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Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site.

15 GEOTHERMAL ENERGY↗

Renewable Energy Potential Model: Geothermal Supply Curves

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. The included paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results provided here should be considered with care due to the high uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for three scenarios: two hydrothermal (3.5km depth, USGS heat flow & SMU temperatures respectively) and one EGS (4.5km depth, SMU temperatures). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

15 GEOTHERMAL ENERGY↗

Geothermal Heat Recovery Complex: Large-Scale, Deep Direct-Use System in a Low-Temperature Sedimentary Basin (Final Report)

A feasibility study of using deep direct-use (DDU) geothermal energy to heat agricultural research facilities (ARFs) was conducted at the University of Illinois at Urbana-Champaign (U of IL) and its similar application to military facilities in the Illinois Basin (ILB). The geothermal energy system (GES) investigated utilizes low-temperature (30–90°C; 90–190°F) geothermal fluid (i.e., brine) from an extraction well that is part of a deep, two-well (doublet) system that extends to the bottom of the ILB. The geothermal reservoir modeled, the Mt. Simon Sandstone (MSS), is about 1,280 m (4,200 feet) deep and 457 m thick (1,500 feet) beneath the U of IL. The DDU GES surface infrastructure includes heat exchangers connected in-parallel to pipelines carrying the geothermal fluid and fresh cold and hot water. Analysis of the GES indicated that the MSS can provide a baseload of 2 MMBtu/hr to heat the ARFs by extracting 954 m³/d (6,000 barrels/day [bbl/d]) of geothermal fluid that has a temperature of 44–46 °C (111–115 °F). In addition to analyzing the levelized cost of heat (LCOH) and life cycle costs, the environmental effects of the DDU GES were evaluated, including reduced greenhouse gas (GHG) emissions and water consumption. Multiple system designs were evaluated and then ranked based on their maximum heating performance, energy efficiency, and cost recovery. This feasibility study identified the key components of the fully-integrated DDU technology that can be implemented, both technically and economically. The results and information from this study provides end-users and policy makers with guidance for additional research on the specific components of DDU technology such that its widespread use can provide an uninterruptible energy source, increase resilience from extreme weather conditions, reduce U.S. dependency on fossil fuels, and reduce greenhouse gas (GHG) emissions. The site-specific part of this study gives U of IL administrators a realistic and pragmatic assessment of the financial resources necessary to add a DDU GES in the MSS to the campus’ energy portfolio.

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Economic Impact of Permitting Timelines on Produced Geothermal Power

Despite having a large geothermal power potential in the United States, only a small fraction has been developed for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to lower contribution of geothermal energy in the national grid. Unpredictable environmental reviews and permitting timelines are some of the non-technical barriers that can cause delays in geothermal exploration and utilization plans. This study shows that the geothermal permitting timelines can vary from six months to several years, depending on the presence or absence of biological resources, cultural resources, and sensitive environmental issues at the project site. The potential impacts of these permit barriers can range from investors abandoning geothermal development to making the product (i.e., electricity) more expensive and uncompetitive.

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What Rocks and What's Not So Hot: U.S. Industry Perception of Geothermal Tax Credits

Nationwide, four U.S. federal tax credits promote the adoption of geothermal heat pumps (GHPs) and geothermal power plants and were recently updated with enactment of the Inflation Reduction Act (IRA).1 However, uptake of these geothermal tax credits has lagged behind other eligible technologies.2 With the support of the U.S. Department of Energy (DOE)'s Geother- mal Technologies Office, researchers at the National Renewable Energy Laboratory (NREL) engaged with the geothermal industry to determine: 1) how the industry will use the tax credits, 2) remaining challenges to utilizing tax credits, and 3) suggestions on solutions that could help accelerate tax credit uptake. Insights were obtained through two industry question- naires (59 responses)3 and 21 interviews with representatives from geothermal industry groups, project developers, com- ponent manufacturers, and financiers, as shown in Figures 1 and 2. This article synthesizes the industry's perception of these tax credits, i.e., Section 25D (residential GHP), Section 48 (commer- cial GHP), Section 48E (investment tax credit [ITC] for electricity), and Section 45Y (production tax credit [PTC] for electricity).

