Stanford Geothermal WorkshopFebruary 8-10, 2027

Nitrogen-doped carbon quantum dots (NCQDs) were synthesised from spent coffee grounds via solventless mechanochemical method at three different N/C ratios (0.5:2, 1:2 and 1:1) to study the effect of N-doping amount on the thermal properties of the dots. NCQDs were examined using FTIR and UV-Vis spectroscopy, SEM, TEM and DLS and their thermal conductivity, thermal resistivity, volumetric heat capacity and thermal diffusivity were measured in aqueous dispersions (0.3, 0.5 and 1.0 wt%) and natural soil (0.5 wt%) via transient line-heat-source analyser (KD2 Pro). The response is highly dependent and strictly monotonic to the amount of doping. The dots with the lowest amount of doping (0.5N:2C) show an increase in the thermal conductivity of water depending on concentration up to 0.69-1.22 W m−1 K−1 at 1.0% (+15-100% relative to water), 1N:2C dots show a smaller increase (0.60-0.87 W m−1 K−1 at 1.0%) and 1N:1C dots do not change conductivity of water or even decrease it down to 0.51-0.59 W m−1 K−1 and enhance the resistivity with concentration. In soil, the dots with 1N:2C ratio have higher thermal conductivity (1.26-1.81 W m−1 K−1) and diffusivity compared to 1N:1C dots (1.29 W m−1 K−1, 0.57 mm2 s−1). The negative correlation between the amount of nitrogen and enhancement of conductivity can be explained by phonon scattering due to substitutional nitrogen and associated lattice defects in the sp2 core, which reduces the intrinsic conductivity and raises interfacial thermal resistance of dots in liquid environment, hence providing another way to tune the thermal properties of coffee-waste-derived NCQDs either as thermal conductivity enhancers or thermally inert additives.

Topic: Low Temperature

The application of geothermal direct use within Indonesia's thermal bathing industry offers substantial potential for advancing sustainable tourism and empowering local economies. To guarantee environmental sustainability, public safety, and the standardization of facilities, the Indonesian government has instituted the Operational Worthiness Certificate (Sertifikat Laik Operasi, or SLO) requirement for industry operators. As this sector moves toward comprehensive formalization, a critical opportunity arises to streamline the SLO application process and expedite regulatory compliance. Utilizing field data and stakeholder insights gathered from local governments and thermal spring operators across Garut and greater West Java, this study pinpoints crucial areas for procedural improvement and capacity development. Key recommendations involve aligning Central and Regional notification systems within the Online Single Submission (OSS) platform, streamlining Geothermal Situation Map prerequisites for Micro and Small Enterprises (MSEs), and establishing uniform Technical Guidelines (Juknis) to assist local authorities in executing accurate field inspections.Rather than delivering a fully developed software solution, this research proposes a multidisciplinary conceptual framework integrating Geothermal Management, Public Policy, and Information Systems. Initially, we examine the potential of an integrated API architecture—drawing inspiration from local platforms like Subang's SINANAS—to theoretically facilitate seamless data exchange between regional and central permitting databases. This concept demonstrates how enhanced system interoperability can reduce administrative bottlenecks and misrouted permits. Furthermore, informed by an empirical capacity-gap assessment, we outline a standardized field verification methodology calibrated to the existing capabilities of regional governments.To catalyze future progress in the industry, this paper outlines a practical toolkit aimed at assisting both operators and regulators. The core strategic proposals include: (1) a comprehensive Technical Guideline (Juknis) framework that defines minimum field-testing criteria (such as temperature, pH, and H2S levels) and evaluates the integration of Regional Health Laboratories (Labkesda) for equipment validation; (2) the deployment of affordable, standardized Situation Map templates designed to alleviate financial pressures on MSEs; and (3) an intuitive procedural roadmap to guide operators through the existing OSS framework. Supported by conceptual system architecture diagrams, user-journey flowcharts, and capacity-building matrices, this research delivers a strategic roadmap to guide policymakers, support local enterprises, and drive the sustainable expansion of geothermal direct-use applications in Indonesia.

Topic: Direct Use

Enhanced geothermal systems represent the next frontier of geothermal energy, yet reservoir characterization in EGS settings remains challenging due to sparse labels, complex fracture networks, and heterogeneous lithologies. The Utah FORGE site provides a unique, fully open dataset combining drilling records, microseismic catalogs, well logs, and temperature measurements from a purpose-built EGS research site, creating an exceptional opportunity for rigorous machine learning evaluation in a controlled field setting. This study applies and s a suite of machine learning methods to two coupled EGS problems: fracture network characterization from microseismic event clustering and well log signatures and subsurface temperature distribution prediction integrating drilling and geophysical observations. We evaluate classical ensemble methods, physics-informed neural networks that embed heat conduction equations directly into the learning objective, and graph neural networks that represent the fracture network as a structured graph to capture spatial connectivity. Results demonstrate that physics-informed approaches reduce data requirements by over ~ ~40% compared to purely data-driven baselines while maintaining competitive predictive accuracy, a finding with direct operational significance for EGS sites where labeled measurements are expensive. Graph-based fracture representation captures connectivity patterns that conventional feature-engineering approaches miss, improving microseismic cluster characterization. Temperature prediction accuracy is strongly governed by the spatial density of conditioning measurements rather than model complexity, pointing to an optimal data acquisition strategy for future EGS sites. These findings translate into concrete recommendations for EGS site characterization workflows and establish a reproducible on the FORGE dataset that the broader community can build upon as EGS deployment accelerates globally.

Topic: FORGE

The Salton Sea geothermal field represents one of the world's major geothermal resources and is characterized by high-temperature, high-salinity brine containing significant concentrations of critical elements, such as lithium. This creates an opportunity for the co-production of renewable energy and critical minerals. However, the complex chemistry of these brines presents considerable challenges for surface processing and subsequent reinjection into the geothermal reservoir. Several reservoir studies have simulated lithium transport and recovery; others have examined long-term lithium evolution and water-rock interactions via reactive-transport studies. These studies have treated lithium recovery and reservoir geochemical response as separate processes, leaving a clear gap in the existing work. The coupled effects of direct lithium extraction (DLE), modified reinjection-brine chemistry, thermal recovery, and reservoir injectivity have not been evaluated within a unified reservoir-scale framework. This study presents an integrated reservoir-geochemical framework to identify the operational tradeoffs between geothermal energy production, lithium recovery, and long-term reservoir sustainability. A geocellular model is designed to represent the reservoir intervals of the Salton Sea geothermal system, with production and reinjection focused on the deeper Palm Spring–Imperial reservoir sequence. Using the Intersect reservoir simulator, the ionic composition of the produced brine is tracked and combined with demonstration-scale DLE processing data to define the composition of the reinjected brine. Mineral precipitation and dissolution reactions are represented through a simplified equilibrium reaction scheme. Reaction stoichiometry and equilibrium states are constrained using published thermodynamic data and PHREEQC calculations, while fluid properties are obtained from the International Association for the Properties of Water and Steam (IAPWS) tables. To isolate the impact of DLE on reservoir performance, multiple scenarios are evaluated. A baseline geothermal case without lithium extraction is compared with a lithium-removal-only case to establish reference thermal and geochemical behavior. Additional cases incorporate measured post-treatment brine chemistry to assess how DLE-induced changes in fluid composition influence reservoir response. The simulations quantify thermal recovery, lithium production, and thermal and chemical breakthrough behavior. Sensitivity analyses examine the influence of extraction efficiency, reinjection temperature, and operating strategy. The results will help to identify the conditions under which DLE-modified brine reinjection affects scaling, injectivity, and the long-term recovery of heat and lithium from the reservoir.

Topic: Reservoir Engineering

Objectives/Scope: Every produced sample carries reservoir intelligence — equilibrium temperatures, boiling and mixing signals, injection returns, scaling precursors — that geochemical surveillance reads for the cost of laboratory analysis. This review consolidates geothermal fluid geochemistry as an operational tool: solute and gas geothermometry reliability, tracking reservoir processes through time-series chemistry, injection-breakthrough detection, integration with physical surveillance, and the operating record of decisions geochemistry demonstrably informed. Methods, Procedures, Process: Geothermometer families are reviewed with their equilibrium assumptions graded against the disequilibrium field fluids actually present — re-equilibration during ascent, mixing, boiling corrections. Time-series interpretation methods are compiled from operating fields: chloride-enthalpy tracking, gas-ratio evolution, isotopic shifts under injection load. Breakthrough-detection performance is assembled against tracer-confirmed cases, multivariate and machine-learning treatments of chemistry streams are assessed, and decision case studies are compiled. Results, Observations, Conclusions: Geothermometry earns its keep in trends, not absolutes: compiled time-series show solute and gas thermometers tracking reservoir cooling and boiling-zone evolution reliably even where absolute temperatures scatter — the derivative is trustworthy, the intercept negotiable. Chloride-enthalpy diagrams remain the workhorse for process discrimination. Chemistry detected injection returns before thermal breakthrough in most compiled confirmed cases, at years of warning in several — surveillance value the sampling budget rarely reflects. Novel/Additive Information: An operations-focused rehabilitation of geochemical surveillance — trend-mode interpretation standards replacing absolute-temperature overreach, breakthrough-warning statistics quantifying the lead time chemistry buys over thermal signals. The integration framework assigns chemistry its role alongside pressure and temperature surveillance, and the sampling-design guidance converts the compiled decision record into monitoring-plan arithmetic for the fields now committing to sustained-yield management

Topic: Emerging Technology

Steam–Water Relative Permeability and Two-Phase Flow Properties in Geothermal Reservoirs: Measurements, Models, and Open Questions Reviewed Objectives/Scope: Flashing reservoirs run on steam-water relative permeability, a property measured by a handful of laboratories under conditions most core facilities cannot reach. We review steam-water kr and two-phase flow properties for geothermal systems: the measurement record, phase-transformation effects that make steam-water unlike gas-water, and the model curves simulators quietly default to. Enhanced-system forecasting inherits the gap most directly, its conditions furthest from the data. Methods, Procedures, Process: The steam-water measurement literature is compiled, sparse enough to review nearly completely; phase-change-coupled flow physics is reviewed to explain where steam-water departs from inert-gas analogy. Simulator default practices are examined against the data, and ML property estimation is surveyed briefly. Condition coverage is mapped against enhanced-system envelopes, sizing the extrapolation. Relative-permeability functional forms are compared for their behavior outside measured ranges. Results, Observations, Conclusions: Measured steam-water curves differed from nitrogen-water analogs on the same rocks, with phase transformation reducing apparent interference between phases; defaults borrowed from gas-water practice misstate that. Data cluster in a narrow condition range, and enhanced-system conditions extrapolate beyond all of it. Forecast sensitivity to the kr choice rivaled sensitivity to permeability itself in compiled studies. Functional-form choice dominated extrapolation behavior, curves agreeing where data exist and diverging beyond. Novel/Additive Information: A near-complete audit of a property everything in flashing-reservoir forecasting depends on and almost nobody measures, with measurement gaps ranked by forecast consequence and functional-form choice exposed as a hidden extrapolation policy. The consequence-ranked wish list is scoped for university and national-laboratory capability — a ready agenda for the geothermal research programs now expanding worldwide.

Topic: Enhanced Geothermal Systems

Geothermal Resource Capacity Estimation: Heat-in-Place, Power-Density, and Stochastic Methods Compared, with AI Applications Objectives/Scope: Resource estimates decide drilling budgets, and the estimation methods disagree by design. We compare geothermal capacity-estimation approaches: volumetric heat-in-place with recovery factors, power-density analogs, and stochastic implementations of both, asking what each actually predicts and why early-stage estimates keep running optimistic. Portfolio-level resource reporting inherits the bias, making calibration an industry credibility issue. Methods, Procedures, Process: Method foundations are reviewed with their buried assumptions surfaced, recovery factor above all; estimate-versus-outcome comparisons are compiled wherever developed fields allow the reckoning. Stochastic practice is examined for whether distributions reflect knowledge or convention, and ML-assisted estimation from sparse exploration data is surveyed. Recovery-factor evidence is assembled by system type from outcome comparisons. Cutoff-choice effects are compiled, temperature and depth cutoffs moving estimates quietly. Results, Observations, Conclusions: Recovery factor carried most of the uncertainty and least of the scrutiny; outcome comparisons showed early volumetric estimates biased high, with the bias traceable to recovery-factor and cutoff choices. Power-density methods performed respectably where analog quality was honest. Stochastic ranges published to date have been too narrow more often than too wide. Cutoff choices moved estimates as much as recovery factors in the compiled decompositions. Novel/Additive Information: Capacity-estimation methods are judged against realized drilling outcomes rather than internal logic, with the documented optimism traced to recovery-factor and cutoff choices — two levers of equal weight and unequal scrutiny. The system-type recovery-factor ranges are formatted for direct citation in resource disclosures, giving developers calibrated credibility in a sector whose inflated estimates keep spending it

Topic: Enhanced Geothermal Systems

The analysis compares medium-enthalpy geothermal systems in a direct configuration with hybrid geothermal-solar thermal systems for cooling applications in data centers. Direct geothermal uses resources with temperatures between 90 and 150 °C, providing a steady, stable, and continuously available energy source, although it is limited by the reservoir's own thermal conditions. The integration of solar thermal energy through concentration collectors allows the fluid temperature to rise to values close to 120–200 °C, significantly improving the available energy quality. This thermal boost makes it possible to use double-effect absorption chillers, increases the coefficient of performance (COP), and expands the system's operational flexibility. From an operational standpoint, geothermal provides the base thermal load while the solar resource adds extra energy during periods of high irradiation. Although the solar contribution introduces some daily and seasonal variability, the system's reliability is maintained thanks to the continuous backup from the geothermal source. Plus, using advanced control and automation systems allows optimizing the mix of both energy sources and adapting to changes in demand. In terms of performance, direct geothermal systems usually operate with thermal COPs between 0.6 and 0.75, while hybrid systems can reach values between 0.8 and 1.3. Although adding a solar field increases the initial investment (CAPEX), operating costs stay low because only renewable resources are used and there’s no need for fossil fuels. In conclusion, geothermal–solar hybrid systems represent a highly promising technological alternative for the sustainable cooling of data centers in Costa Rica. Combining the reliability of geothermal energy with the thermal boost capability of solar power allows for increased energy efficiency, reduced levelized cost of cooling (LCOC), and optimized use of available renewable resources, especially in regions with high geothermal and solar potential like Guanacaste.

Topic: Direct Use

Indonesia’s geothermal sector is pivoting from mature high-temperature fields toward vast low-to-medium temperature resources. However, the bankability of these future projects is threatened by power plant construction costs that remain well above global averages. This paper tackles this critical bottleneck by introducing a novel techno-commercial ing methodology that dissects the most capital-heavy project phases: Power Plant Engineering, Procurement, and Construction (EPC) and Steam Above Ground Systems (SAGS). Utilizing escalated global cost datasets from the U.S. and Türkiye, our analysis demonstrates that Indonesia’s CAPEX disparity stems from monopolized turbine markets, high import dependency, and inflated financial "safety margins" in early EPC bids. To counter these drivers, we propose a compounding cost-reduction framework featuring four actionable strategies: (1) utilizing Organic Rankine Cycle (ORC) technologies to break manufacturer monopolies; (2) de-risking execution through pilot testing; (3) replacing EPC safety margins with rigorous, geospatial data-driven Front-End Engineering Design (FEED); and (4) restructuring procurement into Split-EPC contracts to optimize tax exposure. The study translates these multidisciplinary findings into an Integrated Cost Optimization Roadmap, utilizing high-definition visual tools like waterfall charts and contracting visualizations. By bridging theoretical cost-saving measures with practical application, this blueprint offers Indonesian policymakers, operators, and financiers a replicable pathway to drastically reduce development costs and accelerate the nation's energy transition.

