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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

GeoRePORT Protocol Volume VI: Resource Size Assessment Tool

GeoRePORT is based on the concept that a geothermal system can be described both in terms of the quality of the geothermal resource as it relates to the potential to extract heat ("Resource Grade") and the progress of research and development over the lifetime of the project ("Project Progress"). Resource grade and project progress are reported for three assessment categories: geologic, technical, and socio-economic. Each category has specific criteria and guidelines for assessing both resource grade and project progress, as outlined in each of the following assessment tools (and associated colors): (1) Geological Assessment Tool (representative colors: reds, oranges, browns); (2) Technical Assessment Tool (representative colors: blues, purples); (3) Socio-Economic Assessment Tool (representative colors: greens, yellows). Additionally, users may need to estimate the project size (often reported in MWe or MWth). The resource size assessment tool (RSAT) is an essential addition to GeoRePORT due to the economic and legal context of geothermal development. In order to utilize a geothermal resource, a competitive Power Purchase Agreement (PPA), or similar, often must be obtained, for which the resource's power capacity must be demonstrated. To determine that a geothermal heat or power project is worthy of development, investors or other funding mechanisms often require information on the anticipated heat and/or power potential of the reservoir. They might also be interested in the certainty of that estimate. However, proving the existence and size of a geothermal resource is comparatively expensive and risky relative to other renewable technologies; it can cost developers 5 to 10 million USD to demonstrate a financially viable geothermal resource (Young et al. 2017). GeoRePORT aims to address this barrier to development by providing a consistent and clear assessment of resource quality and certainty. The RSAT will enable GeoRePORT users to not only qualitatively report on a given a resource, but also to compare standard methodologies for quantitatively estimating a resource size in terms of potential heat and/or power output.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Nationwide cost and capacity estimates for sedimentary basin geothermal power and implications for geologic CO 2 storage

Sedimentary basins are naturally porous and permeable subsurface formations that underlie approximately half of the United States. In addition to being targets for geologic CO 2 storage, these resources could supply geothermal power: sedimentary basin geothermal heat can be extracted with water or CO 2 and used to generate electricity. The geothermal power potential of these basins and the accompanying implication for geologic CO 2 storage are, however, understudied. Here, we use the Sequestration of CO 2 Tool (SCO2T PRO ) and the generalizable GEOthermal techno-economic simulator (genGEO) to address this gap by a) estimating the cost and capacity of sedimentary basin geothermal power plants across the United States and b) comparing those results to nationwide CO 2 sequestration cost and storage potential estimates. We find that across the United States, using CO 2 as a geothermal heat extraction fluid reduces the cost of sedimentary basin power compared to using water, and some of the lowest cost capacity occurs in locations not typically considered for their geothermal resources (e.g., Louisiana, South Dakota). Additionally, using CO 2 effectively doubles the sedimentary basin geothermal resource base, equating to hundreds of gigawatts of new capacity, by enabling electricity generation in geologies that are otherwise (with water) too impermeable, too thin, too cold, or not deep enough. We find there is competition for the best sedimentary basin resources between water- and CO 2 -based power, but no overlap between the lowest-cost resources for CO 2 storage and CO 2 -based power. In this way, our results suggest that deploying CO 2 -based power may increase the cost of water based systems (by using the best resources) and the cost of CO 2 storage (by storing CO 2 in locations that otherwise may not be targeted). As such, our findings demonstrate that determining the best role for sedimentary basins within the energy transition may require balancing tradeoffs between competing priorities.

CPG↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update: Preprint

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the Department of Energy's (DOE) Geothermal Technology Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and Levelized Cost of Energy (LCOE) of hydrothermal geothermal systems and EGS, and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and O&G, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Though drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves as of now.

API↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the U.S. Department of Energy's (DOE) Geothermal Technologies Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and levelized cost of energy (LCOE) of hydrothermal geothermal systems and enhanced geothermal systems (EGS), and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) to weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and the O&G sector, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Although drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves at this time.

API↗
DOE OSTI2021

Life Cycle Emissions Factors for Electricity Generation Technologies

This dataset consists of a table containing the distribution of literature estimates of greenhouse gas emissions for the following electricity generation and storage technologies: biopower, coal, concentrating solar power, geothermal, hydrogen storage, hydropower, lithium-ion battery storage, natural gas, nuclear, ocean, oil, photovoltaic, pumped-storage hydropower, and wind. Quartile estimates of life cycle emissions factors in units of grams of carbon dioxide equivalent per kilowatt hour of generation (g CO2e/kWh) are provided for the following life cycle stages: one-time upstream, ongoing combustion, ongoing non-combustion, one-time downstream, and total. Literature estimates were compiled by the LCA Harmonization study and subsequent updates, as detailed in the factsheet which accompanies this dataset, https://www.nlr.gov/docs/fy21osti/80580.pdf .

