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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Feasibility of using distribute chemical sensing for CO2 leakage monitoring

The feasibility study focused on the development of new fiber for distributed chemical sensing (DCS) that will allow direct detection of CO 2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CSS), to provide early warning for an incoming well failure and potential CO 2 leaking through it. We proposed Raman or IR interrogation within gas-filled Holey Fibers (HoFs) interleaved with standard solid core fibers and Fiber Bragg Grating (FBG) sections, so that the location and concentration of the gases would be provided simultaneously by means of reflectometry. The methodology would overcome current roadblocks to using fiber optics for CO 2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure as the baseline of environment background.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Feasibility of using distributed chemical sensing for CO2 leakage monitoring

The feasibility study focused on the development of new fiber for distributed chemical sensing (DCS) that will allow direct detection of CO 2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CCS), to provide early warning for an incoming well failure and potential CO 2 leaking through it. We proposed using optical spectroscopy in optical fiber for direct detection of CO 2 . The main approach is based on Raman interrogation within gas-filled Holey Fibers (HoFs), so that the location and concentration of the gases would be provided simultaneously via backscattering. Additionally, Infrared (IR) Absorption Spectroscopy could also be used, and the architecture would be more discrete since interleaving with standard solid core fibers and Fiber Bragg Grating (FBG) sections is required to enable reflection to the I/O controls. The possible Raman length or the IR numbers of sections would be defined based on signal to noise ratio. The optical spectroscopy methodology would overcome current roadblocks to CCS, as fiber optics will allow for CO 2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure as the baseline of environment background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Seismic H2: Version 1.0

Seismic-H2 is an integrated software package for geological hydrogen reservoir simulation, optimization, and leakage monitoring. The package includes multiple components: (1) code used for modeling seismic wave propagation in 3D heterogeneous elastic media based on finite-difference method to support detection of geological hydrogen storage reservoir leakage; (2) 3D reservoir simulations of leaks from an underground reservoir and 3D simulations of saline aquifers and depleted gas reservoirs; (3) seismic monitoring costs of passive and active seismic monitoring required for UHS; (4) rock physics calculations and interpolations for converting the reservoir simulations from part (2) into the elastic media models in part (1); (5) pre-processing seismic data; and lastly (6), a GUI interface that combines these different components.

Creasy, Neala↗
DOE OSTI2026

The future of subsurface monitoring: AEC’s breakthroughs in CCS technology

Carbon capture and storage (CCS) has emerged as a key solution in the fight against climate change. However, for CCS to succeed, it is crucial to ensure that the sequestered CO2 stays safely trapped underground. The U.S. Department of Energy (DOE) has emphasized the need for advancements in subsurface monitoring, measurement, reporting, and verification. Aside from caprock integrity failure, the other primary failure points usually involve defective cement in the casing annulus of wellbores or plugged and abandoned wells. In addition, many energy producers (e.g., oil and gas, geothermal) and storage and disposal operators (e.g., H2 and water) must deal with the same issue. Poorly placed or degraded cement can create pathways for gas or fluid to escape from casing annuli and in plugged and abandoned or orphan wells, posing environmental risks. Yet, a reliable and cost-effective way to monitor cement and well integrity over multiple decades is still unavailable. Traditional geophysical methods like 4D seismic imaging and surface-based electromagnetic monitoring lack the resolution and accuracy for detecting these types of failures (Vasco et al., 2022; Fawad and Mondol, 2021). Wireline logging is expensive to run continuously and is obtrusive to the operation. While fiber optics can potentially be a solution, its bulkiness can significantly compromise the cement's integrity. To address these challenges, the Advanced Energy Consortium (AEC) at The University of Texas at Austin’s Bureau of Economic Geology (the Bureau) has been pioneering research in subsurface monitoring using its portfolio of distributed autonomous microfabricated sensors for harsh subsurface environments since 2008. A class of these microsensors [System on a Chip (SoC)] can be mixed in cement and permanently placed without compromising the cement column; the sensors would then communicate with each other or a data acquisition (DAQ) master node. Another class of the AEC microsensors can be fully autonomous, with rechargeable micro-batteries capable of exceeding 100°C, flash memory, and, currently, a pressure and temperature sensor. They are designed to circulate in mud, geothermal fluids, U-loops, or pipelines. They can log data into memory and are unobtrusive to operations. Our team has been working on a multi-year DOE-funded project (DE-FE0031856)—supported by $2.95M in federal funding and $0.75M in cost-matching from the AEC—to demonstrate SoC sensor utility for CO2 leakage monitoring in CCS applications. This multi-institutional collaboration developed a novel sensing architecture utilizing radiofrequency (RF) microsensors embedded within the cement sheath. These sensors detect CO2 migration and are interrogated via a Smart Casing Collar (SCC).

