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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Reservoir Storage Capacity Change (ResCap)

Overview Storage capacity is an essential reservoir metric that is directly linked to various water management and energy objectives. Accurate reporting and tracking of change in storage over time is crucial for the safe and reliable operation of the associated dam. While storage information is available for many reservoirs through the National Inventory of Dams, additional details, e.g. water elevation levels as well as changes over time are not included. This dataset contains reservoir storage capacities based on conducted surveys in CONUS. To represent changes in a reservoir’s storage over time, the storage capacity as determined by the first and last conducted survey is listed. The level of detail of surveys can vary greatly and improved with technological advancements. Therefore, the type of survey and year when it was conducted is noted. To ensure a fair comparison of storage capacities, the water elevation level along with the corresponding operation of the dam is reported. Structural changes, e.g. heightening of a dam will have an influence on the storage capacity and are therefore also mentioned. A total of 739 different reservoir storage capacity comparisons are listed, with some reservoirs represented more than once (storage capacity comparison at different water elevation levels). Methodology Data were acquired from USBR reservoir survey reports, TWDB lake survey reports and elevation-area-capacity tables, the RSI Web Portal and the NID (USACE, 2024). Initial storage capacity along with year and type of survey record is compared to the most recent reported storage capacity, survey type and year. Comparison elevation in feet as well as comparison elevation type were either extracted from survey reports (USBR, TWDB) or the Web Portal (RSI) and in some cases cross-referenced with data from other sources (Water Management Data, USACE, Water Data for Texas, TWDB).

Chu, Antonia [ORNL] (ORCID:0009000510540427)↗
DOE OSTI2020

Hydraulic fracturing to enhance injectivity and storage capacity of CO 2 storage reservoirs: Benefits and risks

Several potential CO 2 storage reservoirs have been found to have insufficient porosity and permeability to support cost effective commercial-scale injection. As a result, the use of hydraulic fracturing to enhance injectivity and storage capacity of CO 2 storage reservoirs was explored. Previous modeling studies indicate that fracturing can increase storage capacity by modest to significant amounts (10%–35%), depending on model assumptions. Simulations completed as part of this study confirm that for a range of horizontal well lengths, number of fractures, fracture geometries, and fracture properties, injectivity is improved and capacity increases by 13%–71% over the base case unfractured vertical well. Intuitively, increasing the well length and number of fractures had a corresponding impact on increased capacity. Here, fracture area (i.e., the fracture height multiplied by its width) was an important parameter for increasing capacity but the specific geometry (e.g., the ratio of height-to-width) was unimportant. The most important aspect that affected capacity was the ability of a fracture to connect high permeability horizontal zones in the reservoir. This would allow a single well to access both layers, thereby maximizing total storage capacity of the reservoir while likely leading to an overall increase of the CO 2 footprint, which is an important consideration for Class VI UIC permitting. The results of this work demonstrate that hydraulic fracturing is an attractive option to consider when faced with an underperforming geologic carbon storage site that is at risk of causing a project to fail.

03 NATURAL GAS↗
NASA NTRS1988

On the stability, storage capacity, and design of nonlinear continuous neural networks

The stability, capacity, and design of a nonlinear continuous neural network are analyzed. Sufficient conditions for existence and asymptotic stability of the network's equilibria are reduced to a set of piecewise-linear inequality relations that can be solved by a feedforward binary network, or by methods such as Fourier elimination. The stability and capacity of the network is characterized by the post synaptic firing rate function. An N-neuron network with sigmoidal firing function is shown to have up to 3N equilibrium points. This offers a higher capacity than the (0.1-0.2)N obtained in the binary Hopfield network. Moreover, it is shown that by a proper selection of the postsynaptic firing rate function, one can significantly extend the capacity storage of the network.

Guez, Allon↗
NASA NTRS1991

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications.

Katz, Randy H.↗
DOE OSTI2023

Wettability variation and its impact on CO 2 storage capacity at the Wyoming CarbonSAFE storage hub: An experimental approach