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Low-Temperature Geothermal Resources: Relevant Data and PFA Methods to Reduce Development Risk: Preprint

This project is part of a larger national effort focused on demonstrating the multi-faceted value of integrating low-temperature geothermal resources into national decarbonization strategies and community energy plans. Low-temperature geothermal resources are defined as reservoirs-natural or engineered-with temperatures < 150 degrees C. While the focus in the NREL effort is on geothermal heating and cooling (GHC), resources at the upper end of this temperature range can also be used for small-scale power generation. However, low-temperature geothermal resources have not been studied as extensively as higher-temperature geothermal resources. We identified three major classes of low-temperature geothermal play types: sedimentary basins, orogenic systems, and radiogenic systems. We developed workflows for evaluating the potential of these resources building off the Play Fairway Analysis (PFA) approach to de-risking geothermal exploration. This PFA-based approach to low-temperature geothermal resources includes: (1) identifying relevant data; (2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, economic criteria); (3) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and (4) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool. This project will facilitate future deployment of GHC by providing data, tools, and workflows applicable to low-temperature geothermal resources.

favorability maps↗
DOE OSTI2023

Low-Temperature Geothermal Resources: Relevant Data and PFA Methods to Reduce Development Risk

This project is part of a larger national effort focused on demonstrating the multi-faceted value of integrating low-temperature geothermal resources into national decarbonization strategies and community energy plans. Low-temperature geothermal resources are defined as reservoirs-natural or engineered-with temperatures < 150 degrees C. While the focus in the NREL effort is on geothermal heating and cooling (GHC), resources at the upper end of this temperature range can also be used for small-scale power generation. However, low-temperature geothermal resources have not been studied as extensively as higher-temperature geothermal resources. We identified three major classes of low-temperature geothermal play types: sedimentary basins, orogenic systems, and radiogenic systems. We developed workflows for evaluating the potential of these resources building off the Play Fairway Analysis (PFA) approach to de-risking geothermal exploration. This PFA-based approach to low-temperature geothermal resources includes: (1) identifying relevant data; (2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, economic criteria); (3) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and (4) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool. This project will facilitate future deployment of GHC by providing data, tools, and workflows applicable to low-temperature geothermal resources.

favorability maps↗
NASA NTRS1978

California's geothermal resource potential

According to a U.S. Geological Survey estimate, recoverable hydrothermal energy in California may amount to 19,000 MW of electric power for a 30-year period. At present, a geothermal installation in the Geysers region of the state provides 502 MWe of capacity; an additional 1500 MWe of electric generating capacity is scheduled to be in operation in geothermal fields by 1985. In addition to hydrothermal energy sources, hot-igneous and conduction-dominated resources are under investigation for possible development. Land-use conflicts, environmental concerns and lack of risk capital may limit this development.

Leibowitz, L. P.↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) is supporting the Geothermal Heating and Cooling Geospatial Datasets and Analysis project conducted by the National Renewable Energy Laboratory (NREL) as part of a broader effort to demonstrate the multi-faceted value of integrating geothermal power and geothermal heating and cooling (GHC) technologies into national decarbonization plans and community energy plans. Currently, there is a need to establish baseline low-temperature geothermal resource datasets and evaluate methods for deploying these technologies to provide the basis for supporting private sector investment. This project is focused on collecting baseline datasets, updating conceptual models, and creating Play Fairway Analysis (PFA) workflows for low-temperature (<150 degrees Celsius) geothermal resources of different geothermal play types (i.e., sedimentary basin, orogenic belts, and radiogenic geothermal play types) that could be used for geothermal heating and cooling (GHC), combined heat and power (CHP), and other geothermal direct uses (GDU) applications. Low-temperature geothermal resources are defined as reservoirs - natural or engineered - with temperatures <150 degrees Celsius. While the focus in the NREL effort is on GHC, resources at the upper end of this temperature range can also be used for small-scale power generation. This project does not include Ground Source Heat Pumps (GSHPs) technologies because they can be effectively developed almost anywhere. Low-temperature geothermal resources have not been studied as extensively as higher- to medium-temperature geothermal resources, but there is recent interest in improving understanding of these types of resources with an uptick of interest in geothermal technologies for decarbonizing heating and cooling systems. In addition, Enhanced Geothermal Systems (EGS) and other emerging technologies for exploiting petrothermal resources have opened the possibility of utilizing deep sedimentary basin systems, where porous media provide permeability and high temperatures can be reached at great depths. This project takes the approach of classifying low- temperature geothermal resources by geothermal play type (GPT). We defined and characterized three major classes of low-temperature GPT: sedimentary basins, orogenic systems, and radiogenic systems. We develop methodologies for evaluating and analyzing the potential for these resources building off the PFA approach to de-risking geothermal exploration and characterization. The proposed PFA approach for low-temperature geothermal resources includes: 1) identifying relevant data (e.g., datasets such bottom-hole temperatures from oil and gas wells, heat flow data, Quaternary faults and stress field data, geophysical data, etc.); 2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, and economic criteria); 3) uncertainty quantification; 4) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and 5) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool (RSAT). This project should facilitate future deployment of GHC, CHP, and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources. Increased deployment of GHC and GDU will help achieve national and local decarbonization goals.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Geothermal Uncertainty Representation in reV: the Renewable Energy Potential Model

