Improve resource targeting for all geothermal resource types
Challenges and Barriers
- Cost-prohibitive data collection and limited public data availability:
constrained ability for prospective explorers, developers, and operators to reduce project risk and aggressively increase rates of resource discovery and deployment.
- Low spatial resolution of temperature, permeability, fluid, chemistry, and stress distribution in the subsurface:
reduced ability to understand subsurface features without invasive drilling and testing
The Three Gs of Characterization Technologies
- Geophysics (including remote sensing)
The ability to cost effectively and rapidly characterize hydrothermal and EGS resources has a direct impact on their widespread deployment—which will support a clean, zero-carbon electricity grid and provide nationwide heating and cooling solutions. Technology improvements in exploration and characterization will lower project development timelines, costs, and risks, while increasing access to necessary capital—regardless of geothermal resource type (conventional identified or undiscovered hydrothermal resources, EGS resources, etc.), temperature (<150°C for direct-use applications and >150°C for power generation), or depth. Because financing carries costs (e.g., interest), technology and cost improvements for geothermal resource characterization during early exploration phases hold significant potential to improve project economics. As noted in the GeoVision analysis, the high costs and risks associated with geothermal exploration are major barriers to expanded development of the nation’s undiscovered, or “hidden,” hydrothermal resources and to realizing the economic and environmental benefits that could come with that expanded development. Similarly, successful development of EGS resources—which requires active engineering management throughout the life of the system—depends on resource characterization improvements even when a project is in operation.
The state of the art in resource characterization includes a variety of geological, geophysical, and geochemical tools and techniques that are costly to deploy at the desired levels of data collection and the respective development phases of interest. Publicly available data for areas with prospective geothermal resources are currently limited, placing additional barriers to entry for potential exploration and development companies and restricting geothermal resource discovery and deployment. No singular non-invasive (non-drilling) characterization method provides resolution on the spatial distribution of subsurface permeability, temperature, fluid, chemistry, or stress sufficient to enable the high-confidence well targeting necessary for industry’s desired drilling success rates. Applying machine learning and joint geophysical inversion techniques to enhanced and reduced-cost data collection holds promise to improve this resolution.
To address these challenges and barriers, GTO is developing exploration and resource characterization tools and techniques to create a lower-cost and reduced-risk development profile for the full spectrum of geothermal projects. The characterization technologies addressed in this section span the three “Gs”—geophysics (including remote sensing), geochemistry, and geology. The three Gs are used to assess geothermal resource potential as well as to identify temperature; permeability; and the presence of fluids, their chemistry, and the stress regime in which they exist before developers make capital-intensive drilling decisions. Such assessment is important for geothermal resources regardless of their development phase (i.e., exploration, development, or operations). The geothermal industry has indicated the need for investments to reduce exploration and characterization technology costs and improve spatial resolution of subsurface characteristics to provide high-level guidance on areas in geophysics, geochemistry, and geology where improvements are most likely to be impactful (DOE 2011, DOE 2019). GTO also recognizes the need for additional analysis to support detailed understanding of which specific combinations of geophysical, geological, or geochemical technology improvements can yield the most effective cost reductions.
In addition to the three Gs, the resource characterization technologies discussed here feature a fourth area called “cross-cutting,” which includes RD&D initiatives leveraging a combination of the science and techniques in the three Gs. Industry best practice is that data acquired through existing and new characterization technologies be integrated into a conceptual model of a geothermal resource and that the model is continually updated and refined over the life of the system. Well-constructed, accurate models are powerful decision-making tools for geothermal resource management. Drilling technologies, another cross-cutting area relevant to all parts of the GTO portfolio enabling confirmation or access to geothermal resources, are discussed in Subsurface Enhancement and Sustainability.
Table 2.1 highlights GTO subprogram contributions in Exploration and Characterization RD&D toward meeting overall GTO program goals. The majority of the planned geophysics, geochemistry, geology, and crosscutting RD&D pathways will be through the EGS, Hydrothermal, and Low Temperature subprograms in direct support of Strategic Goals 1, 2, and 3. The DMA subprogram also enables research insights through secondary contributions to Goals 2 and 3.
