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The Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database v1.0 is the output of a data availability assessment workflow that was developed by NETL to create a tool for spatial data availability assessment. This results database is the output of the first version of the workflow performed on the data with the CS TVA Database v2.0.
The Final Technical Report: Field Test Design and Pressure Management Strategies for Phase II Field Demonstration of Optimal Pressure Control, Plume Management, and Produced Water Strategies presents the culmination of multi-year efforts under the U.S. Department of Energy’s Brine Extraction and Storage Test (BEST) program, led by EPRI in partnership with Gulf Power at the Plant Smith site near Panama City, Florida. The project was designed to evaluate and demonstrate the technical feasibility of managing subsurface pressures and fluid movement associated with large-scale CO₂ injection, using low-salinity water as a proxy fluid. Through a combination of field injection testing, reservoir modeling, and optimization studies, the research team developed and refined active and passive brine extraction strategies aimed at controlling injection-induced pressure buildup, mitigating risks of fault activation, and managing plume migration. The field demonstration incorporated a new injection well (TIW-2), a new monitoring/extraction well (TEMW-A), and an existing well (TIW-1) repurposed for passive pressure relief. Complementary geophysical monitoring was designed to track plume development and evaluate the effectiveness of pressure management strategies. The report details the integrated workflow encompassing wellfield development, regulatory permitting, model calibration, and survey design. It includes a comprehensive electromagnetic (EM) modeling and inversion study used to develop a cost-effective, time-lapse geophysical monitoring plan capable of imaging the evolving low-salinity plume within the highly saline Lower Tuscaloosa formation. Reservoir simulation results guided the design of the 17-month injection program and the timing of active extraction to maintain formation pressures below a hypothetical fault reactivation threshold. Supporting analyses evaluated potential injectivity risks related to clay fines migration and geochemical incompatibility, identifying practical mitigation measures such as salinity and pH control. The final design recommends a series of crosswell EM surveys—conducted before, during, and after injection—as the most effective and economical approach for plume imaging, supplemented by continuous downhole pressure and flow monitoring. Collectively, the study provides a field-ready framework for cost-effective pressure management and monitoring in support of future CO₂ storage projects.
This project developed methodologies to measure the in-situ principal stress in the deep subsurface through use of multiple independent, but complementary, seismic methods, laboratory verification, and development of theoretical frameworks. By leveraging existing regional and local datasets we developed, tested, and refined a set of diagnostic tools for determining the in-situ stress state with reduced uncertainty at and below reservoir depths (1.5-6 km). A set of novel tools was produced that are scale independent, such that their utility is equivalent on regional, field scale, and near borehole monitoring of principal stresses in reservoir underburden for carbon storage projects. During a 4-year Department of Energy (DOE) and Southern Company funded project, carried out by the Electric Power Research Institute (EPRI), Lawrence Livermore National Laboratory (LLNL), the University of Oklahoma (OU), and the U.S. Geological Survey (USGS), the project team developed methodologies to measure the far-field in-situ principal stress in the deep subsurface, leveraging induced seismicity data from waste-water disposal projects. These methodologies consisted in the use of well-established and technically advanced seismic processing methods, such as virtual seismometer method-moment tensor (VSM-MT) and shear wave splitting (SWS), that are adept at recovering the stress orientation and certain components of the stress tensor. These methods were applied to robust seismicity catalogs created with matched filter techniques near sites of active fluid disposal—a proxy for carbon storage sites where such datasets are more limited. Estimates of the stress orientation made with seismic processing tools were considered along with laboratory acoustic emission experiments conducted on rock samples from the region of interest. Stress orientations in the studied region do not vary significantly across distances of ~100 km, nor are they found to rotate through time as a consequence of local wastewater disposal, as previously speculated. Finally, the project team investigated the trade-offs among the different seismic methods and evaluated the range of uncertainty that is generated with these methodologies, which led to a practical use and refinement of the VSM-MT technique when it is applied to field datasets. Understanding the trade-offs between these different methods highlighted the potential benefits of improved quantification of uncertainties on stress field estimations.
The Midwest Regional Carbon Sequestration Partnership (MRCSP) has incorporated the work of geologic research teams (Geoteams) in its regional characterization, project planning and carbon dioxide (CO 2 ) injection implementation work since the partnership was established by the U.S. Department of Energy (DOE) in 2003. Over this 16-year period, the cohort of Geoteams has grown from five to ten states and has contributed to the characterization of geologic sequestration opportunities, refinement of reservoir and seal data, and supported injection efforts through both predictive and post-injection assessments. Five geologic cross sections (labeled A through E) were constructed onshore across the parts of the MRCSP Region west of the Valley and Ridge Province, and one section (labeled F) was constructed beginning onshore in New Jersey and running eastward to offshore areas examined for carbon storage. Regional and local stratigraphic units were used in these cross sections to show current nomenclature as well as highlighting specific units/features pertinent to carbon capture, utilization and storage (CCUS) opportunities in the region. Each cross section uses 15 to 25 deep wells and other geologic information to illustrate the relative depth, thickness and location of rock units in the subsurface.