58 GEOSCIENCES↗
DOE OSTI2021

Calibration and field deployment of low-cost sensor network to monitor underground pipeline leakage

Recent technological advances in methane detection have improved leak detection and repair. However, current methods to reliably measure methane concentrations rely on expensive instruments or demand significant labor input. There is interest in using affordable methane sensors that are responsive to ppmv level changes in methane concentrations in both urban and rural environments for monitoring underground natural gas pipeline leaks. This is especially relevant for situations where potentially significant leaks cannot be repaired immediately or smaller leaks that require long-term monitoring and further evaluation. In this work, a low-cost sensor unit, equipped with a metal oxide sensor, was designed, built, and calibrated over a wide range of methane concentrations and environmental conditions in preparation for field application. A network of these sensors was then installed at the test site and used to measure methane concentrations at ground level above known sub-surface natural gas emissions which emulated underground gas pipeline leaks. This low-cost sensor network measured over 4 days total for the two different known leakage rates. Results demonstrate that the sensors can continuously measure relative methane variability for extended periods but require calibration for a wide range of temperature and humidity conditions to properly determine absolute gas (i.e., methane) concentrations. Furthermore, when a regression analysis was conducted to evaluate the effects of meteorological parameters on methane concentration, air temperature and wind speed have strong impacts on the concentration. Overall, the network approach allows improved identification of leak location and monitoring of underground natural gas leaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Monitoring of helium gas leakage from canister storing spent nuclear fuel: Radiological consequences and management

Chloride-induced stress corrosion cracking (CISCC) of canisters has been identified as a potential degradation mechanism requiring ageing management — especially in a marine air environment. Methods for monitoring helium gas leakage from canisters have been developed on the basis of a phenomenon that the bottom temperature of the canister increases as the top temperature of the canister decreases when helium gas leaks during storage. In this paper, we consider the radiological consequences of CISCC based on two scenarios of helium gas leakage and propose effective management that includes a timeline for monitoring and mitigation. Monitoring helium gas leakage by measuring the difference in temperature between canister surfaces in the dry cask storage of spent fuel (SF) can detect leakage before SF undergoes oxidation as a result of air ingress and before country-specific regulatory limits of off-site doses are exceeded, thereby enabling mitigatory action.

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

Quantification of CO 2 Mineralization at the Wallula Basalt Pilot Project

In 2013, the Pacific Northwest National Laboratory led a geologic carbon sequestration field demonstration where ~1000 tonnes of CO 2 was injected into several deep Columbia River Basalt zones near Wallula, Washington. Rock core samples extracted from the injection zone two years after CO 2 injection revealed nascent carbonate mineralization that was qualitatively consistent with expectations from laboratory experiments and reactive transport modeling. In this study, we report on a new detailed analysis of the 2012 pre-injection and 2015 post-injection hydrologic tests that capitalizes on the difference in fluid properties between scCO 2 and water to assess changes in near-field, wellbore, and reservoir conditions that are apparent approximately two years following the end of injection. This comparative hydrologic test analysis method provides a new way to quantify the amount of injected CO 2 that was mineralized in the field test. Modeling results indicate that approximately 60% of the injected CO 2 was sequestered via mineralization within two years, with the resulting carbonates occupying ~4% of the available reservoir pore space. The method presented here provides a new monitoring tool to assess the fate of CO 2 injected into chemically reactive basalt formations but could also be adapted for long-term monitoring and verification within more traditional subsurface carbon storage reservoirs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Induced microseismicity and tremor signatures illuminate different slip behaviours in a natural shale fault reactivated by a fluid pressure stimulation (Mont Terri)

