Stanford Geothermal WorkshopFebruary 9-11, 2026

Geothermal energy development faces significant challenges due to subsurface uncertainties, particularly in identifying economically viable plays where elevated temperatures occur at accessible depths. Geothermal Play Fairway Analysis (GPFA) emerges as a powerful risk-reduction framework, adapted from petroleum exploration, to systematically integrate geological, geophysical, and thermal data at basin and play scales. By mapping Common Risk Segment (CRS) and Composite Common Risk Segment (CCRS) elements, GPFA highlights prospects with anomalous heat mechanisms that elevate local geothermal gradients beyond regional norms, enabling high-temperature resources at shallower depths and thereby slashing drilling costs while boosting return on investment (ROI). Anomalous heat mechanisms often drive these localized thermal enhancements. For instance, salt diapirs act as thermal conductors, funneling heat upward and creating hotspots in sedimentary basins. Overpressured zones can advect deeper, hotter fluids toward shallower reservoirs, amplifying gradients through convective heat transfer. In extensional settings like the Basin and Range province, high-permeability faults linked to deep crystalline basement rocks—such as granites or igneous intrusions—facilitate upward circulation of hot fluids, yielding gradients far exceeding background levels. GPFA's data-driven approach, incorporating borehole temperatures, seismic interpretations, and permeability models, identifies these features by quantifying their impact on heat flow, reservoir quality, and fluid pathways. This targeted identification allows operators to prioritize prospects where temperatures suitable for power generation ( greater than 150°C) are achievable at depths under 6 km, reducing capital-intensive deep drilling and enhancing project economics. A critical pitfall in geothermal assessment is the misuse of geothermal gradients for temperature extrapolation. Linear gradients, derived from bottom-hole temperatures (BHT), cannot be reliably extended beyond well control, as they overestimate deeper temperatures. Gradients inherently decrease with depth due to rising thermal conductivity in compacted, less porous rocks—governed by the equation: gradient = heat flow / thermal conductivity. This leads to flawed temperature-depth profiles; for example, a projected 200°C at 3 km might actually yield only 150°C, inflating drilling budgets and jeopardizing projects amid high upfront costs. To mitigate this, GPFA incorporates 1D basin modeling, simulating heat flow from the lithosphere-asthenosphere boundary (at ~1330°C) upward through a stratigraphic column parameterized with lithology-specific thermal conductivities. This physics-based method accurately predicts non-linear gradients, accounting for radiogenic heat production and conductive/convective processes. Case studies from numerous geothermal exploration prospects demonstrate how GPFA, augmented by such modeling, has de-risked plays with anomalous gradients, improving success rates by 20-30% and optimizing ROI through shallower, cost-effective developments. In summary, GPFA not only pinpoints anomalous heat mechanisms for superior play selection but also enforces rigorous gradient modeling to avoid overestimation pitfalls, paving the way for sustainable geothermal expansion.

Topic: Modeling