We present a preliminary methodology for including geothermal resource uncertainty into the Renewable Energy Potential model, which estimates potential capacity and costs on a gridded surface at the national scale. The uncertainty outputs characterize the 10th, 50th and 90th percentile for geothermal resources using two energy capacity estimation equations. We then present a method and results that demonstrate how other geologic data layers, which may be indicative of permeability, can be used to inform the mean and standard deviation of the geothermal capacity. We demonstrate how the mean and standard deviation can be defined or partially informed by using collocated regression estimates and estimate errors, respectively . These regression results are from 36 observed geothermal power plants in the Great Basin region and are also used to benchmark the P10-P90 calculations.

exclusions↗
DOE OSTI2024

Derisking Superhot Geothermal Plays with Value of Information: Utilizing Play Fairway Analysis, Geophysics and Technoeconomics

This paper describes a methodology for evaluating how the play fairways analysis (e.g., favorability) can improve our chances of making geothermal development decisions. We make statistical resource assessments and couple them with technoeconomic analysis utilizing previous favorability work performed for the Newberry Volcano. We demonstrate how the favorability can be used in a decision analysis framework because the Newberry favorability also estimated an associated uncertainty. The specific decision considered is how large of a power plant to build, which is difficult given the uncertainty about the resource size. Our results focus on two resource types, hydrothermal and enhanced geothermal systems, and they demonstrate how estimates of the minimum, most likely, and maximum estimates of the geothermal resource (denoted as the P10, P50, and P90, respectively) can be used in a decision analysis framework. Lastly, the value of information results explore using favorability with and without the magnetotelluric and gravity data from the Newberry Volcano. As expected, the favorability is more reliable, according to our methodology, at indicating the resource size when it includes the two geophysical models.

enhanced geothermal system↗
DOE OSTI2022

Multidisciplinary Constraints on the Thermal‐Chemical Boundary Between Earth's Core and Mantle

Abstract Heat flux from the core to the mantle provides driving energy for mantle convection thus powering plate tectonics, and contributes a significant fraction of the geothermal heat budget. Indirect estimates of core‐mantle boundary heat flow are typically based on petrological evidence of mantle temperature, interpretations of temperatures indicated by seismic travel times, experimental measurements of mineral melting points, physical mantle convection models, or physical core convection models. However, previous estimates have not consistently integrated these lines of evidence. In this work, an interdisciplinary analysis is applied to co‐constrain core‐mantle boundary heat flow and test the thermal boundary layer (TBL) theory. The concurrence of TBL models, energy balance to support geomagnetism, seismology, and review of petrologic evidence for historic mantle temperatures supports Q CMB ∼15 TW, with all except geomagnetism supporting as high as ∼20 TW. These values provide a tighter constraint on core heat flux relative to previous work. Our work describes the seismic properties consistent with a TBL, and supports a long‐lived basal mantle molten layer through much of Earth's history.