For geologic systems where carbon dioxide (CO 2 ) is injected underground, existing wells represent potential pathways for fluid migration. Here, this study introduces a novel deep learning model to quantify the likelihood and potential magnitude of fluid migration through wellbores at sites with intermediate aquifers or thief zones between the injection units and underground drinking water sources. Synthetic datasets, generated using reservoir simulations, captured a wide range of subsurface conditions, well attributes, operational parameters, and fluid migration scenarios. Among the regression models developed to predict brine and CO 2 leakage rates and CO 2 saturations along leaky wellbores, convolutional neural network (CNN) outperformed both Light Gradient Boosting Machine and deep neural network. Additionally, a CNN-based classification model was created to predict whether brine and CO 2 would leak along a wellbore, further improving performance over regression alone. The best models were integrated into the National Risk Assessment Partnership Open-source Integrated Assessment Model for rapid, stochastic assessment of storage system containment and leakage risks. A case study demonstrated the model’s ability to simulate fluid migration through existing wells with multiple intermediate aquifers. This computationally efficient wellbore model offers value in support of site performance evaluation and risk-informed decision making by stakeholders.
This report documents a risk assessment of CO 2 containment loss and induced shear failure due to geologic carbon storage at the Wabash CarbonSAFE site. The operator, Wabash Valley Resources, has proposed adapting the onsite integrated gasification combined cycle (IGCC) facilities to produce hydrogen and injecting the byproduct CO 2 stream into the subsurface Potosi dolomite formation. The purpose of this study is to assess (1) CO 2 sequestration performance relative to the CarbonSAFE goals of storing 50 Mt over 30 years, (2) the risk of containment loss due to leakage along a wellbore and into an overlying aquifer, and (3) the state of stress and risk of reactivating existing fractures. This study relied upon the initial site characterization work performed by the Illinois State Geologic Survey (ISGS) along with analogue data collected from other carbon sequestration projects in the region.
The multisegmented wellbore model (MSW) semi-analytically estimates the amount of CO 2 and brine leakage from a leaking legacy well by segmenting it into intervals to simulate site-specific stratigraphic and hydrogeologic properties. The model is a component of the National Risk Assessment Partnership Open-Source Integrated Assessment Model (NRAP-Open-IAM), which was developed to perform risk assessment for geologic CO 2 storage. The new wellbore leakage model, which uses deep learning networks for a caprock segment, was developed to enhance the analytical MSW. The model was trained and validated using a synthetic data set of Subsurface Transport Over Multiple Phases (STOMP) multiphase flow simulations from various geological, well attribute, and operational conditions to ensure its quality. The results demonstrate that the model is more accurate than the existing model in predicting the transport of two-phase fluids (brine and injected CO 2 ) through the well. This report provides a detailed explanation of the model development and quality assurance.
Novel and rugged electromagnetic wireless system for long-term subsurface CO₂ plume monitoring and saturation mapping is a Phase I SBIR project led by Cyentech Consulting LLC to develop a permanently installed, outside-casing electromagnetic monitoring system for long-term carbon storage monitoring. The project addresses a major challenge in carbon capture and storage: the need for reliable, cable-free downhole monitoring that can detect CO₂ plume movement and saturation changes without compromising well integrity through casing perforations or external umbilical cables.
SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.
Energy storage is increasingly necessary as variable renewable energy technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological thermal energy storage (GeoTES) is proposed as a solution for long-term energy storage. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. In this article, we describe a techno-economic model that has been developed to evaluate GeoTES systems. The models are developed by combining the output of specialist models, which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models are developed so that the performance can be evaluated at each hour of the year. GeoTES can be charged with two different energy sources: (1) concentrating solar thermal and (2) renewable electricity using heat pumps (henceforth known as a "Carnot Battery"). The stored thermal energy can be used to generate electricity and, uniquely, also directly produce heat that can be used by industrial processes. Furthermore, Carnot Battery GeoTES can also be used to form a cold storage reservoir. Preliminary results that quantify the technical and economic performance of these two GeoTES systems are presented.
