Welcome to Country
Gail Wynne, Aboriginal Whadjuk Elder

Welcome from the Conference Chair
René Sterk, RSC

Ministerial Address
Hon Bill Johnston MLA, Minister for Mines and Petroleum, Energy and Industrial Relations

Welcome from AusIMM
Stephen Durkin, AusIMM

Keynote presentation | Fireside chat

Dr Isobel Clark

Director and Consulting Engineer
Geostokos Limited

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Overcoming implicit modelling software limitations using Python scripting - An innovative geological modelling workflow for George Fisher Mine, Queensland, Australia
Laercio Bertossi, Glencore

SBRE framework: Application to Olympic Dam deposit
Ilnur Minniakhmetov, BHP

Keynote presentation

Tim Lucks

PhD, MAusIMM(CP)
Managing Director
SRK Consulting (UK)

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Technology is a critical driving force for improving the quality of modelling, dealing with skill shortages and reducing the risk for investment and development of projects.  Looking at parallel industries, software is a driving force that has the potential to deliver rapid change. As an industry how do we continue to push change?

Commercial products are limited in their rate of change due to the need to maintain and support applications and existing customer workflows. On the other hand, coding and open-source applications are allowing skilled geologists to customise and build innovative new workflows. But where does the balance lie between using vs creating and extending software?

What is the next frontier for geology software and what impact will this have on mineral resource estimation?

Keynote presentation

Aline Cote

Industrial Lead of Zinc and Lead
Glencore

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A guide to reporting mineral resource exclusive of mineral reserves
Heath Arvidson, K2fly

Environment, Social and Governance considerations in public mineral reporting
Fiona Cessford, SRK Consulting

Resource and reserve category inflation - known rewards, hidden risks
Rayleen Hargreaves, Snowden Optiro

Risk assessment of iron mineral resources using conditional simulations
Will Patton, BHP

Keynote presentation

Professor Cam McCuaig

Head of Geoscience Excellence
BHP's Resource Centre of Excellence

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Introducing deep learning and interpreting the patterns; a mineral deposit perspective
David First, StratumAI

ML and AI for resource estimation: What could possibly go wrong? Nothing! Everything!
Matthew Nimmo, CSA Global

Geostatistics originated in the 1950s and 1960s as an evolution of classical statistics to address prediction problems in mining, forestry, and meteorology. In natural systems, such as mineral deposits, neighbouring measurement points tend to have similar values rather than random fluctuations. Geostatistics provides a more precise mathematical framework for describing this relationship compared to traditional methods, resulting in improved predictions for individual points, as well as areas and volumes.

By the late 1980s, many of the methods currently in use had been developed or were proposed in theory, although some required advances in computer technology to fully realize their potential. In the 1990s, geostatistical methods became more widely adopted in the mining industry.

Today, geostatistics is widely used in fields such as mining, environmental monitoring, agriculture, spatial statistics (GIS), and data science. Linear models are commonly employed, and advances in computer technology have made it possible to use simulations and multiple scenario options more frequently.

Looking forward, this panel discussion will explore current developments in geostatistics and how they can improve the accuracy of predictions and risk evaluations.

Welcome to Day 2
René  Sterk

Keynote presentation

Dr Jacqui Coombes

Managing Director and Chief Executive Officer
Amira Global

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The concept of estimation domains has long been a fundamental part of mineral resource estimation. The ‘domain’ is a primary grouping of the data – thus it affects every aspect of the estimate.  Use different domains and the outcome can be markedly different. 

Like many foundations, however, the meaning of ‘domain’ is not well constrained and is often context specific. This leads to misunderstanding and confusion when the same term is used in different ways in different but closely related specialities, for example, structural geology, economic geology and resource estimation. Many of the ideas behind estimation domains are a function of the estimation method (e.g., kriging) or arise from historical, manual (pre-computer) approaches to modelling. 

 With the lessons from the last 50 years, the advent of new technologies and the changing nature of our economic mineral deposits, are estimation domains still relevant or are there alternatives? 

Maximising the value of drilling program: Case study in a challenging environment
Anne-audrey Latscha, Rio Tinto

Schrödinger's kittens: Lifting the lid on resource drill hole data after mining
Jonathan Moore, Oceanagold

Drill hole spacing analysis for classification and cost optimisation: a critical review of techniques
Ian Glacken FAusIMM(CP), Snowden Optiro

Assembling the geological complexity in mineral resource classification
Bruno Afonseca MAusIMM, Seniro Geologist, Glencore

Q&A + Discussion

AusIMM Social and Environment Society Presentation
Bruce Harvey FAusIMM(CP), Committee Member, AusIMM Social and Envuronmental Society

Testing and quantifying geological uncertainty (or a gram of drill data is worth a kilogram of geological interpretation)
Catherine Barton, IGO

Modelling metal recovery by cokriging the feed and concentrate masses of metal
Amir Adeli, Superior Gold Inc.

An estimation error
Dale Sims, Dale Sims Consulting

Why I don't believe in reconciliation
Scott Dunham, Sd2 Pty Ltd

The Parker Challenge Results
Scott Dunham, Sd2 Pty Ltd