Topic: General

Geothermal power plays a pivotal role in global renewable energy goals by providing sustainable, low-carbon electricity. Nevertheless, a project's overall feasibility relies heavily on executing drilling programs that are both technically robust and economically sound. To attract financial institutions and secure necessary capital, developers must craft bankable drilling plans that satisfy strict operational, financial, and regulatory s. This paper investigates the essential methodologies and components required to formulate these plans, emphasizing the due diligence requirements from both technical and economic standpoints. Crafting a bankable geothermal drilling program demands a holistic methodology that merges industry best practices with site-specific environmental challenges. A resilient plan validates that well targeting, risk management, well design, and drilling sequencing are achievable and financially viable. Critical elements—such as architectural well design, testing protocols, and mitigation strategies—must be meticulously evaluated to circumvent expensive operational failures. From a due diligence perspective, this paper highlights the necessity of preemptively resolving common red flags that could diminish a project's credibility to lenders. Frequent areas of concern during evaluations include aligning the drilling strategy with the resource's conceptual model, establishing consistent success criteria for sequence decisions, and conducting precise rig sizing assessments. Selecting a drilling rig with the appropriate technical capacity is vital for maintaining economic efficiency and preventing budget overruns or schedule delays. Additionally, the paper details the incorporation of comprehensive cost modeling, ensuring that expenditures related to civil infrastructure, access roads, water supply, well testing, and remediation are accurately projected to satisfy investor scrutiny. Ultimately, this study delivers a structured framework designed to assist developers in generating comprehensive, financially appealing geothermal drilling proposals. By proactively tackling these fundamental due diligence criteria, the research aids in refining the project development lifecycle, bolstering lender confidence, and paving the way for successful project execution.

Topic: Drilling

Cryogenic cold sources such as liquefied natural gas (LNG), liquid nitrogen, and liquid air contain substantial recoverable physical exergy that is commonly dissipated during regasification or vaporization processes. Thermoelectric generators (TEGs) have emerged as a promising solid-state technology for harvesting this cold energy because of their structural simplicity, scalability, reliability, and absence of moving parts. This review presents a comprehensive analysis of thermoelectric generator applications using cryogenic cold sources, with emphasis on LNG regasification systems, liquid nitrogen recovery systems, and liquid air energy storage applications. The review systematically examines thermoelectric operating principles under cryogenic conditions, material behavior at low temperatures, system configurations, heat transfer mechanisms, and reported electrical performance. Major technical challenges, including cold-side thermal resistance, frosting effects, contact resistance, and low conversion efficiency, are critically discussed. Reported experimental and numerical studies demonstrate that cryogenic thermoelectric systems can achieve electrical power outputs ranging from sub-watt laboratory-scale devices to hundreds-of-watts industrial-scale configurations, although practical efficiencies generally remain limited. The review further evaluates heat exchanger integration strategies, structural optimization approaches, and system-level performance limitations affecting large-scale implementation. Finally, current research gaps and future development directions are identified to support the advancement of efficient and reliable cryogenic thermoelectric energy harvesting technologies.

Topic: Emerging Technology

In deep U-shaped closed-loop geothermal systems, the ascending production leg passes through progressively cooler formation, and part of the recovered heat leaks back into the rock before it reaches the surface. In the present study, this loss is countered by insulating the upper production well. The system is a 4000 m deep, 200 °C loop with a 1500 m lateral, operated at 10 kg/s from a 20 °C injection state, modeled with a computationally efficient one-dimensional wellbore march coupled to transient radial formation conduction. 28 fluids that remain single-phase liquid throughout the loop are simulated over a 30-year life, with the insulated length swept from zero to the full well depth. Insulating the entire production well proves counterproductive, lowering cumulative exergy for only 22 of the 28 fluids, because the working fluid in the deeper production well sections remains colder than the surrounding formation, and blanketing it blocks heat gain. Each fluid instead has an interior optimum insulated depth; deepest for the halocarbon refrigerants and shallowest for water. Insulating to that optimum reorders the second-law ranking: R1234ze(E) rises to 42.2 GWh of exergy and displaces isobutane, which leads the bare-well case at 38.5 GWh, from the top position. The gain is largest for the fluids that lose the most heat during ascent, and it appears mainly as a hotter, higher-exergy-delivered stream. Production temperature reflects this most clearly: the refrigerants deliver the hottest streams and insulation widens their lead. The year-30 outlet temperature of R11 rises from 89 to 100 °C, while water barely changes, remaining near 54 °C. The temperature ranking is preserved even though the exergy ranking is altered. These results show that production-well insulation is a fluid-specific design variable and that working-fluid selection cannot be decoupled from completion design.

Topic: Modeling

Irregular discharge in multi-feed geothermal wells is commonly attributed to dynamic interactions between feedzones with contrasting pressures and enthalpies, yet quantitative constraints on coupled wellbore--reservoir responses remain limited. This study reconstructs a multi-feed wellbore model for well ULB-01 in the Ulumbu Geothermal Field using a pressure-drop approach calibrated against Pressure Temperature Spinner (PTS) surveys and production-test data. The inferred feedzone boundary conditions are then coupled to a TOUGH2 reservoir simulation to investigate feedzone interaction and wellbore--reservoir response under low wellhead-pressure operation. During a representative cycling interval (10.1--10.5 days), the observed wellhead pressure decreases from 6.8 to 2.7 barg and brine flow declines from 9.2 kg/s to zero, while steam flow remains relatively stable at 5.7--6.3 kg/s. The wellbore simulation captures the broader pressure and steam-rate response but does not fully reproduce the intermittent brine shut-off, indicating that additional transient wellbore or surface-flowline processes may contribute to the observed short-timescale cycling. The coupled TOUGH2--wellbore workflow provides a partial match to measured wellhead pressure, steam mass flow, and produced enthalpy during relatively stable periods, while larger discrepancies remain during transient brine surges and shut-off events. The results suggest that pressure drawdown promotes redistribution of feedzone contributions and cooler liquid inflow at intermediate depth, providing a plausible mechanism for discharge instability. The findings indicate that the coupled workflow is useful for diagnosing feedzone-controlled instability, although resolving intermittent brine shut-off would require a more transient representation of wellbore and surface-flowline processes.

Topic: Reservoir Engineering

Scaling and corrosion remain the most significant operational challenges affecting the efficiency, reliability, and sustainability of geothermal power generation. These processes reduce heat transfer efficiency, impair steam quality, accelerate equipment degradation, increase maintenance costs, and shorten the operational lifespan of geothermal facilities (Nogara & Zarrouk, 2018; Tassew, 2001). Although both phenomena have been widely investigated, they are frequently treated as independent operational problems despite being governed by the same physicochemical evolution of geothermal fluids during production and utilization (Mundhenk et al., 2013). Consequently, limited understanding exists regarding how changes in fluid chemistry within individual process units influence the coupled development of scaling and corrosion throughout a geothermal power plant. This research addresses this knowledge gap by developing an integrated geochemical framework for evaluating the mechanisms controlling scaling and corrosion within the Olkaria I Additional Units (IAU) geothermal power plant, Kenya. Unlike previous studies that primarily emphasize mineral characterization or corrosion assessment independently, this study integrates operational fluid chemistry, steam purity, deposit geochemistry, mineralogical characterization, and process operating conditions to evaluate the evolution of scaling and corrosion across multiple process environments. The framework is designed to identify process-unit-specific geochemical conditions that promote mineral deposition and material degradation, providing a scientific basis for targeted mitigation strategies. Representative deposits were collected from selected process units, including steam scrubbers, condensers, cooling tower basins, and gas extraction systems, where geothermal fluids experience significant physicochemical changes associated with flashing, steam separation, condensation, cooling, and non-condensable gas interactions. Deposit chemistry is being characterized using X-ray fluorescence (XRF), while mineralogical identification is being undertaken using X-ray diffraction (XRD). These datasets are interpreted alongside geothermal fluid chemistry and operational parameters to investigate the relationship between fluid evolution, mineral precipitation, and corrosion processes. Emphasis is placed on steam purity because impurity transport through liquid carryover and vapor-phase contaminants significantly influences deposition and localized corrosion within steam turbines and downstream equipment (Addison & Richardson, 2020; International Association for the Properties of Water and Steam [IAPWS], 2013). Rather than presenting a conventional characterization of geothermal deposits, this research proposes a process-unit-specific methodology for integrating geochemical and operational datasets to improve understanding of the spatial variability of scaling and corrosion within high-enthalpy geothermal systems. The proposed framework is expected to support evidence-based chemical treatment strategies by identifying locations requiring targeted intervention instead of uniform plant-wide chemical dosing. The outcomes are anticipated to contribute toward improved plant reliability, reduced maintenance requirements, enhanced steam quality, and more sustainable operation of geothermal power plants in Kenya and other high-enthalpy geothermal fields.

Topic: Geochemistry

Conventional geothermal exploration has historically focused on areas with prominent surface manifestations such as hot springs, fumaroles, and hydrothermal alteration. However, many high-temperature geothermal resources remain concealed beneath sedimentary cover or volcanic sequences where surface evidence is limited or absent. These "blind" geothermal systems require integrated multidisciplinary exploration approaches capable of reducing drilling uncertainty. This study presents an integrated exploration workflow combining regional geological interpretation, structural analysis, two-dimensional seismic reflection data, magnetotelluric surveys, gravity and magnetic data, geochemical observations, and three-dimensional subsurface interpretation. Rather than relying on individual datasets, the workflow emphasizes the integration of complementary geoscientific information to identify structurally controlled permeability zones, reservoir compartments, potential heat sources, and optimal exploration drilling targets.

Topic: General

A new method for estimating power potential of electric-grade hydrothermal systems has been developed as an alternative to the volume method. The new method is used to estimate power potential for electric-grade systems in the Great Basin conventional hydrothermal assessment area. The results from this method are then compared to estimates from the volume method summarized by DeAngelo and Williams (2010). As part of their work, DeAngelo and Williams used Monte Carlo analysis to evaluate the estimated power capacity of 253 electric-grade hydrothermal systems across the Western US, 100 of which are within the current extent of the northern Great Basin. We have taken a similar approach using a set of parameters selected for Great Basin conventional hydrothermal systems, including distributions of reservoir volume, initial reservoir temperature, and effective fracture spacing. The results from the new method are shown to be comparable to those of DeAngelo and Williams. This new method has advantages over the volume method, including an explicit dependence of power potential on effective fracture spacing, and making the heat-to-electricity conversion a function of reservoir temperature. The data release accompanying this manuscrpt contains publicly available Python code for the estimation of likely power potential for any electric-grade hydrothermal systems (with uncertainty estimates) for systems with estimated distributions of the necessary parameters.

Topic: General

Thermal short-circuiting is one of the key challenges that limit the long-term performance of Enhanced Geothermal Systems (EGS). When a dominant flow path develops by a highly conductive fracture, it reduces the reservoir volume available for heat exchange and causes premature thermal breakthrough. Although near-wellbore flow management has been used to avoid preferential flow path occurrence, controlling permeability away from the wellbore is still challenging, because injected materials need to remain mobile during transport and form a solid flow plug only after it reaches the target location. A laboratory investigation is underway to solve this problem by using microparticles encapsulating reactants within a thin polymer shell. This shell is designed to withstand the lower injection temperatures for a limited time before thermally degrading and releasing diverter-forming reactants at the higher reservoir temperatures, enabling delayed, targeted plug formation away from the wellbore. To deploy this technology in the subsurface at a reservoir scale, it is critical to understand and predict how these microparticles are transported by a viscous carrier fluid in a fracture system before forming diverter plugs and altering the fracture permeability. In this study, we used a Eulerian-Lagrangian approach to numerically simulate multiphase flow within a fracture and the formation of a gel-type diverter plug at a target location. The impact of the factors affecting plugging performance is examined, including carrier fluid properties (viscosity and density), particle properties (particle size, density, and concentration in the mixture), gelation time and stability, fracture geometry, flow rate and boundary condition. Each is varied to evaluate its effect on permeability reduction and plugging effectiveness within the fracture, to identify and optimize the injection conditions that improve the plugging performance. The results of the study will provide the basis for later upscaling to a reservoir model that can assess the field applicability of the technology and the long-term effect on short-circuiting and heat extraction in EGS reservoirs.

Topic: Enhanced Geothermal Systems

The Upper Jurassic Smackover Formation in southwest Arkansas contains high-salinity brines with elevated temperatures and significant lithium concentrations, creating potential for combined lithium extraction and geothermal power co-generation. Using an extensive compilation of bottom-hole temperature (BHT) measurements from regional oil and gas wells, we estimate a lower-bound geothermal gradient of 36 C/km for Lafayette County. This gradient yields a Smackover reservoir temperature of approximately 116 C at a midpoint depth of 2725 m. With a total planned brine flow rate of 0.4166 m^3/s, deterministic flow-power calculations predict net 6.1 MW of geothermal co-generation, while Monte Carlo simulation (10K realizations) yields P5=5.94 MW, P50=8.01 MW, and P95=10.63 MW. Co-generation, using P50, could offset roughly 64.1 GWh/year (14.8%) of electrical demand for the planned lithium extraction facility. These results highlight the importance of robust gradient estimation using BHT-depth envelopes and demonstrate that geothermal co-production can provide a meaningful fraction of operational power for lithium brine facilities in southern Arkansas and adjacent areas.

Topic: Field Studies

Drilling hard, abrasive, and confined formations subjects polycrystalline diamond compact (PDC) cutters to high loads, accelerated wear, and inefficient rock grinding. This study quantifies whether abrasive-water-jet (AWJ) preconditioning immediately ahead of a PDC cutter can reduce cutter loads and mechanical energy demand while increasing rock failure. The scope is limited to completed single-cutter simulations in granite and compares mechanical-only, AWJ-only, and simultaneous hybrid cutting under matched traverse velocities and confinement conditions. The work targets hard-rock drilling applications utilizing current bit architecture. A three-phase LS-DYNA smoothed-particle-hydrodynamics (SPH)/finite-element (FE) framework used a 100×50×20mm granite domain represented by a calibrated Riedel-Hiermaier-Thoma (RHT) material model. Phase 1 simulated mechanical cutting with a rigid single PDC cutter. Phase 2 represented water and 5 wt% iron abrasive using SPH. Phase 3 combined them, positioning a 9.525 mm jet 5 mm ahead of the cutter. Eighteen accepted simulations covered traverse velocities of 1,000, 5,000, and 10,000 mm/s under unconfined and 10 MPa biaxially confined conditions. Matched comparisons used stabilized cutting and axial forces, failed volume per unit travel, and cutter mechanical specific energy (MSE). Mechanical only failed volume remained nearly unchanged across the velocity matrix. In contrast, AWJ only failure was strongly exposure time dependent: increasing traverse velocity from 1,000 to 10,000 mm/s reduced failed volume by 99.76% in unconfined granite and 99.33% under confinement. In all six matched comparisons, hybrid cutting reduced stabilized cutting force by 3.38-18.79% and axial force magnitude by 1.09-17.64%, while increasing failed volume per unit travel by 3.84-65.31%. Cutter MSE decreased by 5.83-51.54% in every hybrid case. The greatest benefits occurred at 1,000 mm/s: failed volume per unit travel increased by 65.31% and 59.46%, and cutter MSE decreased by 51.54% and 49.08%, for unconfined and confined granite, respectively. Confinement had its clearest restrictive effect at this velocity, where AWJ exposure was longest. The consistent force reduction, larger failed zone, and lower cutter MSE demonstrate effective preconditioning, although the benefit diminished rapidly as traverse velocity increased. This study provides a traceable, staged SPH-FEM comparison that separates mechanical cutting and abrasive jet erosion before combining them under identical rock geometry, velocity, and stress conditions. Unlike assessments based on a single force or crater metric, the hybrid response is evaluated using two cutter force components, normalized failed volume, and mechanical energy per failed volume. The resulting dataset quantifies the exposure time dependence of AWJ assistance and demonstrates that a leading abrasive jet can reduce local PDC cutter demand in confined hard rock while enlarging the failed zone.

