For thousands of other reports visit RSC's Mineral Intellingence Map
Fission Uranium Corp.
Summary
| Project: | Patterson Lake South | |
|---|---|---|
| Deposit: | R780E Zone | |
| Location: | Canada | |
| Commodities: | Uranium | |
| Date: | 8/15/2018 | |
| Report Code: | NI43-101 | |
| Report Type: | Exploration/Drilling Update | |
| Project Stage: | Pursuing PEA | |
| Report details: | 15-8-2018: Fission Uranium Corp. announces an Exploration/Drilling Update report for its R780E Zone deposit at the Patterson Lake South project. Drilling results incl. 43.5m @ <300 - >65535 CPS from 113.0m. FISSION URANIUM CORP. ("Fission" or “the Company | |
| Resources: | (not mentioned in this report) | |
| CP/QP: | [Overall Report]: Ross McElroy (Internal) | |
| ABSTRACT: | FISSION URANIUM CORP. ("Fission" or “the Company") is pleased to announce the completion of its summer field program and provide results from all nine summer program holes at the R780E zone, at its’ PLS property, in Canada's Athabasca Basin region. All nine holes have hit wide, high-grade mineralization. The holes are designed to upgrade key sections of the R780E high-grade domain that is currently classified as “inferred” category and convert it to “indicated” category. The successful holes have the potential to positively impact the upcoming pre-feasibility study, expected in Q4, 2018. The holes include PLS18- 584 (line 825E), which intersected 133.0m of total composite mineralization, including 14.25m of total composite radioactivity >10,000 cps (with a peak of >65,535 cps). The summer program also included drilling 5 overburden geotechnical holes designed to collect data for geotechnical and hydrogeological characterization to support PFS-level design of the proposed process plant site, tailings management facility and stockpile areas. | |
Full Report
opaxe is a smart software platform that reconfigures and redistributes information and produces business insights to help mining professionals and investors make better decisions. We utilise technology and machine learning for data collection and human intelligence for the value-added services.
Full Report