For thousands of other reports visit RSC's Mineral Intellingence Map

Rockcliff Metals Corp.

opaxe

Summary

Project:

Rail

Deposit:Rail
Location:Canada
Commodities:Copper-Gold-Zinc-Silver
Date:3/31/2020
Report Code:NI43-101
Report Type:Resource Estimation
Project Stage:Pursuing Resource Increase/Upgrade
Report details:31-3-2020: Rockcliff Metals Corp. announces a Resource Estimation report for its Rail deposit at the Rail project. Updated Mineral Resource Estimate for Project. Sudbury, Ontario--(Newsfile Corp. - March 31, 2020) - Rockcliff Metals Corporation (CSE: RCLF
Resources:(Resources, Ind.): 1.168Mt @ 2.73% Cu, 0.86% Zn, 0.8g/t Au, 8.9g/t Ag
CP/QP:[Resources]: Yungang Wu, Eugene Puritch (P&E Mining Consultants Inc.)
ABSTRACT:Sudbury, Ontario--(Newsfile Corp. - March 31, 2020) - Rockcliff Metals Corporation (CSE: RCLF) (FSE: RO0) (WKN: A2H60G) ("Rockcliff" or the "Company") is pleased to announce an updated Mineral Resource Estimate by P&E Mining Consultants Inc. ("P&E") for the Company's 100% owned Rail Deposit located in central Manitoba. The Rail Deposit is within trucking distance to Rockcliff's fully functional +1,000tpd leased mill and processing facility and is part of the Company's extensive Manitoba property portfolio located within the prolific Flin Flon-Snow Lake greenstone belt. Alistair Ross, President and CEO commented, "We are very pleased that the successful drill programs at Rail have added substantially to the Rail Indicated classification tonnage. They have also identified over 730,000 tonnes of new, high-grade Inferred tonnage. The high-grade Rail deposit remains open along strike and at depth and several additional nearby copper targets remain untested. We look forward to the completion of a Preliminary Economic Assessment on the Rail deposit before the end of Q2 2020."

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