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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze and Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze and Haskins, 2024). The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy, incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Wells of Opportunity: An Assessment of Idle Geothermal Wells in Nevada

Geothermal energy is poised to play an increasing role in the energy transition over the coming decades. At the same time, idled and inactive geothermal wells represent both an opportunity for increased geothermal energy production but also an environmental risk. However, it is unclear how many geothermal wells are idled or inactive, making it difficult to identify pathways to redeploy these wells or prioritize them for additional monitoring, maintenance, or abandonment. Through a comparison of state well databases, this study develops an inventory of all existing large-bore wells at geothermal fields in Nevada to identify idled wells and their characteristics. The results show that at least 91 production or injection wells may be idled (inactive for 7 or more years), representing 21% of inventoried wells across all fields. This idled rate is significantly below the national rate for oil and gas wells (69%), though there are an additional 92 geothermal wells with an unknown status. The average age and length of inactivity for potentially idled geothermal wells is 26 and 23 years respectively, and active generation fields comprise most of the inventory (83%). Idled well incidence varies significantly across active fields, with 6 of the 17 fields having idled rates of 20%-50% and/or more than 5 idled wells, while 3 fields have no idled wells and the remaining fields have rates below 20%. Younger or more recently idled wells at these active fields likely present the best opportunities for future use or enhanced geothermal systems technology testing. However, a significant proportion of the older and long-term idled wells will likely require additional monitoring or eventual abandonment.

geothermal↗
DOE OSTI2015

Induced seismicity in geothermal reservoirs: A review of forecasting approaches

In order to reach Europe's 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced seismicity is often perceived as an unsolicited and uncontrollable side effect of geothermal development. In the last decade, significant advances were made in the development of models to forecast induced seismicity, which are either based on catalogues of induced seismicity, on the underlying physical processes, or on a hybrid philosophy. In this paper, we provide a comprehensive overview of the existing approaches applied to geothermal contexts. This overview will outline the advantages and drawbacks of the different approaches, identify the gaps in our understanding, and describe the needs for geothermal observations. Most of the forecasting approaches focus on the stimulation phase of enhanced geothermal systems which are most prone to generate seismic events. Besides the statistical models suited for real-time applications during reservoir stimulation, the physics-based models have the advantage of considering sub-surface characteristics and estimating the impact of fluid circulation on the reservoir. Thus, to mitigate induced seismicity during major hydraulic stimulations, application of hybrid methods in a decision support system seems the best available solution. So far, however, little attention has been paid to geochemical effects on the failure process and to production periods. Quantitative modelling of induced seismicity still is a challenging and complex matter. Appropriate resources remain to be invested for the scientific community to continue its research and development efforts to successfully forecast induced seismicity in geothermal fields. This is a prerequisite for making this renewable energy resource sustainable and accessible worldwide.

58 GEOSCIENCES↗
DOE OSTI2018

Super Hot EGS and the Newberry Deep Drilling Project

A productive geothermal well drilled into super-hot rock (SHR) with a temperature above 400°C will produce super-critical fluid. At a flow rate of 60 kg/s, a SHR well could produce 50 MWe compared to 5-7 MWe for the same flow at 200°C. Even though these deeper, super-hot wells will cost more, the high energy density means power produced by engineered geothermal systems (EGS) can meet the market ($46 MW-hr) by directly tapping the heat source. We propose a proof of concept where hot rock is close to the surface (~5 km), and the cost of drilling and EGS stimulation will be lowest. A suitable, ready-to-go SHR site is on Newberry Volcano, Oregon, one of the largest geothermal heat reservoirs in the USA, extensively studied for the last 40 years. Millions of dollars have already been invested in the site by private geothermal developers and the US Department of Energy (DOE), resulting in a ready-to-use facility with the necessary infrastructure, environmental permits, land commitments, and monitoring plans. The Newberry Deep Drilling Project (NDDP) will be located at an idle geothermal exploration well, NWG 46-16, drilled in 2008, 3500 m deep and 320°C at bottom, which will be deepened another 1000 to 1300 m to reach 500 °C. The original well was drilled with few lost circulation zones and the temperature profile indicates conductive heat flow. Compared to other SHR projects world-wide, this well would return more materials (cuttings, core and fluids) with more predictable drilling conditions, thus providing a suite of data near and across the brittle-ductile transition in silicarich rocks. After drilling, a hydraulic well stimulation will both change the pore pressure in fractures and cool the fracture walls resulting in permeability enhancement through both thermal fracturing, and hydro-shearing. The first step for the NDDP was an International Continental Drilling Program (ICDP) sponsored workshop held at the OSU-Cascades campus in Bend from Sept. 10-14, 2017. The workshop concluded by setting ambitious goals for NDDP: 1) test EGS above the critical point of water, 2) collect samples of rocks within the brittle-ductile transition, 3) investigate volcanic hazards, 4) study magmatic geomechanics, 5) calibrate geophysical imaging techniques, and 6) test technology for drilling, well completion, and geophysical monitoring in a very high temperature environment. The second step, completed January 15, 2018, was submitting a proposal to ICDP for 46-16 deepening. The next steps will be to continue building a team with project, technology, and investment partners to make NDDP a reality.

