Results for “exploration risk” — Page 2

DOE OSTI2020

Modeling study of deep direct use geothermal on the West Virginia university campus-morgantown, WV

To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use (DDU) system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of the great depth of the geothermal reservoir, few data are available to characterize reservoir features and properties. Consequently, the study focuses on the following three aspects: 1. model choice for predicting reservoir impedance and thermal breakthrough: after investigating three potential models (one single permeability model and two dual permeability models) for flow through fractured rock, it is decided only the single permeability model is needed; 2. well placement (horizontal vs. vertical) options: horizontal well placement seems to be more robust to heterogeneity and the impedance is more acceptable; 3. Prediction uncertainty: the most influential parameters are identified using a First-Order-Second-Moment uncertainty propagation analysis, and the uncertain range of the model predictions is estimated by performing a Monte Carlo simulation. Heterogeneity has a large impact on the prediction, therefore, heterogeneity is included in the predictive model and uncertainty analysis. The numerical model results and uncertainty analysis will be used for further economic studies.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology is based on the method proposed by Poux et al. (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., 2022. For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. More information on this process is described in the following sections. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty. There are two different versions of the Leapfrog model and associated favorability models: - v1.0: The first release in June 2023 - v2.1: The second release, with improvements made to the earthquake catalog (included additional identified events, removed duplicate events), to the temperature model (fixed a deep BHT), and to the index models (updated the seismicity-heat source index models for supercritical and EGS, and the resistivity-insulation index models for all three play types). Also uses the jet color map rather than the magma color map for improved interpretability. - v2.1.1: Updated to include v2.0 uncertainty results (see below for uncertainty model versions) There are two different versions of the associated uncertainty models: - v1.0: The first release in June 2023 - v2.0: The se...

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

DEEPEN: Newberry Volcano MT and Gravity Data - 2022 and 2023 Acquisition and Processing

As part of DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments), a 3D play fairway analysis (PFA) was conducted at Newberry Volcano in Central Oregon for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). For use in this PFA, combined full tensor broadband magnetotelluric (MT) and gravity data were acquired, processed, and inverted by Enthalpion Energy LLC (Enthalpion) with support from NREL staff. The data collection efforts took place from June 19th to July 24. Data were collected with the goal of gaining an improved understanding of the South Flank and the extent of the magma chamber. This GDR submission includes the raw data, single inversions, joint inversions, resolution matrices, and a report on these processes. More detailed information about the folder structure of the datasets included in this submission may be found on pages 94-97 of Magnetotelluric and Gravity Survey Report.pdf below.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology, detailed in the journal article below, is based on the method proposed by Poux & O'brien (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., (2022). For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Towards A Geo-Data Science Method for Assessing Rare Earth Element and Critical Mineral Occurrences in Coal and Other Sedimentary Systems

While preliminary analyses of data from open-source resources (Ekmann, 2012) show promising concentrations of REE in individual coal samples from a number of sites and basins in the U.S., other sparse data for REE in domestic coal-related strata suggest that many occurrences are low, “subeconomic” concentrations. At present, there is no method for systematically assessing potential sedimentary occurrences of REE. However, the geologic processes responsible for REE occurrences in coal-related strata are systematic; the unpredictability of REE resources in coal-related strata is due to poorly quantified spatial resource trends and the lack of an exploration method tailored to these resources. Thus, there exists a need for a systematic assessment approach that incorporates knowledge of geological variation in the mechanisms of REE enrichment within coal basins to help minimize geologic uncertainty and reduce commercial exploration risk.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Shallow Geothermal Potential of the Snake River Plain

