All Outputs (5)

From geothermal brine to battery: balancing technological innovation with environmental and social responsibility: a case study from Lithium Valley. (2025)
Presentation / Conference Contribution
ALGAIAR, M. 2025. From geothermal brine to battery: balancing technological innovation with environmental and social responsibility: a case study from Lithium Valley. Presented at the 16th Workshop of the Society of petrophysicists and well log analysts Saudi Arabia chapter 2025 (SPWLA-SAC 16th Workshop) , 7-8 May 2025, Al Khobar, Saudi Arabia.

This study synthesizes current research on lithium extraction, focusing on technological advances, the growing demand for lithium in the energy transition, and the environmental and social challenges associated with its production. It uses the Lithiu... Read More about From geothermal brine to battery: balancing technological innovation with environmental and social responsibility: a case study from Lithium Valley..

AiION: novel deep learning chemical geothermometer for temperature prediction of deep geothermal reservoirs. (2025)
Journal Article
ALGAIAR, M., BANO, S., LASHIN, A., HOSSAIN, M., FAISAL, N.H. and ABU SALEM, H.S. 2025. AiION: novel deep learning chemical geothermometer for temperature prediction of deep geothermal reservoirs. Renewable energy [online], 248, article number 123154. Available from: https://doi.org/10.1016/j.renene.2025.123154

This study introduces AiION, a novel deep learning chemical geothermometer designed to predict deep geothermal reservoir temperatures and address the limitations of traditional geothermometry methods. By integrating classical geothermometry, multi-co... Read More about AiION: novel deep learning chemical geothermometer for temperature prediction of deep geothermal reservoirs..

aiION: a machine learning approach to geothermal exploration. (2025)
Presentation / Conference Contribution
ALGAIAR, M.M. 2025. aiION: a machine learning approach to geothermal exploration. Presented at the 2025 Geothermal seminar (GEOTHERMAL 2025): gaining momentum, 26-27 February 2025, [virtual event].

Geothermal energy, a renewable resource derived from the Earth's subsurface, holds great promise for sustainable power generation. This research aimed to develop a data-driven geothermometer using supervised machine learning (ML) to predict subsurfac... Read More about aiION: a machine learning approach to geothermal exploration..

Applications of artificial intelligence in geothermal resource exploration: a review. (2024)
Journal Article
ALGAIAR, M., HOSSAIN, M., PETROVSKI, A., LASHIN, A. and FAISAL, N. 2024. Applications of artificial intelligence in geothermal resource exploration: a review. Deep underground science and engineering [online], 3(3): geothermal energy, pages 269-285. Available from: https://doi.org/10.1002/dug2.12122

Artificial intelligence (AI) has become increasingly important in geothermal exploration, significantly improving the efficiency of resource identification. This review examines current AI applications, focusing on the algorithms used, the challenges... Read More about Applications of artificial intelligence in geothermal resource exploration: a review..

Unlocking hidden geothermal potential: leveraging artificial intelligence for subsurface exploration. (2024)
Presentation / Conference Contribution
ALGAIAR, M.M. 2024. Unlocking hidden geothermal potential: leveraging artificial intelligence for subsurface exploration. Presented at the 3rd Annual geothermal seminar (Geothermal 2024): heating up the market, 21-22 February 2024, [virtual event].

Geothermal energy shows potential as a renewable and sustainable energy source. However, geothermal exploration is challenging and costly due to the subsurface complexities involved in locating potential reservoirs. Recent advancements in artificial... Read More about Unlocking hidden geothermal potential: leveraging artificial intelligence for subsurface exploration..