Topic: Drilling

Rock integrity is a critical factor in the long-term performance of geothermal reservoirs. Chemical alteration of the host rock during brine circulation can progressively weaken the mechanical strength, reduce injectivity, and compromise wellbore stability over the life of a field. This study assesses the impact of four candidate treatment fluids (0.1 wt.% silica fume, 0.1 wt.% silica flour, 5 wt.% GLDA, and 5 wt.% EDTA) on the structural and mechanical integrity of carbonate rocks flooded at 100°C under both CO2-free and 5v/v% CO2-rich Red Sea water (RSW). The rock samples were characterized before and after the flooding experiments by conducting medical CT imaging, compressional and shear wave velocities (Vp/Vs), porosity, and permeability measurements. Medical CT imaging showed no wormholes or dissolution channels in core samples treated with silica fluids. GLDA-flooded cores showed a significant reduction in the CT number, indicating severe face dissolution. Flooding the core samples with EDTA fluid led to localized rock dissolution and a slight reduction in the CT number. However, the rock porosity changed by less than 0.3 percentage points in all tested cores, indicating that porosity alone cannot capture the loss of rock integrity. The dissolution mainly occurred within the intergranular cement rather than throughout the rock matrix. The elastic properties (Vp/Vs) proved more sensitive to the chemical injection. Young's modulus was reduced by an average of 7.5% post-flood across the treated cores. Young’s modulus decreased by an average of 7.5% after flooding across all treated cores. Poisson’s ratio increased from 0.27 to 0.32 for the EDTA-treated samples and from 0.18 to 0.21 for the GLDA-treated samples. The obtained results are consistent with grain-contact cement dissolution. Moreover, permeability showed a similar trend: it remained nearly unchanged after silica-fume treatment, decreased by 35% after silica-flour treatment due to fluid retention, and increased by 44% after EDTA treatment due to mineral dissolution. Overall, this study introduces an integrated approach to evaluate how fluid chemistry controls rock integrity during geothermal treatment. CT imaging and elastic properties were the most reliable indicators for evaluating rock integrity. Silica-based fluids preserved carbonate rock integrity better than chelating agents. These findings can guide fluid selection to maintain wellbore stability and support safe, long-term geothermal energy production

Topic: Reservoir Engineering

Reliable assessment of geothermal potential remains challenging because subsurface thermal behavior reflects nonlinear interactions among geological architecture, structural permeability, geophysical signatures, and well conditions, while available observations are spatially heterogeneous and often unevenly sampled. This study develops a generalizable physics informed machine learning framework for predicting geothermal thermal potential, quantifying predictive uncertainty, interpreting the physical controls learned by data driven models, and translating complex model behavior into an analytical screening criterion. A large nationwide geothermal well database from the United States is used as a heterogeneous development and validation test bed, while the framework is formulated using physically defined predictors that can be reconstructed in other geothermal provinces. Exploratory data analysis, spatial statistics, feature engineering, nonlinear relevance analysis, redundancy screening, and spatially stable feature selection are first used to construct a physically consistent predictor space while preventing target leakage and geographic memorization. Strong tabular and neural baselines are compared with a physics informed cross attention architecture that represents geological, structural, geophysical, and well context as interacting information domains. Model selection and hyperparameter optimization are performed using nested spatial cross validation, with geographically separated holdouts used to assess transferability beyond randomly partitioned observations. Predictive reliability is characterized through heteroscedastic uncertainty modeling, deep ensembles, and conformal calibration to distinguish high predicted geothermal potential from high confidence geothermal potential. Model reasoning is investigated using SHAP attribution, SHAP interaction analysis, accumulated local effects, attention based interpretation, and physics consistency tests to identify both individual controls and coupled mechanisms governing predicted thermal conditions. Finally, symbolic regression is applied to stable physical predictors and out of fold model responses to derive a compact geothermal screening index and a locked decision threshold for distinguishing elevated thermal potential. The proposed framework therefore moves beyond black box geothermal prediction toward an uncertainty aware and physically interpretable scientific machine learning approach capable of producing continuous thermal estimates, prospect probabilities, confidence bounds, mechanistic insights, and a transferable analytical screening relationship for regional geothermal exploration.

Topic: Emerging Technology

[Horne]

Introduction to the 52nd Stanford Geothermal Workshop Roland HORNE [Stanford University, USA]

An introduction to the 52nd Stanford Geothermal Workshop.

Topic: Introduction

[Horne1]

Test Paper: A Grand New Concept in Geothermal Roland HORNE, Bob JONES and ZHANG Ziyi [Stanford University, USA]

The deeply hidden fires of the earth Provide a constant source of power and heat, A steady force of planetary worth, Where strength and clean utility will meet. No fickle wind or shifting cloud restrains This steady energy from deep below, A constant current through the metal veins, Where endless streams of boiling waters flow.

Topic: Reservoir Engineering

Supercritical geothermal energy has long been regarded as one of the most promising pathways to transformational renewable power generation; however, despite more than four decades of international drilling efforts, sustained commercial production from confirmed supercritical reservoirs has not yet been achieved. This paper presents the first comprehensive engineering-framework post-mortem analysis of supercritical geothermal wells (T greater than 374°C and/or P greater than 221 bar) drilled worldwide between 1981 and 2026. The dataset comprises 20 entries across six countries-Iceland, Japan, Italy, the United States, Mexico, and Kenya-evaluated using a consistent seven-category failure mode taxonomy (FM-1 to FM-7), including one aggregated entry representing five Los Humeros wellbores with an identical failure profile. For each well, failure mechanisms are systematically examined through quantified operational parameters, root-cause determination, and cross-well pattern analysis to identify recurring engineering limitations. Moving beyond retrospective assessment, the paper proposes four original candidate engineering frameworks intended for independent review and validation by the wider geothermal community: (1) a Deterministic Failure Chain (DFC) describing progressive failure evolution across all basin types; (2) an Axial Compliance Framework (ACF) integrating five coupled thermomechanical mechanisms with the Norton Power Law and Larson-Miller creep rupture criterion to quantify structural survivability; (3) a dual-constraint Thermo-Mechanical and Chemical Survivability Envelope (DCSE) defining simultaneous operating limits for long-term well integrity; and (4) a Basin Risk Index (BRI) providing a structured predictive methodology for assessing technical risk during future supercritical geothermal well planning.

Topic: General

The mid-to-deep single-well closed-loop geothermal system (CLGS) is considered an important pathway for efficient geothermal energy exploitation. However, under long-distance circulation conditions, significant hydraulic pressure losses in the wellbore result in excessive pumping power consumption, which limits the overall efficiency of the system. Existing studies mainly focus on wellbore structure and heat transfer parameter optimization, while the coupling between working-fluid rheology and deep-well hydraulic losses has not been systematically quantified. This study proposes a non-Newtonian fluid-based drag reduction strategy for geothermal wellbores. The objective is to investigate whether polymer additives can effectively reduce circulation resistance and identify optimal operating conditions for non-Newtonian fluids through multi-parameter optimization, thereby reducing pumping energy consumption. An integrated framework combining experimental characterization, numerical simulation, and optimization is developed. Polymer materials including Hydrolyzed Polyacrylamide (HPAM), Xanthan Gum (XG), Polyethylene Oxide (PEO), and Welan Gum (WG) are used to modify conventional water-based working fluids. Rheological properties are characterized through power-law parameters measured under different concentrations and temperatures. A thermo-hydraulic coupled model of a single-well CLGS is established to simulate heat transfer and pressure loss under deep geothermal conditions. Furthermore, a genetic algorithm (GA) is applied to optimize operating parameters, including circulation flow rate, well depth, and geothermal gradient. Compared with conventional water, non-Newtonian polymer fluids at specific concentrations demonstrate significant drag reduction performance in deep well circulation, with wellbore pressure losses reduced by 63%–75%. The GA optimization identifies optimal operating parameter combinations under different geothermal gradients, further improving the drag reduction performance of various non-Newtonian fluids. The study provides a new fluid regulation strategy for CLGS design and offers theoretical insights and engineering guidance for achieving low-pumping-power and high-efficiency development of mid-to-deep geothermal resources.

Topic: Modeling

Regional groundwater flow changes both the apparent thermal conductivity measured around a geothermal borehole and the operating life of the surrounding borefield for ground source heat pump applications. Conventional thermal-response-test interpretations assume conduction-dominated heat transfer. When a borehole intersects an active aquifer, groundwater advects heat away from the borehole and produces a directional, depth-dependent temperature response. A conduction-only interpretation attributes this additional heat transfer to an elevated thermal conductivity, although the intrinsic conductivity of the formation has not changed. This study develops a three-dimensional coupled groundwater-flow and heat-transport model for geothermal boreholes partially penetrating an active aquifer. The simulations quantify the effects of groundwater velocity, aquifer thickness, penetration ratio, formation thermal properties, borehole spacing, and operating time. Synthetic temperature responses are interpreted using a conventional conduction-based model to determine how groundwater advection affects the inferred apparent thermal conductivity. The results are organized using the thermal Péclet number, dimensionless aquifer thickness and penetration ratios, conductivity and diffusivity ratios, and the borehole Biot number. The Nusselt number measures the resulting heat-transfer enhancement. These dimensionless groups define conduction-dominated, transitional, and advection-dominated regimes and allow the results to be transferred among different aquifer and borehole configurations. Groundwater flow increases apparent thermal conductivity, displaces the thermal plume downstream, and directly controls borefield service life. It supplies thermally undisturbed water to upstream boreholes and can delay temperature decline, while transporting cooled or heated water toward downstream boreholes and accelerating thermal interference. Consequently, the commonly adopted 20-year design horizon is not a universal limit. Depending on groundwater velocity, flow direction, and borefield configuration, it can either underestimate or overestimate the useful operating life. The resulting dimensionless response maps support correction of thermal-response-test interpretations and performance-based prediction of borefield service life. They also provide a practical basis for selecting borehole depth, spacing, orientation, and sustainable thermal load in direct-use geothermal, ground-source heat-pump, and borehole thermal-energy-storage systems.

Topic: Direct Use

Several approaches implementing supervised machine learning have been proposed for mapping hydrothermal favorability in the Great Basin over the last two decades. Models are typically pointwise (each cell predicted from its own feature values alone) and evaluated with random train-test splits that can place training and testing wells spatially very near to one another. Because both labels and evidence layers are spatially autocorrelated, random pointwise splits can reward memorizing local conditions over learning transferable relationships, inflating reported predictive skill. We quantify this inflated predictive skill using three architecturally distinct models trained on the same 53 evidence layers and 100 Monte Carlo realizations: a pointwise linear regression, XGBoost, and an image-based convolutional neural network (U-Net) that predicts favorability from 12.8 km patches, adding spatial context. Models are evaluated under two spatial split protocols: 1) random pointwise splits used by prior work; and 2) spatially buffered cross-validation (SB-CV), which withholds entire image patches rather than individual wells. The SB-CV protocol also includes a buffer to guarantee no training point is within 4 km of a test point or a known power-producing system. Each model produces a favorability map from the median prediction over the 100 realizations; we score the area under the curve (AUC) of power-producing systems versus prediction percentile. All models lose skill under the SB-CV versus random pointwise splits: AUC falls from 0.916 to 0.887 for linear regression, from 0.959 to 0.894 for XGBoost, and from 0.955 to 0.856 for the U-Net, the largest drop belonging to the model with the most spatial context, which under SB-CV ranks below both pointwise models. Skill and the footprint of the map reported as highly favorable are decoupled; at comparable AUC, the fraction of the basin flagged as highly favorable ranges from ~1% (U-Net) to ~20–37% (pointwise models). Model architecture also changes which known systems rank as having the highest favorability. The two pointwise models rank systems nearly identically (Spearman correlation ρ≈0.81), whereas the U-Net favors a materially different set (ρ≈0.47). We recommend reporting spatially buffered metrics, map footprint, and system-ranking agreement alongside random-split AUC.

Topic: General

Previous oil-and-gas studies have evaluated surface-to-borehole, borehole-to-surface, crosswell, and single-well electromagnetic (EM) configurations for appraising fractures containing electrically conductive proppant. For deep enhanced geothermal systems (EGS), a single-well architecture is operationally attractive but electromagnetically challenging: both transmitted and fracture-induced secondary fields must traverse steel casing, which attenuates and redistributes them. Resistive crystalline host rocks improve field propagation and target contrast outside the well but do not eliminate casing-related attenuation of EM fields. This study develops a synthetic 2D axisymmetric COMSOL forward-modeling and inversion workflow to quantify the detectability and parameter recoverability of a single circular fracture containing electrically conductive proppant under representative cased-hole geothermal conditions found in the Utah FORGE site. A transition boundary condition represents the thin steel casing. The analysis identifies spacing-specific operating frequencies and compares residual-weighting strategies, background-response transformations, and receiver configurations. Our optimized workflow was evaluated using a noise model comprising zero-mean Gaussian perturbations with an 8% relative standard deviation and a 10-9 V absolute noise floor combined in quadrature. Under these conditions, the workflow yields a mean 95th-percentile absolute percentage error of 23.47% across the evaluated parameters and target cases. For the 92 m target fracture radius, the P95 absolute radius error is 41.43% (38.11 m), whereas for the 14 m target radius, the error decreases to 17.30% (2.42 m). Reducing the absolute noise floor to 10-10 V decreases these errors to 26.12% (24.03 m) and 7.86% (1.10 m), respectively, indicating that long-spacing measurements are strongly limited by the assumed voltage floor. Under the corresponding fiberglass or electrically nonconductive casing model, errors decrease further to 7.44% (6.84 m) and 1.59% (0.22 m), respectively. These results establish a quantitative synthetic basis for designing multi-frequency, multi-spacing, single-well EM measurements through steel casing to constrain conductive-proppant extent. Coupling this workflow with short-spacing 3D inversion could additionally enable fracture dip and asymmetric geometry to be represented within a unified inversion result. The assumed noise model represents a conservative stress test rather than a calibrated instrument specification.

