Amplify EGS Project: Seismic Monitoring for In-field and Near-field Enhanced Geothermal Systems Stimulation at Wells of Opportunity (WOO) Sites in Nevada
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Su, Jiann-Cherng↗
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Hybrid geothermal-wind integration in the US energy grid
Here, we combine US wind generation—a cheap yet intermittent source of electricity—with the latest geothermal resource estimates to understand the technoeconomic possibilities of pairing enhanced geothermal systems (EGSs) with existing wind farms to develop a hybrid energy system. Using observed generation data from 583 wind farms, generation gaps are quantified and geographically paired with the latest EGS estimates. Results demonstrate that EGS potential within a 1 km 2 footprint can supplement wind generation at 56% of onshore wind farms. Each wind farm can be supplemented by EGSs when 10% of its surface-occupying footprint is available. The cost of EGSs at wind farms is lowest in the western US and southern Texas border and highest in the central US. While further experiments are warranted, a wind + EGS hybrid system offers an opportunity to increase power output from the same land footprint while maximizing the use of existing electrical infrastructure.
EGS↗
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Team has shared the following files from the project: - 149 microearthquakes (MEQs) between 2012 and 2013 at Newberry EGS sites, 'Normalized Waveform Inputs.npz' are normalized waveforms. - labels of 149 MEQs: Processed Waveform Inputs.npz - location labels of 149 MEQs: Location Data.npz Note: .npz is the python file format by NumPy that provides storage of array data.
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Newberry SHR Demonstration Project – Bipartisan Infrastructure Law Enhanced Geothermal (EGS) Pilot Demonstration (Abstract)
This project will create an Engineered Geothermal System (EGS) comprising two or more wells drilled to a depth of 4.25 km into superhot rock (SHR) with a temperature of 425 °C at Newberry Volcano in Central Oregon. An EGS is a manufactured heat exchanger in which water is injected in a deep injection well, or injector, to extract heat from the hot rock at depth and steam is returned to the surface in a production well, or producer, to generate electricity. In this project, the SHR EGS will be made using new methods and technologies to stimulate and connect hydraulic and natural fractures to enable multiple flow pathways between wells, allowing for optimal heat mining from the reservoir rock. The new technologies are designed to operate at rock temperatures much higher than those encountered in traditional geothermal. Following EGS completion, water will be injected into the injector well and steam extracted from the producer well in a long-term connectivity flow test demonstrating SHR reservoir evolution with time and use. Success will be measured by demonstrating the efficacy of new technologies and by producing economic quantities of steam (>40 MWth).
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Exploring the physical limits of hydraulic fracture caging to forecast its feasibility for geothermal power generation
Not Available
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Utah FORGE Well 16A(78)-32 Simplified Discrete Fracture Network Data
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 16A(78)-32. This is a simplified DFN (discrete fracture network) dataset, that was generated using FracMan, for Utah FORGE well 16A(78)-32. A short, well-illustrated, report describing the data is also included in the provided archive file.
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Mixed-Mechanism Stimulation Enabled Enhanced Geothermal Systems (CRADA FP00007509 Final Report)
In this project, we aimed to develop a robust, novel EGS design that would enable broad deployment of geothermal energy at costs competitive with other sources of renewable energy. The technical objectives included developing reservoir models for synthetic geothermal systems that meet target reservoir performance characteristics, performing a quantitative assessment of selection criteria for candidate geothermal sites, perform proppant studies under relevant geothermal conditions, and complete an induced seismicity risk analysis for potential geothermal development sites. The project team made significant progress towards these objectives. Specifically, we developed a prioritization to rank candidate sites for suitability of our technology based on 10 separate technical, operational, logistic, regulatory, and commercial criteria. The team performed laboratory testing at Lawrence Berkeley National Laboratory to characterize the functionality of several different types of proppant materials at temperatures of up to 200 C for durations of up to 9 weeks. We also created an Induced Seismicity Mitigation Plan for the top two sites selected for our future field demonstrations.
58 GEOSCIENCES↗
Introduction to this special section: Geothermal energy
Geothermal energy is a global renewable resource that has the potential to provide a significant portion of baseload energy in many regions. In the United States, it has the potential to provide 8.5% of the electric generation capacity by the middle of the century. In general, geothermal systems require heat, permeability, and water to be viable for energy generation. However, with current technologies, only heat is strictly necessary in a native system. Engineered geothermal systems (EGS) introduce water into the subsurface at elevated pressures and reduced temperatures and enhance permeability through hydraulic and/or shear fracturing. Additionally, although moderate- to high-temperature resources currently dominate geothermal energy production, low-temperature resources have been utilized for direct-use cases. When well balanced and maintained, geothermal resources can produce significant amounts of heat and achieve long-term sustainability on the order of an estimated tens to hundreds of years.