58 GEOSCIENCES↗
DOE OSTI2021

Introducing the GeoRePORT Resource Size Tool: Reporting on Geothermal Resource Size Estimations Using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT): Preprint

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. The assessment protocols used in GeoRePORT allow for comparison of project attributes across locations and geological settings to understand the feasibility of geothermal development. This work introduces the Resource Size Tool, a new feature within the GeoRePORT package that compiles two independent methods for estimating geothermal resource size in terms of energy capacity in MW. Energy production potential for twenty-three case studies was estimated with the Resource Size Tool in order to 1) generate a reasonable range of resource size estimates for a particular geothermal field; 2) illustrate the advantages and limitations of each methodology (such as data input requirements, estimate accuracy and precision, and the appropriate circumstances of use); and 3) test the ability of the resource size tool to provide useful and accurate information for geothermal stakeholders. The tool employs two methods widely used in the geothermal industry: (1) USGS Volumetric and (2) Power Density. Results from our case studies show general overlap between these two methods in terms of resource size estimates; however, they also reveal key differences between the two approaches that should be considered when using such estimates to drive development. First, the two methods rely on different input parameters and therefore one method may be more appropriate and/or accurate for a given project than the other. Second, the Power Density method was found to generate wider ranges of resource size predictions, more consistently aligning with actual power production of the field but with larger scales of error; whereas the USGS Volumetric method predicts narrower ranges but tends to overestimate when compared to current MW production. Future work will refine variables used in the methods with input data from other sections of GeoRePORT and modify uncertainty levels based on the particular datasets used for a given project.

geological↗
DOE OSTI2025

Oakridge Geothermal Resources Assessment

Through the Communities Local Energy Action Program (LEAP), NREL provided technical assistance to a coalition of stakeholders from Oakridge, Oregon. The coalition included community-based non-profit organizations, the city government, the local utility, and others. Technical assistance provides analysis and information to support Oakridge stakeholders with their goals to increase energy reliability and resilience in the community, while promoting economic development. The Geothermal Resource Assessment provides technical analysis related to the geothermal resource in the Oakridge area, possible technology applications, and information related to further geothermal exploration. Technical analysis includes a review of a previous geothermal study conducted for Oakridge, thermal modeling to estimate reservoir temperatures, and technoeconomic simulation of a combined heat and power application in the Oakridge area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

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↗
DOE OSTI2023

Eastport Energy Resilience Opportunities [Slides]

This presentation offers a high-level overview of the Energy Transitions Initiative Partnership Project's (ETIPP's) work in Eastport, Maine. It covers the project's work to explore microgrid options for the island community; opportunities for incorporating renewable energy technology such as tidal power, solar power, and battery storage; potential benefits and costs for the community; and an estimated timeline for implementing different options.

14 SOLAR ENERGY↗
DOE OSTI2022

Techno-Economic Performance of Eavor Loop 2.0

This project evaluated techno-economic performance for a sample Eavor-Loop 2.0 design for electricity production and direct-use heating. The Eavor-Loop 2.0 design investigated is a 7.5-km deep closed-loop geothermal system consisting of 12 laterals for a total of more than 90 km of downhole well and lateral length. Both a high geothermal gradient scenario of 60 degrees C/km and a low geothermal gradient scenario of 30 degrees C/km were considered. With pure water injected at 60 degrees C and 80 kg/s, reservoir simulations with the Slender-Body Theory simulator indicate average production temperatures over a 30-year lifetime of ~125 degrees C and ~210 degrees C for the low and high geothermal gradient scenario, respectively. These correspond to heat production of ~22 M Wth and ~51 M Wth, respectively. Using IPSEpro simulations, we find average power production of ~2.2 M We and ~8.6 M We, respectively, for a subcritical organic Rankine cycle power plant with air-cooled condensers. Cost estimates indicate the overall capital and levelized costs are dominated by the lateral drilling cost. Obtaining a levelized cost of electricity below $70/M Wh requires a geothermal gradient of 60 degrees C/km, a discount rate below 9%, and lateral drilling cost below $400/m. A well cost model indicates that ~$400/m for the Eavor-Loop 2.0 design investigated can be obtained for a drilling rate of penetration about 40 ft/hr (with bit life of 50 hours), and omitting casing and cement. Traditional (geothermal) well drilling has achieved these drilling rate conditions, including the Utah FORGE project where the rate of penetration has exceeded 50 ft/hr in granite. However, it is unclear if these conditions are still valid for drilling the Eavor-Loop 2.0 laterals (i.e., ~82 km of laterals at 4 to 7.5-km vertical depth with rock temperatures up to 460 degrees C), as such downhole completion has never been developed before. Competitive levelized cost of heat values ($1.2-$8.2/GJ) are calculated, even for the low geothermal gradient scenario (30 degrees C/km) and lateral drilling cost of $600/m.

advanced geothermal system↗