Topic: Reservoir Engineering

Acidic fluids in high-temperature geothermal systems create reservoir and well integrity management challenges beyond corrosion control, because acidity can influence reservoir performance, reinjection strategy, well integrity, and long-term production sustainability. Although many field experiences exist, lessons are often separated between geochemistry, reservoir engineering, and well materials studies, which limit their transfer across projects. This paper synthesizes reservoir and well integrity management lessons from geothermal systems where acidic fluids have affected field development and operation. A comparative review used three field case studies: Rotokawa (New Zealand), Los Humeros (Mexico), and Krafla (Iceland). Published conceptual models, geochemistry and alteration studies, reinjection histories, reservoir monitoring data, and well integrity reports were evaluated to compare acid-fluid origins, operational impacts, mitigation responses, and decision trade-offs. Firstly, the review indicates that acidic-fluid risks are strongly site-specific. At Rotokawa, CO2-rich steam-heated fluids and acid-sulfate conditions in an aquifer above the deep reservoir contributed to severe external casing corrosion in several wells. Early shallow reinjection appears to have helped resaturate and partly neutralize this corrosive aquifer by diluting or displacing acidic fluids and suppressing boiling, but this strategy also created ground uplifting concerns. Later management therefore shifted toward deeper and more peripheral reinjection, which improved pressure support, reduced shallow operational constraints, and helped limit direct cooling returns to the production sector. At Los Humeros, acidic conditions are linked to a complex superhot system involving boiling, phase separation, steam condensation, advanced argillic alteration, meteoric recharge, and possible magmatic contribution. Alteration zoning and surface CO2 monitoring indicate active fluid pathways and reservoir response, showing the value of combining geochemistry, structural interpretation, and reinjection surveillance. At Krafla, IDDP-1 demonstrated the large energy potential of HCl- and HF-bearing superheated steam, but also revealed severe operational limits from acid condensate, silica scaling, casing failure, and high-temperature material degradation. These cases show that acidic geothermal systems should be managed as coupled reservoir and well integrity problems, rather than merely surface facility problems. Effective reservoir and well integrity management requires site-specific fluid characterization, adaptive reinjection planning, corrosion-aware well design, and continuous monitoring from early field development through long-term operation under evolving reservoir and production conditions.

Topic: Reservoir Engineering

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 the Basin and Range province, high-permeability faults linked to deep crystalline basement rocks facilitate upward circulation of hot fluids, yielding gradients far exceeding background levels. GPFA's data-driven approach 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, applying Adaptive Heat Flow/Temperature 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 variable heat flow, thermal conductivity, radiogenic heat production, temperature dependent thermal conductivity 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.

Topic: Enhanced Geothermal Systems

Geothermal wells frequently experience declining injectivity and productivity due to stress-induced alteration of flow paths, mineral scaling, and loss of connectivity within natural fracture networks. Stimulation through Hydroshearing has historically been employed to enhance permeability, where elevated pressures promote slip along pre-existing fractures. However, extensive field evidence demonstrates that the effects are largely transient. Recent field diagnostics show that sustained enhancement in geothermal systems requires maintaining mechanical aperture, achievable only through opening-mode (tensile) fractures stabilized by various proppants. This article builds a technical and economic case for proppant-based hydraulic fracturing as a sustainable stimulation strategy in hydrothermal geothermal reservoirs. Drawing on historical EGS examples, three principal paradigms where proppant placement provides distinctive value, have been proposed: (1) extending permeability away from major faults to connect low-flow zones into active reservoir corridors; (2) strategically fracturing within injector–producer patterns to improve field-scale connectivity and thermal sweep; and (3) directly propping fault and feed-zone structures to prevent stress- or thermally-induced closure. Collectively, these strategies can maintain or restore plant capacity without costly make-up wells. The article addresses overcoming the existing operational challenges, including deviated well trajectories, slotted liners, high formation temperatures, and complex fracture geometries. Modern completions and fracturing technologies including advances in stimulation chemistry portfolio are discussed. High-viscosity, non-damaging fluids, zonal isolation packers, reliable degradable diverters, and temperature-resistant ceramic proppants can enable reliable placement even in geothermal wells at 250–300°C. Laboratory tests and modeling confirm that such proppants maintain conductivity under sustained stress and thermal cycling, resisting creep and chemical degradation that limit traditional sand systems. An economic analysis contrasts the cost-benefit analysis of proppant stimulation ($1 – 2 million per well) with new, makeup well drilling ($6 – 10 million) and shows that modest injectivity improvements (5 – 10%) can preserve several megawatts of capacity in a 30 - 50 MW power plant, translating to a significant reduction in levelized cost of electricity. Beyond economics, proppant-based fracturing offers improved predictability and design control relative to hydroshearing, supported by decades of oil-and-gas modeling tools adaptable to geothermal stress regimes. In conclusion, proppant-assisted hydraulic fracturing provides a durable, mechanically supported permeability enhancement mechanism for hydrothermal reservoirs where shear and thermal stimulation alone are inadequate. By integrating EGS learnings, high-temperature materials, and modern stimulation design, this approach can extend the productive life of hydrothermal fields, reduce the frequency of make-up drilling, and help close the gap between hydrothermal and engineered geothermal resources. The study advocates for pilot demonstrations to quantify performance gains and refine techno-economic parameters, marking a critical step toward sustainable, high-efficiency geothermal power generation.

Topic: Enhanced Geothermal Systems

The Rukwa Rift Basin (RRB), located within the western branch of the East African Rift System (EARS), hosts numerous thermal springs that indicate the presence of an active geothermal system associated with rift-related tectonics and elevated heat flow. However, the hydrogeochemical processes governing fluid evolution, reservoir characteristics, and geothermal potential within the basin remain poorly constrained. This study investigates the hydrogeochemistry of geothermal waters from the southern and southeastern parts of the RRB to determine fluid origin, evaluate water–rock interaction processes, assess mixing and cooling mechanisms, estimate reservoir temperatures, and develop a conceptual geothermal model. Hydrogeochemistry, trace elements, and geothermometric analyses were performed on thermal spring waters and associated groundwater samples. The geothermal fluids are predominantly characterized by the Na–HCO₃ hydrochemical facies, indicating extensive interaction between meteoric recharge waters and the reservoir rocks during deep circulation within the rift system. The hydrogeochemical signatures further indicate that fluid migration is strongly controlled by fault systems, which facilitate deep circulation, heating, and prolonged water–rock interaction. Geothermometric evaluations using silica and cation geothermometers indicate reservoir temperatures of approximately 140-150 °C, suggesting a moderate-enthalpy geothermal resource. Relationships among conservative ions (B, Li, Cs, Rb, Sr) against chloride reveal that ascending geothermal fluids undergo varying degrees of mixing with shallow groundwater and conductive cooling before discharge at the surface. Based on the integrated hydrogeochemical evidence, a conceptual geothermal model is proposed in which meteoric waters recharge the system through elevated rift shoulders and surrounding highlands with minimum inputs from Lake Rukwa, infiltrate along major extensional faults, and circulate to depth where they are heated by anomalous geothermal gradients associated with lithospheric extension and tectono-magmatic activity. The heated fluids subsequently ascend through permeable fault networks, undergo further water–rock interaction, partial mixing, and cooling, and finally emerge as thermal springs at the surface. The study demonstrates that the Rukwa Rift Basin hosts a fault-controlled geothermal system with significant geothermal resource potential and provides a hydrogeochemical framework for future exploration and development of geothermal energy resources in southwestern Tanzania.

Topic: Geochemistry

Tracer flow testing is the routine measurement of well output in terms of mass flow and enthalpy in two phase pipelines and is of utmost importance in understanding reservoir performance. This is carried out by injection of exclusively non-radioactive and non-toxic tracers of high chemical and thermal stability- greater than 330oC. High precision multi-phase tracer metering systems with rapid-pulse tracer injection is used as the injection equipment to maximize concentrations at high flow and pressure. Multi-phase sampling separators are used for water-brine and gas-steam sampling. Analysis of samples is carried out by use ultra-specific and sensitive methods which include Gas chromatography and UV-Vis/fluorescence. Interpretation of data is carried out by numerical reservoir simulation services and not just qualitative and quantitative interpretation of results. This kind of tracers are injected in the flow line and sampling is downstream of the injection point. Liquid tracers injected must be conservative- cannot partition significantly to the vapor phase, decay chemically or thermally while in the reservoir for the measurement period. They must also be very detectable at ultra low concentrations without interference from high concentrations of dissolved minerals in the produced water. Naphthalene sulphonates (NSA) are used for brine phase and Sulphur Hexafluoride (SF6) for gas phase. Interpretation of tracer flow test data is only used quantitatively.

Topic: Tracers

Injection flow in a multistage enhanced geothermal system is rarely distributed uniformly, yet the long-term thermal consequences of that heterogeneity are not well constrained. This study uses a three-dimensional, field-informed Utah FORGE discrete-fracture model to examine how alternative stage-level injection allocations affect production temperature, thermal breakthrough, instantaneous power, and cumulative heat recovery. Decadal thermo-hydraulic simulations compare the field-observed allocation with equal, toe-biased, mid-well-concentrated, and heel-and-toe-biased profiles over a range of total circulation rates. The results show a consistent performance ranking across the tested rates. Toe-biased injection preserves the highest production temperature, delays thermal decline, and delivers the greatest cumulative energy, whereas the field-observed allocation cools most rapidly. The toe-side advantage reflects both favorable circulation pathways and access to deeper, hotter reservoir zones along the inclined Utah FORGE wells. Equal and mid-well allocations provide intermediate improvements, while concentrating flow at both ends offers only a modest benefit. The advantage of favorable allocation becomes more pronounced as total rate increases, demonstrating that injection rate and flow placement cannot be optimized independently. These findings identify stage-level flow allocation as a practical reservoir-management control. Redistributing flow toward pathways with greater effective heat-transfer volume and higher formation temperature can improve thermal sweep and sustain heat recovery without changing the stimulated reservoir volume.

Topic: FORGE

Few published data of average pore pressure are available for two-phase flow in fractures from field studies. The in-situ water and gas saturations are normally not known for two-phase flow in natural fractures; therefore, the direct measurements of average pore pressure are difficult in field-scale. With the help of a case study prior to the 2003 Mw 6.8 Chengkung earthquake, groundwater radon was used as a tracer to determine the gas and water saturations in a small naturally fractured aquifer. By taking the volume average of the pressure in the two phases (air and water), we can determine average pore pressure. Using the radon-concentration data prior to the 2003 Mw 6.8 Chengkung earthquake, we gain an improved understanding of precursory behavior of average pore pressure and two-phase flow in a fractured aquifer.

Topic: Reservoir Engineering

Comparative Hydrothermal Alteration and Clay Mineralogy of Intracaldera and Extracaldera Wells in the Olkaria Geothermal Field: Within Caldera OW-736 and outside the ring OW-922 Abstract Clay minerals serve as critical indicators of hydrothermal alteration, providing valuable insights into temperature gradients, fluid chemistry, permeability patterns, and the evolution of geothermal reservoirs. This study compares the subsurface clay mineralogy between intracaldera and extracaldera environments within the Olkaria geothermal field to evaluate structural controls on hydrothermal alteration. Drill cuttings and core samples from well OW-736 (drilled within the caldera boundary) and well OW-922 (drilled outside the caldera ring structure) were analyzed using X-ray Diffraction (XRD), the Methylene Blue spot test, and Scanning Electron Microscopy (SEM). The investigation evaluated the vertical distribution, transition zones, and relative abundance of key clay assemblages, including smectite, mixed-layer illite-smectite (I/S), illite, chlorite, and chlorite-smectite (C/S). Results indicate that well OW-736 displays a shallower onset of high-temperature alteration assemblages (illite and chlorite) and more intense mineral replacement, reflecting higher heat flow, enhanced permeability, and proximity to primary upflow zones driven by intracaldera magmatic activity. Conversely, well OW-922 is characterized by a deeper smectite-to-illite transition zone and a dominance of low-to-moderate temperature clays, consistent with lower thermal gradients and lateral fluid outflow towards the extracaldera margins. These mineralogical distinctions elucidate the subsurface hydrological and thermal framework of Olkaria, offering critical criteria for refining the conceptual reservoir model, delineating clay-cap geometry, and optimizing future drilling targets.

Topic: Geology

Enhanced geothermal systems have attracted increasing attention for the development of deep hot dry rock geothermal resources. Water is generally considered the preferred working fluid for extracting heat from hot dry rock reservoirs. CO2 can serve as an alternative working fluid while providing a pathway for carbon capture and utilization. However, whether CO2 provides economic advantages over water remains uncertain. This study establishes a three-dimensional coupled thermo-hydraulic numerical model to simulate an enhanced geothermal system with dimensions of 300 m × 300 m × 300 m over a 30-year operational period. Discrete fracture networks generated through Monte Carlo simulations are coupled with an equivalent porous medium model to represent fractured reservoirs. For reservoir conditions where temperature exceeds 31 °C and pressure exceeds 7.38 MPa, CO2 exists in a supercritical state. A life-cycle techno-economic assessment framework is developed, covering capital expenditures such as well drilling, surface power plant construction, pressurization equipment, and working fluid procurement, as well as geothermal power generation revenue, to calculate the levelized cost of electricity and discounted payback period. The results indicate that under the investigated reservoir conditions and operating parameters, for the same working pressure, the specific heat capacity of water is 2.8 times that of CO2. However, CO2 has much lower viscosity and achieves a mass flow rate of 17.5 kg/s, compared with only 3.4 kg/s for water. Thermal breakthrough occurs at Year 4 for the CO2 system, earlier than Year 5.2 for the water system. Nevertheless, the CO2 system maintains a higher thermal extraction rate throughout the entire operation period. Economic calculation shows that the upfront capital investment of the CO2 system is approximately twice that of the water system. However, higher annual electricity generation revenues, resulting in a discounted payback period of only 15.8 years, compared to 18.6 years for the water system. The minimum levelized cost of electricity of the CO2 system reaches 0.32 CNY/(kW·h), less than half of the water system's value of 0.67 CNY/(kW·h). Overall, under the specific reservoir parameters and operating conditions investigated in this study, CO2 has better techno-economic performance than water as a heat extraction fluid in the studied hot dry rock enhanced geothermal system, indicating its potential as a cost-effective pathway for geothermal power generation. These findings provide quantitative guidance for working fluid selection in hot dry rock reservoir development.

Topic: Enhanced Geothermal Systems

The long-term performance of a multistage enhanced geothermal system (EGS) depends on the ability of individual fractures to extract heat from their surrounding rock volumes. Conventional one-dimensional half-space models neglect lateral heat recruitment beyond the active fracture footprint, whereas infinite-domain models do not represent depletion of the finite tributary volume assigned to each fracture. These assumptions can produce substantial and opposing errors as fracture geometry, stage spacing, and operating time change. This study develops a reduced-order framework for quantifying conductive heat transfer between a thermally active fracture and a finite anisotropic rock matrix, with direct application to multistage fractured geothermal reservoirs. Each fracture face is represented by a finite axisymmetric matrix cell containing a circular active contact. The model accounts for aligned thermal anisotropy, insulated outer boundaries, and a prescribed area-averaged contact temperature. The resulting boundary-value problem is reduced to a Laplace-domain thermal impedance. Responses to maintained temperature conditions are obtained by numerical inverse Laplace transformation, while a direct spectral-state formulation evaluates arbitrary temperature histories without repeated convolution. The behavior is described primarily by dimensionless variables including the cell-to-contact radius ratio, the effective thermal aspect ratio, and the normal Fourier number. These scaling variables separate the effects of fracture contact area, stage spacing, anisotropy, thermal storage, and operating duration, allowing results to be transferred across reservoir scales and used efficiently in system design and optimization. The illustrative example is designed to identify controlling heat-transfer regimes and quantify errors introduced by simplified matrix models, rather than reproduce a specific field history. The analysis is therefore presented first in dimensionless form. The resulting response maps show when lateral heat recruitment increases fracture heat supply and when finite-volume depletion becomes dominant. A dimensional baseline with a 24 m symmetric fracture spacing is then used to demonstrate the engineering interpretation. For an 80 K maintained mean temperature deficit, the model extracts 27.06 TJ after 30 years, corresponding to 50.9% of the assigned thermal inventory. The one-dimensional half-space approximation underpredicts this result by approximately 43% because it excludes lateral heat supply. Comparison with a finite-volume simulation gives differences of 0.033% in heat rate and 0.117% in cumulative energy for the finest tested mesh. The spectral solver also reproduces thermal memory and heat-flow reversal under a nonmonotonic temperature history. For multistage EGS applications, the finite-cell response provides a stage-level thermal kernel that can be coupled with fracture-flow and reservoir models. Dimensionless response maps enable rapid screening and optimization of stage spacing, thermally active area, conductivity anisotropy, and operating duration. Extension to hydraulically communicating fractures, unequal stage loading, and coupled production-temperature prediction provides a path toward practical reservoir-scale design.

