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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP) User’s Manual

This user’s manual describes version 1.0 of the SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP)) tool and provides instructions for use. The purpose of the SHASTA-HELP tool is to integrate the suite of tools developed by the SHASTA research team in a web-based framework for ease of access and more advanced, integrated analysis. This tool contains functionality for estimating the storage potential of pure and blended natural gas-hydrogen mixtures in various subsurface formations and is intended to be used for pre-characterization or site screening purposes. Detailed storage analysis should be conducted by full reservoir simulation models.

08 HYDROGEN↗
DOE OSTI2025

MRCI Subtask 2.4/2.5: Regional/Subregional Analysis and Risk Assessment Final Technical Summary Report

The objective of the Midwest Regional Carbon Initiative (MRCI) project is to implement a collaborative Regional Initiative (RI) to accelerate the deployment of carbon capture, and storage (CCS) in the Midwest-Northeastern quadrant of the United States. This report is a Technical Summary report describing work performed on Tasks 2.4 (Conducting Regional/Subregional Analysis) and 2.5 (Assessing and Managing Risk) during the MRCI project. In Task 2.4, detailed numerical reservoir simulation models were developed for selected carbon storage (CS) systems identified under Task 2.1 (Battelle, 2021a) in the MRCI study area. The objective of Task 2.4 is to demonstrate a dynamic modeling methodology for evaluating the suitability of the (selected) CS systems in the MRCI region for hosting a commercial-scale storage project. In this study, CO2 injectivity was evaluated for different CS systems with an annual injection rate of 1 million metric tonnes (MMT) of CO2 considered as the minimum requirement for a commercial scale project. The objective of Task 2.5 is to assess key risks associated with storing CO2 in the different CS systems across the MRCI region and to demonstrate a method(s) for assessing these risks that may be used by developers of future CO2 storage projects in the region. The risk analysis was limited to evaluating two types of leakage risks (i.e., wellbore leakage, flow across unfractured caprock) at three modeled sites considered in Task 2.4.

MRCI,Report,Summary,Technical Challenges,dynamic m↗
DOE OSTI2026

Prairie State Generating Company Site: Storage Field Development Plan

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, operational plans, and costs associated with the proposed Prairie State Energy Campus - Carbon Capture and Storage (PSEC-CCS) project in Washington County, Illinois, near Marissa. The proposed storage complex, known as the St. Peter-Everton Storage Complex, comprises the St. Peter Sandstone and Everton sandstone reservoirs, with the Maquoketa Shale serving as the primary confining unit and the Knox Group as lower confining unit. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Pennsylvanian section.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

StrmtbFlow Fortran Program, Version 2

<span>This zip file contains files storing Fortran source code, compiled files, an executable file for Windows computers, and example input and output files for StmtbFlow. StrmtbFlow is a Fortran program that solves the multiphase flow equations within stream tubes and can be used to estimate the oil produced and CO2 stored from the application of CO2 EOR to an oil field. StrmtbFlow and StrmtbGen comprise the FE/NETL CO2 Prophet Model, which is a streamline/stream tube reservoir simulator for modeling CO2 EOR. StrmtbFlow's user&rsquo;s manual as well as StrmtbGen and its user's manual and a report on the mathematical basis for the FE/NETL CO2 Prophet Model are available on NETL's website under the Collection Name: FE/NETL CO2 Prophet Model.</span><span>&nbsp;</span>

Morgan, David↗
DOE OSTI2020

StrmtbGen Fortran Program, Version 2

This zip file contains files storing Fortran source code, compiled files, an executable file for Windows computers, and example input and output files for StrmtbGen. StrmtbGen is a Fortran program that generates streamlines and stream tubes. StrmtbGen and StrmtbFlow comprise the FE/NETL CO2 Prophet Model, which is a streamline/stream tube reservoir simulator for modeling CO2 EOR. StrmtbGen's user’s manual as well as StrmtbFlow and its user's manual and a report on the mathematical basis for the FE/NETL CO2 Prophet Model are available on NETL's website under the Collection Name: FE/NETL CO2 Prophet Model.