Energy storage is increasingly necessary as Variable Renewable Energy (VRE) technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological Thermal energy storage (GeoTES) is proposed as a solution for long-term energy storage. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. In this article, we describe a techno-economic model that has been developed to evaluate GeoTES systems. The models are developed by combining the output of specialist models which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models are developed so that the performance can be evaluated at each hour of the year. GeoTES can be charged with two different energy sources: (1) concentrating solar thermal and (2) renewable electricity using heat pumps (henceforth known as a "Carnot Battery"). The stored thermal energy can be used to generate electricity and - uniquely - also directly produce heat that can be used by industrial processes. Furthermore, Carnot-Battery-GeoTES can also be used to form a cold storage reservoir. Preliminary results that quantify the technical and economic performance of these two GeoTES systems are presented.
Abstract Increasing sea levels associated with climate change threaten the survival of coastal forests, yet the mechanisms by which seawater exposure causes tree death remain poorly understood. Despite the potentially crucial role of nonstructural carbohydrate (NSC) reserves in tree survival, their dynamics in the process of death under seawater exposure are unknown. Here we monitored progressive tree mortality and associated NSC storage in Sitka-spruce (Picea sitchensis) trees dying under ecosystem-scale increases in seawater exposure in western Washington, USA. All trees exposed to seawater, because of monthly tidal intrusion, experienced declining crown foliage during the sampling period, and individuals with a lower percentage of live foliated crown (PLFC) died faster. Tree PLFC was strongly correlated with subsurface salinity and needle ion contents. Total NSC concentrations in trees declined remarkably with crown decline, and reached extremely low levels at tree death (2.4% and 1.6% in leaves and branches, respectively, and 0.4% in stems and roots). Starch in all tissues was almost completely consumed, while sugars remained at a homeostatic level in foliage. The decreasing NSC with closer proximity to death and near zero starch at death are evidences that carbon starvation occurred during Sitka-spruce mortality during seawater exposure. Our results highlight the importance of carbon storage as an indicator of tree mortality risks under seawater exposure.
Energy storage is increasingly necessary as variable energy technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological Thermal Energy Storage (GeoTES) is proposed as a solution for long-term energy storage [1]. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. The energy capacity cost of GeoTES is very low which makes it suitable for both daily- and seasonal storage of Concentrating Solar Thermal (CST) energy, thus enabling CST to provide value to electricity markets and thermal energy off-takers. A CST-GeoTES demonstration system has been funded by the U.S. Department of Energy, Solar Energy Technology Office. In this article, we will describe this demonstration system and progress that has been made in its development. The demonstration system will comprise a 2 MWth parabolic trough with an 8m aperture developed by Gossamer Space Frames, seven wells, and a 100 kWe power cycle. The demonstration system will be deployed in Kern County, California by Premier Resource Management. A techno-economic model for CST-GeoTES systems has also been developed [3] and is applied to the demonstration system and its planned future expansion. The model integrates the output of specialist models of each subsystem, which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models enable the performance to be evaluated at each hour of the year, before being aggregated to evaluate the economic potential of CST-GeoTES. Initial analysis indicates that CST-GeoTES can provide long duration energy storage capabilities with low marginal costs of energy capacity - leading to a low value of Levelized Cost of Storage (LCOS) compared to alternative technologies, see Figure 2. In this article, we investigate the cost and performance of the specific demonstration site being developed by PRM and explore a range of operational profiles that can deliver different value streams, such as daily and seasonal storage, capacity, and resiliancy.
Abstract Geologic carbon storage in deep saline aquifers has emerged as a promising technique to mitigate climate change. CO 2 is buoyant at the storage conditions and tends to float over the resident brine jeopardizing long-term containment goals. Therefore, the caprock sealing capacity is of great importance and requires detailed assessment. We perform supercritical CO 2 injection experiments on shaly caprock samples (intact caprock and fault zone) under representative subsurface conditions. We numerically simulate the experiments, satisfactorily reproducing the observed evolution trends. Simulation results highlight the dynamics of CO 2 flow through the specimens with implications to CO 2 leakage risk assessment in field practices. The large injection-induced overpressure drives CO 2 in free phase into the caprock specimens. However, the relative permeability increase following the drainage path is insufficient to provoke an effective advancement of the free-phase CO 2 . As a result, the bulk CO 2 front becomes almost immobile. This implies that the caprock sealing capacity is unlikely to be compromised by a rapid capillary breakthrough and the injected CO 2 does not penetrate deep into the caprock. In the long term, the intrinsically slow molecular diffusion appears to dominate the migration of CO 2 dissolved into brine. Nonetheless, the inherently tortuous nature of shaly caprock further holds back the diffusive flow, favoring safe underground storage of CO 2 over geological time scales.