Topic: Reservoir Engineering

Outflows are the regions of lateral convection/advection away from deep upflow zones of geothermal systems that are a function of buoyant hot fluid reaching the water table or shallower permeability features that initiate more horizontally-direct flow. These features are intrinsic components of liquid-dominated convective geothermal systems, and many initial indications of geothermal systems that can be detected at the surface, commonly including thermal manifestations and a significant fraction of low resistivity caps, are more closely related to outflows rather than to upflows. Outflow attributes are controlled by, and provide insight into, the subsurface permeability structure, fluid saturation state, interaction with adjacent marginal fluids, regional hydrology, and natural state mass flux, and their characterization provides valuable information that can be applied to vectoring upflow locations during exploration. Additionally, while outflows are common targets for injection, high-, medium-, and low-temperature geothermal outflows are also targets for production in many developed systems around the world. Some notable advantages of targeting outflows for either injection or production include the shallower associated target well depths as well as the elevated matrix or fracture-based permeability that is commonly encountered in outflows. Outflow parameters such as temperature, lateral temperature gradient, depth, thickness, area, directionality, chemistry, permeability, flux, quantity, and termination style all affect their development potential for production. Twenty well-characterized reservoir case histories from around the world are included to illustrate the parameters for outflows from producing and drilled but undeveloped geothermal fields and to support recommendations for terminology to assist with outflow characterization. The distribution of manifestations, trends in geochemistry, geophysical data, and temperature profiles are included to illustrate the importance of considering outflow properties into conceptual models and numerical simulation sensitivity analyses are performed to illustrate the influence of mass flux and permeability contrasts on outflow geometries.

Topic: Geology

Direct energy drilling using Millimeter Wave (MMW) technology has the potential to access deep geothermal resources, circumventing some technical limitations of conventional mechanical drilling. The ablation process generates a dusty plume of rock fragments or vapor with a measured mean particle diameter of 100 µm, that must be rapidly quenched and removed from the ablation cavity. Although scattering losses are limited for such fine particles, prolonged residence may increase local particle concentrations and promote plasma breakdown. Efficient particle removal is therefore important both to maintain exposure of fresh rock and to limit particulate accumulation within the high-field region. While one-dimensional wellbore models are capable of describing particle transport through the annulus, gas–particle dynamics within the ablation cavity remain unresolved and must otherwise be represented through prescribed closure conditions. To address this, a compressible Eulerian–Eulerian multiphase model is applied to study the evolution and transport of a dusty plume within a representative MMW ablation cavity. The model captures viscous gas–particle interactions in a confined geometry across dilute to dense particle concentrations and has been validated across subsonic to hypersonic flow conditions. These simulations can then be used to characterize entrainment, recirculation, accumulation, and particle residence time within the cavity, and to quantify the particulate flux entering the return annulus.

Topic: Modeling

This paper presents a time-domain series approximation, herein termed the erfc solution, for the Gringarten et al.\cite{1975gwo} geothermal reservoir model involving multiple parallel vertical fractures. The original model requires numerical inversion from the Laplace domain, while this approximation offers an analytically transparent alternative derived through a linear expansion of the exponential function. The time-domain indicates clearly how the numerous parameters of the problem enter into the solution. Using parameters from the Fervo Blue Mountain project, we evaluate the accuracy of this approximation against the exact Laplace solution. Results indicate that the dimensionless Fourier number serves as a critical threshold for solution validity. The erfc solution is highly accurate for short-term simulations where thermal interaction is weak. However, it significantly overestimates produced fluid temperature and electrical power output as thermal interference becomes strong over extended production times. This work provides a practical tool for early-stage geothermal well design and reservoir cooling forecasts.

Topic: Modeling

Drilling long inclined/horizontal wells in hard, crystalline rock remains one of the principal economic barriers to next-generation geothermal systems. Downhole Drive Unit (DDU) addresses these chalenges directly – modular, stackable downhole units grip the formation and apply thrust and torque at the bit itself, independent of drillstring weight, under closed-loop control electronics capable of modulating WOB with high frequency. DDU has now completed three sequential field-test phases in 2026 at the NORCE Ullrigg Research and Test Centre in Stavanger, Norway, demonstrating that hydraulically gripping the borehole wall to react weight-on-bit (WOB) and torque directly into the formation is a viable route to overcoming the two dominant barriers to economic hard-rock geothermal drilling: insufficient, poorly controlled WOB delivered through a long, compliant drillstring, and torsional stick-slip dysfunction that caps achievable rate of penetration (ROP). Across the programme, the system delivered up to 32,000 lbf of controlled downhole thrust while the drillstring above continued to rotate, drilled hard Phyllite and operated also in oversized and irregular borehole geometry. The Ullrigg programme progressed from single-unit gripping and drive validation through synchronised dual-unit drilling towards drilling with downhole motor. A phase planned for October 2026, will run a direct side-by-side with and without the system in harder and deeper formation to isolate the performance uplift attributable to the technology, with results available ahead of the workshop. These results speak directly to the drilling economics that constrain deep and enhanced geothermal development. The paper presents the full 2026 Ullrigg field validation dataset, the engineering challenges encountered and resolved between phases, and the outlook for commercial deployment as an enabling technology for cost-effective drilling of deep, hot, hard-rock geothermal wells.

Topic: Drilling

The thermal performance of enhanced geothermal systems (EGSs) can be substantially degraded by premature thermal breakthrough caused by preferential fluid pathways and hydraulic short-circuiting. This study provides a critical review of recent techniques for alleviating thermal breakthrough in EGS reservoirs and outlines emerging research opportunities. The review is intended to highlight advanced methods with demonstrated or potential effectiveness, clarify the principal technical limitations that remain unresolved, and establish perspectives for future investigation. Distinct from earlier reviews, this work synthesizes recent advances from multiple disciplines and systematically examines the relationships, differences, advantages, and limitations among major thermal breakthrough mitigation strategies. Five principal approaches that have been proposed or investigated are assessed: optimization of fluid-flow management, intermittent heat-production schemes, application of carbon dioxide (CO2) as a circulating fluid, modification of fracture conductivity, and implementation of temperature-responsive fluids. Results reported in the literature indicate that regulation of circulation rates together with real-time reservoir monitoring and operational control can significantly enhance EGS thermal performance; however, such measures may increase operational expenditures and potentially elevate induced-seismicity risks. Intermittent heat extraction, involving alternating production and shut-in periods, facilitates thermal recharge of the reservoir and consequently postpones the deterioration of production-fluid temperature. The use of CO2 as a heat-transfer medium may improve fluid distribution and expand effective heat exchange throughout fracture networks, thereby increasing recoverable thermal energy. Temperature-sensitive proppants provide another promising mechanism by adaptively modifying fracture flow capacity in response to local thermal conditions. Similarly, temperature-responsive fluids can increase flow resistance within cooled regions and preferentially divert circulation toward hotter fractures, resulting in a more spatially uniform thermal sweep. Promising future directions include the development of nanofluid-based heat-transfer systems and reactive-tracer technologies for improved reservoir characterization and control. Ultimately, combining complementary mitigation mechanisms within the proposed multi-level framework may enable an integrated strategy for managing thermal breakthrough and sustaining long-term EGS heat production.

Topic: Enhanced Geothermal Systems

Heat extraction in traditional closed-loop geothermal systems is limited by the small heat exchange area between the rock and wellbore. To overcome this limitation, an augmented closed-loop geothermal system (ACLGS) is proposed in this study to improve heat production. The ACLGS integrates a hydraulic fracture, segmented by a horizontal isolator to achieve zonal isolation of fluid flow within the fracture, into the closed-loop system's circulation. A three-dimensional numerical model of the ACLGS was developed and validated to simulate heat extraction under various conditions, including different fracture geometries, rock permeability, and temperature dependence of rock thermal properties. The performance of smart working fluid, with automatic response to temperature, in improving heat extraction is also explored. The effectiveness of complex fracture designs, including branched and multi-wing fractures, in boosting heat production was also investigated. Results show that incorporating a double-wing fracture significantly increased cumulative heat extraction by more than 150% over a 20-year period. Both fracture half-length and height were found to have a substantial impact on the system's heat production. A branched fracture improved cumulative heat extraction by above 320% over 20 years, and incorporating interlaced sub-branches can further enhance heat extraction. The system’s thermal performance is better when considering temperature-dependent rock thermal properties than when assuming constant properties. Notably, smart fluid with strong temperature responsiveness can noticeably mitigate thermal breakthrough of the ACLGS, thus improving long-term heat extraction performance.

Topic: Emerging Technology

Geothermal reservoirs are commonly associated with elevated rates of earthquakes, motivating concerns about potential seismic hazards with new or expanded geothermal energy projects. While this seems to be true at high-enthalpy hydrothermal systems (Coso, The Geysers) and in enhanced geothermal systems (Basel, Cape Station), low-enthalpy hydrothermal systems in the Basin and Range are typically seismically quiet. We monitored one such system, Lightning Dock Geothermal in New Mexico, with four borehole geophones for over 17 months (05/2025 – 09/2026). We implemented a near-real time monitoring system for seismic detection and location using QuakeMigrate, then re-processed the full dataset using QSeek. We observed 18 microearthquakes total, with moment magnitudes ranging from Mw=-0.5 to Mw=0.75. The microearthquakes did not vary in response to major changes in the reservoir such as the initiation of a new production well, or to intermittent hiatuses in power operations (grid trips). We hypothesize that the low rate of microseismicity is related to a combination of low tectonic stress conditions and extensive permeability networks that rapidly distribute any localized changes in pore pressure.

Topic: Geophysics

High-pressure high-temperature (HPHT) oil and gas wells and geothermal wells share significant similarities in thermal and mechanical environments; nevertheless, their engineering challenges are commonly addressed separately. This paper presents an integrated literature review that looks into both well types through a shared engineering perspective, examining how well construction, drilling-fluid, and downhole tool performance manifest as some of the most important challenges for these types of wells. The review uses documented field and technology development case studies showing that, although the underlying failure mechanisms are often the same, geothermal wells are more severe environments than most HPHT well applications, with temperatures exceeding 300°C. Some of the challenges include temperature-dependent fluid degradation, thermal damage to downhole tools, and thermally induced cement degradation, all of which should be addressed not only by applying documented HPHT knowledge but also by developing new testing standards for these extreme conditions. The review finds that geothermal operations have largely adopted HPHT well protocols for cementing, tool qualification, and fluid selection, even when those protocols were not designed for geothermal well conditions. Progress requires both transferring existing HPHT knowledge and extending it: developing higher-temperature material standards, adapting downhole tools for higher thermal resistance, and recognizing that water-based fluids serve a different role in geothermal than oil-based mud does in HPHT wells. The findings support treating the operational challenges of both well types as related engineering problems, while identifying where technology can be transferred directly, where adaptation is needed, and where new standards are required.

Topic: Drilling

The scanning electron microscopy has been used for the microscopic work in the analysis of rock cuttings dependent on the electron emission and provides a more detailed field characterisation images It has been used worldwide for the analysis of both organic and inorganic materials on a nanometres and micrometre scale. The EDS, Energy dispersive x-ray spectroscopy (EDS) Works together with the SEM to provide qualitative and semi quantitative results, these two techniques can therefore provide the composition of the material scanned, which sometimes cannot be done with the other laboratory microscopic techniques. The SEMS are equipped with EDS and modern software to analyse the received data. The EDS adds the advantage of evaluating the composition of various elements in the sample with the aid of a computer programme. The EDS converts the intensity of the x-ray’s ratios to chemical composition in a short time and increases the effectiveness of the quantitative analysis.

Topic: Field Studies

Hydrothermal alteration mapping is considered as a widely adopted step in hydrothermal mineral exploration. In this works, the wavelength mapping and Spectral Angle Mapper (SAM) techniques were applied to map and identify hydrothermal alteration minerals in geothermal drill cuttings. Hydrothermal alteration minerals rich in Al-OH, Mg-OH and Fe-OH were targeted. Using wavelength mapping approach. As a result, wavelength position and the depth of the absorption features were generated. Wavelength stretches of between 1850-1950 nm, 2160-2228nm and 2300-2370 nm were generated to map Al-OH, Mg-OH and Fe-OH rich group of minerals respectively. For the wavelength stretch between 1350-2400 nm pixels of light green to yellowish occurring near 1900 nm represent deepest absorption features within that range. Equally, wavelength stretch between 2160-2228 nm differentiates various Al-OH minerals found in the sample with the deepest features occurring at 2214 nm. Results for the third stretch between 2300-2370 nm shows dominant yellow pixels at 2337-2342 nm which corresponds to epidote minerals sample while cyan color pixels between 2314-2320 nm correspond to actinolite minerals. SAM classification was performed on all images using various spectra subsets and image-derived endmembers and 0.1 thresholds. The most commonly hydrothermal mineral classified by this algorithm includes zeolite, smectite, illite, chlorite, calcite, epidote and amphiboles. Mineral mixtures were classified in separate classes to distinguish them from pure endmembers minerals. This study shows the combination of wavelength mapping and SAM techniques proves to be a powerful approach for accurately identifying and characterizing hydrothermal alteration features using specific wavelength ranges. The findings from this study can aid future mineral exploration endeavors in similar geological settings, providing guidance for locating important hydrothermal alteration minerals in a geothermal system.

Topic: Emerging Technology

[Mclin]

An Update on Activities at Utah FORGE Kristie MCLIN [Stanford University, USA]

The Utah Frontier Observatory for Research in Geothermal Energy (Utah FORGE), located near Milford, Utah, serves as the primary field laboratory for testing, optimizing, and de-risking Enhanced Geothermal System (EGS) technologies. This presentation discusses a comprehensive update on field operations, research initiatives, and technical milestones achieved at the Utah FORGE site throughout the 2026 campaign. Key operational highlights include insights from extended multi-well circulation testing and heat sweep evaluations between injection and production doublets, advanced subsurface monitoring using high-resolution microseismic processing and distributed fiber-optic sensing (DAS/DTS), and the field deployment and validation of innovative high-temperature downhole tools, zonal isolation systems, and stimulation techniques under crystalline basement conditions. Data and operational metrics gathered from these 2026 activities continue to refine numerical reservoir models, advance industry understanding of inter-well connectivity and thermal performance, and inform best practices for commercial EGS scalability.

Topic: Introduction

Geothermal Arrays -- networks of large numbers of standard geothermal wells -- open up many opportunities for scaling up clean, cheap, safe, reliable, and abundant baseload electricity.

