A thorough examination of machine learning techniques used to detect geological lineaments in the Afar Triangle. This detailed study delves into the methodology, data analysis, and geospatial strategies developed to enhance geothermal resource mapping.

An insightful overview of the current state and challenges of geothermal energy development in Canada, highlighting the nation's renewed interest in deep geothermal systems and the supportive roles of governmental policies and research advancements.

This study explores the radiogenic heat production (RHP) from uranium, thorium, and potassium decay in SE Alberta, utilizing airborne gamma-ray spectrometry to estimate the potential for clean electric energy generation.

Explore a detailed visual summary of key findings from our study on radiogenic heat production, featuring maps and data visualizations.

This version of the study, presented at GeoConvention 2024, emphasizes practical applications of machine learning for geothermal exploration in the Afar Triangle. Enhanced with visual aids and adapted for a conference audience, this document offers a concise, visually engaging overview of the findings.