Table 2.1. GTO Subprogram Contributions in Exploration and Characterization RD&D for Meeting GTO Strategic Goals
|Enhanced Geothermal Systems||Hydrothermal Resources||Low-Temperature and Coproduced Resources||Data, Modeling, and Analysis|
|Goal 1: Drive toward a clean, carbon-free electricity grid 60 GW of EGS and hydrothermal resource deployment by 2050||Define site conditions needed for engineering an EGS reservoir (1)||Discover hydrothermal systems (i.e., confluence of heat, water, and permeability) (1)||(3)||(3)|
|Goal 2: Decarbonize building heating and cooling loads by capturing the economic potential for 17,500 GDH installations and by installing GHPs in 28 million households nationwide by 2050||Define site conditions needed for engineering an EGS reservoir (1)||(2)||Resource assessments for geothermal heating and cooling (1)||(2)|
|Goal 3: Deliver economic, environmental, and social justice advancements through increased geothermal technology deployment||Sustainable development of geothermal resources will benefit environmental, economic, and social well-being of communities across the nation (1)||(2)|
|1: GTO subprograms with primary Research Area contributions toward GTO Strategic Goals
2: GTO subprograms with secondary Research Area contributions toward GTO Strategic Goals
3: GTO subprograms with tertiary Research Area contributions toward GTO Strategic Goals
Highlighted Performance Goals
Table 2.2 outlines key GTO performance goals through FY 2026 for enhancing the ability to locate and characterize geothermal resources.
Table 2.2. Exploration and Characterization Highlighted Performance Goals
|Activity/Objective||Mechanism||Target FY to Achieve||Baseline (current status)|
|Validate multi-physics inversion methods, high-fidelity models, and machine learning through well targeting||Test and validate inversion and 3D modeling methods by drilling, testing, and confirming well targets as part of DE-FOA-0002219.||FY 2023||While physics-based inversion methods have been used, they are limited in quantitative rigor and have not extensively incorporated machine learning models for improved well targeting.|
|Double the discovery rate for undiscovered (or “hidden”) geothermal systems||Data being collected through ongoing PFA* and GeoDAWN** initiatives, along with other exploration RD&D initiatives under development, can be leveraged with machine learning techniques developed as part of DE-FOA-0001956 to improve the discovery rate of undiscovered hydrothermal systems.||FY 2026||Paucity of new publicly available data limits commercial exploration and deployment, impacting the acceleration along an exploration learning curve. The current discovery rate is estimated at ~190 megawatts-electric/year (Augustine 2019).|
* GTO’s Play Fairway Analysis
** GTO’s Geoscience Data Acquisition for Western Nevada
Research and Development Pathways
Geophysics and Remote Sensing
As articulated in the GeoVision analysis, progress is needed in detecting subsurface signals to remotely identify and characterize underground attributes. Similar to the use of radiology in the medical field to assess the need for and improve the success rates of costly and invasive procedures, the geothermal industry would benefit from technology breakthroughs in non-invasive, lower-cost geophysical and remote-sensing technologies. A range of geophysical methods are available for geothermal characterization and investigation. Improvements in geophysical methods have sizeable potential impact because of their ability to image the subsurface prior to costly, risky, and invasive drilling.
Geophysical techniques are principally used to map subsurface structures that help identify and define geothermal systems, such as fracture networks, faults, lithologic changes, heat flux, the presence of fluids, and permeability boundaries. These subsurface features are mapped using reflections of acoustic (seismic) and electro-magnetic waves, variations in the local gravity and magnetic fields, and thermal gradients (Gasperikova and Cumming 2020). Remote-sensing techniques enable large-scale mapping of surface features—e.g., mineral, vegetation, and thermal properties—as identifiers of geothermal resources. There are two main types of remote sensing: passive and active. Passive sensors detect natural emitted and reflected radiation. Active remote sensing uses the reflected, or backscattered, signal from energy emitted at predetermined wavelengths. Satellite and airborne imagery can map zones of secondary mineral alteration associated with emerging geothermal fluids and attributes such as heat flux. Aerial photography and terrain mapping with laser ranging also illuminate surface structural features associated with geologic settings.
Geophysical models and geophysical and remote-sensing data are required to advance geothermal technologies, as are advancements in temperature-gradient and heat-flow measurement tools and processing methods. Other needs include improved techniques for measuring thermal conductivity in high-temperature environments and broader understanding of existing heat-flow measurement tools and their effect on the accuracy of geothermal system characterization. Advancements in seismic data interpretation, such as efficient waveform inversion techniques, will provide better interpretation of geothermal resources at resolutions required to support effective exploration, development, and operations decision making.