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Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1
EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.
numerical simulation, embedded fractures and boreh↗
Experimental investigation of flow distribution in enhanced geothermal systems with deep eutectic solvent
Geothermal energy has been recognized as a valuable alternative to fossil fuels and nuclear power, as it is renewable and reliable. Enhanced Geothermal Systems (EGSs) have the potential to expand geothermal energy production by enabling access to previously untapped geothermal resources. Geothermal short-circuiting poses a significant challenge to EGS development, leading to reduced heat extraction. Deep Eutectic Solvent (DES) exhibits favorable thermal and rheological properties, making it a candidate for geothermal applications. Here, this paper examines Choline Chloride-Based Deep Eutectic Solvent (DES) as a working fluid in geothermal applications and its potential to mitigate geothermal short-circuiting. Hydraulic experiments using a dual fracture flow loop were conducted at high temperatures. The results showed that DES exhibited higher differential pressure behavior compared to water. Flow distribution results revealed that DES enhances flow allocation within the small fracture, particularly when a temperature difference exists between fractures. Specifically, DES increased flow distribution by an average of 11% when the temperature difference was 85°C, and by 13% when the difference was 45°C, relative to water. These findings suggest that DES responds to thermal fracture differences, making it a potential remedy to address geothermal short-circuiting.
15 GEOTHERMAL ENERGY↗
EGS Collab Experiment 2: Continuous Active Source Seismic Monitoring (CASSM)
The dataset contains continuous active-source seismic monitoring (CASSM) data collected during EGS Collab Experiment 2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to investigate enhanced geothermal systems through high-pressure fluid injections at depths of 1200-1500 meters. The seismic monitoring system included 16 three-component piezoelectric accelerometers and 24 hydrophones installed in boreholes around the injection zones, recording signals from piezoelectric seismic sources. Data were acquired using both continuous and triggered recording systems, with sampling rates of up to 100 kHz. The raw data are organized by timestamps and stored in .dat format, with accompanying log files. Calibration certificates for selected accelerometers are provided to aid in correcting sensor responses, though users are advised to consider possible effects of enclosures and installation on sensor performance. Users are strongly advised to consult the accompanying report, which outlines the experimental setup, data acquisition, sensor specifications, and recording systems.
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Analysis of Hydraulic Fracturing on the 4100 Level at the Sanford Underground Research Facility
A series of hydrofractures were performed on the 4100 ft. level of the Sanford Underground Research Facility (SURF) to quantify the minimum principal stress and stress orientation. The motivation for this work was to determine the suitability of the site as a second testbed for the EGS Collab project and to inform the testbed design. EGS Collab is a meso-scale project where experiments are being performed to increase permeability in low-permeability rock and improve our understanding of appropriate techniques and models required for developing enhanced geothermal systems. In order to design the second testbed, a ~50 m vertical HQ (96 mm) pilot borehole was drilled in June, 2019, to perform a series of mini-frac tests to determine rock stress state. Utilizing an elastic model based on the ISIP (Instantaneous Shut In Pressure), testing indicates that the minimum principal stress is 20.4 MPa oriented NNE (24°) and plunges at an angle of approximately 28°.
Ingraham, Mathew↗
Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems
Abstract A major challenge in the inversion of subsurface parameters is the ill‐posedness issue caused by the inherent subsurface complexities and the generally spatially sparse data. Appropriate simplifications of inversion models are thus necessary to make the inversion process tractable and meanwhile preserve the predictive ability of the inversion results. In this study, we investigate the effect of model complexity on fracture aperture inversion and thermal performance prediction in a field‐scale EGS model. Principal component analysis was used to map the aperture field to a low‐dimensional latent space. The complexity of the inversion model was quantitatively represented by the percentage of total variance in the original aperture fields preserved by the latent space. Tracer, pressure and flow rate data were used to invert for fracture aperture through an ensemble‐based inversion method, and the inferred aperture field was used to predict thermal performance. With an over‐simplified aperture model, ensemble collapse occurred. The inverted aperture models failed to resolve necessary flow and transport features, leading to a biased thermal performance prediction. A complex aperture model involved excessive features and was prone to overinterpreting the inversion data. Both the tracer/pressure/flow rate data reproduction and thermal prediction showed significant uncertainties, making it difficult to properly estimate long‐term thermal performance. Fortunately, our results indicate that there exists an appropriate model complexity which can simultaneously match inversion data and predict thermal performance with an acceptable uncertainty. The quality of the fit of tracer data appears to be a useful indicator of such an appropriate model complexity.
