Geological exploration and resource modelling
At a time when mining operations are under growing pressure to optimise resource use, reduce waste, and demonstrate environmental stewardship, access to real-time data is no longer a luxury - it’s a necessity.
The South Australian Government has sharpened its focus on mining investment and global positioning with the release of a new Trade and Investment Strategy to 2030, launched today alongside a landmark global magnetite comparison study.
Explorers operating in Australia's greenfield and undercover regions face a common challenge: how to make confident decisions when the surface reveals so little.
As critical minerals projects advance in complexity and urgency, early-stage metallurgical testing is no longer a “nice to have”—it’s a gatekeeper to technical and financial viability.
As mineral explorers delve deeper into complex regolith terrains and undercover targets, the need for geochemical techniques that offer both precision and sensitivity has never been greater.
At this year’s AusIMM Mineral Resource Estimation Conference (MREC2025) in Perth, one presentation stood out not just for its rigour, but for its challenge to long-standing assumptions in resource modelling.
In the ever-evolving field of mineral exploration, the challenge of interpreting surface geochemical data in complex terrains has long limited early-stage targeting success.
When Laércio Bertossi took to the stage at AusIMM’s 2025 Mineral Resource Estimation Conference in Perth, he didn’t unveil a new machine learning model or simulation breakthrough.
In the remote Altai Mountains of eastern Kazakhstan, a centuries-old underground mine is undergoing a transformation.
At the 2025 Mineral Resource Estimation Conference (MREC2025) in Perth, Glencore principal geologist Bruno Afonseca presented a compelling case study that could help reshape how the mining industry quantifies and manages risk.