In addition to temperature gradient, heat-flow measurement technology, and seismic data interpretation, there is a need to improve airborne geophysical data. This need could be met by testing advanced airborne tools—including magnetotelluric and time-domain electromagnetic tools over known geothermal systems—or by leveraging other agencies’ satellites and airborne data and combining multiple airborne sensors on a single platform.
Remote-sensing advancements are needed to enable the acquisition of high-resolution remote sensing data sets via multiple methods over large areas in new regions. Specific needs include establishing reliable automated processing tools and techniques and developing affordable software for subsurface data-set model integration. GTO will focus on innovations in geophysics and remote sensing that improve surface-based, subsurface, and in-situ measurement tools and techniques.
Improve subsurface/in-situ measurement tools and techniques. In general, geothermal developers need better and potentially new borehole tools for measuring the spatial distribution of subsurface permeability, temperature, fluid, chemistry, and stress. More widespread understanding and use of advanced and commercially available characterization tools will significantly improve the accuracy of geothermal system characterization. Use of some commercially available temperature measurement technologies is currently limited because the tools are not easily accessible or the techniques to analyze the data are cost prohibitive. Additionally, the stability of fiber-optic cables (a distributed temperature-sensing tool) can be problematic, especially under high temperatures. Some progress has been made, but current technology does not function within the temperature ranges required by the geothermal industry. GTO will focus on improving the commercial availability of existing reservoir characterization measurement technologies by conducting research to improve the stability of fiber-optic cables in high-temperature environments; conducting research on thermal properties of rocks, including thermal conductivity; and researching and developing easier and more cost-effective ways to measure properties at high spatial and temporal resolutions. This research may involve longer-term technology improvements and the development of new logging tools for thermal conductivity.
Improve surface-based geophysical and remote-sensing techniques. The geothermal industry will benefit from improved, next-generation geophysical surface and airborne-derived data. Advances in this technology area will help identify undiscovered, or “hidden,” geothermal resources. Technical challenges include issues with flying surveys and interception in areas of high relief. There is also a need to improve other, non-invasive geophysical techniques and data collection critical for subsurface monitoring and characterization. Advances in ambient noise tomography, seismoelectric effects, geodetics, and the inversion of these and other innovative geophysical data sets will contribute significantly to attaining proficiency in characterizing where fluid exists in the subsurface and how it moves over the lifetime of a geothermal project. RD&D in this area will focus on improving and validating data collection tools (e.g., control source electromagnetic) and improving data processing techniques through advanced coupling processing techniques to better interpret geophysical signals, e.g., seismic reflection data in crystalline geological environments. Advances are needed to enable the acquisition of high-resolution remote sensing data sets via multiple methods over large areas in new regions. Additionally, there is a need to establish reliable automated processing tools and techniques and to develop affordable software for subsurface data-set model integration. Reducing the cost of these data collection activities through technology RD&D and leveraging federal dollars directly toward data acquisition activities in areas known to be prospective for geothermal resources are likely to be impactful activities that advance the state of the art for geothermal. For example, GTO intends to leverage interagency agreements in data collection and machine learning initiatives, such as the Geoscience Data Acquisition for Western Nevada (GeoDAWN), to make progress in these areas.
Geochemical techniques provide information on fluid source, heat source, subsurface temperature, and local and regional fluid flow paths and histories. The chemical and isotopic compositions of fluids collected at the surface provide indications of subsurface temperatures using a variety of empirical and experimental water-rock-gas geothermometers. Fluid and heat sources can often be identified through characteristic isotopic signatures. Spatial changes in fluid chemistry and isotopic compositions reveal important information on the flow rates and paths of geothermal fluids through the system.