Topic: Modeling

The U.S. Geological Survey (USGS) is currently updating the conventional hydrothermal resource assessment of the Great Basin. As part of the update, the methods from the 2008 USGS assessment are being revised to use the best available strategies and to incorporate new data. The new assessment workflow estimates total electric power generation potential from both discovered and undiscovered resources for conventional hydrothermal systems in the Great Basin. Estimates of electric power generation potential for identified systems with high confidence in electric-grade viability (i.e., discovered systems) are stochastically estimated using an updated Monte Carlo analysis from the 2008 method that substitutes a fractured and/or porous reservoir model for the previously used volume method (Burns et al., 2027). The 2008 list of discovered systems is stochastically amended with additional discovered systems identified as potentially being electric-grade in DeAngelo et al. (2026) and then used to estimate the density of electric-grade systems per unit area (DeAngelo et al., 2027). Combining the Monte Carlo approach with the system-per-area density enables stochastic estimation of the undiscovered resources. Estimates of the frequency of undiscovered systems, and therefore the total electric power generation potential, depend upon how much of the region is considered explored. Area explored is estimated using the masking method of DeAngelo et al. (2027), where masks of different exploration radii are constructed around the set of points where electric-grade geothermal resources are known to exist or known not to exist. Exploration bias, from past exploration having potentially focused on more favorable areas based on best professional judgment, is addressed in the Monte Carlo analysis by stochastically allowing for the possibility that system-per-area density may be less in unexplored areas than explored areas. Masking radii of 2 km, 4 km, and 6 km are considered, and the range of undiscovered resources is estimated for each radius. The 6-km mask produces estimates of total hydrothermal power potential similar to the 2008 estimate. The 4-km and 2-km masks produce sequentially larger resource estimates with the mean prediction being, respectively, 43% and 309% larger than that of the 2008 assessment, demonstrating the dependence on the selected estimate of explored area.

Topic: General

The present paper is a comprehensive review on induced seismicity in Enhanced Geothermal Systems (EGS) as well as on the related processes. It furthermore describes the monitoring of an injection area for seismic activities and outlines different options for seismic hazard prediction and mitigation in order to handle the risks. An integrated descrption of the mechanisms of induced seismicity (pore pressure increase and thermal stress) and of the criteria for fault reactivation. The monitoring of microearthquakes in the area of injection. The last advances of machine-learning methods for the improvement of the short-term seismic hazard forecast and for the real-time seismic-risk management (so-called “traffic-light control”) of geothermal operations. Results, Observations, Conclusions. Increasing both pore pressure and thermal stress can cause reactivation of faults leading to earthquakes. The related increase in seismic hazard can be managed with an appropriate injection strategy. Short-term seismic hazard forecasts can be improved with the aid of machine learning. However, their accuracy strongly depends on the corresponding monitoring density. This Review provides a fully integrated view of induced seismicity and of associated seismic hazard, for EGS, including management. It also briefly outlines the recent approaches, using machine-learning, of short-term and of real-time seismic hazard and of seismic risk monitoring and management for geothermal projects, and for their on-line real-time on-line seismic risk management (traffic-light control).

Topic: Enhanced Geothermal Systems

This review is intended to give a status report to the field of tracer testing for reservoir characterization of geothermal wells. The main issues are identification of the flow paths, determination of swept-volume and of thermal-breakthrough and the use of machine-learning for improved interpretation of the obtained tracer profiles. We review conservative and reactive tracers as well as flow-path and swept-volume assessment, thermal breakthrough prediction and most recently machine-learning enhanced interpretation of a tracer return to improve our analysis of the connectivity and heat-life of a geothermal reservoir. Tracer testing as a dynamic characterization tool going beyond static models in order to better constrain inter-well-connections as well as thermal breakthrough. In addition, machine learning can be used to improve the interpretation of complex return signals of tracers. But also tracer testing has its limitations. Non-uniqueness of results cannot be solved by tracer testing itself. Additional data is required. the review is of the view that tracer testing is a form of dynamic characterization that can be added to static models, and Machine Learning can be used to interpret the tracer returns in terms of reservoir connectivity and heat lives.

Topic: Tracers

In this review we critically review recent advances of machine-learning in geothermal resource exploration and reservoir management, and assess their current stage of development for favorability, property estimation as well as for process optimization. The review covers supervised learning for favorability and property prediction as well as physics-constrained and hybrid modeling for optimization. The review discriminates between points regarding data-scarcity, validation and transferability to other applications. Data-driven exploration targeting and property prediction for geothermal fields can be supported with ML approaches. However, due to data-scarcity, results are sensitive to the degree of site-specific data incorporation and the corresponding disciplinary validation scope. Results also have limited transferability between sites. A Maturity map for tasks within geothermal applications is presented and it is argued that, in a data-scarce domain such as geothermal resources, the key to durable value from ML is the extent of physics constraints and disciplined validation, rather than the specific ML model used. A maturity map is developed for the application of machine learning in geothermal exploration and reservoir management. The value of machine learning models in geothermal is largely determined by the degree to which they are embedded in physical models and are subject to rigorous validation as opposed to specific model choices.

Topic: Enhanced Geothermal Systems

During exploration drilling campaigns, early predictions of reservoir temperature can improve targeting decisions and help to optimize dynamic campaign decisions. Fully stabilized downhole temperature measurements require months of waiting, but data while drilling, such as from maximum registering thermometers (MRTs), and from early-heat up surveys can be used mid-campaign. Corrections which are proposed based on a systematic review of dozens of drilling examples which can use early data to reliably predict the true reservoir temperature. These methods are particularly critical in small-diameter wells which cannot be reliably flowed. If a flow test is possible, temperatures from flow tests can also provide a highly reliable predicton of reservoir temperature in permeable zones, with appropriate correction.

Topic: Reservoir Engineering

As the global energy transition accelerates, Project Financing Institutions are increasingly tasked with funding a wider spectrum of geothermal resources. The established Probability of Discovery (POD) framework provides a quantitative assessment of exploration risk. However, its current grading parameters implicitly favor high-enthalpy, vapor-dominated systems associated with classical volcanic heat sources and extensive surface manifestations. Consequently, structurally controlled, low-to-medium temperature systems are often penalized in the scoring matrix, resulting in low POD grades that could impact the project became unfavorable and have high risk profiles. This study aims to identify and adjust specific parameters within the existing POD framework to accurately reflect the commercial viability of low-to-medium temperature geothermal fields. By recalibrating the weighting of geological, geochemical, and permeability indicators, this research seeks to provide lenders with a modified assessment tool that maintains rigorous risk mitigation while ensuring lower-enthalpy projects remain favorable for project financing. The study utilizes pre-exploration drilling data from two low-to-medium temperature geothermal prospect areas. The original POD framework which evaluates temperature expectation, temperature probability, permeability, chemistry, and drilling probability is applied to both fields to establish a baseline score. Subsequently, a sensitivity analysis is conducted to test parameter adjustments. Key modifications include down-weighting the reliance on high-temperature surface manifestations, such as fumaroles, and up-weighting indicators critical to binary plant success, including deep fault permeability and the presence of neutral, benign reservoir fluids. The application of high-enthalpy POD parameters increase the risk of low-to-medium temperature geothermal resources. By selectively adjusting permeability and chemistry weightings, lenders can utilize a more applicable POD framework for low-medium temperature system. This recalibrated tool not only prevents the premature abandonment of viable projects but actively expands the pipeline of bankable geothermal investments, accelerating the deployment of renewable energy generation.

Topic: Low Temperature

The Great Basin contains the United States' largest identified geothermal resource, with surface features like hot springs, fumaroles, and altered ground historically guiding explorers to almost every currently producing field. However, undiscovered geothermal systems leave no such surface expressions. Uncovering these hidden resources requires predicting subsurface temperatures, though temperature data alone cannot pinpoint drill sites. Because conductive heat transport through rock varies smoothly with regional crustal structure, it contrasts sharply with localized advective heat carried by fluids along permeable fault networks—which production wells must precisely intersect. Traditional mapping methods that extrapolate surface heat flow using assumed conductivity profiles lump these two mechanisms together and fail to isolate the advective component. To untangle this, we calculated temperatures at depth across 10,587 grid nodes throughout Nevada and Utah to successfully decouple the conductive background from advective signatures and rank the region for hidden potential. By feeding 407 Curie-point depths and 3,874 conductivity measurements into a physics-informed neural network, we solved the steady conduction equation across the entire crustal column while holding back 2,847 independent heat-flow observations for unbiased validation. Each node was then scored based on predicted heat flow, estimated temperatures at a 4 km depth, and local Quaternary fault density. Our analysis revealed that fluid advection—rather than simple conduction—drives regional resource distribution, with observed heat flow surpassing the conductive baseline at 65% of our validation sites (exceeding it by a median of 19 and up to 179 mW m⁻², and clearing 20 mW m⁻² across 34% of the province). Furthermore, predicted temperatures at 4 km surpass 200 °C across 48% of the region and 250 °C across 28%. Notably, our ranking successfully flagged 78 known Nevada geothermal systems at a median percentile of 75, including 28 systems completely devoid of surface expressions at a 76th percentile, proving the model's ability to uncover blind resources. We identified 25 top-tier prospects sitting squarely within the top one per cent of the province, every single one anchored to a mapped Quaternary fault with predicted reservoir temperatures of 293–400 °C across a 2,537 km² footprint. This direct spatial alignment confirms that fault permeability acts as the primary vertical conduit delivering deep heat to drillable depths. As an independent blind test using withheld data, our model accurately predicted the temperature profile of a deep well near Utah FORGE—situated 19 km from one of our identified thermal peaks—matching a 2.3 km equilibrated log within a tight 10.7 °C root-mean-square.

Topic: Geology

Indonesia’s geothermal power development has mostly relied on high-temperature (≥230°C) volcanic systems, where self-flowing wells and flash or dry-steam plants are commonly used. This experience has shaped assessment practice. However, future development in Indonesia is expected to include medium-temperature resources (190 to less than 230°C), including outflow zones, peripheral systems, and fault-controlled reservoirs. These resources should not be assessed as smaller high-temperature flash fields because their development is constrained by different reservoir deliverability and conversion characteristics. This paper examines how stored heat Monte Carlo can be applied more appropriately to medium-temperature resource assessment. The method remains useful as an early-stage screening tool, especially where subsurface data are limited, but its results can be misleading when assumptions inherited from high-temperature flash projects are applied without adjustment. Common issues include using one large resource volume, inappropriate cut-off temperatures, optimistic recovery factors, fixed or flash-like conversion efficiency for binary plants, and high reservoir temperatures across the entire prospect without support from conceptual model. Practical adjustments are proposed, including selecting cut-off temperature based on intended plant technology and final usable reservoir temperature rather than reinjection temperature, selecting recovery factors from relevant analogue fields and expected permeability regime, using binary net conversion efficiency that accounts for parasitic loads, and differentiating reservoir thickness and temperature between upflow, proximal, and outflow zones where supported by the conceptual model. A multi-volume stored heat Monte Carlo approach is recommended, in which all volumes are sampled together within each iteration and P90, P50, and P10 are derived from the total distribution. This avoids spreading high-temperature assumptions across the whole resource area and prevents incorrect summation of percentile values from separate simulations. The Kotamobagu (North Sulawesi) and Momotombo (Nicaragua) case studies suggest that this approach can provide reasonable early-stage resource estimates before detailed numerical reservoir modelling is conducted. This is indicated by general agreement between multi-volume stored heat estimates, numerical model results, and actual stable power generation. Nevertheless, stored heat Monte Carlo estimates heat-based potential and does not directly calculate permeability heterogeneity, well productivity, pressure support, thermal breakthrough, or downhole pumping requirements. Numerical reservoir modelling remains the appropriate next step for assessing these aspects in detail.

Topic: Reservoir Engineering

In geothermal wells in the Olkaria, Kenya Rift Valley, smectite clays such as montmorillonite and nontronite remain the dominant cause of wellbore instability. When exposed to water-based drilling fluids, these clays rapidly hydrate, swell, and induce wellbore constriction, bit balling, differential sticking, sloughing, and pack-off. The resulting stuck-pipe events generate significant non-productive time and inflate the already elevated costs of geothermal drilling. Conventional mitigation relies on mechanical freeing techniques and spotting fluids, augmented by calcium chloride to promote clay shrinkage via cation exchange. Although inexpensive, calcium-based exchange yields only modest volume reduction in smectite interlayers, limiting its effectiveness. Potassium chloride delivers markedly superior shrinkage but is routinely excluded on economic grounds. Laboratory and field data demonstrate that ammonium chloride offers a superior, cost-effective alternative. When ammonium ions occupy the interlayer sites of smectite, they induce substantially greater lattice contraction than calcium ions, producing a more stable, collapsed clay structure. At the same time, ammonium chloride is considerably less expensive than potassium chloride, enabling routine deployment without compromising project economics. This paper presents ammonium chloride as a practical mitigation measure that directly addresses the root cause of clay swelling while maintaining operational affordability. Implementation in Olkaria-type rift settings is expected to reduce stuck-pipe incidents, shorten drilling times, and lower overall well-construction costs, advancing the economic viability of East African geothermal development.

Topic: Geochemistry

Carbonate-hosted geothermal reservoirs can generate and release CO2 through coupled brine-CO2-rock reactions, particularly where calcite dissolves under high-pressure and high-temperature conditions. These reactions simultaneously govern scaling tendency, corrosion risk, permeability evolution, pore structure, and mechanical response, making CO2-equivalent generation an integrated reservoir problem rather than a purely geochemical one. This study develops new chemical treatments for reducing CO2 emissions from carbonate geothermal systems. Multiple chemical treatments were explored, including the injection of silica additives (silica fume, silica flour) and chelating-agent pre-flushes (EDTA, GLDA), using Red Sea water (RSW) and CO2-rich RSW as base main fluids. This work combined static chemical screening, HPHT disk aging at 70°C, and staged core flooding in dry carbonate cores (10 in length and 1.5 in diameter) at 100°C, 2000 psi confining pressure, 1500 psi backpressure, and 0.5 cm³/min injection flow rate. Phase 1 injected RSW baseline, a chemical slug, and an RSW post-flush; Phase 2 repeated this sequence using CO2-rich RSW as the baseline and post-flush fluid. Effluent was analyzed by ion chromatography and total inorganic carbon (TIC), with CO2-equivalent generation cross-checked against Ca2+/Mg2+ stoichiometry. Pre- and post-flood CT imaging, porosity, pore volume, dry mass, and dynamic elastic properties linked fluid chemistry to rock alteration, while outlet-temperature records were interpreted using local thermal equilibrium (LTE) and non-equilibrium (LTNE) models. Silica fume and silica flour emerged as the most effective mitigation additives. In HPHT screening, 0.1wt% silica fluids did not increase Ca2+/Mg2+ release relative to the base case and maintained near-neutral pH, whereas EDTA produced the strongest carbonate attack. In Phase 1 core flooding, 0.1wt% silica fume lowered cumulative TIC-based CO2-equivalent from 105.20 mg (RSW baseline) to 50.10 mg during the additive stage and 28.13 mg during post-flush; silica flour likewise sustained low CO2-equivalent output. In Phase 2, under CO2-rich RSW, 0.1wt% silica fume reduced the cumulative CO2-equivalent from 357.51 mg to 129.69 mg, and 0.1wt% silica flour reduced it from 248.42 mg to 109.65 mg. By contrast, 5wt% EDTA increased CO2-equivalent from 221.60 mg to 783.33 mg, confirming its role as an active carbonate-dissolving pre-flush rather than a suppressant, while 5wt% GLDA reduced CO2-equivalent from 399.57 mg to 279.30 mg but showed complexation-affected free-ion behavior. Post-flood CT and petrophysical data indicated only limited alteration and no severe sustained plugging across the silica runs, and LTE and LTNE models produced nearly identical outlet-temperature predictions, supporting LTE as an adequate outlet-scale descrption. The obtained results show that CO2-equivalent generation in calcite-dominated geothermal core floods is controlled by the combined effects of CO2-rich brine, carbonate dissolution, sulfate-related ion partitioning, chemical speciation, and thermal stabilization. Silica fume and silica flour reduce net inorganic-carbon release without causing severe flow impairment, while EDTA should be used only cautiously as a short pre-flush requiring metal complexation, and GLDA occupies an intermediate position requiring joint interpretation of TIC, pressure response, and rock-property change. The findings support a reservoir-centered chemical-selection framework for carbonate geothermal systems that weighs scale control against CO2-equivalent generation, injectivity, and rock integrity.