EGS, Geothermal, Newberry↗
DOE OSTI2014

Final Report: Mapping Fracture Network Creation with Microseismicity During EGS Demonstrations

Effective enhanced geothermal system (EGS) sites require optimal fracture networks for efficient heat transfer between hot rock and fluids. Microseismic mapping is a key tool used to infer the subsurface fracture geometry and is widely used in the petroleum industry to monitor fracture propagation during hydraulic stimulations. Traditional earthquake detection techniques (e.g. STA/LTA detectors) and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection even in difficult signal processing environments.

58 GEOSCIENCES↗
DOE OSTI2018

Kinetics of D/H isotope fractionation between molecular hydrogen and water

At equilibrium, the D/H isotope fractionation factor between H 2 and H 2 O (α H 2 O-H 2 (eq) ) is a sensitive indicator of temperature, and has been used as a geothermometer for natural springs and gas discharges. However, δD H 2 measured in spring waters may underestimate subsurface temperatures of origin due to partial isotopic re-equilibration during ascent and cooling. In this work, we present new experimental data on the kinetics of D–H exchange for H 2 dissolved in liquid water at temperatures below 100 °C. Comparing these results with published exchange rates obtained from gas phase experiments (100–400 °C), we derive a consistent activation energy of 52 kJ/mol, and the following rate expressions; ln k =9.186 - 6298/ T and k 1 = 9764.61[H 2 O] e-6298/ T where T is absolute temperature (K), k is the universal rate constant ([L/mol]/hr), and k 1 is a pseudo-first-order constant (hr -1 ) applicable to water-dominated terrestrial systems by constraining [H 2 O] as the density of H 2 O (in mol/L) at the P-T of interest. The density-dependent rate constant accounts for the kinetic disparity of D–H exchange with H 2 when dissolved in liquid H 2 O relative to a gas/steam phase, exemplifed by 1/ k 1 at 100 °C of ~2 days in liquid, versus ~7 yrs in saturated steam. This difference may explain the high variability of δDH 2 observed in fumarolic gases. Fluids convecting in the crust frequently reach T > 225 °C, where isotopic equilibrium is rapidly attained (<1 hr). We compare fractionation factors measured in natural fluids (α OBS ) with values expected for equilibrium at the T of acquisition. Where these values differ, we use kinetic models to estimate cooling rates during upward advection that account for the observed disequilibrium. Models fit to fluids from Yellowstone Park and the Lost City (deep-sea) vent field, both recovered at ~90 °C, require respective transit times of ~7 hrs and ~11 days between higher temperature reaction zones and the surface. Using estimates of subsurface depths of origin, however, suggests similar mean fluid flow rates (10 s of meters/hr). Additional complications must be considered when interpreting the δDH 2 of lower-temperature effluent. When applied to data from deep-sea hydrothermal systems, our kinetic models indicate microbial catalysis accelerates D–H exchange once fluids cool below ~60 °C. The H 2 measured in both continental alkaline springs and fracture fluids from Precambrian shield rock is likely produced at T < 100 °C, through processes such as serpentinization. In these settings, δDH 2 values appear closer to equilibrium with H 2 O than those from geothermal systems. Considering kinetic isotope effects may yield H 2 that is out of equilibrium when generated at lower temperatures, we calculate maximum (isothermal) times to apparent isotopic equilibrium of 1.3 yrs at 50 °C, 9 yrs at 25 °C, and 35 yrs at 10 °C. A similar calculation applied to Antarctic brines (-13 °C), where measured δDH 2 is far from equilibrium, yields ~350 yrs. This time is shorter than the fluids have been isolated (2.8 ka), suggesting kinetic isotope effects associated with H 2 destruction or loss via diffusion may also be possible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Exergy of air, CO 2 , and H 2 O for use as geothermal fluids

Geothermal energy refers to the thermal energy naturally stored in the hot rock formation buried deep beneath the Earth’s surface. To harvest this source of energy, a fluid is pumped down in a set of injection wells, circulates through the hot rock and then is collected via a set of production wells for heating or other purposes. Furthermore, the selection of this fluid is an important component of a geothermal system. In this work, we review, evaluate, and develop the fundamental equations that can reliably predict the thermodynamic and the transport properties of air, CO 2 , and H 2 O. Using these equations, we characterize and compare the heat extraction and exergy carried by these fluids as they circulate through a hot rock reservoir to determine which fluid offers better functionality for geothermal heat harvesting applications. The results indicate that, in terms of heat extraction and exergy, air is a better fluid compared to CO 2 and water.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Expanding Geothermal Resource Utilization through Directed Research, Education, and Public Outreach

