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DOE OSTI2022

A Bayesian Approach for In-Situ Stress Prediction and Uncertainty Quantification for Subsurface Engineering

Many subsurface engineering applications require accurate knowledge of the in-situ state of stress for their safe design and operation. Existing methods to meet this need primarily include field measurements for estimating one or more of the principal stresses from a borehole, or optimization methods for constructing a 3D geomechanical model in terms of geophysical measurements. These methods, however, often contain considerable uncertainty in estimating the state of stress. Here, in this paper, we build on a Bayesian approach to quantify uncertainty in stress estimations for subsurface engineering applications. This approach can provide an estimate of the 3D distribution of stress throughout the volume of interest and provide an estimate of the uncertainty arising from the stress measurement, the rheology parameters, and a paucity of measurements. The value of this approach is demonstrated using stress measurements from the In Salah carbon storage site, which was one of the world’s first industrial carbon capture and storage projects. This demonstration shows the application of this Bayesian approach for estimating the initial state of stress for In Salah and quantifying the uncertainty in the estimated stress. Also, an assessment of a maximum injection pressure to prevent geomechanical risks from CO 2 injection pressures is provided in terms of the probability distribution of the minimum principal stress quantified by the approach. With the In Salah case study, this paper demonstrates that using the Bayesian approach can provide additional insights for site explorations and/or project operations to make informed-site decisions for subsurface engineering applications.

58 GEOSCIENCES↗
DOE OSTI2022

DECOVALEX-2023 Task F Specification (Rev. 9)

This report is the revised (Revision 9) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

DECOVALEX-2023: Task F Specification (Revision 10)

This report is the revised (Revision 10) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Preliminary Analysis of Postclosure DPC Criticality Consequences

One of the objectives of the United States (U.S.) Department of Energy's (DOE) Office of Nuclear Energy's Spent Fuel and Waste Science and Technology Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the U.S. has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act 1982). Any repository licensed to dispose the SNF must meet requirements regarding the longterm performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently being used to store and transport SNF but were not designed for permanent geologic disposal. A two-phase study has been initiated to begin examining the potential consequences, with respect to longterm repository performance, of criticality events that might occur during the postclosure period in a hypothetical repository containing DPCs. Phase I, a scoping phase, consisted of developing an approach intended to be a starting point for the development of the modeling tools and techniques that may eventually be required either to exclude criticality from or to include criticality in a performance assessment (PA) as appropriate; Phase I is documented in Price et al. (2019). The Phase I approach guided the analyses and simulations done in Phase II to further the development of these modeling tools and techniques as well as the overall knowledge base. The purpose of this report is to document the results of the analyses conducted during Phase II. The remainder of Section 1 presents the background, objective, and scope of this report, as well as the relevant key assumptions used in the Phase II analyses and simulations. Subsequent sections discuss the analyses that were conducted (Section 2), the results of those analyses (Section 3), and the summary and conclusions (Section 4). This report fulfills the Spent Fuel and Waste Science and Technology Campaign deliverable M2SF-20SN010305061.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Postclosure Criticality Analysis Results

The United States Department of Energy’s (DOE) Office of Nuclear Energy’s Spent Fuel and Waste Science and Technology Campaign seeks to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF must meet requirements regarding the long-term performance of that repository. The evaluation of long-term performance of the repository may need to consider the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential for this situation to occur in dual-purpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal. DOE has been considering disposing of SNF in DPCs to avoid the costs and worker dose associated with repackaging the SNF currently stored in DPCs into repository-specific canisters. This report examines the consequences of postclosure criticality to provide technical support to DOE in developing a disposal plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Analysis of the Effects of Postclosure Criticality on Repository Performance

The United States Department of Energy’s (DOE) Office of Nuclear Energy’s Disposal Research & Development Campaign seeks to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste (HLW). Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF will be subject to requirements regarding the long-term performance of that repository. Evaluating the long-term performance of the repository may consider the consequences of the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential for this to occur in dual-purpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal. DOE has been considering disposing of SNF in DPCs to avoid the costs and worker dose associated with repackaging the SNF currently stored in DPCs into repository-specific canisters. This report examines the consequences of postclosure criticality to provide technical support to DOE in developing a disposal plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

State of Stress Uncertainty Quantification and Geomechanical Risk Analysis for Subsurface Engineering

All subsurface stress measurement methods available for deep subsurface applications are indirect and involve a significant amount of uncertainty. Quantifying these uncertainties is critical for applications where the state of stress is a component of a risk analysis with significant safety, environmental, and economic considerations. A publicly available and open source tool called the State of Stress Analysis Tool (SOSAT) has been developed to aid in performing a Bayesian uncertainty quantification and geomechanical risk analysis using many types of commonly available data. A new feature of this tool is using data from the FutureGen 2.0 site. The new feature of the tool was uses information about the absence or presence of borehole breakouts to constrain the state of stress. This new feature allows the user to specify probability distributions for the relevant parameters such as the drilling mud pressure, temperature, and the formation strength properties. The tool computes the posterior joint probability distribution of the horizontal principal stresses. Using random samples from this posterior distribution the tool then computes the probability of activating a critically oriented fault at a range of pore pressures. This latter feature can be used to aid in the assessment of the risk of induced seismicity and leakage in geologic carbon sequestration and enhanced geothermal systems.