Topic: Reservoir Engineering

The geothermal wellbore is where reservoir heat becomes deliverable energy or fails to, flashing depth, heat loss, and flow stability all negotiated over a few kilometres of pipe. We review geothermal wellbore flow and heat transfer: the two-phase modeling record against measured profiles, flashing-depth prediction and its sensitivity chain, flow-stability boundaries in cycling service, and the completion-design levers, insulation, diameter staging, that the physics rewards. The wellbore is the component where geothermal projects convert reservoir promise into plant feed, and its modeling record deserves the validation grading it receives here. Wellbore-simulation approaches were assembled with validation against measured pressure-temperature profiles, the scarce but decisive data, flashing-depth sensitivity examined across the input chain, productivity, enthalpy, wellhead pressure, stability evidence reviewed from cycling and throttled operation, and machine-learning wellbore-model surrogates surveyed. Validation against measured pressure-temperature profiles is the organizing standard, scarce data given the decisive role it deserves. Model skill was genuine for stable production and degraded exactly where operations get interesting, transients, low rates, near stability boundaries, where correlation-based two-phase closures showed their non-geothermal ancestry. Flashing depth proved most sensitive to inputs operators know worst, feed-zone enthalpy distribution above all. Design levers mattered asymmetrically: diameter staging moved deliverability more than insulation in the compiled cases, except in cold-climate low-enthalpy service where the ranking flipped. The sensitivity finding directs instrumentation: feed-zone enthalpy distribution, the input operators know worst, moves flashing depth most. The first validation-graded synthesis of geothermal wellbore modeling with the sensitivity chain exposed and design levers ranked by demonstrated effect. Well designers gain closure-selection and instrumentation guidance for the component where reservoir performance becomes, or fails to become, plant feed. Well designers gain closure-selection and instrumentation guidance for the kilometres of pipe where deliverability is won, lost, and usually under-modeled.

Topic: Production Engineering

Binary geothermal plants are designed for a resource condition that begins drifting the day production starts, and the reservoir and plant optimization literatures have mostly drifted apart the same way. We review coupled reservoir-plant optimization for binary systems: ORC design-point matching against resource-decline trajectories, off-design performance evidence, reinjection-temperature coupling where plant choices feed back into resource life, and the value of optimizing the system rather than its halves. Plants are designed for a resource condition that starts expiring at first production, and the optimization literatures on either side of the wellhead have barely met. Coupled optimization studies were assembled and compared against sequential design practice, off-design ORC performance evidence reviewed from operating plants, resource drift moves plants off design early, the reinjection-temperature feedback examined, plant thermal choices set injection temperatures that reshape reservoir evolution, and machine-learning coupled surrogates surveyed. Coupled studies are ed against sequential design practice directly, so the value of closing the loop is measured rather than asserted. Coupled optimization shifted design points away from day-one resource conditions toward trajectory-weighted conditions, sacrificing initial output for lifetime energy in every compiled study, and the value grew with resource-decline uncertainty. Off-design evidence showed real plants losing more to drift than design-point comparisons capture. The reinjection feedback was material and almost universally ignored: plants optimized in isolation chose injection temperatures that cost reservoir life their own economics never saw. The feedback finding is the buried one: plant-chosen injection temperatures reshape reservoir evolution in ways isolated plant optimization never sees. NThe first synthesis to close the reservoir-plant loop for binary geothermal with the reinjection feedback quantified and trajectory-weighted design shown to beat design-point practice. Developers gain a coupled-design case stated in lifetime energy, the number their financing actually discounts. Developers gain the coupled-design case in lifetime energy terms, the number financing discounts, and designers the trajectory-weighted method that beats day-one optimality.

Topic: Reservoir Engineering

The Dieng geothermal field in Indonesia is two-phase liquid-dominated geothermal field that was developed by PT Geo Dipa Energi (Persero) in 2002 with an installed plant capacity of 60 MWe. Several numerical models have been developed over the last 2 decades. The latest numerical model of the Dieng geothermal field was constructed in 2026 with an aim of quantifying lithium resources within the Dieng reservoir as well as estimating how lithium concentration within the reservoir and in the production fluids would change when a lithium extraction facility is put into operation. This paper describes the process of numerical simulation via model calibration considering the production and injection data of wells in Dieng Unit 1 and includes additional wells drilled for Dieng Unit 2 wells. A robust model that includes calibration to natural-state and operational history for 22 years of production from the field is described. The calibrated numerical model is used to forecast the field’s performance under various operating conditions with the aim of identifying long-term challenges and opportunities to maintain stable production of lithium from this field.

Topic: Modeling

Geothermal energy systems generates significant volumes of geothermal brines enriched with dissolved minerals and metals as a by product of power production. These high temperature, saline fluids represent both environmental management challenge and an untapped resource. Properly managed Geothermal brines can support sustainable energy generation while enabling resource recovery, reducing waste and improving overall technoecomic viability of geothermal operations.Thus large volumes of geothermal brines are enriched with dissolved metals and nutrients, creating extreme physiochemical environments characterised by high temperature, salinity and pH. These conditions support extremophylic microorganisms capable of metal tolerance, transformation and bioaccumulation. Harnessing extremophile-driven processes in combination with phytomining approaches, offers a sustainable pathway for recovering valuable and critical metals such as li thium (Li), cesium (Cs), rubidium (Rb), strontium (Sr), manganese (Mn), zinc (Zn), copper (Cu), and i ron (Fe), along with rare earth elements (REEs) present in trace concentrations from Geothermal brines while mitigating environmental impacts.These metals represent a strategic resource for energy storage, electronics, and clean technologies, making geothermal brines an attractive target for bio-based recovery.Overall, extremophile-driven phytomining aligns strongly with circular economy principles and represents a low-carbon pathway for critical metal recovery in future geothermal resource management Keywords: Geothermal energy , Geothermal brines, Phytomining, Extremophile,Sustainable energy resource, Sustainable energy.

Topic: Geochemistry

The Salton Sea Geothermal Field (SSGF) is characterized by high-temperature, high-salinity brines, a stratified reservoir system with a low-salinity cap above a hypersaline zone, and complex thermodynamic and geochemical behavior. This study presents the development and calibration of a numerical reservoir model focused on the Hudson Ranch area, with the goal of validating prior conceptual and geochemical interpretations (including double-diffusive convection models) through numerical simulation. The model aims to capture the natural-state behavior of the system and provide a framework to evaluate long-term changes associated with both geothermal energy production and critical mineral extraction using new commercial numerical modeling software (Volsung). In recent years, growing interest in lithium and other critical mineral recovery from geothermal brines has emphasized the need to understand how post-extraction reinjection alters reservoir chemistry, pressure, and temperature. This model incorporates mineral depletion and fluid re-equilibration mechanisms to assess the potential reservoir impacts of large-scale lithium extraction. The work supports future feasibility studies by quantifying the thermodynamic and chemical evolution of the system under dual-use scenarios of power generation and mineral recovery. This model provides critical insights for sustainable co-production of energy and minerals from hypersaline geothermal systems.

Topic: Modeling

In two-phase geothermal fields, monitoring the enthalpy of produced fluids is important in under-standing the reservoir performance. Decreasing enthalpy can indicate breakthrough of injection water or invasion of cooler groundwater, while increasing enthalpy can indicate reservoir boiling and the formation of a steam cap. Enthalpy and mass flow rate govern the amount of steam availa-ble from each well and ultimately the energy output of the powerplant. Mass flow rate of steam and water phases and total enthalpy of the flow can be measured directly for individual geothermal wells that produce to dedicated separators. However, due to the high capital cost of production separators, most geothermal fluid gathering systems are designed with satellite separation stations in which several wells produce to a single separator. In many cases all of the two-phase fluids produced from a field are combined by the gathering system and separated in a large vessel at the power plant. Without dedicated production separators for each well, the steam and water mass flow rates and total enthalpy of individual wells cannot be measured during pro-duction. We have thus incorporated a method of mass balance to ascertain whether the production from each well is still maintained and the output tallies after separation in the field. This informs whether we experience losses or not after separation.

Topic: Field Studies

The U.S. Geological Survey is updating its assessment of conventional hydrothermal resources in the Great Basin. The assessment applies conditional statistics, which consider areas of similar geologic conditions as having similar likelihoods for hosting a geothermal resource. Hence, partitioning a study area into spatially contiguous and statistically similar regions (i.e. regionalization) can aid the computation of conditional statistics. Recent examples of regionalization include a supervised tree-ensemble leaf-distance workflow and an unsupervised principal components with k-means clustering (PCAk). Herein, we present an unsupervised alternative, Agglomerative Regionalization via Information Divergence (ARID), and compare ARID to leaf-distance and PCAk. ARID starts with small sub-regions and then repeatedly merges the most similar adjacent zones, comparing each feature distribution via Kullback-Leibler divergence rather than averages alone. All algorithms regionalize the Great Basin from 52 features (e.g., heat flow, strain). Partitions are scored internally based on the similarity of feature values within zones and the separation of feature values between zones. Partitions are scored externally by continuous ranked probability score (CRPS) against subsurface temperature estimates from two independent geothermometers (silica [n=2,678], Na–K–Ca [n=2,614]) to test if zones distinguish resource temperatures. Because geologic properties are typically spatially autocorrelated, apparent skill can arise from spatial proximity alone; to control for spatial autocorrelation, comparisons are referenced against randomized contiguous zonations. Despite being unsupervised, ARID predominantly presents the same zonation pattern as the supervised leaf-distance approach, with 63% of the area of the same zones overlapping, suggesting identification of similar structure(s) in feature space. ARID is also the only method to exceed the randomized contiguous zonations on internal criteria (p=0.005). No method exceeded the 5th percentile of the randomized contiguous zones for the external temperature score, although both ARID and leaf-distance beat the median (p=0.34 and p=0.42, respectively). These results suggest that, given the features evaluated here, geographic proximity to measured sites was more informative for characterizing subsurface temperature than the feature-based partitioning methods. ARID demonstrates advantages in producing internally coherent sub-regions without the need for labels and is independently corroborated by the supervised zonation of the leaf-distance workflow. While slight, ARID beats the median external temperature characterization of the spatial null; highlighting the skill occupied by spatial proximity alone. Future work may investigate incorporating these zones into a conditional statistic workflow.

Topic: General

Repurposing existing oil and gas infrastructure for geothermal and waste-heat power generation offers a low-capital pathway to expand domestic clean energy production, but it introduces a distinct engineering challenge: operators must remotely monitor and control heat-to-power assets that vary widely in source type, mechanical configuration, and geographic location, often without the benefit of a purpose-built, single-site power plant's centralized instrumentation. This paper presents a unified, vendor-certified SCADA and remote operations architecture developed to address this challenge, and reports field results from its deployment across three structurally different heat-to-power source types. The architecture is built on a Unified Namespace using MQTT Sparkplug B, standardizing data flow and enabling centralized data governance across more than 100,000 monitored points spanning geographically distributed sites. A centralized Unified Control Layer integrates heterogeneous power generation equipment through OPC UA and multi-vendor programmable logic controller connectivity, providing real-time telemetry, alarming, and operator interfaces from a single platform regardless of underlying hardware or physical location. This architecture underlies three deployed projects representing distinct heat-to-power source types. First, a project supported by the U.S. Department of Energy Geothermal Technologies Office, part of the Wells of Opportunity initiative, applies the platform to generate electricity from repurposed oil and gas wells in California San Joaquin Valley, demonstrating the architecture applicability to geothermal energy recovery from existing wellbore infrastructure. Second, a waste heat to power deployment at a natural gas compressor station in Dry Ridge, West Virginia, in partnership with CNX Resources, generates approximately 0.5 MW of zero emission power from compressor exhaust heat, reducing an estimated 1,325 metric tons of CO2 emissions in its initial phase, with a scaling pathway toward approximately 4,000 metric tons of annual reduction. Third, an industrial waste heat to power system at a seafood processing facility in Dutch Harbor, Alaska, operated in partnership with UniSea Inc, generated 67 MWh of electricity during a three week startup phase alone, representing approximately 5,000 gallons of displaced diesel fuel, and now displaces an estimated 3,500 gallons of diesel per week at full operation in a remote, off grid environment. Across all three deployments, the same underlying control architecture supported integration, monitoring, and remote operation without site specific rearchitecting, demonstrating that a standardized, vendor certified SCADA and namespace approach can generalize across geothermal wellbore heat, oilfield adjacent compressor waste heat, and industrial process waste heat. This paper details the technical architecture, integration methodology, and field validated outcomes, and discusses implications for scaling remote heat to power operations across additional repurposed oil and gas assets and off grid or resource constrained sites nationally.

Topic: Emerging Technology

Low-temperature geothermal resources are widespread and accessible but often unsuitable for electricity generation because of their low enthalpy. In Iceland, where low-temperature geothermal fields are widely used for heating and non-recyclable municipal solid waste is still exported, waste-to-energy provides both a domestic waste-management pathway and a stable external heat source. This study evaluates how externally supplied waste-to-energy heat can enhance electricity generation from Icelandic low-temperature geothermal resources and how the point of heat addition influences thermodynamic and economic performance. Steady-state first- and second-law analyses are applied to a baseline single-flash steam plant and two hybrid configurations in which external heat is added either to the geothermal brine upstream of the flash separator or to the separated steam at the turbine inlet. Brine-side heating increases the mass of steam available for expansion, while turbine-inlet heating increases the work extracted per unit of steam. Results show that upstream brine heating yields substantially higher power output by increasing steam production, whereas turbine inlet heating achieves higher exergy efficiency with considerably less external heat input. When external heat is treated as a purchased input, improved thermodynamic performance does not necessarily reduce the levelized cost of electricity. At an assumed heat price of 15 EUR/MWh thermal, the cost of external heat strongly influences the comparative economic performance. Although district heating revenue is excluded from the electricity-only cost metric, a separate revenue assessment shows that the use of recoverable heat can substantially improve the economics of hybrid configurations. Overall, the analysis demonstrates that geothermal waste-to-energy hybridization can increase electricity generation from low-temperature geothermal resources, but its value depends strongly on the integration strategy and the economics of the heat source.

Topic: Low Temperature

Kenya's electricity sector is undergoing a transformative expansion driven by the country's vast geothermal resources, estimated at over 10,000 MW along the Great Rift Valley. This paper presents a comprehensive analysis of the impacts of stepwise geothermal energy integration—from 950W small-scale binary systems to 5000MW utility-scale installations—on existing tariff structures in the Kenya power system. Using a 50MW stepwise integration framework, we examine the techno-economic implications for Kenya Power and Lighting Company (KPLC), the single-buyer utility, and various consumer categories. The analysis synthesises regulatory frameworks including the Energy Act 2019, the draft National Geothermal Strategy 2026–2036, and Feed-in-Tariff policies, while modelling tariff dynamics under Kenya's unique generation mix where geothermal already contributes approximately 40% of baseload electricity. Our findings indicate that geothermal expansion follows a fundamentally different tariff-impact trajectory compared to variable renewable sources due to its baseload characteristics and near-zero fuel costs. The levelized cost of geothermal generation in Kenya ranges from USD 0.06 to 0.08 per kWh, compared with over USD 0.20 for heavy fuel oil. The stepwise approach reveals that tariff benefits accrue most significantly through displacement of expensive thermal generation, with the Menengai model demonstrating that public-private partnerships can deliver geothermal power at approximately Sh8 per kWh. Threshold effects centre on the transition from public to private financing models and the development of geothermal fields at Menengai, Silali, Paka, and Suswa, with Kenya's entry into the 1-GW geothermal club marking a significant milestone. Policy recommendations address tariff reform, public-private partnership frameworks, and mechanisms to protect consumer affordability while ensuring continued investment in geothermal development.

