) (“GoldSpot” or the “Company“) is pleased to announce that Manitou Gold Inc.’s (“Manitou“) successful drill target intercepts in drill hole MTU-20-14 located on the Patents Property at the Goudreau Project in northeastern Ontario provide early confirmation of GoldSpot’s machine learning (artificial intelligence) – prospectivity mapping in that area. While these results are from one hole only and there can be no assurances that additional drilling will continue to yield such positive results, management of GoldSpot is encouraged by the solid data received by Manitou to date. The major structure intersected at the Patents Property is directly within GoldSpot’s previously highlighted prospective zone and conforms to the Company’s proprietary structural geology interpolation mapping techniques (see the prospectivity and structural interpolation maps, below). GoldSpot’s prospectivity assessment work results from the integration of new field data collected by Company geologists in the summer of 2019, integrated with publicly available geophysical data and filed assessment reports.
“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,” stated Richard Murphy, President and CEO of Manitou. “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. We are also eager to follow up on other areas of our properties interpreted as having high prospectivity through the GoldSpot process.”
2019 field work provided essential insights on the structural setting and overall controls on mineralization in the area and resulted in a useable dataset for the machine learning exercise. Field work was also essential to perform quality control on historical data to better integrate it in the prospectivity analysis.
Insights gained through field work allowed the selection of the ideal input variables (features) and the optimal approach to engineering them for the prospectivity analysis.
Location of the successful Patents drill hole (red star) with respect to GoldSpot’s prospectivity mapping (hexes), known showings (yellow diamonds) and present and past producing gold mines (black crossed hammers).
Success of a machine learning system in assessing gold prospectivity relies on the quality and relevance of its input variables, which in turn is directly related to the design quality of the field data collection program and a comprehensive geological understanding of the area. GoldSpot employed several techniques to develop a successful machine learning – assisted prospectivity map, which include:
- detailed structural and lithological mapping;
- detailed interpretation of geophysical surveys for prospective lineaments;
- feature engineering of mapping and geophysical data; and
- rigorous performance assessment of the algorithms used.
Below is a brief overview of a selection of products generated by GoldSpot which were used in the targeting process on the Patents Property.
Narrowing down the search area
Refining outlines of deformation zones
Study of known deposits and mineral occurrences in the area revealed the importance of local to regional scale deformation zones in the development of fertile vein systems. GoldSpot focused its efforts on better defining known and identifying new deformation zones within the Patents Property. Historical structural (Heather and Arias, 1992) and 1:50k scale geological mapping (Bruyere and Riggs townships; Walker, 2018 and Srivastava and Bennett, 1978) from the Ontario Geological Survey (“OGS“) have very coarse resolution within Manitou’s Goudreau Project and the Patents Property due to limited road access, water bodies and extensive boreal forest cover.
To better define deformation zones on the Patents Property, GoldSpot combined geophysical, structural and lithological interpretations. GoldSpot’s expert geophysicists traced significant lineaments on the Patents Property using publicly sourced data. Simultaneously, GoldSpot’s field mappers refined the outline of known deformation zones using the work from Heather and Arias (1992) as a starting point. Glacial cover and dense forested areas locally limited direct bedrock observation. The need to see through the cover spurred GoldSpot’s data scientists and geologists to collaborate and produce a model of strain intensity and direction using field mapping data and non-stationary numerical interpolation techniques (illustrated in the map, below). The final outline of deformation zones comes from the combination of both geological and geophysical interpretations.
The updated outline of the well-endowed Goudreau Lochalsh deformation zone is shown below. This deformation zone dips to the south towards Manitou’s property, with a series of zone-parallel prospective lineaments north and east of the Rockstar mineral occurrence. The Patents Property and the significant 2020 drilling lies within the newly refined Goudreau Lochalsh deformation zone (see the map below).
Modelled strain direction over the Goudreau Project and the Patents Property (stream plot colour-coded by fabric orientation) overlaid on the deformation zone outlines (light red polygons), prospective zones (hexes) and known showings (yellow diamonds). The red star highlights the location of successful drilling on the Patents Property.