The Snake River Plain (SRP) terrestrial heat flow and subsurface thermal regime are not well understood but are important for assessing the local geothermal resource potential, both for conventional and for Enhanced Geothermal Systems (EGS) development in the region. Resource evaluation for the SRP is complicated by the disparate data density, along with the known lateral advection of heat in the Eastern Snake River Plain Aquifer and vertical heat transport by fluids in the bounding faults, primarily in the southwestern section. Fortunately, recent studies, e.g., the Snake River Plain Play Fairway Analysis, the Idaho FORGE site, and site-specific investigations, which included drilling within the Camas Prairie and on the Mountain Home Air Force Base, near Twin Falls, and in the Eastern Snake River Plain as part of the HOTSPOT Project, add both additional drilling and geophysical data. The SMU Geothermal Laboratory has conducted detailed studies of SRP tectonics and heat flow since the 1970's and used this knowledge as part of the EGS geothermal potential estimation for the conterminous United States in 2006 and again in 2011, calculating geothermal potential from 3.5 km to 10 km depth. Recent temperature modeling refined the calculation methodology to estimate shallow (1 km to 4 km) resource potential using an improved thermal conductivity model and incorporation of shallow groundwater flow. By incorporating the new SRP geology, geophysics, and 206 thermal data sites into the SMU thermal modeling methodology, this project updates the resource estimate for the SRP, and generates new temperature-at-depth maps for the shallow subsurface (1 km to 4 km). The project results highlight the EGS potential resource areas (=150°C) and areas with more exploration risks based on minimal and/or low-quality data. The newest temperature modeling results suggest EGS potential is near five times greater in the SRP than previously estimated.

EGS↗

DOE OSTI2026

Large Load Integration - Task List and Overview

Large Load Integration Tasks: Task 1 – Workshops Support stakeholder engagement across industry to promote collaboration and identify solutions to challenges that will guide other work Task 2 – Ancillary Services Characterize different types of large loads to assess under what conditions they may be utilized to provide grid stability services Task 3 – Communications Explore the cybersecurity and communications infrastructure required to enable large loads to interface with grid operations to provide ancillary services Task 4 – Nuclear Integration Explore risks and methods for supporting large load energy needs with SMRs and incorporating them into the wider power system Task 5 – Decision Support and TA Provide support to stakeholders through the creation of planning tools and direct technical assistance.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Hot Springs and Geysers: Exploring Historical and Modern Impacts of Geothermal Energy Production on Associated Natural Surface Systems and Standardizing Management Practices

Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.

Best Practices↗

DOE OSTI2021

Common risk segment mapping: Streamlining exploration for carbon storage sites, with application to coastal Texas and Louisiana

Large-scale deployment of Carbon Capture and Storage (CCS) will require a commensurately large number of sites. Efficient screening methods are needed to create investment assurance and focus efforts on the most promising sites. The problem is similar to petroleum exploration, for which there are well-developed (though seldom published) workflows, including Common Risk Segment (CRS) mapping. In brief, the process requires 1) defining the key play elements; 2) identifying candidate geologic intervals for each; 3) creating fact-based maps for those intervals; 4) determining minimum criteria for the success of each element; 5) reinterpreting the fact-based maps in terms of chance of success; and 6) combining the individual maps to form a composite, basin-scale view of prospectivity. We adapt the CRS process to screening for CO 2 storage sites. Critically, we redefine the process in terms of cost of characterization and development, rather than chance of success. For illustration, we apply the process to the example of the Lower Miocene on the Texas and Louisiana Gulf Coast. We show that the predictions are consistent with historic hydrocarbon production volumes and rates. The power of the CRS method is that it creates a systematic approach to geologic evaluation and translates complex, multidimensional analysis into clear, graphical and easily comprehended business inputs. The results highlight sweet spots and identifies critical risks, suggesting a focus for further data collection and analysis. Furthermore, the method developed here can be applied to both surface and subsurface factors anywhere that there is interest in geologic storage of CO 2 .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Restrictive spirometry pattern among construction trade workers

