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SEMACRET

SEMACRET

Sustainable Exploration of Critical Raw Materials

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    • 3D models of the Suwałki Anorthosite Massif
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Project

SEMACRET aims to promote sustainable exploration for green transition Critical Raw Materials in the EU securing the continued supply for its industries.

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Methodology and Work Packages

Summary of the methodologies and work packages employed in SEMACRET.

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Reference Sites

The sites to be studied in SEMACRET cover a diversity of geological settings and ages including several Belts across Europe.

Bayesian imaging method for towed transientelectromagnetic data using probabilistic neural networks

GNGTS 2024– Jian Chen, Gianluca Fiandaca

Three-dimensional AEM inversion considering IP effect using Octreemesh

1st ASEG DISCOVER Symposium– Jian Chen, Bo Zhang, Gianluca Fiandaca

Bayesian inversion for large-scale towed transient electromagnetic data using probabilistic neural networks

NSG 2024 30th European Meeting of Environmental and Engineering Geophysics– Jian Chen, Gianluca Fiandaca

On the carbonaceous materials and sulfides in the black shales and schists of theMatarakoski Formation: characteristics of the possible sulfur source of the KevitsaCu-Ni-(PGE) sulfide deposits

2nd GeoDays– Hector Campos, Ville Virtanen, Shenghong Yang

Full-decay spectral modelling of time-domain inducedpolarization decoupling model and forward meshes

GNGTS 2024– Arcangela Bollino, Gianluca Fiandaca

Closing the gap between galvanic and inductive induced polarization: EEMverter, a new modelling tool for Electric and Electromagnetic data

7th International IP Workshop– Gianluca Fiandaca, Bo Zhang, Jian Chen, Alessandro Signora, Francesco Dauti, Stefano Galli, Nicole Sullivan, Arcangela Bollino, Andrea Viezzoli

Inversion of galvanic time-domain IP data in terms of Debye-Warburg decomposition

7th International IP Workshop– Arcangela Bollino, Gianluca Fiandaca

SEMACRET project and UNFC resource mappingof selected CRM in Europe

UNECE Resource Management Week– Blažena Wertichová, Vojtěch Wertich, Shenghong Yang

Machine learning topic detection of social media

MineArc– Kyle Bahr

Machine learning topic detection of social media attitudes about mineral development in Europe

EU Supercluster Lapland Geoconference– Kyle Bahr, Tuija Mononen

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