SUMMARY Fault slip induced by fluid perturbation in shale formations may only lead to a sparse seismicity. However, fault slip may strongly impact the integrity of shale formations that serve as caprocks for geological reservoirs holding buoyant fluids such as CO2, natural gas or hydrogen. A better understanding of the fluid reactivation processes of fault and the seismic triggering process is therefore critical for reservoir monitoring and fault stability. Here we analyse the seismic responses of a shale fault exposed to fluid pressurization during an in situ field-scale injection experiment at ∼340 m depth in the Mont Terri underground research laboratory (Switzerland). Two main types of seismic signals are observed as the fault was activated and started to slowly slip. After an aseismic phase, we observed tremor signatures and an increase in noise amplitude, which were directly associated with the slowly propagating fault slip in response to fluid injection. These signatures were later followed by micro-earthquakes that seem to occur further away from the fluid-pressurized area. We interpret these micro-earthquakes to be triggered by stress perturbations from the main slip growth. These two classes of seismic responses therefore highlight two different processes. Tremors seem to be a more direct observation for the fluid-induced slip propagation than micro-earthquakes. Even hidden in the noise, they precede earthquake failures, thus providing a useful tool for monitoring fluid leakage activated by slow deformation on low permeable shale faults, with applications for sealing integrity of caprocks.

De Barros, Louis (ORCID:0000000255419162)↗
DOE OSTI2022

Radiation testing of 2.4 micron wavelength extended InGaAs photodiodes for 100 MeV/n carbon ions

We have successfully tested simultaneously 2.4 Micron Wavelength, Extended InGaAs Photodiodes having diameters of 20, 30, 40, 50, 100, 150, 200, 250, and 290 Micron, coupled with a Single Mode Fiber using 100 MeV/n Carbon (C) Ions up to a cumulative dose of ~40 krad. During irradiation, the devices were maintained at dry ice temperature, reverse biased at 100 mV, and their leakage current was continuously monitored in-situ during the run. After the exposure was completed, all nine devices were monitored for any change in their leakage current at 100 mV and room temperature for several weeks to monitor any annealing effects that may occur. Nine Photodiodes with the above varying diameters were radiated with 100 MeV/n Carbon Ions with a fluence of 10 6 , 10 7 , 10 8 , 10 9 , and 10 10 ions/cm 2 at each fluence level. At 100 MeV/n the Linear Energy Transfer (LET) of Carbon Ion is ~0.156 MeV-cm 2 /mg in Extended InGaAs, which is an order magnitude more than Proton (H) and Helium (He) Ions of 100 MeV/n energy. Thus, significant displacement damage is anticipated in the Extended InGaAs Photodiode with 100 MeV/n Carbon Ions with a total fluence of 1 × 1010 ions/cm 2 . Pre- and Post- radiation results were also measured for: (1) Leakage Current Vs. Voltage for the Extended InGaAs Photodiodes; (2) Responsivity (Quantum Efficiency) in A/W for Photodiodes; and (3) Bandwidth of the Photodiodes. All devices were found to be fully functional at the normal operating conditions and at both dry ice and room temperature. The leakage current increased up to a factor of ~2X at lower bias of 100 mV at the highest fluence of 10 10 ions/cm 2 , but not significantly at higher bias of 2 V. Finally, we did not observe any post radiation annealing effect for leakage current at room temperature and 100 mV bias for any of the devices after several weeks of data logging.