Spirometry-based studies of occupational lung disease have mostly focused on obstructive or mixed obstructive/restrictive outcomes. We wanted to determine if restrictive spirometry pattern (RSP) is associated with occupation and increased mortality. Study participants included 18,145 workers with demographic and smoking data and repeatable spirometry. The mortality analysis cohort included 15,445 workers with known vital status and cause of death through December 31, 2016. Stratified analyses explored RSP prevalence by demographic and clinical variables and trade. Log-binomial regression models explored RSP risk factors while controlling for important confounders such as smoking, obesity, and comorbidities. Cox regression models explored mortality risk by spirometry category. Prevalence of RSP was very high (28.6%). Mortality hazard ratios for RSP were 1.50 for all causes, 1.86 for cardiovascular diseases, 2.31 for respiratory diseases, and 1.66 for lung cancer. All construction trades except painters, machinists, and roofers had significantly elevated risk for RSP compared to our internal reference group. RSP was significantly associated with both parenchymal and pleural changes seen by chest X-ray. Construction trade workers are at significantly increased risk for RSP independent of obesity. Individuals with RSP are at increased risk for all-cause mortality as well as mortality attributable to respiratory diseases, cardiovascular diseases, and lung cancer. RSP deserves greater attention in occupational medicine and epidemiology.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities

Artificial intelligence (AI) methods have revolutionized and redefined the landscape of data analysis in business, healthcare, and technology. These methods have innovated the applied mathematics, computer science, and engineering fields and are showing considerable potential for risk science, especially in the disaster risk domain. The disaster risk field has yet to define itself as a necessary application domain for AI implementation by defining how to responsibly balance AI and disaster risk. (1) How is AI being used for disaster risk applications; and how are these applications addressing the principles and assumptions of risk science, (2) What are the benefits of AI being used for risk applications; and what are the benefits of applying risk principles and assumptions for AI-based applications, (3) What are the synergies between AI and risk science applications, and (4) What are the characteristics of effective use of fundamental risk principles and assumptions for AI-based applications? This study develops and disseminates an online survey questionnaire that leverages expertise from risk and AI professionals to identify the most important characteristics related to AI and risk, then presents a framework for gauging how AI and disaster risk can be balanced. This study is the first to develop a classification system for applying risk principles for AI-based applications. This classification contributes to understanding of AI and risk by exploring how AI can be used to manage risk, how AI methods introduce new or additional risk, and whether fundamental risk principles and assumptions are sufficient for AI-based applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Risk to Ecological Resources on Burial Waste Sites on the Hanford Site, Washington - 20248

The US and other nations have a large nuclear and chemical waste remediation task remaining from World War II, the Cold War, and industrial activities. The US Department of Energy (DOE) has the largest task in the U.S., with Hanford (Washington State) being the most contaminated site, with the longest and most costly cleanup program projected to extend to the end of the century. One of the greatest remediation problems at Hanford are the burial waste facilities, some of which are inside the 200 Areas on the Central Plateau, while others are outside the 200 Areas. These areas are associated with waste sites, pipes, and contaminated trenches, posing technical cleanup challenges to meet DoE's remediation goals, including protection of human health and the environment commensurate with Tri- Party Agreement and current regulatory requirements. In this paper we select one of the legacy waste sites (the BC Cribs and Trenches) as a case study to explore how risk to ecological resources varies during and as a consequence of remediation on sites primarily considered legacy waste sites. We used the risk methodology developed by the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) during the Hanford Site-wide Risk Review. The CRESP methodology included evaluating the risk to receptors, including human health, the Columbia River, groundwater, and ecological and cultural resources. The risk evaluation process for ecological receptors included defining the boundaries of each evaluation unit (EU) to be remediated, definition of a suitable buffer area that might be affected, and consideration of the known resource value based on field work. This information, coupled with known remediation options or strategies, allowed us to develop a risk rating for ecological resources. Site risks were evaluated on a scale of 'not discernible' to 'very high' risk. Consideration of the risks at the buried waste sites was complicated by uncertainties in remediation methods and the degree of restoration that would occur as part of the remediation process. We use the BC Cribs and Trenches as a case study to explore why the risks are low currently but increase during remediation. The current 'not discernible to low' risk rating is due to the lack of high quality ecological resources on the BC Cribs and Trenches EU, except for edge areas (with some state-listed species). During remediation the risks increase to 'medium', mainly due to high quality resources on adjacent buffer lands, which could be disrupted during active remediation. Medium and high quality resources on the edge of the site are continuous with higher quality native shrub-steppe habitat on the buffer. Ecological resources on some of the areas surrounding the 200 East and West Areas are some of the highest quality shrub-steppe areas on the Hanford Site, and risk to these resources could be prevented by planning before and during remediation to minimize disruption. For example, lay down areas for the BC Cribs and Trenches can be minimized by careful planning. Heavy truck and other vehicular traffic can be minimized. Spread of the noxious weeds now on some of the site can be prevented, and the spread of invasive species into the site (particularly near undisturbed shrub-steppe habitat) can be reduced. Further, the areas around and between the 200 East and West Areas have been largely undisturbed and can serve as a source of seeds and propagules for any revegetation that occurs as part of the remediation process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Probabilistic Evaluation of Geomechanical Risks in CO2 Storage: An Exploration of Caprock Integrity Metrics Using a Multilaminate Model

