Periodic Reporting for period 1 - SEMACRET (Sustainable exploration for orthomagmatic (critical) raw materials in the EU: Charting the road to the green energy transition)
Reporting period: 2022-06-01 to 2023-11-30
The targeted raw materials include Ni, Cu, PGM, Co, V, Ti, Cr hosted in orthomagmatic ore deposits. Six of these are listed as either critical raw materials, or strategic raw materials. PGM are essential components in fuel cells in hydrogen based EV, Cobalt (Co) and nickel (Ni) are important battery components, and vanadium (V) is used in electricity storage facilities. The use of copper (Cu) in electric vehicles is 4 times higher than in gasoline-powered vehicles. These metals are thus fundamental for the transition to the green economy, yet their future demand will exceed the current supply by more than 100% within a decade. Currently, there is only one orthomagmatic sulfide deposit (Kevitsa Ni-Cu-PGE-Co, Finland) and one orthomagmatic oxide deposit (Kemi Cr, Finland) in production. However, there is potential in different Eu countries. The main focus of this project will be technology development and validated at small scales. The main output would be more efficient, and environmentally and societally friendly exploration methods and technologies, and the long term impact would be increasing the domestic supply of (critical) raw materials in the EU, and a diversified supply from third countries, and thus supporting green energy transition. Currently, major new data acquisition has been completed, and now in data modelling and interpretation stage.
SEMACRET intends to apply the mineral system approach to guide exploration for orthomagmatic CRMs, generate refined ore deposit models, improve socially and environmentally friendly exploration methods, promote social awareness on the needs of responsible exploration raw materials and responsible sourcing of raw materials. Further, SEMACRET aims to map the exploration and production potential of CRM in the EU and key CRM supplier countries. Our research will be conducted at five reference sites in Finland, Portugal, Poland and the Czech Republic representing different geological, social and environmental conditions. The ultimate goal is to promote responsible sourcing of CRMs in the EU and diversify the supply from third countries, thereby securing the continued supply of CRMs for EU industries. The main output are machine learning related prospectivity modelling and resource modelling, surficial geochemistry methods used for exploration, refined mineral deposit models, and mineral system guided prospectivity modelling, machine learning based language analyses to extract information from social media.
SEMACRET intends to apply the mineral system approach to guide exploration for orthomagmatic CRMs, generate refined ore deposit models, improve socially and environmentally friendly exploration methods, promote social awareness on the needs of responsible exploration raw materials and responsible sourcing of raw materials. Further, SEMACRET aims to map the exploration and production potential of CRM in the EU and key CRM supplier countries. Our research will be conducted at five reference sites in Finland, Portugal, Poland and the Czech Republic representing different geological, social and environmental conditions. The ultimate goal is to promote responsible sourcing of CRMs in the EU and diversify the supply from third countries, thereby securing the continued supply of CRMs for EU industries. The main output are machine learning related prospectivity modelling and resource modelling, surficial geochemistry methods used for exploration, refined mineral deposit models, and mineral system guided prospectivity modelling, machine learning based language analyses to extract information from social media.
In WP1 (Ore deposit model refinement), the magma source been suggested to be mainly from plume magma from geochemical study and thermodynamic modelling of large igneous provinces. However, geochemical study of subduction zone related magmatism may derived from metasomatized sub-continental lithospheric mantle. Computational modelling suggest that mantle derived magma may form large magma reservoir at different crustal level (e.g. lower crust, middle crust). These ore-formation factors may potentially be reflected by large scale geophysical data for regional scale prospectivity modelling including thickness of lithosphere and crustal thickness. High temperature experimental study has started to constrain the metal sink mechenisms and themodynamic modelling has also been used to constrain the magma fractionation and sulfide saturation processes and tools for identifying sulfide saturated magma. Based on ore formation factors, in WP2 (Regional exploration targeting), we try to utilize new exploration predictors for prospectivity modelling with relevant justification. The modelling has been tested in one reference site for two types of ore deposits including layered intrusions hosted Cr-PGE-V deposits and conduit type Ni-Cu-(Co)-(PGE) deposits. To process large amount of high resolution geochemical data which could be used to reflect the sink mechanism, an outliner detection tool has been developed based on statistic study. For local scale exploration in WP3, 3D EM modelling, useful for detecting conductive sulfide ore body, is in an advanced status of development, with frequency-domain forward response implemented in a moving-footprint framework and Jacobian computation in debug phase. A new software suite, named EEMstudio, is under development as a Python plugin of Q-GIS. EEMstudio is developed in order to process, visualize and model AEM and Ground-IP data in the same environment, handling as well induced polarization. Joint inversion of electric and electromagnetic data has shown promising result as well. For validation of these geophysical methods, majority of the planned new geophysical data acquisition has been conducted. Lithogeochemical study of reference site has been conducted, but still ongoing for data collection. Surficial geochemical task has completed most sampling campaigns with some geochemical data analyses result is available. For machine learning based 3D prospectivity modelling and resource modelling optimization, three workshops have been conducted to define the modelling criterias, and the modelling work is in progress. In WP4, social communication events have been implemented in 4 different reference countries, and machine learning based analyses on peoples’ altitude towards mining has made good progress. In WP5, a preliminary collection criteria of mineral resource data has been defined with a template being created, and in the data collection stage.
We will use the Mineral Systems Approach to generate an improved ore model for orthomagmatic ore deposits. We will use the improved ore models to define mappable exploration criteria. Integrating key proxy data layers together can discriminate regional high prospective and low or non-prospective areas, promoting new discoveries of CRMs. In the present project we will develop sustainable solutions for exploration at regional and local scale, including, geophysical methods low- to zero impact surficial geochemical exploration method, and machine learning based 3D prospectivity mapping and resource assessment. For these methods, we will validate it using data from reference sites, and thus elevate the TRL level from 3 to 5. The combined solution of exploration integrates sustainable exploration methods and social awareness provides a clear pathway towards responsible exploration means. These methods can potentially be upscalled in the future by follow up projects from TRL level 5 to 7 or higher, and be commercialized to by new SMEs (e.g. exploration consulting company). We will generate a database on the distribution of mineral resources and ore reserves of green transition CRMs hosted in orthomagmatic ore deposits (Ni, Cu, PGE, V, Ti, Cr) in line with the UNFC code in the EU and globally. These data will be referenced by exploration companies for investment, and policymakers to plan the CRM strategy, diversifying and securing the supply of (critical) raw materials to the EU. After a long term, the method developed in the project will potentially promote discovery of new resources of these metals in the EU and result in increased production in future, with the potential to promote the manufacture of green technologies in the EU, thus enabling industrial leadership of the EU in green- transition-related technologies, such as batteries, fuel cells, energy storage facilities, and make European industries climate-neutral and sustainable.