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The Effect of Hydrothermal Alteration and Microcracks on Hydraulic Properties and Poroelastic Deformation: A Case Study of the Blue Mountain Geothermal Field

Abstract Geothermal energy plays a vital role in decarbonizing electricity and heat supply. Effective utilization of geothermal resources hinges on identifying or generating permeable reservoir zones and understanding how effective pressure variations affect fluid circulation and reservoir properties by poroelastic deformation. Hydrothermal alteration can modify the petrophysical properties of geothermal reservoir rocks, which may increase or decrease its productivity. Understanding these alteration effects is essential to predict and optimize long‐term sustainable geothermal operations. Here, we investigate the impact of hydrothermal alteration on poroelastic and hydraulic properties of diverse lithologies in a series of deformation tests performed at several confining (0–80 MPa) and pore pressure (10–30 MPa) levels. Experimental results of hydrothermally altered dikes and phyllites obtained from the Blue Mountain geothermal field (Nevada, USA) are compared to thermally cracked La Peyratte granite (France) and correlated with petrophysical properties, mineral composition, and microstructures. Argillic alteration of dikes increases porosity and storage capacity but lowers thermal conductivity and increases pore compressibility. Conversely, silicate precipitation in phyllites increases stiffness and thermal conductivity but also reduces porosity and permeability. Experimentally determined effective pressure coefficients range from 0.1 to 0.9, differ for permeability and volumetric strain and decrease with increasing effective pressure. The presence of compliant microcracks and crack‐like pores significantly increases the stress sensitivity of La Peyratte granite and silicified phyllites. This study demonstrates how thermal and chemical alteration impacts poromechanical and petrophysical characteristics of geothermal targets, which ultimately govern reservoir stability and subsidence, induced seismicity as well as fluid and heat extraction efficiency during geothermal operations.

Schuster, Valerian [Helmholtz Centre Potsdam GFZ G↗

A Fusion of Geothermal and InSAR Data with Machine Learning for Enhanced Deformation Forecasting at the Geysers

The Geysers geothermal field in California is experiencing land subsidence due to the seismic and geothermal activities taking place. This poses a risk not only to the underlying infrastructure but also to the groundwater level which would reduce the water availability for the local community. Because of this, it is crucial to monitor and assess the surface deformation occurring and adjust geothermal operations accordingly. In this study, we examine the correlation between the geothermal injection and production rates as well as the seismic activity in the area, and we show the high correlation between the injection rate and the number of earthquakes. This motivates the use of this data in a machine learning model that would predict future deformation maps. First, we build a model that uses interferometric synthetic aperture radar (InSAR) images that have been processed and turned into a deformation time series using LiCSBAS, an open-source InSAR time series package, and evaluate the performance against a linear baseline model. The model includes both convolutional neural network (CNN) layers as well as long short-term memory (LSTM) layers and is able to improve upon the baseline model based on a mean squared error metric. Then, after getting preprocessed, we incorporate the geothermal data by adding them as additional inputs to the model. This new model was able to outperform both the baseline and the previous version of the model that uses only InSAR data, motivating the use of machine learning models as well as geothermal data in assessing and predicting future deformation at The Geysers as part of hazard mitigation models which would then be used as fundamental tools for informed decision making when it comes to adjusting geothermal operations.

Yazbeck, Joe (ORCID:0000000302235260)↗

A comparison of economic evaluation models as applied to geothermal energy technology

Several cost estimation and financial cash flow models have been applied to a series of geothermal case studies. In order to draw conclusions about relative performance and applicability of these models to geothermal projects, the consistency of results was assessed. The model outputs of principal interest in this study were net present value, internal rate of return, or levelized breakeven price. The models used were VENVAL, a venture analysis model; the Geothermal Probabilistic Cost Model (GPC Model); the Alternative Power Systems Economic Analysis Model (APSEAM); the Geothermal Loan Guarantee Cash Flow Model (GCFM); and the GEOCOST and GEOCITY geothermal models. The case studies to which the models were applied include a geothermal reservoir at Heber, CA; a geothermal eletric power plant to be located at the Heber site; an alcohol fuels production facility to be built at Raft River, ID; and a direct-use, district heating system in Susanville, CA.

