Agentic real-time data-driven decision-making for geothermal systems (T02-A03-LBP2)

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Agentic real-time data-driven decision-making for geothermal systems (T02-A03-LBP2)

Phase:	Theme
Theme:	Carbon CUS (T02)
StatusStatut:	Active
Start DateDate de début:	2026-02-01
End DateDate de fin:	2026-08-31
Principal Investigator
Zhang, Bo

Aperçu de Project Overview

This project develops an agent-enabled, real-time decision-support framework for geothermal systems by integrating subsurface modeling, monitoring data, and data-driven methods into a unified workflow.

The framework builds upon established thermal–hydraulic–mechanical (THM) models and monitoring, measurement, and verification (MMV) data, augmented by AI-based agents that coordinate data retrieval, simulation execution, and scenario evaluation. Rather than replacing physics-based models, the agent layer automates complex modeling and analysis workflows, enabling timely and informed operational decision-making under uncertainty.

By supporting adaptive evaluation of well configurations and operational strategies, the project aims to improve the efficiency, robustness, and scalability of geothermal development. Overall, it provides a flexible digital foundation for next-generation geothermal systems and contributes to reliable, low-carbon energy solutions.

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