GeoDAWN to GeoTGo: from Complex Data to Decisions Related to Geothermal Prospectivity

Abstract

GeoTGo is a cloud-based application designed to streamline geothermal exploration, monitoring, and resource utilization. The platform leverages advanced data analytics, cloud/high-performance computing, machine learning, and GIS technology to optimize the entire geothermal energy lifecycle—from exploration and site assessment to real-time well monitoring and energy output optimization. Key features include AI-powered geothermal mapping, thermal gradient analysis, and reservoir simulations. The app is also designed to support near-real-time data analytics integrated with remote sensors. GeoTGo will also offer financial analysis tools for energy yield estimation, cost-benefit analysis, and scenario modeling, helping developers and investors evaluate the economic feasibility of geothermal projects. The application will also provide collaboration and project management capabilities through a centralized cloud dashboard, enabling teams to work efficiently on geothermal projects. GeoTGo's environmental monitoring tools will track sustainability metrics and link users with compliance methods with regulations. By leveraging cloud infrastructure and HPC, GeoTGo significantly reduces exploration time, optimizes geothermal resource utilization, and enhances decision-making. The app is targeted at geothermal exploration companies, energy providers, investors, regulators, and research institutions, aiming to promote sustainable energy development and maximize the potential of geothermal resources. Here, we demonstrate how GeoTGO is applied to process the GeoDAWN airborne datasets collected over Nevada. Our ML analyses extracted features (signals) in the data that are potentially important for the evaluation of geothermal prospectivity. We also demonstrated the applicability of our ML techniques to impute and blindly predict missing data.