Meeting global and national net zero carbon emission targets will require geologic carbon disposal. The U.S. Department of Energy (DOE) has accordingly funded significant research in this area, including the Wyoming CarbonSAFE project at Dry Fork Station (DFS) in Campbell County, Wyoming. This work studied wettability on micro- and macro-scales, CO 2 storage potential, and the correlation between the two to support the Wyoming CarbonSAFE project’s subsurface assessment. During the study, a target formation’s wettability was found to affect how much CO 2 can be stored in a given formation. Here, in this study, representative rock samples were selected from the target storage formations— Lakota, Hulett, and Minnelusa—based on the heterogeneity of the lithology, permeability, and porosity of the respective formations. The rock samples are all fine-grained sandstone with variable cementation and bedding structure, including different scales of laminated bedding. The porosity and permeability vary within the range of 9.0–14.3% and 0.1–28.9 mD, respectively. These rock samples were prepared for the micro-scale wettability (contact angle measurement), macro-scale wettability (wettability index derived from unsteady-state flow characterization for the core plugs), and CO 2 storage evaluation. The macro-scale experiments suggested that wettability appeared to dominate the CO 2 storage potential performance during the drainage process, where less water-wet behavior promoted higher CO 2 storage potential. The micro-scale wettability tests showed that the rock samples at the studied reservoir conditions behaved water-wet and became more water-wet as pressure increased. This kind of wettability change discourages further CO 2 storage potential yet benefits the CO 2 residual trapping as the CO 2 injection proceeds for the studied area. The results allow the recommendation of the best reservoir candidate for storage based on wettability that affects CO 2 storage. The work presented in this study provides valuable insights into wettability’s effect on the CO 2 storage capacity and wettability’s importance when identifying the optimal CO 2 storage formation to meet the project’s goals.

58 GEOSCIENCES↗
DOE OSTI2023

Hydropower Energy Storage Capacity (HESC) Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogs characteristics that are relevant to evaluating reservoir storage and estimates of energy storage capacity based on varying levels of detail. Hydropower dams and reservoirs were included based on information from the National Inventory of Dams (NID; USACE, 2021) and Global Reservoir and Dam (GRanD v1.3) and Existing Hydropower Assets datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Estimates of energy storage capacity include: • Level 1 – nominal energy storage capacity based on maximum storage capacities and hydraulic head • Level 2 – nominal energy storage capacity based on historical models or observations of reservoir volume and hydraulic head. These estimates are provided based on capacity from the entire historical period as well as monthly values. • Level 3 – modeled energy generation based on volume-elevation relationships, historical storage, observed/modeled inflows, and hydraulic capacity of turbines and calculated both as overall and on a monthly basis. • Level 4 – modeled energy generation incorporating information from Level 3 and operational constraints. For facilities where installed capacity is known, there are also estimates for discharge duration (the length of time when a facility could provide generation at a given capacity).

13 HYDRO ENERGY↗
DOE OSTI2021

Hydropower Energy Storage Capacity Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogues estimates of nominal energy storage capacity based on varying levels of detail. Dams and reservoirs selected were selected based on those reported in the National Inventory of Dams (NID 2019) and/or the Global Reservoir and Dam (GRanD v1.3) datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Current estimates include Level 1 (based on maximum storage capacities and hydraulic head) and Level 2 (based on historical models or observations of reservoir volume and hydraulic head). For facilities where installed capacity is known, there are also estimates for discharge duration or the length of time when a facility could provide generation at a given capacity. Essential information used to calculate the energy storage capacity and discharge duration (volume, hydraulic head, and details about the sources or records used to obtain those parameters) and summaries of historical generation (for context) are also included.

13 HYDRO ENERGY↗
DOE OSTI2021

Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

02 PETROLEUM↗
DOE OSTI2021

Applying design principles to improve hydrogen storage capacity in nanoporous materials

Hydrogen is an attractive option for energy storage because it can be produced from renewable sources and produces environmentally benign byproducts. However, the volumetric energy density of molecular hydrogen at ambient conditions is low compared to other storage methods like batteries, so it must be compressed to attain a viable energy density for applications such as transportation. Nanoporous materials have attracted significant interest for gas storage because they can attain high storage density at lower pressure than conventional compression. Here, we examine how to improve the cryogenic hydrogen storage capacity of a series of porous aromatic frameworks (PAFs) by controlling the pore size and increasing the surface area by adding functional groups. We also explore tradeoffs in gravimetric and volumetric measures of the hydrogen storage capacity and the effects of temperature swings using grand canonical Monte Carlo simulations. We also consider the effects of adding functional groups to the metal–organic framework NU-1000 to improve its hydrogen storage capacity. We find that highly flexible alkane chains do not improve the hydrogen storage capacity in NU-1000 because they do not extend into the pores; however, rigid chains containing alkyne groups do increase the surface area and hydrogen storage capacity. Finally, we demonstrate that the deliverable capacity of hydrogen in NU-1000 can be increased from 40.0 to 45.3 g/L (at storage conditions of 100 bar and 77 K and desorption conditions of 5 bar and 160 K) by adding long, rigid alkyne chains into the pores.