Ziman, G. M.↗

The value of integrating a geothermal district heating system into a microgrid

As electrical grids increasingly rely on variable renewable energy, maintaining reliability and cost efficiency becomes more complex. To address these challenges, this study analyzed the integration of geothermal district heating as a grid-responsive thermal resource within a microgrid in Tuttle, Oklahoma. Building energy modeling using EnergyPlus estimated annual district heating demand at 2.9 GWh, with a peak load of 2.8 MW th . Techno-economic analyses were conducted to meet the heating demand under three geothermal scenarios, varying by production depth, flow rate, and thermal output, each supplemented by natural gas peaking boilers. In parallel, equivalent electrical load profiles were developed using typical coefficients of performance (COPs) for air-source heat pumps and electric boilers to establish an electrified baseline scenario. A complete end-use electrical load profile was also developed for the microgrid using Cambium dataset. The modeling results demonstrated reliable and economic operation of the geothermal systems over 30 years, with COPs ranging from 2.6 to 8.9 and the lowest levelized heating cost at $\$$54.6/MWh. Geothermal integration reduced electricity consumption by up to 94.7 % compared to the non-geothermal base case, yielding annual energy savings of up to $\$$803 k. Avoided grid costs ranged from $\$$65 k–$\$$147 k per year, with individual events avoiding up to $\$$4,863 per hour. Grid-responsive operation further reduced wholesale energy costs by 53–56 %. These findings demonstrate geothermal heating, traditionally treated as a non-grid-responsive thermal resource, can be reconfigured to support dynamic grid services, offering a scalable pathway to enhance reliability and reduce costs in renewable-rich microgrids and district heating networks.

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Three-dimensional seismic characterization and imaging of the Soda Lake geothermal field

Accurate characterization of subsurface geophysical properties and detection of the fault system are essential for geothermal energy exploration and production. The Soda Lake geothermal field is in western Nevada with a complex fault system. Previous seismic characterization only produced a low-resolution, smooth velocity model along with a simple, conceptual fault model. Using optimized correlation-based full-waveform inversion, wavefield-separation-based reverse-time migration, and automatic fault detection techniques, we present 3D seismic characterization for the Soda Lake geothermal field using 3D surface seismic data acquired with Vibroseis sources. Here, we obtain 3D high-resolution velocity, density, and acoustic impedance models, 3D seismic images with different grid spacings, and a high-resolution fault system. Consistency check between the constructed faults and currently active injection and production geothermal wells verifies that our seismic inversion and imaging results and detected faults are reliable. These results can provide valuable information for optimizing well placement and geothermal energy production at the Soda Lake geothermal field.

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Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin, USA

This study discovers various geothermal prospects in the Great Basin, USA based on shallow groundwater chemical (geochemical) data. The geochemical data are expected to include hidden (latent) information that is a proxy for geothermal prospectivity. We processed the sparse geochemical data in the Great Basin at 14,341 locations including 18 attributes. Next, a non-negative matrix factorization with customized k-means clustering is applied to the geochemical data matrix that automatically finds three hidden geothermal signatures representing modestly, moderately, and highly confident geothermal prospects. The algorithm also evaluated the probability of occurrence of these types of resources through the studied region. There is a consistency between regional geothermal prospectivity as estimated by our ML methodology and the traditional play fairway analysis conducted over a portion of the study area. We also identify the dominant data attributes associated with each signature. Finally, our ML analyses allow us to reconstruct attributes from sparse into continuous over the study domain. The predicted continuous attributes can be used for future detailed geothermal explorations in the Great Basin.