The probabilistic uncertainty assessment of geomechanical risk—specifically, caprock failure—attributable to CO2 injection, as presented in a simplified hypothetical geological model, was the focus of this study. Our approach amalgamates the implementation of a multilaminate model, the creation of a response surface model in conjunction with the Box–Behnken sampling design, the execution of associated numerical modeling experiments, and the utilization of Monte Carlo simulations. Probability distributions to encapsulate the inherent variability (elastic and mechanical properties of the caprock and reservoir) and uncertainty in prediction estimates (vertical displacement, total strain, and F value) were employed. Our findings reveal that the Young modulus of the caprock is a key factor controlling equivalent total strain but is insufficient as a stand-alone indicator of caprock integrity. It is confirmed that the caprock can accommodate significant deformation without failure, if it possesses a low Young’s modulus and high mechanical strength properties, such as the friction angle and uniaxial compressive strength. Similarly, vertical displacement was found to be an unreliable indicator for caprock integrity, as caprock failure can occur across a broad spectrum of vertical displacements, particularly when both the Young modulus and mechanical strength properties have wide ranges. This study introduces the F value as the most dependable indicator for caprock failure, although it is a theoretical attribute (the shortest distance between the Mohr circle and the nearest failure envelope used to measure the sensitivity to failure) and not physically measurable in the field. Deviatoric stress levels were found to vary based on stress regimes, with the maximum levels observed under extensive and compressive stress regimes. In conjunction with the use of the response surface method, this study demonstrates the efficacy of the multilaminate framework and the Mohr–Coulomb constitutive model in providing a simplified, yet effective, probabilistic model of the mechanical behavior of caprock failure, reducing mathematical and computational complexities.

Energy & Fuels↗

DOE OSTI2023

Historical Pattern Analysis of Global Geothermal Power Capacity Development: Preprint

Between 1913 and 1958, Italy was the only country with an operational geothermal power plant until New Zealand installed its first plant in 1958. At present, 24 countries are involved in the geothermal power market, and they have a combined installed capacity of 16,127 GW. This study analyzes the historical patterns of geothermal power capacity in the world and in individual countries to investigate the ideal global geothermal development pattern by examining the annual cumulative capacity (ACC) and the annual capacity addition (ACA) graphs of the historical development of geothermal power capacity in 24 countries. First, the global patterns are analyzed using these graphs in five periods (1945-1957, 1958-1976, 1977-1991, 1992-2002, and 2003-2020) that are marked by a series of characteristics of ACA peaks separated by two major troughs. Then, five characteristic patterns are developed in five periods globally. These patterns correspond to the early-stage linear, the first acceleration, the first steady-state linear, the second acceleration, and the second steady-state linear developments. A positive relationship exists between global patterns and the 5-year shifted oil-price curve: two major factors influenced global development: 1) increasing oil prices and increasing awareness of global climate change, and 2) global development of geothermal power. Last, we investigate these patterns in each country. The top ten countries, which comprise 93.3% of the world's total installed capacity are separated into five groups based on the availability and characteristics of patterns globally developed in five periods. Group-1 (the United States) has an installed capacity of 3,794 MW, Group-2 (Mexico and Philippines) 963-1935 MW, Group-3 (New Zealand, Italy, Iceland, and Japan) 601-1,037 MW, and Group-4 (Indonesia, Kenya, and Turkiye) 944-2,356 MW. The remaining 14 countries (6.7%), which are called Group 5, are still in an immature stage and have installed capacities of 7-262 MW and are not involved in pattern analysis. Overall, geothermal power in the world is in its third stage of development, which had its peak development after 1977. A fourth development peak may be expected to occur after this through business-as-usual cases. The biggest barrier to the development of the global geothermal power market is the risk associated with exploration and drilling. If risk mitigation systems and funds are employed, the growth of geothermal power production projects could accelerate.