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A combined experimental and modelling study of granite hydrothermal alteration
Geochemical reactions can induce significant changes of rock reservoir porosity and permeability via mineral dissolution and precipitation processes, affecting the long-term fluid behaviour within various geological systems. Here, the understanding and quantification of these reactions rely on field and experimental studies and on the predictions of reactive transport models. The present study was aimed at assessing the extent to which current geochemical models integrating available mineral dissolution/precipitation rate equations can reproduce the experimental data obtained from 4 to 17-day long hydrothermal alteration experiments of a muscovite-biotite granite and, thus, help provide an accurate description of the evolution of geothermal systems within granitic reservoirs. The experiments were conducted at a constant temperature of 180 °C and over an aqueous fluid pH range of 2 to 8.5, using both mixed-flow and static batch reactors. Modelled major element (K, Al, Si, Ca, and Mg) concentrations were generally in satisfactory agreement with the corresponding measured elemental fluxes – the differences between modelled and experimental values were generally within a factor of 5 – and the predicted identity and mass of formed secondary phases were consistent with the microscopic observations of the reacted solids. However, larger differences between measured and modelled element concentrations were observed when significant amounts of secondary phases formed, notably at pH 2 to 3, and for longer-term batch experiments. Much of this concentration difference stems from the underestimation of the amounts of Al-phases formed at acid to near-neutral pH. Although an idealized rock composition was considered, the observed mismatch between model calculations and experimental data can be attributed to inadequate mineral precipitation reaction rates and a poor description of reactive surface areas in existing geochemical modelling codes. More accurate quantification of precipitation kinetics, including nucleation and growth, and improved descriptions of the temporal change of mineral surface area would enhance the predictive capabilities of reactive transport models and benefit, particularly, the efforts aimed at increasing the sustainability of EGS reservoirs.
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Increasing Power Generation at the Patua Nevada Geothermal Field through Targeted and Adaptive EGS
In 2020, Patua Acquisition Company LLC, submitted the proposal “Increasing Power Generation at the Patua Nevada Geothermal Field through Targeted and Adaptive EGS”, in response to the DOE’s Geothermal Wells of Opportunity Funding Opportunity Announcement. The primary goal of the project was to convert an idle well, Patua 16-29, to an active producer and generate at least an additional 5 MWe at the Patua plant. The project was intended to provide an example of a reproducible methodology for well stimulation in Enhanced Geothermal Systems The project was proposed to be performed in three phases over a period of performance of four years. A first project go/no-go decision was made at the end of Phase 1 based on feasibility of the wellbore, site, and ability to realize a 5 MWe benefit from the project. Several factors were recognized that led to a no-go decision at this phase: • Electrical needs for placing the stimulated well on production were not considered in the initial scoping. Costs of pipeline costs were also underestimated in the original cost share. Easements and rights-of-way to establish a geothermal pipeline underneath or across an interstate highway were also found to be intractable on the time scale of the project. • The plant is injection limited, and no design or cost estimate was in place to handle the additional production needed to realize a 5 Mwe benefit. A new injection well would need to be drilled in addition to the other facility improvements to bring in the stimulated well. Patau Acquisition Company attempted to locate additional wells of opportunity that could realize the SOPOs goals, but was unsuccessful. As a result, this project is being terminated at the end of Phase 1.
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Deep learning forecasts the spatiotemporal evolution of fluid-induced microearthquakes
Microearthquakes generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems, carbon dioxide sequestration and other geoengineering applications. Here we propose a transformer neural network model that ingests hydraulic stimulation history and prior microearthquake observations to forecast four key quantities: cumulative microearthquake count, cumulative logarithmic seismic moment, and the 50th- and 95th-percentile extents of the microearthquake cloud. Applied to the EGS Collab Experiment 1 dataset, the model achieves R2 > 0.98 for the 1-s forecast horizon and R2 > 0.88 for the 15-s forecast horizon across all targets, and supplies uncertainty estimates through a learned standard deviation term. These accurate, uncertainty-quantified forecasts enable real-time inference of fracture propagation and permeability evolution, demonstrating the strong potential of deep-learning approaches to improve seismic-risk assessment and guide mitigation strategies in future fluid-injection operations.
Chung, Jaehong↗
EverGREEN 2045: An Energy Mix to Decarbonize Washington State
Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Experimental investigation of shear in granite fractures at Utah FORGE: Implications for EGS reservoir stimulation
Not Available
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