Topic: Emerging Technology

The development of the geothermal reservoirs involves the processes of heat transfer, fluid flow, rock deformation, and chemical reactions. This review explores the thermo‑hydro‑mechanical‑chemical (THMC) modeling as a way to capture those couplings and assess their impact on injectivity, temperature, scaling, deformation, and reservoir life. Field observations at Soultz‑sous‑Forêts highlight the importance of fracture‑controlled flow and mineral deposition, while the lessons learned from Groß Schönebeck demonstrate that how machine‑learning surrogates could make complex THMC simulations practical for uncertainty analysis and operational planning. AI tools, such as reduced‑order models, neural operators, and physics‑informed network, extend the reach of high‑fidelity simulations, enabling rapid forecasts, sensitivity studies, and digital twins. These surrogates should complement, not replace, process‑based models, with conservation checks and validation that are essential for safe and long‑term use. Together, this integrated workflow makes coupled geothermal modeling more feasible to predict the reservoir performance, sustain the reservoir injectivity, manage the scaling, and safeguard the integrity under complicated subsurface uncertainties.

Topic: Modeling

[Vasantharajan]

An Update on Mazama 2025 Activities Sriram VASANTHARAJAN and Alain BONNEVILLE [Stanford University, USA]

An Update on Mazama 2025 Activities

Topic: Introduction

Geothermal operators must balance near-term energy production with long-term reservoir performance while managing uncertainty and environmental risks. Changes in production and injection can generate delayed responses across multiple wells, complicating decisions about where, when, and how much fluid to extract or inject. To address these challenges, we are developing a physics-informed decision-support framework to forecast these responses and evaluate alternative operating strategies. The central objective is to move beyond predicting reservoir conditions toward assessing the consequences of specific operating choices and determining when predictions are sufficiently reliable to support decisions. The proposed multiwell architecture integrates a reduced-order reservoir model with adaptive machine learning and uncertainty-aware optimization. Connected reservoir compartments conserve fluid mass and energy while representing effective interwell connectivity, fluid transport, and rock–fluid heat exchange. Machine learning combines operational observations with modeled reservoir states to characterize delayed, spatially distributed responses and account for discrepancies between simplified physics and field behavior. Forecasts are conditioned on candidate production and injection schedules. Predictive uncertainty, model disagreement, and physical plausibility checks determine which alternatives can be ranked within operator-defined constraints and when recommendations should be withheld. A cloud-based dashboard makes forecasts, uncertainties, and operating tradeoffs accessible while preserving operator authority over field actions. Preliminary development includes work with Fenton Hill data and a two-well forecasting and optimization prototype. Planned multiwell validation at the Coso geothermal field will progress from independent historical testing to prospective forecasting without operational intervention, followed by selected operator-approved trials. Evaluation will separate model development, uncertainty calibration, and testing, comparing forecasting accuracy, uncertainty reliability, and computational efficiency against physics-only and data-driven baselines. Forecast performance will be assessed separately from demonstrated operational benefits. This work advances a testable approach to connecting reservoir physics, adaptive learning, and transparent decision support, with the goal of improving geothermal resource management under evolving, partially observed conditions

Topic: Modeling

Hydraulic fracturing with proppants is essential for sustaining permeability in enhanced geothermal systems (EGS), yet monitoring fracture geometry and proppant placement remains a major challenge. In this work, we demonstrate that electrically conductive (EC) proppants provide a robust platform for simultaneous fracture support and electromagnetic imaging. We experimentally quantify the coupled hydraulic and electrical transport properties of EC proppant-supported fractures under stress and temperature conditions representative of the Utah FORGE geothermal reservoir. Hydraulic conductivity exhibits a non-monotonic dependence on proppant loading, revealing that high fracture conductivity can be maintained with partial-monolayer proppant packs. In contrast, electrical transport is governed by distinct conduction mechanisms that evolve with packing structure: particle–fluid–particle electrical pathways dominate at sparse coverages, whereas direct particle contacts control electrical conductivity in densely packed fractures. Consequently, EC pathways emerge before full monolayer coverage is achieved, enabling detection of proppant-deficient regions near fracture tips. Even under monolayer packing, EC proppant-supported fractures remain more than five orders of magnitude more conductive than the surrounding granite, providing a strong electromagnetic contrast for subsurface imaging. Measurements on FORGE field samples further confirm the applicability of this approach under realistic EGS conditions. These results establish the transport physics of EC proppant networks and provide a foundation for real-time electromagnetic monitoring of hydraulically fractured geothermal reservoirs.

Topic: FORGE

It is almost universal in geothermal well cements to include silica in some form, coupled with Class G (dedicated oil-well) cement. The use of silica is to prevent cement strength retrogression at elevated temperatures, and Class G because it is intended for well construction. This design requirement seems be one of the untouchable 'sacred cows' of the industry. The question of 'how strong does the cement actually need to be?' seems to have been largely overlooked. This paper presents calculations and assessments to determine the minimum acceptable cement strengths for geothermal casing cement. It comes to two conclusions - different strengths are required in different parts of the well and, for the vast majority of the cemented sections, the required strength is almost ludicrously low. The learnings from this assessment leads to a new conceptualisation of the role and design requirements of cement in geothermal well construction. This perspective can help future projects to reduce costs and eliminate un-needed logistical issues with no discernible detriment to well quality.

Topic: Drilling

The Tecuamburro–Infiernitos geothermal system combines, a high enthalpy resource with a shallow natural steam cap beneath a low-permeability clay cap, and an adjacent medium enthalpy system requiring artificial lift for a substantial fraction of its wells. Realistic resource assessment (RA) under uncertainty for this combined system depends on two capabilities not covered by standard tools: a reservoir simulator equation of state (EOS) that handles simultaneous CO2 and air non-condensible gas (NCG) species with salt at production-relevant temperatures, and a well-deliverability model that accounts for pump-limited, rather than purely wellhead-pressure-limited, production. For the first, we developed wsace, a custom water–salt–CO2 –air EOS for the Waiwera open-source geothermal simulator. Waiwera’s existing multi-component EOS family covers water+salt+CO2 and water+salt+air separately, via subclasses of a shared water+salt+single-NCG base implementation; neither the base class nor its subclasses support two simultaneous NCG species, which both Tecuamburro/Infiernitos and other target systems (e.g. high-salinity, high-temperature reservoirs such as Salton Sea) require. wsace extends Waiwera’s phase-transition and primary-variable framework to two independent NCG partial pressures. This custom eos allows to model a more realistic atmosphere in which the the CO2 partial pressure ≈ 40 Pa and Air partial pressure ≈ 99 KPa. Validated against a real production-scale Tecuamburro RA case. Reservoir fluid chemistry is further characterized by post-processing Waiwera’s simulated pressure/temperature/composition fields through PHREEQC (Pitzer database, appropriate for high-salinity, high-temperature brine), yielding detailed aqueous speciation at each grid block for water-chemistry evaluation of special important in the natural state calibration. For the second, RA well selection for Infiernitos now uses a two-tier pump-aware deliverability model: a closed-form screening calculation (referenced against pump intake pressure and simulated CO2 partial pressure, rather than surface wellhead pressure) evaluates every candidate block cheaply during the search, and a full pump-curve sizing algorithm combined with a NPSH/gas-breakout-pressure check runs once a well is actually selected, creating a delv type source with a scalar sink pressure instead of an enthalpy table. This replaces a simplified post-hoc power correction with per-well, physically grounded net power reporting and lets the well-selection algorithm itself account for pump feasibility rather than assuming natural flow. Together, these developments let uncertainty-quantified natural-state ensembles propagate through resource assessment for both resources – staged or simultaneously interleaved – with numerically robust multi-phase, multi-NCG chemistry and realistic artificial-lift approach that provides a probabilistic range of power production scenarios for both systems under a sustainable development scheme.

Topic: Modeling

This review focuses on Enhanced Geothermal Systems (EGS) in low-permeability rock, with respect to four areas: (1) stimulating to create engineered permeability for improved reservoir connectivity, (2) fluid circulation for heat extraction and control of hydraulic and thermal short-circuiting, (3) design levers for sustaining a long-term reservoir performance, and (4) techno-economic factors governing the commercial viability. Across these topics, the review brings together research on stimulation methods, fracture creation, coupled thermal–hydraulic modeling, circulation strategies, approaches for limiting hydraulic or thermal bypassing, and the growing use of machine‑learning tools to design and forecast. The economic discussion highlights the parameters that most strongly shape the project outcomes—drilling and completion costs, stimulation requirements, achievable flow rates, produced‑fluid temperatures, thermal decline behavior, reservoir impedance, plant efficiency, operational lifetime, and the financial uncertainties that accompany subsurface development. Long‑term heat extraction depends on establishing a broad, well‑connected network of flow paths that provides sufficient surface area for heat transfer without allowing rapid short‑circuiting or premature cooling. Because the fracture network is created under a specific stress environment and cannot be corrected later, early design choices have lasting consequences for reservoir performance. Economic viability is also tied to subsurface behavior. Higher flow rates and hotter produced fluids generally improve the power generation and lower the levelized cost of energy. However, issues such as high impedance, steep thermal decline, water losses, ineffective stimulation, or elevated drilling costs can challenge a project. Any realistic evaluation must therefore link reservoir performance to capital and operating costs, project duration, financing assumptions, and the uncertainties in long‑term geothermal development. The review concludes by outlining an integrated design framework that covers reservoir creation, circulation management, AI‑supported optimization, and techno‑economic analysis. It emphasizes the role of machine learning to improve the stimulation design, forecast the hydraulic and thermal behavior, identify the emerging short‑circuiting pathways, update the reservoir models with field data, and guide the design choices that would technically and economically resilient under various subsurface uncertainties.

Topic: Enhanced Geothermal Systems

Seram Island in eastern Indonesia hosts numerous thermal surface manifestations in a non-volcanic tectonic setting, with no Quaternary volcanism on the island. The surface manifestations provide an opportunity to examine the surface expression of geothermal systems developed in a collisional and structurally complex environment. This study compiles and characterizes physical thermal-manifestation data acquired between 2009 and 2018 from five areas distributed across Seram Island: Kelapa Dua, Pohon Batu, Banda Baru, Tehoru, and Nif-Bula. The study aims to identify surface feature thermal trends of surface features across Seram’s non-volcanic geothermal areas and to assess how these features relate to the island’s distinctive geological and tectonic setting, providing a basis for regional geothermal exploration. A total of 35 thermal springs were inventoried, with measured temperatures of 37.3–100.5°C and discharge rates of 0.05–3 L/s. Several manifestations are associated with carbonate/travertine deposition, iron-oxide staining, steam and gas discharge, and sulphurous or saline odors. The springs occur in beach and alluvial sediments, fractured schist, and limestone,and are preferentially localized along low-elevation river valleys, coastal zones, and structural trends rather than around volcanic edifices. The highest measured temperature, 100.5°C at Tehoru, indicates near-boiling surface conditions and is accompanied by vigorous steam discharge and hot ground. Estimated natural thermal discharge, calculated from spring discharge and fluid enthalpy, ranges from approximately 100 kWth at Pohon Batu to 850 kWth at Banda Baru. The thermal surface features identified across Seram Island are dominated by hot springs, while surface alteration is generally limited. The occurrence and thermal characteristics of these features reflect localized geothermal fluid discharge within a non-volcanic geological and tectonic setting. These results provide a baseline for understanding Seram’s non-volcanic geothermal systems and help classify and catalog their thermal features and system types.

Topic: Geology

Objectives/Scope. Automated slide-drilling systems optimize toolface hold and rate of penetration (ROP) but treat the resulting build rate as an outcome to check afterward, not a joint objective. This study tests whether slide ROP and achieved build rate can be jointly predicted from surface and near-bit drilling parameters, and whether such a model generalizes across wells drilled in the same field. Methods, Procedures, Process. Slides were identified from rig sensor flags in two Utah FORGE wells and validated against each well’s end-of-well report. Effective toolface was reconstructed from survey inclination and azimuth changes where no toolface channel existed, and validated against real measured toolface in the second well. Weight on bit, differential pressure, and mechanical specific energy (MSE) were tested as predictors of slide ROP and build rate using bivariate correlation, a random-forest joint model, leave-one-well-out cross-validation, and a within-well performance ceiling check. Results, Observations, Conclusions. The toolface-reconstruction method achieves 6.8 deg median error once restricted to slides with adequate net curvature. MSE correlates with slide ROP and build rate in the same direction in both wells when computed independently (r = -0.16 to -0.28 for ROP, +0.23 to +0.30 for build rate). A joint model trained on one well fails to predict the other (leave-one-well-out R2 = -1.33 for build rate). Within-well cross-validation, with no cross-well transfer required at all, shows the same weak result (R2 near zero), demonstrating the failure is not primarily a transfer problem: weight on bit, differential pressure, and MSE alone do not carry enough signal to predict achieved build rate reliably. Novel/Additive Information. This work introduces a validated method for reconstructing toolface from survey data alone, and, unlike prior automated-sliding literature that treats ROP optimization and build-rate outcome separately, provides a rigorous diagnostic test of whether standard drilling parameters carry enough information to jointly predict both - with a documented negative result that has direct implications for how automated slide systems should be tuned and evaluated.

Topic: FORGE

EGS-based geothermal development offers unique solutions to certain challenges facing data center developers in the western US. Data center development is locationally-constrained by existing or planned fiber communication pathways and existing or planned high-voltage grid connections. These two constraints are presenting speed-to-power timeline issues and overall energy supply uncertainty. This two-pronged uncertainty on interconnection actually adds to data center permitting risk, when the public asks for such details in sensitive county meetings, and the developer is unable to clearly articulate on those matters. As a fuel-less and low surface footprint powerplant, EGS geothermal offers data centers solutions to these problems which cannot be matched by classic renewables powerplants (solar, solar) nor modern thermal powerplants (nuclear, gas). Solutions include: a reusable bridge-to-interconnection power supply, no added combustion air emissions permitting risk, and the ability to show the public that the price of new powerplants are being carried by the data center, not utility ratepayers. This paper will dwell on the northern portion of the western states, with Idaho (via Idaho Power Company service area) used specifically as an example.

Topic: Enhanced Geothermal Systems

Recent Play Fairway Analyses of Idahos Snake River Plain produced hydrothermal-based geothermal development heatmaps of attractiveness, built from multi-tiered and expert-weighted data layers associated with heat source, reservoir permeability, and reservoir seal. This hydrothermal geothermal PFA approach was adapted from proven oil & gas PFA philosophies in shale. Our paper presents initial results of producing an EGS geothermal PFA heatmap in Idaho. This is accomplished by re-wiring and inverting certain data layers in the prior PFA work, to better incorporate play conditions for modern EGS project development.

Topic: Enhanced Geothermal Systems