Burghardt, Jeffrey A.↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering

Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, in this study, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (<90°C) and medium (90-150°C)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTensors/GeoThermalCloud.jl.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Transient Postclosure Criticality Model Development

A key objective of the United States Department of Energy’s (DOE) Office of Nuclear Energy’s Spent Fuel and Waste Science and Technology (SFWST) Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF must meet requirements regarding the long-term performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential behavior of SNF in dualpurpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Recommended Practices for Managing Induced Seismicity Risk Associated with Geologic Carbon Storage

The geologic storage of carbon dioxide (CO 2 ) is one method to help reduce or eliminate atmospheric CO 2 emissions. The sequestered CO 2 is originally captured from the atmosphere or from a stationary industrial source and subsequently injected into a deep subsurface porous rock formation. To facilitate the successful deployment of field scale carbon storage projects, the U.S. Department of Energy (DOE) is developing tools and protocols for defensible, science-based frameworks to quantify and mitigate risks associated with the long-term storage of CO 2 . This protocol specifically addresses the risk of induced seismicity due to injection in a geologic carbon storage (GCS) site. This integrated and risk-based protocol is a product of the U.S. DOE Fossil Energy’s National Risk Assessment Partnership (NRAP), a multi-year collaborative research effort of Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), National Energy Technology Laboratory (NETL), and Pacific Northwest National Laboratory (PNNL). These recommended practices describe a set of 7 steps to evaluate, manage, communicate, and mitigate the risk of induced seismicity at GCS sites. The base methodology of the recommended practices follows a framework similar to the Protocol for Addressing Induced Seismicity Associated with Enhanced Geothermal Systems (Majer et al., 2012), developed for the Geothermal Technology Office of the U.S. DOE. These recommended practices present a framework to systematically assess the induced seismicity risk and quantify the associated uncertainties. These recommendations are based on current research and are sufficiently general to allow for modification and application to a variety of different types of sites. The substance of the recommended practices contained herein includes both technical and non-technical issues, and covers all operational stages of the GCS project lifecycle. They start at the preliminary risk assessment phase, continue through site assessment and characterization, include best practice communication and seismic monitoring plan methodologies, discuss the evaluation and mitigation of seismic hazard and risk, and closes with an exploration of operational management plans, which conclude when the induced seismicity risk abates back to background level. The focus of these recommendations is on actively managing the risks associated with induced seismicity by developing an actionable risk management plan that starts at the project proposal stage and continues through site closure through an iterative assessment and improvement process. The audience of this document is expected to include all interested stakeholders (e.g., operators, project developers, regulators, and the general public) and is expressly written to be accessible to this broad range of partners. This document is intended to disseminate knowledge gained through recent advances in the science of induced seismicity hazard and risk assessments, to provide updates based on recent experience gained by similar corollary injection-induced seismicity cases, and most importantly to establish a uniform framework to carry out a successful induced seismicity risk management plan for carbon storage projects in the future. These recommendations do not directly address any domestic or international regulations or standards. A complementary NRAP report makes recommendations for the assessment and management of environmental subsurface risks associated with unwanted fluid migration at GCS sites (Thomas et al., 2021) and should be referred to in order to address those additional GCS site risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Recommended Practices for Managing Induced Seismicity Risk Associated with Geologic Carbon Storage

The geologic storage of carbon dioxide (CO 2 ) is one method to help reduce or eliminate atmospheric CO 2 emissions. The sequestered CO 2 is originally captured from the atmosphere or from a stationary industrial source and subsequently injected into a deep subsurface porous rock formation. To facilitate the successful deployment of field scale carbon storage projects, the U.S. Department of Energy (DOE) is developing tools and protocols for defensible, science-based frameworks to quantify and mitigate risks associated with the long-term storage of CO 2 . This protocol specifically addresses the risk of induced seismicity due to injection in a geologic carbon storage (GCS) site. This integrated and risk-based protocol is a product of the U.S. DOE Fossil Energy’s National Risk Assessment Partnership (NRAP), a multi-year collaborative research effort of Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), National Energy Technology Laboratory (NETL), and Pacific Northwest National Laboratory (PNNL). These recommended practices describe a set of 7 steps to evaluate, manage, communicate, and mitigate the risk of induced seismicity at GCS sites. The base methodology of the recommended practices follows a framework similar to the $\textit{Protocol for Addressing Induced Seismicity Associated with Enhanced Geothermal Systems}$ (Majer et al., 2012), developed for the Geothermal Technology Office of the U.S. DOE. These recommended practices present a framework to systematically assess the induced seismicity risk and quantify the associated uncertainties. These recommendations are based on current research and are sufficiently general to allow for modification and application to a variety of different types of sites. The substance of the recommended practices contained herein includes both technical and non-technical issues, and covers all operational stages of the GCS project lifecycle. They start at the preliminary risk assessment phase, continue through site assessment and characterization, include best practice communication and seismic monitoring plan methodologies, discuss the evaluation and mitigation of seismic hazard and risk, and closes with an exploration of operational management plans, which conclude when the induced seismicity risk abates back to background level. The focus of these recommendations is on actively managing the risks associated with induced seismicity by developing an actionable risk management plan that starts at the project proposal stage and continues through site closure through an iterative assessment and improvement process. The audience of this document is expected to include all interested stakeholders (e.g., operators, project developers, regulators, and the general public) and is expressly written to be accessible to this broad range of partners. This document is intended to disseminate knowledge gained through recent advances in the science of induced seismicity hazard and risk assessments, to provide updates based on recent experience gained by similar corollary injection-induced seismicity cases, and most importantly to establish a uniform framework to carry out a successful induced seismicity risk management plan for carbon storage projects in the future. These recommendations do not directly address any domestic or international regulations or standards. A complementary NRAP report makes recommendations for the assessment and management of environmental subsurface risks associated with unwanted fluid migration at GCS sites (Thomas et al., 2021) and should be referred to in order to address those additional GCS site risks

