SGA 2025 EIS Short Course

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IMPORTANT INFORMATION:

Advanced open-source tools for mineral predictive mapping applied to critical raw materials exploration and assessment

ABRIDGED COURSE TITLE:

Advanced open-source tools for mineral predictive mapping

ORGANIZERS:

Geological Survey of Finland (GTK), Finland
Beak Consultants GmbH, Germany
U.S. Geological Survey (USGS), USA
GISPO, Finland
JATAWARE, USA
Michigan Tech Research Institute (MTRI), USA

LEVEL OF COMPREHENSION:

All levels

COURSE FORMAT:

1 day

Location:

SGA 2025 Conference

TOPICS INTRODUCTION

Artificial intelligence has proven to be applied successfully to mineral exploration targeting in the last decade. The aim of this short course is to provide an introduction into artificial intelligence applied to mineral predictive mapping to generate drilling targets during mineral exploration and to estimate mineral resource for the assessment of critical raw materials.

COURSE DESCRIPTION:

In the first part of the short course, a short review will be provided about the concept of mineral predictive mapping. Following up, different machine learning algorithms are being presented and discussed on how they may be used for mineral predictive mapping.

The second main part of the short course is strongly focusing on the practical hands-on-training for a newly developed open source tool for mineral predictive mapping (MPM) for exploration and assessment of critical raw materials called “EIS” – Exploration Information System.

In the third and final part, new digital tool developments for critical raw materials assessment are showcased and demonstrated, being introduced through CriticalMAAS - Critical Mineral Assessments with AI Support: “Polymer” and “StatMaGIC”.

All demonstrated software tools are open-source and will be able to run on the computer of the participants.

Specific topics of the short course include:

Short introduction to mineral predictive mapping concepts,
Review of machine learning algorithms applied to mineral predictive mapping, e.g. neural networks, self-organizing maps, fuzzy logic, random forest,
Hands-on-training on open source tool “EIS” for mineral predictive mapping:
- “EIS” provides a library of tools for using mineral systems approach and mineral predictive mapping in a combined graphical user interface. It runs under Quantum GIS (QGIS) on Windows systems. Training tutorial starts from installation of EIS Toolkit and EIS Plugin on the computer leading up to the final compilation of a mineral prospectivity map using the EIS Wizard in QuantumGIS,
Demonstration of further open source tools for Human-in-the-loop learning (HITL) and mixed-initiative modeling:
- “Polymer” is a web-based application to assist a human in geologic map digitization. Annotation and correction of ground control points, projections, legend information, points, lines, and polygons can be a time-consuming process and Polymer aims to apply AI with the human input to rapidly accelerate the process of turning a map into data.
- “StatMaGIC” is a web-based interface for automated machine-learning pipelines in support of critical mineral assessments. The tool supports precise provenance preservation of all input data products as well as any applied intermediate operations to enable rigorous, reproducible workflows.
Case studies for mineral predictive mapping from Europe and Northern America
Presentation of on-going new developments in mineral exploration and prospectivity mapping.

The short course is a joint effort by the EU-funded project “EIS – Exploration Information System” , lead by the Geological Survey of Finland (GTK), and the DARPA-funded project “CriticalMAAS” , lead by U.S. Geological Survey (USGS).

TOP “TAKEAWAYS”:

This short course will provide best practices, new ideas and insights in mineral exploration, especially with regards to application of the newly developed open source for mineral predictive mapping.

At the end of the course, participants will be able to run mineral predictive mapping on their own computer using the provided and trained open-source software tools.

COURSE DELIVERY STRATEGY:

The short course will consist of a series of presentations and demonstrations. The presentations will be informal and fluid to maximize engagement of the participants. Open question and discussion throughout the presentation sessions will be an integral part of the short course. Integral part of this course, software demonstrations of and hands-on training for selected open-source software packages and tools will be provided.

HANDOUT MATERIALS:

Slides will be provided in digital format to all participants before the short course.

SOFTWARE AND HARDWARE REQUIREMENTS:

Participants are required to bring their own laptop running in Windows 10 environment with administrator rights to be able to install and run the software tools. Before the short course, the installation packages will be provided together with tutorial data for the hands-on training.

AGENDA:

PRELIMINARY TIME SCHEDULE:

07:30 – 08:00 Morning coffee & tea
08:00 – 09:30 Session 1
- Welcome and Course Layout (15 min) – Andreas Knobloch
- Overview of Mineral Predictive Mapping (MPM) Approach: Algorithms and Methods (15 min)– Andreas Knobloch
- Introduction EIS - Exploration Information System (15 min) – Andreas Knobloch
- EIS Toolkit and EIS Plugin Overview (15 min) – Ina Storch
- EIS Toolkit and EIS Plugin Installation, Hands-On Training (45 min) – Ina Storch
09:45 – 10:00 Coffee & tea break
10:00 – 11:30 Session 2
- EIS Wizard Demonstration & Hands-On Training / Tutorial, Part 1 (90 min) - Bijal Chudasama
11:30 – 12:30 Lunch break
12:30 – 14:00 Session 3
- EIS Wizard Hands-On Training / Tutorial, Part 2 (90 min) - Bijal Chudasama
14:00 – 14:15 Coffee & tea break
14:15 – 16:45 Session 4
- Introduction CriticalMAAS - Critical Mineral Assessments with AI Support (30 min) – Joshua Coyan
- Automated georeferencing and feature extraction: Polymer Demonstration (45 min) – Justin Gawrilow
- Human-in-the-loop learning (HITL) and mixed-initiative modeling: StatMagic Demonstration (45 min) – George Case
- Mineral potential mapping exploiting multi-modal fusion for CRMA in USA (30 min) – Ina Storch