2.4 micron wavelength↗
DOE OSTI2021

Kimberlina 1.2 Velocity Models and Seismic Data

Kimberlina 1.2 Velocity model and synthetic seismic data, produced in collaboration of teams at the National Energy Technology Laboratory, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory through the National Risk Assessment Partnership. Data is associated with the following publication: Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019. The Kimberlina 1.2 Velocity models were produced by Zan Wang, Robert Dilmore, William Harbert, and Lianjie Huang at NETL. The following citations are directly related to the creation of the velocity models: Wang, Z. Harbert, W., Dilmore, R., Huang, L. Modeling of time-lapse seismic monitoring using CO2 leakage simulations for a model CO2 storage site with realistic geology: Application in assessment of early leak-detection capabilities. International Journal of Greenhouse Gas Control. V. 76, September 2018, Pages 39-52. https://doi.org/10.1016/j.ijggc.2018.06.011 Wang, Z., Dilmore, R., Harbert, W. Inferring CO2 saturation from synthetic surface seismic and downhole monitoring data using machine learning for leakage detection at CO2 sequestration sites. International Journal of Greenhouse Gas Control, V. 100, September 2020. https://doi.org/10.1016/j.ijggc.2020.103115 The velocity models were built based on the Kimberlina 1.2 aquifer impact data which is associated with the following publications: Buscheck, T.A., Mansoor, K., Yang, X., Wainwright, H., and Carroll, S. (2019). Downhole pressure and chemical monitoring for CO2 and brine leak detection in aquifers above a CO2 storage reservoir. International Journal of Greenhouse Gas Control. 91. 102812. 10.1016/j.ijggc.2019.102812. Xianjin Yang, Thomas A. Buscheck, Kayyum Mansoor, Zan Wang, Kai Gao, Lianjie Huang, Delphine Appriou, Susan A. Carroll, Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, Volume 90, 2019, 102803, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2019.102803 The synthetic seismic data was produced by Youzuo Lin and team at LANL, and are associated with the following citations: Jordan, P. D., and J. L. Wagoner. Characterizing Construction of Existing Wells to a CO2 Storage Target: The Kimberlina Site, California. Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019.

CO2 Leakage↗
DOE OSTI2022

NRAP Recommended Practices for Containment Assurance and Leakage Risk Quantification

This report presents recommendations for quantitatively assessing and managing leakage risk and effective containment assurance at geologic carbon storage (GCS) sites, amidst uncertainty in site characteristics and performance. These recommended practices are a product of the U.S. Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management’s National Risk Assessment Partnership (NRAP)—a multi-year collaborative research effort of Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, National Energy Technology Laboratory, and Pacific Northwest National Laboratory. These recommended practices are organized as a set of conceptual workflows that correspond with the stages of the GCS project lifecycle. They consider aspects of site characterization, quantification of potential leakage, assessing the spatial extent of potential environmental impacts, optimizing monitoring design for detection of potential leakage, evaluation of concordance between monitored and forecasted reservoir response, assessing conformance with expected/accepted performance, and determination of the timeline over which risk of impactful leakage can be expected to abate. These conceptual workflows are intended to aid stakeholders in making risk management decisions at GCS sites and to support development of sound, risk-based justifications for characterizing the subsurface, defining area of potential leakage impact, designing site monitoring plans, selecting leakage risk management/mitigation alternatives, and estimating site closure timelines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Physics-informed machine learning for fault-leakage reduced-order modeling

Geologic carbon storage (GCS) is a promising technology for mitigating CO 2 emissions. The overall success of GCS depends on safe operations that are informed by risk assessment and have proper mitigation plans in place. Performing quantitative probabilistic risk assessment for a GCS site using traditional reservoir simulators can be challenging due to the high computational costs. To overcome this challenge, the US Department of Energy’s National Risk Assessment Partnership (NRAP) project has developed an integrated assessment modeling approach that utilizes computationally efficient reduced-order models (ROM) for simulating various parts of a GCS storage site to quantify uncertainty. Here, in this study, we develop a reduced-order model for fault leakage risk assessment. We use a deep learning approach to build the reduced-order model. We perform a sensitivity analysis and find that the deep learning model yields high accuracy with a much smaller computational cost than full-physics simulation. We also evaluate the performance of the model in scenarios where simulations are not possible to run, providing analysis not previously performed in fault-leakage ROM analyses. Based on a sensitivity analysis of the model, we suggest a simplified conceptual model for fault leakage and site monitoring.

58 GEOSCIENCES↗