Hydrologic exchange flows (HEFs) have environmental significance in riverine ecosystems. Key river channel factors that influence the spatial and temporal variations of HEFs include river stage, riverbed morphology, and riverbed hydraulic conductivity. However, their impacts on HEFs were often evaluated independently or on small scales. In this study, we numerically evaluated the combined interactions of these factors on HEFs using a high-performance simulator, PFLOTRAN, for subsurface flow and transport. The model covers 51 square kilometers of a selected river corridor with large sinuosity along the Hanford Reach of the Columbia River in Washington, US. Three years of spatially distributed hourly river stages were applied to the riverbed. Compared to the simulation when riverbed heterogeneity is not ignored, the simulation using homogeneous riverbed conductivity underestimated HEFs, especially upwelling from lateral features, and overestimated the mean residence times derived from particle tracking. To derive a surrogate model for the river corridor, we amended the widely used transient storage model (TSM) for riverine solute study at reach scale with reactions. By treating the whole river corridor as a batch reactor, the temporal changes in the exchange rate coefficient for the TSM were derived from the dynamic residence time estimated from the hourly PFLOTRAN results. The TSM results were evaluated against the effective concentrations in the hyporheic zone calculated from the PFLOTRAN simulations. Our results show that there is potential to parameterize surrogate models such as TSM amended with biogeochemical reactions while incorporating small-scale process understandings and the signature of time-varying streamflow to advance the mechanistic understanding of river corridor processes at reach to watershed scales. However, the assumption of a well-mixed storage zone for TSM should be revisited when redox-sensitive reactions in the storage zones play important roles in river corridor functioning.
Developing and deploying commercial-scale carbon dioxide (CO 2 ) storage at a site requires operational strategies to manage pressure and CO 2 plume distribution. In the natural gas storage and oil and gas industries, fluid extraction has been successfully implemented as a strategy to manage pressure and control fluid distribution (i.e., hydrocarbon recovery and natural gas storage efficiency, respectively). The technical challenges of integrating brine extraction at CO 2 storage sites are expected to be similar, if not identical, to those in the natural gas storage and petroleum industries. Major technical challenges of using brine extraction to manage storage in a storage unit include (1) designing and completing the brine extraction wells, (2) locating the brine extraction well, (3) assessing the efficacy of brine extraction, and (4) handling the extracted brine. The design and completion of the brine extraction well include the well type (i.e., vertical or horizontal) and perforated interval. The location of the well is influenced by the timing of extraction operations (i.e., prior or after CO 2 injection starts) and project objectives (i.e., desired directional movement of the CO 2 plume and avoid or minimize CO 2 extraction). The efficacy of brine extraction requires a baseline projection of the pressure and CO 2 plume distribution. Options for handling extracted brine include subsurface disposal, surface disposal, and industrial use. Here this paper addresses means of overcoming technical challenges that may likely be encountered before or after CO 2 injection starts.
Abstract In the coastal regions of the western United States, atmospheric rivers (ARs) are associated with the largest precipitation generating storms and contribute up to half of annual precipitation, but the impact of ARs on the integrated hydrologic cycle, specifically on groundwater storage and hydrodynamics, is largely unknown. To better explore the hydrologic behavior of AR versus non‐AR event precipitation, we present a novel combination of two water tracking methods (one in the atmosphere and one in the subsurface) to explicitly track the full lifecycle of water parcels generated by ARs. Simulations of northern California's Cosumnes River watershed during the record wet 2017 water year are performed via the coupling of a high‐resolution regional climate model and a land surface‐groundwater model accounting for lateral groundwater flow. Despite ARs contributing more precipitation than non‐AR storms, we find less AR water is preferentially stored in aquifers by year end. Fractionally, ARs result in 300% less snow derived groundwater‐recharged compared to non‐AR precipitation. Rain‐on‐snow (RoS) plays an important role in AR‐driven discharge, where over 50% of total discharge from ARs snow is from RoS events. Finally, despite record‐breaking annual precipitation, simulated groundwater depletion occurs by year end due to estimates of groundwater pumping activities. The results from these simulations serve as a partial analogue of future hydrologic conditions where ARs are expected to intensify and provide a greater fraction of annual precipitation due to climate change.
The Carbon Storage Technical Viability Approach (CS TVA) database was developed to support the implementation of the CS TVA Matrix to a national data availability assessment for technically viable carbon storage. This database leverages the efforts of multiple adjacent and overlapping databases by non-redundantly combining the databases into a single database along with additionally providing tags facilitating the CS TVA. The non-redundant aspect of the database permits an accurate assessment of the concentration of available data, aiding in spatial and categorical data gaps analysis relative to the individual CS TVA Matrix Components. Version 2.0 of the database is an expansion of Version 1.0. Version 2.0 was created to include additional data gathered to fill gaps in the existing data set. Downloading the CS TVA v2.0 database will result in two separate databases, the version 1.0 original .gdb, and a second addendum .gdb with the new data gathered, together these two databases make up v2.0. Please see the ReadMe file below for full details, metadata information, use disclaimer, and attributions.