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SPEAKERS:

Bijal Chudasama, Geological Survey Finland (GTK)

Geological Survey of Finland, Espoo, Finland,Senior Scientist (GTK)

Bijal is a Senior Scientist at the Geological Survey of Finland. She has an educational background in geology (M.Sc., 2014), and in geo-informatics and applications of machine learning methods to different geological research domains (Ph.D., Indian Institute of Technology Bombay, India, 2019). Her main research area is exploration targeting of mineral deposits using GIS-based mineral prospectivity analysis that involves a complex workflow of mineral systems modelling, geoscientific data processing, spatial data analysis, pattern recognition and integration of regional-to-deposit-scale geophysical, geochemical, earth observation and geological datasets using statistical and machine learning methods. She is also involved in the development of open-source tools for geoscience research and demonstrating the scientific applicability of new tools and methods in practical use case studies.

Andreas Knobloch, Beak Consultants GmbH

Andreas studied Geology at the Technical University Bergakademie Freiberg and the South Dakota School of Mines and Technology from 1998 to 2004. He joined Beak Consultants GmbH in 2005 and has been a project manager in various mineral exploration projects, among others in Kosovo, Rwanda, Uganda, Namibia, DR Congo and Nigeria. Since 2007, his research is focusing on application of artificial intelligence for mineral predictive mapping. Currently, he is leading related work packages in the Horizon Europe project "EIS – Exploration Information System." Since January 2023, he is Managing Director of Beak Consultants GmbH.

Ina Storch, Beak

Ina Storch is an expert in software development and mineral predictive mapping using artificial intelligence. She holds a Master's degree in Geophysics from Technical University Bergakademie Freiberg in Germany and received her Ph.D. at the same institution in 2022, focusing on controlled source deep seismic imaging at the North Chilean subduction zone. Since 2021, Ina has been employed as a Geophysicist and software developer at Beak Consultants GmbH in Germany. Her work involves diverse research projects since 2021 like Europe Horizon 2020 project “EIS” (“Exploration Information System”), the EIT Raw Malerials project “DroneSOM”, and CriticalMAAS project in the United States, co-funded by DARPA. In those projects she developed software and workflows for 2D and 3D mineral predictive mapping. As of 2023, she leads the team behind Beak’s in-house developed advangeo® prediction software for 2D and 3D geospatial data.

George Case, U.S. Geological Survey (USGS)

George case graduated from West Virginia University, with a BSci in Geology ( with Honors), in May 2012. He has experience in the practical applications of geology, including field mapping methods, laboratory methods, and geological software (Leapfrog Geo, ArcGIS). He recently earned my PhD in Economic Geology. His PhD project focused on understanding the ore genesis of the E1 Iron Oxide-Cu-Au (IOCG) deposit near Ernest Henry Mine, Cloncurry, northwest Queensland, Australia. His current research interests are centered on the metallogenic evolution of polydeformed terranes, tackling problems such as the origins of hydrothermal fluids and the resolution of superimposed alteration and mineralization events.

Joshua Coyan, U.S. Geological Survey (USGS)

Research Geologist at the US Geological Survey (USGS)

Dr. Joshua Coyan is a Research Geologist at the US Geological Survey. He specializes in geostatistics and mineral resource assessments. He received his master’s degree from Arizona State University in 2005 specializing in structural geology with an emphasis in hydrogeology and contaminant remediation. He went on to pursue a Ph.D. specializing in structural geology with an emphasis in ore deposits. Josh joined the USGS in 2016 and has had the opportunity to work on numerous mineral resource assessments. More recently, Dr. Coyan has started working with NASA to assess the presence of water-ice in the polar regions of the moon with plans to send a rover in the near future.

Justin Gawrilow, JATAWARE

Justin is a Technical Director and CEO of Jataware Corporation. He is a technologist and leader who has worked in the DoD and IC space for 18 years, supporting various DARPA Information Innovation Office programs across a wide range of technical and subject domains as a Principal Investigator. His work focuses on data science, applied machine learning, software engineering, and rapid prototype development. He holds a BS and MS in Computer Science from Virginia Tech. He is currently a Principal Investigator on the DARPA/USGS CriticalMAAS Artificial Intelligence Exploration project where his team is developing human-machine interfaces to more efficiently and accurately digitize and extract information from geologic maps, mining reports, mineral inventory information with the human in the loop.