The Great Basin Center for Geothermal Energy (GBCGE or the Center) was established at the University of Nevada, Reno (UNR) in May 2000 to promote research and utilization of geothermal resources. The Center received funding through this grant to promote increased geothermal development in the Great Basin, with most of the funding used for peer-reviewed research. Funding to the Center and work under the contract were initiated in March 2002, with supplemental funding in subsequent years. The Center monitored the research projects that were competitively awarded in a series of proposal calls between 2002 and 2007. Peer-reviewed research promoted identification and utilization of geothermal resources in Nevada. Projects used geology, geochemistry, geophysics, remote sensing, and the synthesis of multi-disciplinary information to produce new models of geothermal systems in the Western U.S. and worldwide. Funds were also used to support graduate student research and training. Part of the grant was used to support public outreach activities, including webpages, online maps and data resources, and informational workshops for stakeholders.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Thermal shock resistance of lightweight cements developed for geothermal conditions

Cements are a critical component in well construction, as they act to prevent well fluid and gas escape, prevent corrosion of the casing, and strengthen the wellbore to prevent deformation. Under the high temperature/pressure conditions common in geothermal systems, the injection of cold water for energy production is expected to induce cyclic damage to the borehole cement through the rapid temperature fluctuations. These “thermal shocks” are expected to cause casing shrinkage, annulus formation, and cement tensile stresses. To understand the effect of cold water injection on the wellbore environment, a set of rock-cement-steel samples were created to simulate the structure of a geothermal well. Lightweight thermally-insulating cement blends were tested under thermal shock conditions in this study. In each test, the samples were pressurized to an effective pressure of ~3.5 MPa and placed at high temperatures. Thermal shocks were performed by injecting cold water (~10-15 °C) through the samples at a constant rate while keeping the samples at high temperatures until the sample temperature stopped decreasing and deformation ceased. Eight thermal shock tests were conducted with each sample – two at 100 °C and six at 200 °C. Post-tests analysis was then conducted by cutting open each sample to examine the damage in each component of the simulated wellbore. Experimental results suggest that all samples experienced similar degrees of axial and lateral contraction during cold water injection, but for the most part this contraction is recoverable when injection halts. Post-test analysis revealed that fly ash cenosphere pre-treatment had the best effect on improving thermal shock resistance in the cement blends. Thermomechanical modeling of likely stress paths experienced by the cements during heating/cooling cycles shows that elasto-plastic cement constitutive behavior results in most plastic strain occurring during the initial heating steps, with mostly elastic strain occurring during the thermal shock cycles. In conclusion, this agrees with experimental evidence, suggesting that cement damage from shocking occurs via other mechanisms such as chemical alteration, corrosion, and fatigue.

36 MATERIALS SCIENCE↗
DOE OSTI2013

3D Model of the Neal Hot Springs Geothermal Area

The Neal Hot Springs geothermal system lies in a left-step in a north-striking, west-dipping normal fault system, consisting of the Neal Fault to the south and the Sugarloaf Butte Fault to the north (Edwards, 2013). The Neal Hot Springs 3D geologic model consists of 104 faults and 13 stratigraphic units. The stratigraphy is sub-horizontal to dipping

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

Creating Optimal Fracture Networks

The primary goal of this project is the development of a multi-physics, multi-scale simulation capability to predict the initiation, propagation and maintenance of hydraulically driven fracture networks in heterogeneous geologic materials. The development and validation of integrated code capability, GEOS, that accurately captures the phenomenology of these complex physical processes across a wide range of time-­ (~10 -6 to ~10 8 s) and length- (~10 -3 to ~10 4 m) scales is the main scientific objective of the proposed initiative. GEOS constitutes a new analytical framework incorporating the underlying physics that drives fracture development – e.g. dynamically changing fracture network topologies, fluid/solid interactions taking place along discrete interfaces, and complex matrix/fracture transport processes. Enhanced seismic observational tools and inversion methods will also be developed. This initiative has positioned LLNL to play a leading role in the development of Enhanced Geothermal Systems, unconventional gas energy resources, risk assessment associated with geologic sequestration of CO 2 and the detection of radioactive gases from clandestine nuclear tests, impacting both energy and national security.