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Dataset for report: Non-Technical Barriers to Geothermal Development in California and Nevada

In California and Nevada, geothermal projects are subject to non-technical barriers, which may create development delays leading to higher project costs and risks and decreased competitiveness with other electricity generation technologies. These non-technical barriers may include federal and state permits, authorizations, environmental reviews, and other regulatory requirements that are applicable throughout different phases of geothermal project development. The 2022 National Renewable Energy Laboratory (NREL) report, "Non-Technical Barriers to Geothermal Development in California and Nevada" presents findings of a study on non-technical barriers that may influence geothermal project development. The set of data resources relied upon for the report includes: 1) interviews conducted with relevant geothermal stakeholders including regulators and project developers, 2) federal and state environmental review documents developed for specific projects, 3) a techno-economic analysis conducted using the NREL Annual Technology Baseline (ATB) framework, and 4) an analysis of the impacts of site-specific land access and permitting considerations on project development readiness conducted using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) Socioeconomic Assessment Tool (SEAT).

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Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin

This dataset is part of an effort to highlight the advantages of incorporating low-temperature (< 150 C) geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). For this Denver Basin example, resource favorability maps were created to identify potentially favorable areas for further geothermal exploration and are provided here. Favorability was based on three types of data: (1) geologic, (2) economic, and (3) risk. This raw data is also provided below. Geologic data include bottom-hole temperatures (BHT) from oil and gas wells, water co-production volumes from oil and gas wells, well groundwater levels, hot spring locations, temperatures, and chemistries, faults, and earthquakes. Economic feasibility data include population, thermal energy demand, infrastructure, and roads. Risk data (which includes data on excluded areas) include flood plains, protected lands (e.g. wildlife conservation areas, national parks). The included report describes this project in detail, covering workflows, relevant datasets, Python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The figures in this report include: maps of the original datasets; maps of transformed data and derived parameters (such as the geothermal gradient or thermal conductivity); results of uncertainty analyses; results of data completeness (using the GeoRePORT tool); examples of the data combination and processing (using the geoPFA Python library, which is introduced in the attached report); favorability maps for each criteria; and a final combined favorability map. This project is designed to facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

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Nontechnical Barriers to Geothermal Development

Geothermal energy presents a significant opportunity for the United States (US). The US has the largest known geothermal resource in the world, with over 31 GW of conventional geothermal (i.e., hydrothermal) potential. Despite this, the development of geothermal power plants has lagged other renewable resources. Though some of the gaps stem from technical barriers numerous non-technical barriers are preventing geothermal energy from reaching its full potential. The gaps include a need to reduce the cost impacts of seismic risk, environmental risk, exploration, drilling and permitting cost risk, and reduced summer capacity on plant profitability. This report identifies pathways to overcome these barriers. We find that geothermal energy could increase its market presence by acting as a complement to lower cost renewables, providing flexible or baseload power in low carbon scenarios. We also outline several contractual and operational strategies (including the use of hybrid systems) that plant operators can pursue to improve the value of their resource, such as multi part remuneration mechanisms that guarantee revenue (e.g., availability payments or a Contract for Differences approach) or resource risk hedging approaches (e.g., shaped market products and portfolio resource approaches).

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Geothermal Interagency Collaboration Task Force: Summary of Findings

This report summarizes the findings of the Geothermal Interagency Collaboration Task Force (Task Force) and associated stakeholder forums and Tribal listening sessions. The Task Force included federal agencies and state agencies in California and Nevada with a nexus to geothermal regulatory and permitting approvals. The Task Force met twice over the course of 2022 to discuss current geothermal regulatory and permitting challenges and strategies for improved coordination and permit processing. In addition, the project team held four forums/listening sessions in 2022 with geothermal industry representatives, environmental non-governmental organizations, and Tribes to gain additional insight and perspective on the geothermal regulatory process and managing potential cultural and natural resource conflicts that may arise during geothermal development.