Refining the area’s lithological map
Lithological contacts juxtaposing rocks with contrasting rheology is an important factor for vein development, with gold-bearing examples within the Goudreau-Lochalsh deformation zone (Island Gold) and Manitou’s Goudreau property (Tracanelli showing). To better inform the machine learning system and further refine our search area within deformation zones, the existing 1:50k geological map was refined to a 1:35k scale, with a focus on accurate contact mapping (see below). Such contacts were identified in the 2019 mapping at the Patents Property (see below) and were an important feature in the machine learning prospectivity analysis.
OGS provincial scale bedrock map on the left and GoldSpot’s updated lithological map (on the right). Red star represents the location of the Patent Property’s claim block.
Integrating and interrogating datasets for gold prospectivity
Once all of the maps and models were generated, a series of variables were extracted and used in the integrated prospectivity analysis. This analysis trains machine learning algorithms to predict the presence of gold using all variables (features). Once the model performs to a satisfactory level, results produced include: 1) a series of zones with high probability of containing gold, illustrated in the map above as a series of hexagons; and 2) a ranking of feature importance for each input feature.
As demonstrated, prospectivity analysis of the Goudreau Lochalsh area was a multi-step process which involved significant field work and collaboration between the different geoscience specialists. GoldSpot is pleased to observe that one of its highest priority targets at the Patents Property may prove to be a significant blind zone of mineralized quartz vein (see below) and is looking forward to see the results from its other prospective areas on the Patents Property and surrounding Goudreau Project.
Quartz-carbonate±pyrrhotite veins in strongly altered mafic volcanic rocks from initial drilling at the Patents Property described in this press release.
The technical information in this press release has been prepared in accordance with the Canadian regulatory requirements set out in National Instrument 43-101 (Standards of Disclosure for Mineral Projects) and reviewed and approved by Lindsay Hall, professional geoscientist (APGO # 0891), a Qualified Person as defined in NI 43-101.
According to Manitou Gold and their press release, the third hole, MTU-20-14, intersected the vein zone at a vertical depth of approximately 50 m below surface and returned 12.8 g/t Au over 0.5 m within a wider interval of veining and intense alteration.
The four drill holes at the Patents have been drilled on two sections with a lateral spacing of 550 m. All four holes intersected a wide shear zone with intersections up to 50 m in width, with such intersections displaying a similar style of alteration and hosting mineralization consisting of pyrrhotite, pyrite and minor chalcopyrite, along with quartz veining. Results reported herein represent partial results for three of the holes and additional assays will be released as they become available.
MTU-20-14 was drilled at an angle of -45°. The veining was intersected between 71.7 and 72.2 m down hole at an angle of 65 to 70o to core axis. The hole was collared at UTM (NAD 83; Zone 16) 699705 E, 5355680 N.
Core sampling was completed on select intervals ranging from 0.1 to 1.0 m. Samples were cut in half with a core saw and half-core samples were individually bagged, sealed and labelled; the other half core was placed back in the core box and is retained on site for verification and reference purposes. Standards and blanks were routinely inserted into the sample stream. At least 20 per cent of the samples submitted to the laboratory comprise samples used for quality control.
Samples were delivered to Activation Laboratories in Thunder Bay, Ont. At the laboratory, samples were crushed up to 80 per cent passing two millimetres, riffle split (250 g) and then pulverized to 95 per cent passing 105 microns. Gold was analyzed by fire assay with an AA finish, using the 50 g subsample. Overlimit analysis was performed on all primary assay results over three g/t gold. All overlimits were tested by fire assay with gravimetric finish using a 50 g subsample. Actlabs is a certified and ISO 17025 accredited laboratory. Actlabs routinely inserts certified reference materials for at least 20 per cent quality control in each batch.
About GoldSpot Discoveries
GoldSpot Discoveries Corp. (TSXV: SPOT) is a technology and investment company that leverages machine learning to reduce capital risk while working to increase efficiency and success rates in resource exploration and investment. GoldSpot Discoveries combines proprietary technology with traditional domain expertise, offering a front-to-back service solution to its partners, and in some cases, capital to kickstart exploration programs. GoldSpot’s solutions target big data problems, making full use of historically unutilized data to better comprehend resource property potential.
For further information please contact:
President, CEO and Director
GoldSpot Discoveries Corp.