From Conceptual Models to Feasibility: Modern Technologies Driving Geothermal Resource Evaluation

Abstract

Geothermal energy is a key pillar of the low-carbon energy transition, yet project success remains highly sensitive to subsurface uncertainty and up-front capital expenditures. This paper examines how modern geophysical, geochemical, and digital technologies can be integrated into a staged exploration workflow that links initial conceptual models to feasibility level resource evaluation. Building on established practices in geothermal and petroleum subsurface evaluation, an integrated framework is proposed that combines magnetotelluric imaging, advanced geochemical analysis, temperature gradient drilling, and numerical reservoir modeling with play-based portfolio methods, risked volumetrics, and techno-economic screening. High-temperature downhole logging, fiber-optic distributed temperature logging, three-dimensional magnetotelluric inversion, and coupled thermal-hydraulic-mechanical simulators are used to iteratively refine conceptual models and reduce uncertainty as projects progress from appraisal to deep exploration drilling. Digital technologies - including Monte Carlo-based uncertainty quantification, machine learning-based reservoir modeling, and real-time monitoring - are embedded to improve decision-making and reduce risk in both conventional hydrothermal systems and enhanced or hybrid geothermal configurations. The framework is explicitly structured around phase-specific go/no-go decisions and integrates environmental baseline assessment and stakeholder engagement throughout the exploration lifecycle. The paper concludes by highlighting how methods, tools, and skills from oil and gas exploration and reservoir engineering can be applied to geothermal projects, and how digital transformation can accelerate investment-grade feasibility decisions across a wider range of play types.