Morgan, David↗
DOE OSTI2020

Sensitivity and history match analysis of a carbon dioxide “huff-and-puff” injection test in a horizontal shale gas well in Tennessee

Due to improvements in well development, shale gas production has gained importance recently, especially in the United States. To improve gas production and develop a better understanding of shale reservoirs, researchers are conducting field tests to monitor CO 2 storage and enhanced gas recovery. Reservoir simulations can then utilize these field results for sensitivity studies, uncertainty analysis, history matching, gas production forecasts, and CO 2 storage capacity estimations. One such field test was performed for the Chattanooga Shale formation in Morgan County, Tennessee. Approximately 463 tonnes (510 tons) of CO 2 was successfully injected into a hydraulically fractured horizontal well over a thirteen-day period in March 2014. The injection test was achieved in four steps: pre-injection, injection, soaking, and flowback. In this paper, those steps were modeled with a reservoir simulator to match the historic production and injection rates with gas component compositions and forecast the production for five years. The reservoir fluid was modeled as a multi-component gas, including CH 4 , C 2 H 6 , C 3 H 8 , N 2 , and CO 2 . Langmuir constants, reservoir pressure, and fracture network volume were adjusted to match simulation results with observed production rates and gas composition. Results showed that, under the same reservoir conditions, each gas component behaves differently by way of compositional changes in production. CH4 behaves like N2, while CO 2 behaves like heavier hydrocarbons such as C 2 H 6 and C 3 H 8 . CO 2 plume results showed that, after injection, the produced CO 2 is mostly derived from fractured limestone (i.e., Fort Payne Formation) because the injected CO 2 is not adsorbed in limestone but rather by shale formations.

03 NATURAL GAS↗
DOE OSTI2025

Surrogate models for development of unconventional shale reservoirs by an integrated numerical approach of hydraulic fracturing, flow and geomechanics, and machine learning

We develop well-completion surrogate models by taking an integrated workflow of hydraulic fracturing, flow, geomechanics, and machine learning simulation. There are three steps in the proposed workflow. First, history-matching processes are conducted with the field data including pumping and production data for characterization. Second, full-physics simulation is performed with various parameters of the field development (e.g., cluster spacing, clusters per stage, pumping rates and times, amount of proppant, and well spacing) to generate multiple simulation results by changing the parameters of the completion design with well-known hydraulic fracturing, reservoir, geomechanics simulators to calculate fracture geometry, reservoir depressurization, induced stress changes. The workflow is demonstrated over a field in the Southern Midland Basin. Here, we take two completion scenarios: a single well case followed by a multi-well case. Finally, a Long Short-Term Memory (LSTM) machine learning algorithm is employed to create surrogate models that can replicate the full-physics simulation results. Furthermore, results show that the trained models applied in the single well and multi-well cases for a particular geological system can provide good accuracy close to those provided by full-physics simulations. Specifically, the site-specific surrogate models can predict fracture parameters (length, height, and surface area) and cumulative production accurately with computational efficiency, suggesting our proposed workflow can be used as a pragmatic tool for expediting the well completion optimization process.

Geomechanics↗
DOE OSTI2026

HydroDCM: Hydrological Domain-Conditioned Modulation for Cross-Reservoir Inflow Prediction

Deep learning models have shown promise in reservoir inflow prediction, yet their performance often deteriorates when applied to different reservoirs due to distributional differences, referred to as the domain shift problem. Domain generalization (DG) solutions aim to address this issue by extracting domain-invariant representations that mitigate errors in unseen domains. However, in hydrological settings, each reservoir exhibits unique inflow patterns, while some metadata beyond observations like spatial information exerts indirect but significant influence. This mismatch limits the applicability of conventional DG techniques to many-domain hydrological systems. To overcome these challenges, we propose HydroDCM, a scalable DG framework for cross-reservoir inflow forecasting. Spatial metadata of reservoirs is used to construct pseudo-domain labels that guide adversarial learning of invariant temporal features. During inference, HydroDCM adapts these features through light-weight conditioning layers informed by the target reservoir’s metadata, reconciling DG’s invariance with location-specific adaptation. Experiment results on 30 real-world reservoirs in the Upper Colorado River Basin demonstrate that our method substantially outperforms state-of-the-art DG baselines under many-domain conditions and remains computationally efficient.