58 GEOSCIENCES↗
DOE OSTI2021

Repository-Scale Performance Assessment Incorporating Postclosure Criticality

A key objective of the United States Department of Energy’s (DOE) Office of Nuclear Energy’s Spent Fuel and Waste Science and Technology Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF must meet requirements regarding the long-term performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal. A study has been initiated to examine the potential consequences, with respect to long-term repository performance, of criticality events that might occur during the postclosure period in a hypothetical repository containing DPCs. The first phase (a scoping phase) consisted of developing an approach to creating the modeling tools and techniques that may eventually be needed to either include or exclude criticality from a performance assessment (PA) as appropriate; this scoping phase is documented in Price et al. (2019a). In the second phase, that modeling approach was implemented and future work was identified, as documented in Price et al. (2019b). This report gives the results of a repository-scale PA examining the potential consequences of postclosure criticality, as well as the information, modeling tools, and techniques needed to incorporate the effects of postclosure criticality in the PA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Analysis of Transient Postclosure Criticality

The United States Department of Energy’s (DOE) Office of Nuclear Energy’s Spent Fuel and Waste Science and Technology Campaign seeks to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF must meet requirements regarding the long-term performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

A Review and Outlook on Experimental Advances and Innovations in Geological CO 2 Storage: Insights from Depleted Gas Reservoirs and Saline Aquifers

Geological storage of carbon dioxide (CO 2 ) in depleted gas reservoirs and deep saline aquifers is a key part of global decarbonization efforts. As carbon capture and storage advances toward commercial-scale deployment, the credibility and scalability of laboratory experiments are increasingly vital for guiding safe and effective field implementation. This review offers a comprehensive, cross-scale evaluation of experimental methodologies, including core flooding, high-pressure, high-temperature systems, microfluidic visualization, and emerging systems such as multilayer commingled/compartmentalized core flooding, 3D-printed micromodels, and AI-powered digital twins. These innovations are demonstrated to enhance representativeness, reproducibility, and real-time insight, thereby addressing the limitations of conventional workflows. A critical analysis of methodological gaps, such as inconsistent pressure–temperature conditions, oversimplified brine chemistry, and a lack of standardization, reveals experimental sources of scale translation errors and performance uncertainty. By comparing the unique challenges of depleted gas reservoirs (such as low water saturation and legacy well leakage) to those of saline aquifers (including pressure buildup and caprock integrity), this review identifies formation-specific priorities for experimental design. Novel contributions include a synthesis of best practices, integration strategies for model calibration, and recommendations for standardizing core handling, saturation procedures, and reporting protocols. Furthermore, this work serves as a guide for developing robust, field-relevant experimental strategies that can increase the deployment and regulatory acceptance of CO 2 storage technologies at scale.

58 GEOSCIENCES↗
DOE OSTI2024

A simple method for obtaining heat capacity coefficients of minerals

Abstract Heat capacity data are unavailable or incomplete for many minerals at geologically relevant temperatures. Despite the availability of entropy and enthalpy values in numerous thermodynamic tables (even sometimes at elevated temperatures), there remains need for extrapolation beyond, or interpolation between, temperatures. This approach inevitably results in estimates for entropy and enthalpy values because the heat capacity coefficients required for optimal thermodynamic treatment are less frequently available. Here we propose a simple method for obtaining heat capacity coefficients of minerals. This method requires only the empirically measured temperature-specific heat capacity for calculation via a matrix algorithm. The system of equations solver is written in the Python computing language and has been made accessible in an online repository. Thermodynamically, the solution to a system of equations represents the heat capacity coefficients that satisfy the mineral-specific polynomial. Direct coefficient calculation will result in more robust thermodynamic data, which are not subject to fitting uncertainties. Using hematite as an example, this method provides results that are comparable to conventional means and is applicable to any solid material. Coefficients vary within the traditional large 950 K temperature interval, indicating that best results should instead utilize a smaller 400 K temperature interval. Examples of large-scale implications include the refinement of geothermal gradient estimation in rapidly subsiding sedimentary basins or metamorphic and hydrothermal evolution.

Geochemistry & Geophysics↗
DOE OSTI2023

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