Geochemical and isotopic techniques for identifying fluid and heat sources in geothermal systems are well established. However, the geothermal industry lacks reliable tools for determining subsurface temperatures, fluid flow paths, and rates and for identifying potential surface manifestations of hidden systems. Chemical and isotopic geothermometers are based largely on empirical data, and interpretations of calculated temperatures for natural systems rely largely on experience. Next-generation geothermometers that incorporate chemical and isotopic thermodynamics of the water-rock-gas systems of interest need to be developed. These new tools will also provide an enhanced assessment of fluid flow histories, such as dilution, phase separation, flow rates, and flow paths. GTO will therefore focus its efforts on the RD&D of improved geochemical techniques to estimate reservoir temperatures, processes, fracture flow, and sustainability.
Improve techniques to estimate reservoir temperatures and processes. At conventional hydrothermal power generation temperatures (150°C and up, to the critical point of water [374°C]), RD&D is needed to validate the thermodynamic databases that underpin existing liquid, gas, and isotope geothermometry and fluid-rock equilibria. As with conventional hydrothermal systems, understanding and managing the chemical evolution of EGS systems will be essential to ensuring their resource sustainability.
At present, geothermometers largely reflect empirical correlations and are not specifically related to the range of lithologic and tectonic regimes, nor the range of solution compositions in which geothermal systems may be found. There is a need to validate existing thermodynamic data under different geothermal conditions. Geothermal reservoirs and hydraulically connected aquifers exist at a range of temperatures and depths, such that equilibrium fluid compositions can be overprinted by re-equilibration (sometimes multiple times). These signatures may still be present in fluids (water and gas) that are sampled at the surface and thus have a “memory” of a deeper reservoir condition. However, decoupling these processes is difficult with existing methods. New insights may be gained from principal component analysis and machine learning technologies, especially when coupled with other exploration data sets.
Beyond the critical point of water (374°C), existing thermodynamic data must generally be extrapolated; by definition, then, these data incorrectly describe equilibrium chemistry or kinetic rates of reaction within the systems of interest. Acquiring experimental data is necessary to (1) define the thermodynamics of mineral-supercritical fluid equilibria to conduct the coupled numerical modeling of these systems and (2) support the production and use of high-temperature and high energy-density geothermal resources.
Geologic techniques provide the historical and structural framework within which geophysical, geochemical, and remote-sensing data are interpreted. A geologic model that incorporates structural data with data from these three technical areas can be used as guidance for subsequent exploration, development, and operational strategies. Surveying and mapping local and regional geologic structures, lithologies, and past and present strain rates are the most common geological methods for identifying potential geothermal sites.
The geology field requires advances in stress and strain data mapping and in correlating improved tectonic stress and strain data with thermal data. Stress and strain maps would help predict fractures and assist in understanding subsurface permeability distribution. Advances could be made by acquiring additional data to address gaps in borehole, local structural, and regional geodetic data and by developing detailed district maps and 3D models of strain and stress. Overall, there is a need for improved conceptual models to understand the subsurface, which will in turn improve drilling success rates and reduce costs.
Map stress and strain data. Stress and strain data are currently sparse in most geographic areas. Some areas lack well-exposed strain indicators, whereas others lack detailed geologic mapping and/or borehole data. Advancing the state of the art will require continued support for quaternary fault studies and studies comparing borehole data to local fault kinematic data. Developing and publishing detailed district stress and strain maps that include stress inversions and modeling, slip tendency analysis, and induced seismicity estimates will improve understanding of the geologic context within which geothermal resources may be developed and placed into production. An additional area of focus is tools and techniques that provide insights of in situ stress directions and magnitudes and their variability throughout reservoirs. GTO will also support quaternary fault studies, which could be aided significantly by remote-sensing and airborne geophysical data collection as described in Geophysics and Remote Sensing. This GTO support will lead to improved statistically based permeability determinations for well targeting and better understanding of induced seismicity for geothermal fields.
Conduct regional geologic mapping. GTO support to state and federal geological surveys to conduct regional-scale geologic mapping in prospective geothermal areas would provide essential, low-cost, and high-value data. Such data are critical to establishing the structural and lithologic context for both identified and undiscovered geothermal systems. In the United States, geologic mapping is conducted primarily through the U.S. Geological Survey’s (USGS) STATEMAP component of the National Cooperative Geologic Mapping Program. According to the USGS website, the primary objective of STATEMAP is “to establish the geologic framework of areas determined to be vital to the economic, social, or scientific welfare of individual States.” The website also explains that STATEMAP mapping priorities are established by State Geological Surveys in consultation with a multi-representational State Mapping Advisory Committee, and state-level priorities may not necessarily prioritize regions that are highly prospective for geothermal resources. GTO can coordinate with the USGS Geothermal Resources Investigations Project to identify high-priority areas that require regional geologic mapping, which can then be elevated for priority acquisition through the STATEMAP program and potentially supported through interagency cooperation.
