Geothermal Energy

Geothermal energy incorporates the Earth's natural heat as a sustainable and renewable energy source. This technology represents a promising solution for meeting rising energy demands while minimizing environmental impact. Geothermal systems generate electricity, heat, and cool using vast thermal reservoirs beneath the surface. Our research group is dedicated to advancing this field by addressing challenges and investigating novel techniques to improve geothermal energy's efficiency and accessibility. 

Our research focuses on various aspects of geothermal energy systems, such as developing thermal conductivity models, optimizing working fluids, and converting abandoned oil and gas wells to geothermal use. We use advanced methodologies such as machine learning, deep learning, experimental testing, and heat transfer analysis to develop cutting-edge solutions that combine theory and practice. Recent projects have included developing advanced methods for modeling single-well closed-loop geothermal systems, studying the thermal conductivity of carbonate rocks under different conditions, and determining the effective thermal conductivity of tight porous media. In addition, our team uses deep learning techniques to characterize geothermal reservoirs by estimating rock properties from seismic data, as well as machine learning for comprehensive thermal conductivity analyses. 

The findings of our study have the potential to transform geothermal energy systems by increasing their efficiency and economic viability. We hope to contribute to the development of innovative models and technologies that will help the world transition to cleaner energy. Our work not only advances geothermal exploration but also addresses key industry challenges, promoting long-term energy solutions for future generations.