Hu, Pengfei [ORNL] (ORCID:0009000367130950)↗
DOE OSTI2024

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada: Preprint

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead-observed temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260degreesF (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2025

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260 degrees F (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2024

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗
DOE OSTI2022

Implications of rootless geothermal models: Missing processes, parameter compensation, and imposter convection

Numerical models of geothermal systems commonly capture only the top of a reservoir. Deeper areas of the reservoir are simplified to a boundary at the base of the model domain. Commonly, the basal boundary is given either a heat source or a source of mass and enthalpy. Here we developed and present simple numerical experiments which demonstrate that these approaches do not produce the correct model behavior in comparison to a model that captures the entire convecting domain with a heat flux only. We describe a variety of incorrect types of model behavior that arise directly from the choice of boundary condition, independent of the specific parameterization of the model. Heat sources are sensitive to the thickness of the domain and parameters take unphysical values to compensate for the reduced height. The combined mass/heat boundary can produce temperatures that show similarities to circulating geothermal systems, but with incorrect fluid flow and a strong boundary layer focused at the base of the simulated clay cap. These errors likely cause parameters to adjust their values to compensate for the incorrect physics. We highlight these issues and show an example from a developed reservoir model. Initial calibrations to natural state temperature were unsuitable for history matching. The 3D model required parameter adjustments to achieve a more realistic production model. Appropriate mitigation measures should be considered to reduce parameter compensation and improve decision-support models.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Coupling strongly correlated electron systems to a tunable electronic reservoir

Here, we study the effect of coupling an electronic reservoir to a Hubbard model and to a dimer Hubbard model. This is motivated by recent experiments on the effect of illumination on the insulator-metal transition in a vanadium oxides and photoconductive cadmium sulfide heterostructure. We model the system as an electronic reservoir hybridized to the correlated system. We assume that the light intensity controls the hybridization coupling strength. We find that the light intensity acts similarly as the temperature in the weak interaction regime. This is consistent with the role played by electronic reservoirs in out-of-equilibrium systems. In contrast, qualitative differences appear at strong coupling. We show that modeling the V 2 ⁢O 3 compound with a Hubbard model, our results describe qualitatively well the observed illumination-driven suppression of the insulator-metal transition. In contrast, in the DHM results fail to capture the mild suppression observed in the case of VO 2 . This indicates that the lattice may play an important role in this case.

Materials Science↗
DOE OSTI2021

Chromium Isotopic Evidence for Mixing of NC and CC Reservoirs in Polymict Ureilites: Implications for Dynamical Models of the Early Solar System

Nucleosynthetic isotope anomalies show that the first few million years of solar system history were characterized by two distinct cosmochemical reservoirs, CC (carbonaceous chondrites and related differentiated meteorites) and NC (the terrestrial planets and all other groups of chondrites and differentiated meteorites), widely interpreted to correspond to the outer and inner solar system, respectively. At some point, however, bulk CC and NC materials became mixed, and several dynamical models offer explanations for how and when this occurred. We use xenoliths of CC materials in polymict ureilite (NC) breccias to test the applicability of such models. Polymict ureilites represent regolith on ureilitic asteroids but contain carbonaceous chondrite-like xenoliths. We present the first 54 Cr isotope data for such clasts, which, combined with oxygen and hydrogen isotopes, show that they are unique CC materials that became mixed with NC materials in these breccias. It has been suggested that such xenoliths were implanted into ureilites by outer solar system bodies migrating into the inner solar system during the gaseous disk phase ~3–5 Myr after CAI, as in the "Grand Tack" model. However, combined textural, petrologic, and spectroscopic observations suggest that they were added to ureilitic regolith at ~50–60 Myr after CAI, along with ordinary, enstatite, and Rumuruti-type chondrites, as a result of the breakup of multiple parent bodies in the asteroid belt at this time. This is consistent with models for an early instability of the giant planets. The C-type asteroids from which the xenoliths were derived were already present in inner solar system orbits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Thermo-Hydrological Modeling of Thermal Energy Storage in a Depleted Oil Reservoir