02 PETROLEUM↗
DOE OSTI2016

Development of a 300°C 3C Fiber Optic Downhole Seismic Receiver Array for Surveying and Monitoring of Geothermal Reservoirs

To address the critical site characterization and monitoring needs for Enhance Geothermal Systems (EGS) programs, US Department of Energy (DOE) awarded Paulsson, Inc. in 2011 a contract to design, build and test a high temperature fiber optic based ultra-large bandwidth clamped borehole seismic vector array capable of deploying a large number of 3C sensor pods suitable for deployment into high temperature and high pressure boreholes. Paulsson, Inc. has completed a design or a unique borehole seismic system consisting of a novel drill pipe based deployment system that includes a hydraulic clamping mechanism for the sensor pods, a new sensor pod design and most important – a unique fiber optic seismic vector sensor with technical specifications and capabilities that far exceed the state of the art seismic sensor technologies. These novel technologies were all applied to the new borehole seismic system. In combination these technologies will allow for the deployment of up to 1,000 3C sensor pods in vertical, deviated or horizontal wells. Laboratory tests of the fiber optic seismic vector sensors developed during this project have shown that the new borehole seismic sensor technology is capable of generating outstanding high vector fidelity data with extremely large bandwidth: 0.01 – 6,000 Hz. Field tests have shown that the system can record events at magnitudes much smaller than M-4.0 at frequencies over 2,000 Hz. The sensors have also proved to be about 100 times more sensitive than the regular coil geophones that are used in borehole seismic systems today. The fiber optic seismic sensors have furthermore been qualified to operate at temperatures over 300°C (572°F). The data telemetry fibers used for the seismic vector sensors in the system are also used to simultaneously record Distributed Temperature Sensor (DTS) and Distributed Acoustic Sensor (DAS) data allowing additional value added data to be recorded simultaneously with the seismic vector sensor data.

02 PETROLEUM↗
DOE OSTI2023

Temperature uncertainty modelling with proxy structural data as geostatistical constraints for well siting: an example applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural geology information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aims of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations. The data used to support the modelling are measured temperatures and structural proxies from 3D geologic modelling (distance to fault, distance to fault intersections and terminations, Coulomb stress change and dilation tendency), the latter considered ‘secondary’ data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally-likely temperature models (i.e. realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: V prior and entropy. V prior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because of the dipping ellipsoid shape created and that the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e. linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g. dilation v. distance to fault termination) should be used given the specific geothermal system. In general, V prior from local varying mean results identify locations that are close to high values for the structural proxies: areas with higher probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comparison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

3D temperature modeling↗
DOE OSTI2017

Simultaneous inversion of multiple microseismic data for event locations and velocity model with Bayesian inference

We have applied Bayesian inference for simultaneous inversion of multiple microseismic data to obtain event locations along with the subsurface velocity model. The traditional method of using a predetermined velocity model for event location may be subject to large uncertainties, particularly if the prior velocity model is poor. Our study indicated that microseismic data can help to construct the velocity model, which is usually a major source of uncertainty in microseismic event locations. The simultaneous inversion eliminates the requirement for an accurate predetermined velocity model in microseismic event location estimation.Here, we estimate the posterior probability density of the velocity model and microseismic event locations with the maximum a posteriori estimation, and the posterior covariance approximation under the Gaussian assumption. This provides an efficient and effective way to quantify the uncertainty of the microseismic location estimation and capture the correlation between the velocity model and microseismic event locations. We have developed successful applications on both synthetic examples and real data from the Newberry enhanced geothermal system. Comparisons with location results based on a traditional predetermined velocity model method demonstrated that we can construct a reliable effective velocity model using only microseismic data and determine microseismic event locations without prior knowledge of the velocity model.

58 GEOSCIENCES↗
DOE OSTI2013

3D Model of the San Emidio Geothermal Area

The San Emidio geothermal system is characterized by a left-step in a west-dipping normal fault system that bounds the western side of the Lake Range. The 3D geologic model consists of 5 geologic units and 55 faults. Overlying Jurrassic-Triassic metasedimentary basement is a ~500 m-1000 m thick section of the Miocene lower Pyramid sequence, pre- syn-extensional Quaternary sedimentary rocks and post-extensional Quaternary rocks. 15-30 degrees eastward dip of the stratigraphy is controlled by the predominant west-dipping fault set. Both geothermal production and injection are concentrated north of the step over in an area of closely spaced west dipping normal faults.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

geoPFA: A Python-Based Open-Source Software for 3D Geothermal PFA

This work presents a novel Python-based framework, geoPFA, for conducting 3D play fairway analysis (PFA) tailored to superhot geothermal systems. The workflow has been applied to the Nesjavellir field in Iceland, a candidate site for the third Iceland Deep Drilling Project's superhot production scenarios. This application demonstrates the value of modular, transparent, and extensible workflows for integrating geological, geophysical, and simulation-derived datasets in high-enthalpy environments. Preliminary results indicate favorable zones consistent with known hydrothermal activity. The geoPFA library will soon be publicly available, offering a scalable and reproducible approach to geothermal exploration across varied geological contexts.

15 GEOTHERMAL ENERGY↗