GEOTHERMAL ENERGY↗

DOE OSTI2023

Historical Pattern Analysis of Global Geothermal Power Capacity Development

Between 1913 and 1958, Italy was the only country with an operational geothermal power plant until New Zealand installed its first plant in 1958. At present, 24 countries are involved in the geothermal power market, and they have a combined installed capacity of 16,127 GW. This study analyzes the historical patterns of geothermal power capacity in the world and in individual countries to investigate the ideal global geothermal development pattern by examining the annual cumulative capacity (ACC) and the annual capacity addition (ACA) graphs of the historical development of geothermal power capacity in 24 countries. First, the global patterns are analyzed using these graphs in five periods (1945-1957, 1958-1976, 1977-1991, 1992-2002, and 2003-2020) that are marked by a series of characteristics of ACA peaks separated by two major troughs. Then, five characteristic patterns are developed in five periods globally. These patterns correspond to the early-stage linear, the first acceleration, the first steady-state linear, the second acceleration, and the second steady-state linear developments. A positive relationship exists between global patterns and the 5-year shifted oil-price curve: two major factors influenced global development: 1) increasing oil prices and increasing awareness of global climate change, and 2) global development of geothermal power. Last, we investigate these patterns in each country. The top ten countries, which comprise 93.3% of the world's total installed capacity are separated into five groups based on the availability and characteristics of patterns globally developed in five periods. Group-1 (the United States) has an installed capacity of 3,794 MW, Group-2 (Mexico and Philippines) 963-1935 MW, Group-3 (New Zealand, Italy, Iceland, and Japan) 601-1,037 MW, and Group-4 (Indonesia, Kenya, and Turkiye) 944-2,356 MW. The remaining 14 countries (6.7%), which are called Group 5, are still in an immature stage and have installed capacities of 7-262 MW and are not involved in pattern analysis. Overall, geothermal power in the world is in its third stage of development, which had its peak development after 1977. A fourth development peak may be expected to occur after this through business-as-usual cases. The biggest barrier to the development of the global geothermal power market is the risk associated with exploration and drilling. If risk mitigation systems and funds are employed, the growth of geothermal power production projects could accelerate.

GEOTHERMAL ENERGY↗

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↗

DOE OSTI2025

Advancing Manufacturing Water Resilience: Addressing Risks through New Approaches and Technologies

Water is indispensable in manufacturing operations, and many manufacturers operate on the assumption that water of sufficient quality and quantity will be available whenever and wherever needed. As such, the importance of water to this sector has been overlooked, despite its critical importance for operations and meeting production demands, due to perceived sufficient availability and low cost of water to manufacturers. However, the situation is changing as water-related risks are markedly increasing due to aging infrastructure, changing climate, and resource extraction, which alter global and regional water cycles and characteristics. These changes are occurring against a backdrop of intensifying competition from other sectors for scarce and/or unevenly distributed water resources and changing trends in water needs. Section 1 of this report explores those risks in the U.S. context, while the remaining sections detail the work needed to advance the resilience of manufacturing water supplies to these changing risks by filling critical data gaps, re-evaluating the value of water to manufacturers, and advancing opportunities for novel technologies and analyses. The intended audience for this report is broad, including manufacturers, decision makers, researchers, and policymakers.

36 MATERIALS SCIENCE↗