08 HYDROGEN↗
DOE OSTI2022

A Hierarchical Framework for CO2 Storage Capacity in Deep Saline Aquifer Formations

Carbon dioxide (CO 2 ) storage in deep saline aquifers is a vital option for CO 2 mitigation at a large scale. Determining storage capacity is one of the crucial steps toward large-scale deployment of CO 2 storage. Results of capacity assessments tend toward a consensus that sufficient resources are available in saline aquifers in many parts of the world. However, current CO 2 capacity assessments involve significant inconsistencies and uncertainties caused by various technical assumptions, storage mechanisms considered, algorithms, and data types and resolutions. Furthermore, other constraint factors (such as techno-economic features, site suitability, risk, regulation, social-economic situation, and policies) significantly affect the storage capacity assessment results. Consequently, a consensus capacity classification system and assessment method should be capable of classifying the capacity type or even more related uncertainties. We present a hierarchical framework of CO 2 capacity to define the capacity types based on the various factors, algorithms, and datasets. Finally, a review of onshore CO 2 aquifer storage capacity assessments in China is presented as examples to illustrate the feasibility of the proposed hierarchical framework.

58 GEOSCIENCES↗
DOE OSTI2021

Pore characterization of the Marcellus Shale by nitrogen adsorption and prediction of its gas storage capacity

In a shale gas reservoir, pore characterization is an important factor used to determine gas storage capacity. However, the nanometer (nm)-scale pore system in shale is difficult to explore by traditional optical, scanning electron microscopy, or even nuclear magnetic resonance well logging. We have investigated the pore structure and storage capacity of the Marcellus Shale through integration of petrophysical analysis from laboratory and well-logging data and nitrogen adsorption. The isotherm of Marcellus Shale is a composite isotherm, which has features of type I, type II, and type IV isotherms with type H4 of the hysteresis loop, suggesting slit-like pores developed in the Marcellus Shale. Quantitative analysis of pore volumes from the nitrogen adsorption indicates that density porosity may be more properly used to approximate the shale porosity and estimate the shale gas volume. In addition, the specific surface area, micropore, and mesopore volumes have a positive relationship with the kerogen volume and total organic content (TOC). By using the Langmuir and Brunauer-Emmet-Teller models, the simulated result indicates that the higher adsorbed quantity of the Marcellus Shale could be the result of the increase of micropore volume contributed, by the increase of kerogen or TOC content. The proposed equations rapidly compute TOC, a key parameter to predict gas storage capacity in overmature shale such as the Marcellus Shale.

Geochemistry & Geophysics↗
DOE OSTI2019

Krypton storage capacity of the Earth's lower mantle

Noble gases are important geochemical tracers allowing reconstructing global volatile cycles in Earth's reservoirs. To constrain these fundamental processes, precise data on their partitioning behavior at deep Earth conditions are needed. Such data are only available at moderate pressures up to 25 GPa due to experimental challenges. We have investigated the possibility of noble gas storage in the Earth's lower mantle up to 115 GPa. We studied the incorporation of krypton in the second most abundant lower mantle mineral (Mg 1-x ,Fe x )O (ferropericlase) as well as in liquid metal-alloys by performing experiments up to 115 GPa and 3700 K using the laser-heated diamond anvil cell coupled to post-mortem EMPA analysis and X-ray absorption spectroscopy. The results reveal that, at these extreme conditions, up to 3 wt.% of krypton can be stored in (Mg 1-x ,Fe x )O and 3000 ppm in the Fe-rich liquid metal. For both phases the storage capacities increase with pressure (between 40 GPa and 60 GPa) at a constant high temperature of 2300 K. Fpc has never been considered as a NG host, despite being the second most abundant mineral in the Earth's LM. Using recent accurate compressibility data, we demonstrate that a substitution of krypton into the anion site of (Mg 1-x ,Fe x )O in form of neutral oxygen Schottky defects at diluted lower mantle conditions is possible. This noble gas incorporation mechanism is in agreement with a previous study on bridgmanite. We show that (Mg 1-x ,Fe x )O exhibits higher noble gas storage capacities than bridgmanite through the lower mantle using lattice strain modeling and including experimental solubility and thermoelastic data for neon, argon, krypton and xenon. We also demonstrate that both phases exhibit the highest solubilities for argon and krypton. We used the solubility data from lattice strain modeling to predict noble gas abundances stored in the solid lower mantle after magma ocean crystallization. The modeled abundances show apparent similarities with estimates for the deep noble gas reservoir that are based on either 3He abundances in ocean island basalts or radiogenic 40Ar abundances in the bulk Earth. This strongly indicates that the crystalline lower mantle may play an important role as deep noble gas storage reservoir. We propose, based on considerations on noble gas replenishment from the lower mantle to the atmosphere, that the lower mantle can only contribute to a small fraction of the present-day atmospheric noble gases. This suggests that the lower mantle is an un-degassed reservoir.

58 GEOSCIENCES↗
DOE OSTI2021

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗
DOE OSTI2024

CO2 Saline Storage: Costs and Storage Capacity

This document provides a brief description of the current state of CO2 saline storage. It then discusses factors determining the cost of storage and provides examples for two storage formations. It concludes by discussing the factors influencing CO2 storage capacity and provides cost supply cirves for CO2 storage.

Morgan, David↗