Newsletter – Project Results, Mar 21, 2024
Inlecom Unveils Revolutionary Approach to Geothermal Lithium Exploration with CRM AI Tool
Understanding the complex processes governing Lithium occurrence within geothermal fluids has long been a challenge in geological exploration. Today, Inlecom Innovation proudly announces a groundbreaking solution – the CRM AI Tool. This innovative platform represents a fusion of geological insights and cutting-edge Machine Learning methodologies, poised to revolutionize geothermal resource exploration.
Lithium, a highly sought-after element, exhibits diverse behaviors influenced by geological and hydrochemical conditions within reservoirs. By discerning correlations among major cations, anions, and fluid characteristics, Inlecom aims to unravel the intricate web of factors controlling Lithium concentrations. These insights not only optimize geothermal resource exploration but also contribute to a deeper understanding of Lithium’s broader geological context, given its pivotal role in energy storage technologies.
The AI tool, developed in the context of the CRM-Geothermal project, is designed to provide accurate estimations of Lithium concentrations while ensuring interpretability in geothermal data analysis. The journey commenced with the refinement of the REFLECT Dataset into the upgraded CRM-AI Database, laying a robust foundation for subsequent analyses. Through meticulous data pre-processing and the application of advanced Machine Learning models such as Tree-Based regression, Inlecom has enhanced data reliability and accuracy in Lithium concentration estimations.
The CRM AI Tool offers a multifaceted approach to Lithium concentration estimation in geothermal waters:
- Data Input: Users can input elemental concentrations from geothermal fluid samples.
- Machine Learning Algorithms: Leveraging sophisticated Machine Learning algorithms, such as Decision Trees, the tool analyzes the input data to estimate Lithium concentrations accurately.
- Real-time Exploration: With backward navigation through Decision Tree nodes, users can explore the AI model decision process.
- Explainable AI (XAI): The tool incorporates Explainable AI techniques, including Shapley values, to provide transparency into the decision-making process of Lithium concentration estimation.
- Visualizations: The tool generates visualizations such as scatterplot maps, showcasing geographical variations in Lithium concentrations.
- Sensitivity Analysis: Additionally, the CRM AI Tool offers Sensitivity Analysis, empowering users to explore how variations in parameters affect Lithium concentration estimations.
To get a glimpse into how our CRM AI Tool works, please read here.
CRM-Geothermal aims to develop an innovative technology solution which combines the extraction of Critical Raw Materials (CRM) and energy from geothermal fluids to decrease the European Union’s dependency on imported resources, supporting the EU Green Deal. Inlecom brings its extensive expertise in Artificial Intelligence, Modelling, and Simulation systems to the project.
Learn more about the project
This project has received funding from the Horizon Europe research and innovation programme under GA 101058163. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the granting authority can be held responsible for them.