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Non-Technical Barriers to Geothermal Development in California and Nevada [Slides]

This presentation presents the findings of our study, including an analysis of federal, state, and local geothermal regulatory and permitting processes, case studies analyzing site-specific attributes that may impact project development at four selected geothermal project sites, an analysis of cost and timeline implications for geothermal project development, and the results of a qualitative study focused on inter-agency coordination and collaboration efforts between federal, state, and/or local agencies for geothermal projects located in California and Nevada. Our analysis found that development timelines may be impacted by multiple federal and state environmental review processes and duplicative permitting requirements as well as coordination efforts between numerous federal, state, and local agencies involved in issuing authorizations and permits necessary for project development. In addition, projects in California and Nevada may face site-specific environmental challenges due to the presence of sensitive resources (e.g., biological species and species habitat, cultural resources) that may result in project construction delays. Our study results also indicate that protracted geothermal development timelines caused by delays in acquiring necessary permits and environmental reviews may result in loss of generated electricity revenue and additional financing costs, which may increase economic uncertainty associated with project development. Through our qualitative analysis, we found that utilization of best practices, including tiering to existing environmental review documents and developing memoranda of understanding, which clearly delineate agency roles and responsibilities may reduce overall project timelines, costs, and uncertainties associated with geothermal project development in California and Nevada.

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Techno-Economic Analysis of Greenfield Geothermal Hybrid Power Plants using a Solar or Natural Gas Steam Topping Cycle

The relatively low generation costs associated with wind, solar PV, and natural gas power plants make it challenging for geothermal power plants to produce and sell the power that has the reliability and sustainability characteristics that are greatly needed in US power markets. This is especially true for geothermal resources with low to medium temperatures, which results in relatively low thermal efficiency and generation costs that are higher than those for wind, solar PV, and natural gas. This analysis evaluates solar thermal- and natural gas combustion waste heat recovery-based topping cycle hybridization of geothermal binary power plants. This approach provides several benefits that may allow geothermal power plants to generate power at more competitive costs. First, the addition of solar thermal energy or natural gas combustion waste heat input to a geothermal power plant provides additional heat input that can be converted to electrical power. Second, the temperature level of the heat obtained from concentrating solar collectors or natural gas combustion exhaust is higher than that of geothermal heat, which provides opportunities for improving the efficiency of the conversion of thermal energy to electrical power. Third, the ease with which solar thermal systems integrate with energy storage and the flexibility of natural gas means power generation can occur during peak demand periods.

14 SOLAR ENERGY↗

Imaging Complex Subsurface Structures for Geothermal Exploration at Pirouette Mountain and Eleven-Mile Canyon in Nevada

Accurate imaging of subsurface complex structures with faults is crucial for geothermal exploration because faults are generally the primary conduit of hydrothermal flow. It is very challenging to image geothermal exploration areas because of complex geologic structures with various faults and noisy surface seismic data with strong and coherent ground-roll noise. In addition, fracture zones and most geologic formations behave as anisotropic media for seismic-wave propagation. Properly suppressing ground-roll noise and accounting for subsurface anisotropic properties are essential for high-resolution imaging of subsurface structures and faults for geothermal exploration. We develop a novel wavenumber-adaptive bandpass filter to suppress the ground-roll noise without affecting useful seismic signals. This filter adaptively exploits both characteristics of the lower frequency and the smaller velocity of the ground-roll noise than those of the signals. Consequently, this filter can effectively differentiate the ground-roll noise from the signal. We use our novel filter to attenuate the ground-roll noise in seismic data along five survey lines acquired by the U.S. Navy Geothermal Program Office at Pirouette Mountain and Eleven-Mile Canyon in Nevada, United States. We then apply our novel anisotropic least-squares reverse-time migration algorithm to the resulting data for imaging subsurface structures at the Pirouette Mountain and Eleven-Mile Canyon geothermal exploration areas. The migration method employs an efficient implicit wavefield-separation scheme to reduce image artifacts and improve the image quality. Our results demonstrate that our wavenumber-adaptive bandpass filtering method successfully suppresses the strong and coherent ground-roll noise in the land seismic data, and our anisotropic least-squares reverse-time migration produces high-resolution subsurface images of Pirouette Mountain and Eleven-Mile Canyon, facilitating accurate fault interpretation for geothermal exploration.

15 GEOTHERMAL ENERGY↗