The sold out 2025 MRE Conference

In early May more than 560 delegates from across 26 countries attended the Mineral Resource Estimation (MRE) Conference hosted at Optus Stadium in Perth, WA.

Now in its third year, the conference featured a phenomenal technical program, having originally received more than 80 abstract submissions for the 16 available slots. The incredible response demonstrated the immense support for resource estimation events and the demand for practical insights to help educate and advance the resource geology community.

Spanning over two days, the program featured engaging keynote presentations, interactive sessions, expert panel discussions and peer-reviewed papers.

Attendees welcomed a high calibre of presentations from industry experts, with key themes exploring data science, input data, machine learning and AI, domaining and geological modelling, estimation, classification, RPEEE and reporting, as well as quantifying, integrating and modelling.

The cultural aspects of resource estimation, showcasing both successes and failures as opportunities for learning were also explored.

Sharpen decisions by embracing uncertainty

Insightful presentations were abundant, but a call to action for estimation professionals to reassess the way they operate rang clear.

AngloGold Ashanti chief technology officer Dr Marcelo Godoy delivered a keynote calling for serious introspection across the resource estimation profession. Titled ‘I’d rather be approximately right than precisely wrong’, Dr Godoy’s keynote challenged long-held conventions in resource modelling and mine planning, focusing specifically on the reliance on deterministic workflows that disregard geological uncertainty.

“Using estimated models as inputs to a production schedule will produce misleading results,” Dr Godoy said.

“This becomes even more significant in mining complexes, where non-linearities dominate and reconciliation is poor.”

University of Alberta School of Mining Engineering director and professor Dr Clayton Deutsch also challenged the audience to consider their approach to estimating.

“Best estimates are a myth,” Dr Deutsch said.

“Mineral deposits are fixed in time and space.

“They are not changing, but they are inherently unknown, and because they’re variable at all scales and our drilling is sparse, uncertainty is intrinsic and permanent,”

Dr Deutsch argued that resource professionals must transition from being passive estimators of ore to active managers of risk.

“We have a responsibility to do high-quality work, and that means quantifying uncertainty.”

Domain modelling and estimation strategies

Geologist Jordan McDivitt demonstrated to delegates how machine learning and structural geology can work together to model complexity in orogenic gold systems in his technical presentation.

Mr McDivitt unpacked a compelling case study from the Oberon deposit in the Tanami region of the Northern Territory, drawing on work he had undergone during his time at Newmont (ASX: NEM).

The deposit is a structurally complex pre-production asset that challenged conventional domaining with its stockwork-style veining, localised high-grade ore shoot and lack of strong lithological contacts. The challenge that Oberon presented required a full overhaul of how domains are defined and how estimation workflows can adapt to variability at scale.

“You look at it in section and think you’ve got a clean model,” Mr McDivitt said.

“But once you start digging into the data, you realise you’re chasing plunging shoots through a folded, anisotropic rock mass.

“It became clear that the traditional approach wasn’t going to cut it.”

Mr McDivitt’s team combined machine learning, standard drillhole logging, high dimensional data, numerous clustering models and secondary indicators to assess the complex deposit.

The case study demonstrated a new way forward for resource geologists, working in complex orogenic systems, where domain knowledge, structural modelling and machine learning are allies.

Geostatistics and neuroscience

Experienced resource modeller Mo Srivastava blended personal narrative with professional mastery to deliver a remarkable interdisciplinary and thought-provoking presentation. Following a personal catastrophe that sparked a professional curiosity Mr Srivastava recounted how suffering a stroke led him to apply geostatistics to his own brain.

Using his own MRI scans and an open-source 3D wireframe model of the ‘Montreal brain,’ Mr Srivastava exploring solutions to spatially associate brain damage with seizure risk in a way that could offer predictive insight — not just diagnosis.

Mr Srivastava’s method utilised resource geologist’s tools, including, indicator kriging, coordinate transformations and anisotropy modelling, to interpolate a seizure probability map across the surface of the brain.

“Each of us has ridges and grooves unique like a fingerprint,” Mr Srivastava said.

“But the broad architecture is similar enough to allow transformation and interpolation.”

This mapping workflow relied on public data, standard imaging and geostatistical techniques commonly used in mine site planning.

Mr Srivastava encouraged his peers to estimate probabilities, not just grades, and to embrace qualitative data such as colour logs, geological insight and known mineralisation.

“Prediction often works better when you take soft or secondary information into account,” he said.

“What’s important is not what you’re estimating, but the decision you’re making.”

A legacy in resource modelling

The sold-out event was closed with the announcement of the Parker Challenge winners. Designed to showcase professional expertise and innovation, the challenge presented a unique opportunity for participants to address the lack of transparency in MRE output and resource classification and contribute to building a knowledgebase that will benefit the industry for years to come.

Named after resource modelling expert Harry Parker, challenge participants were tasked with estimating the gold in a real-world deposit disguised as the ‘Enterprise’ deposit. The actual deposit is one of several sites that compile a multi-million-ounce complex in the northern Carlin Trend, located in northeastern Nevada in the US.

AusIMM chief executive Stephen Durkin says the MRE Conference and Parker Challenge showcase AusIMM’s unique ability to mobilise the global professional community to discuss solutions to complex issues.

“This is particularly important in a sector rapidly undergoing transformation with the rise of sophisticated technologies such as AI and machine learning,” he said.

The 22 challenge entries highlighted the abundant skills, perspectives and highly specialised knowledge of estimation professionals. Guy Desharnais and Lucy Potter were awarded first place for their submission that demonstrated great attention to detail and a well-thought-out approach to domaining, estimation and classification.

“We are proud of how AusIMM has been able to spotlight some of our industry’s brightest minds at this week’s conference, and help drive resource estimation best practice forward,” Mr Durkin said.

“Congratulations to Guy and Lucy for providing an outstanding entry and thank you to all participants who were part of this one-of-a-kind Challenge.”

The challenge was a fitting finale to the highly successful AusIMM conference and was sponsored by Barrick Mining Corporation, who provided the base dataset and $45,000 prize.

“This year’s Parker challenge was a unique opportunity for Barrick to assess the critical thought cadence of the industry with one of its more challenging deposits,” Barrick Mining resource geology lead Mark Roux said.

“The success of this challenge was made possible due to the strong partnership between AusIMM, Barrick and the MREC Advisory Committee.”

Following the highly successful event, the Mineral Resource Estimation Conference is anticipated to make another sold out return in 2026.