Thermal energy storage in oil and gas reservoirs leverages the existing surface and subsurface infrastructure, which can pave the way for economic production of geothermal energy. Existing studies on geothermal energy storage are focused mostly on the use of aquifers with more homogeneous rock and fluid properties. Coupling of heat and fluid flow in a multiphase-multicomponent system, such as an oil reservoir, is imperative especially if existing oil field assets need to be repurposed as required for a sustainable energy transition. The objective is to model the subsurface thermo-hydrological processes associated with reservoir performance and operational sustainability. The model evaluates formation pressure and temperature within the reservoir and at the injection/production wells during multiple charge and discharge cycles. Hot water (approximately 200 degrees C) heated by Concentrating Solar Power (CSP) at high pressure is injected into the existing oil reservoir for storage and produced as thermal energy for power generation, which will be accompanied by enhanced oil recovery. To demonstrate the coupled fluid and heat flow during the injection/production cycle in the subsurface reservoir, TOUGH3 (developed by Berkeley Lab) is used to simulate the thermo-hydrological (TH) processes in a multiphase, multicomponent system. Two well geometries are considered within the reservoir grid: 1) a single-well huff-n-puff system (same well is used for injection and production), and 2) an isolated injection-production well doublet. Seasonal charge and discharge cycling are implemented based on the scheduling specified in the model input file. The model reports pressure, temperature, enthalpy, liquid fluxes, heat fluxes, pore velocities, and changes in porosity & permeability due to temperature and pressure variations during the cyclic Reservoir Thermal Energy Storage (RTES) operations. The results from the simulations can be used to optimize the operational parameters (such as well spacing and injection/production rates) and round-trip efficiency for surface power-plants coupled with thermal energy storage over time. They can also serve as important inputs for levelized cost of storage estimations. The research will help to design and integrate surface renewable energy sources, such as concentrating solar power (CSP), with RTES to help balance out power supply and demand on the grid.

CSP↗
DOE OSTI2024

Modeling Cost of Offshore Carbon Storage in Saline Reservoirs

Poster presentation to the AAPG-SEG-SPE CCUS 2024 Conference. Offshore saline reservoirs provide a significant and accessible resource for geologic carbon storage (CS). The offshore environment requires distinct approaches to site selection, operations, monitoring, and risk that affect the technoeconomic assessment of offshore CS projects. The National Energy Technology Laboratory (NETL) has developed a CS cost model for offshore saline reservoirs known as CO2_S_COM_Offshore. Based on NETL’s widely used CO2_S_COM cost model for onshore saline CS, CO2_S_COM_Offshore enables technoeconomic analysis of CS in offshore areas. This model comprehensively incorporates multiple facets of offshore CS projects, from regional evaluation and site selection to permitting, transport, operations, monitoring, site closure, and decommissioning. Developed to model cost for offshore United States (US) Exclusive Economic Zones, aspects of this model can be adapted to international projects. Presented at the SPE/AAPG/SEG Carbon Capture Utilization and Storage Conference in Houston, TX, March 11-13, 2024.

Mark-Moser, Mackenzie K.↗
DOE OSTI2020

Inferred inflow forecast horizons guiding reservoir release decisions across the United States

Abstract. Medium- to long-range forecasts often guide reservoir release decisions to support water management objectives, including mitigating flood and drought risks. While there is a burgeoning field of science targeted at improving forecast products and associated decision support models, data describing how and when forecasts are applied in practice remain undeveloped. This lack of knowledge may prevent hydrological modelers from developing accurate reservoir release schemes for large-scale, distributed hydrology models that are increasingly used to assess the vulnerabilities of large regions to hydrological stress. We address this issue by estimating seasonally varying, regulated inflow forecast horizons used in the operations of more than 300 dams throughout the conterminous United States (CONUS). For each dam, we take actual forward observed inflows (perfect foresight) as a proxy for forecasted flows available to the operator and then identify for each week of the year the forward horizon that best explains the release decisions taken. Resulting “horizon curves” specify for each dam the inferred inflow forecast horizon as a function of the week of the water year. These curves are analyzed for strength of evidence for contribution of medium- to long-range forecasts in decision making. We use random forest classification to estimate that approximately 80 % of large dams and reservoirs in the US (1553±50 out of 1927 dams with at least 10 Mm3 storage capacity) adopt medium- to long-range inflow forecasts to inform release decisions during at least part of the water year. Long-range forecast horizons (more than 6 weeks ahead) are detected in the operations of reservoirs located in high-elevation regions of the western US, where snowpack information likely guides the release. A simulation exercise conducted on four key western US reservoirs indicates that forecast-informed models of reservoir operations may outperform models that neglect the horizon curve – including during flood and drought conditions.

54 ENVIRONMENTAL SCIENCES↗