Cross-Cutting Initiatives and Technologies
Cross-cutting initiatives and technologies are those that involve some combination of science and the exploration and characterization techniques described in the preceding technology areas. The goal of cross-cutting technologies is to improve data interpretation by combining techniques to minimize the ambiguity of stand-alone data.
Opportunities exist for technical advancements that will provide cross-cutting support for all geothermal exploration and characterization technologies. Improved, multi-disciplinary conceptual models in prospective areas of undiscovered hydrothermal resources (as determined through GTO’s Play Fairway Analysis [PFA]) hold promise for increasing understanding of the subsurface, thereby improving drilling success rates and project economics. Subsurface permeability can be better understood by developing and confirming a model that connects geophysics, hydro-geochemical data, and geologic data along with mapping permeable paths in the subsurface.
Opportunities also exist for developing projects to model fluid flow in the fractured crust. Research for this work can include 3D modeling techniques and software as well as improved and more user-friendly data integration tools and software for model development. Improvements in 2D and 3D data-inversion codes, especially of multiple data sets, offer opportunities to improve the imaging resolution of key subsurface features in geothermal environments. The application of stochastic or Monte Carlo inversions to match cross-disciplinary datasets can generate a range of possible models.
Extend Play Fairway Analysis and enhance multi-disciplinary models. GTO has funded RD&D to adapt the PFA technique from the oil and gas industry to the geothermal industry. PFA targets the identification of undiscovered or “hidden” hydrothermal systems by incorporating the regional or basin‐wide distribution of known geologic factors that control the occurrence of a particular type of geothermal system. By conducting PFA in unexplored or underexplored regions or by using new play concepts in basins with known geothermal potential, GTO research quantified and reduced uncertainty in geothermal exploration. This effort focused on the resource potential of 30 GWe of undiscovered hydrothermal resources that the USGS estimates exist in the United States. The successful PFA work yielded numerous favorable prospects, with the potential for further study to unlock that geothermal potential.
Significant additional work in developing new, multi-disciplinary conceptual models for geothermal play fairways remains and could contribute to exploring prospective geothermal play fairways in the Aleutians, Cascades, Hawaii, and Snake River Plain. Conceptual models are in various stages of development for these play fairways; in many cases these models have reached an exploration stage where some level of drilling is required, as in the case of recently undertaken GTO-supported demonstration projects in Nevada. If successful, such efforts can support additional demonstration projects that validate the play concepts. Through continued support to PFA, GTO will test and validate multi-physics inversion methods, 3D modeling techniques, machine learning approaches, and conceptual modeling through field-demonstration well targeting.
Develop 3D modeling techniques, software, and innovative data processing and analysis. Enhanced software will lead to better understanding of conceptual models and improved numerical geothermal system models, in turn leading to improved resource management and reduced drilling costs. Currently, 3D software exists for imaging and mapping magnetotelluric data. While multiple software programs are available from various vendors, each software has its pros and cons. Academic institutions have developed 3D magnetotelluric inversion algorithms, but the code is not shared; by contrast, many academic groups offer open-source 3D microearthquake inversion packages. The high cost of these modeling techniques limits the commercial application of what is otherwise a proven technology.
Physics-based numerical modeling codes have improved substantially in the national laboratory space. Commercialization of those codes, however, has lagged. Practical adoption and application of fully coupled thermo-hydraulic-mechanical-chemical modeling codes in the geothermal industry has also been limited. Additionally, the commercial availability of full-field numerical modelling software that couples a physics-based numerical reservoir model to a surface network through a wellbore simulator is limited and a full-field model that couples thermo-hydraulic-mechanical-chemical codes is currently unavailable.
GTO support for 3D modeling software advancements will result in a greater ability to integrate complete datasets, use of a common platform enabling greater interoperability and easier exchange of information, lower cost, and better availability. GTO will support continued RD&D of high-fidelity, fully coupled, full-field numerical models in pursuit of commercializing a low-cost and user-friendly software package.