Data-Driven Mineral Exploration Using Advanced Methods

Date: 20.05.2026Location: Arktikum, Pohjoisranta 4, Rovaniemi and Teams

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Date and time: Wednesday 20 May 2026 at 13.00–16.00
Venue: Arktikum, Pohjoisranta 4, Rovaniemi, Finland (map)
You can also participate online.

In this seminar we present how data-driven methods are transforming mineral exploration. The seminar highlights the use of advanced machine learning techniques to integrate geological, geochemical, and geophysical data for more accurate and informative mineral prospectivity mapping and mining feasibility prediction.

Who should attend?

This seminar is intended for professionals in mineral exploration and resource development, including geologists, geophysicists, and geochemists.

It is also relevant for experts in exploration data, GIS, and digitalisation, as well as stakeholders from mining companies, geological surveys, research organisations, and public authorities interested in data-driven and sustainable exploration.

Register – Join onsite or online

The event is free of charge and will not be recorded. You can participate either onsite in Rovaniemi or online. For onsite participation, the registration deadline is 11 May 2026.

For additional information please contact events@gtk.fi

Register now

Program

13:00 Opening Words
Johanna Pesonen, Geological Survey of Finland GTK

General overview of the AIMEX project
Vesa Nykänen/Hafsa Munia, Geological Survey of Finland GTK

ArcSDM toolbox introduction and demonstration
Juho Laitala, Geological Survey of Finland GTK

Sokli mineral potential modeling
Mikael Vasilopoulos, Geological Survey of Finland GTK

New methdologies for mineral potential modeling
Javad Sheikh, University of Turku

Rajapalot mineral potential modeling
Mikael Vasilopoulos, Geological Survey of Finland GTK

14:25–14:55 Coffee break

Environmental data in mineral exploration
Emmi Vähä, Finnish Environment Institute (Syke)

Integration of mineral potential to restricting ESG factors
Bijal Chudasama, Geological Survey of Finland GTK

Compositional data analysis for mineralization related weak anomaly detection
Bijal Chudasama, Geological Survey of Finland GTK

Enhancing geological modeling through integrated drill-core hyperspectral and geochemical point data
Kirsi Luolavirta, Geopool Oy

Closing and discussion
Johanna Pesonen, Geological Survey of Finland GTK

16:00 Seminar ends

AIMEX – Artificial Intelligence in Mineral Exploration

This seminar introduces the methodologies and key outcomes developed within the AIMEX project.

AIMEX research partners: Geological Survey of Finland GTK, University of Turku Computer Science, Finnish Environment Institute Syke

AIMEX industry partners: GeoPool Oy, Mawson Oy, Sokli Oy, Rovjok Oy, Astrock Oy, Muon Solutions Oy, CRS Laboratories Oy, Radai Oy.

AIMEX industry collaborators: Boliden Kevitsa Mining Oy, FinnAust Mining Finland Oy, Kenex Ltd.

AIMEX project funding: Business Finland

Read more about the AIMEX project