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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluation of geophysical and anthropogenic sources of hydroacoustic noise in the Alaskan arctic

Quantifying the ocean soundscape is crucial for ocean-based seismoacoustic monitoring; it sets a baseline for the kinds and sizes of signals that can be detected above the background noise. As sea ice recedes, human activity in and around the Arctic Ocean is increasing, elevating sound levels and heightening the urgency of monitoring. Here, seven years of passive acoustic recordings from a National Oceanographic and Atmospheric Administration hydrophone in the Beaufort Sea are analyzed, focusing on frequencies between 1 and 125 Hz, a band of interest for detecting regional earthquakes and similar events. Sound is related to geophysical and anthropogenic sources, and seasonal and intraseasonal variations in the soundscape are examined. Sea ice emerges as a keystone feature of the Arctic Ocean acoustic environment, controlling or contributing to ambient sound levels at all frequencies studied. During low-ice months, sound levels are dominated by wind and sea surface waves, and in ice-covered months, wind-driven ice noise dominates. Seismic air gun surveys are prominent during low-ice periods, with sound levels decreasing with increasing distance and bathymetric complexity along the propagation path. The implications of this baseline soundscape for event detection in the Alaskan Arctic are discussed.

Niklasson, Siobhan [Los Alamos National Laboratory↗
DOE OSTI2022

Near-surface seismic anisotropy in Antarctic glacial snow and ice revealed by high-frequency ambient noise

Ambient seismic recordings taken at broad locations across Ross Ice Shelf and a dense array near West Antarctic Ice Sheet (WAIS) Divide, Antarctica, show pervasive temporally variable resonance peaks associated with trapped seismic waves in near-surface firn layers. These resonance peaks feature splitting on the horizontal components, here interpreted as frequency-dependent anisotropy in the firn and underlying ice due to several overlapping mechanisms driven by ice flow. Frequency peak splitting magnitudes and fast/slow axes were systematically estimated at single stations using a novel algorithm and compared with good agreement with active source anisotropy measurements at WAIS Divide determined via active sources recorded on a 1 km circular array. The approach was further applied to the broad Ross Ice Shelf (RIS) array, where anisotropy axes were directly compared with visible surface features and ice shelf flow lines. The near-surface firn, depicted by anisotropy above 30 Hz, was shown to exhibit a novel plastic stretching mechanism of anisotropy, whereby the fast direction in snow aligns with accelerating ice shelf flow.

58 GEOSCIENCES↗
DOE OSTI2022

MAGIS-100 environmental characterization and noise analysis

We investigate and analyze site specific systematics for the MAGIS-100 atomic interferometry experiment at Fermi National Accelerator Laboratory. As atom interferometers move out of the laboratory environment passive and active mitigation for noise sources must be implemented. To inform the research and development of the experiment design, we measure ambient temperature, humidity, and vibrations of the installation site. We find that temperature fluctuations will necessitate enclosures for critical subsystems and a temperature controlled laser room for the laser system. We also measure and analyze the vibration spectrum above and below ground for the installation site. The seismic vibration effect of gravity gradient noise is also modeled using input from a low-noise seismometer at multiple locations and a mitigation scheme is studied using a stochastic simulation and characterized by a suppression factor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1976

Apollo 14 and 16 Active Seismic Experiments, and Apollo 17 Lunar Seismic Profiling

Seismic refraction experiments were conducted on the moon by Apollo astronauts during missions 14, 16, and 17. Seismic velocities of 104, 108, 92, 114 and 100 m/sec were inferred for the lunar regolith at the Apollo 12, 14, 15, 16, and 17 landing sites, respectively. These data indicate that fragmentation and comminution caused by meteoroid impacts has produced a layer of remarkably uniform seismic properties moonwide. Brecciation and high porosity are the probable causes of the very low velocities observed in the lunar regolith. Apollo 17 seismic data revealed that the seismic velocity increases very rapidly with depth to 4.7 km/sec at a depth of 1.4 km. Such a large velocity change is suggestive of compositional and textural changes and is compatible with a model of fractured basaltic flows overlying anorthositic breccias. 'Thermal' moonquakes were also detected at the Apollo 17 site, becoming increasingly frequent after sunrise and reaching a maximum at sunset. The source of these quakes could possibly be landsliding.

Source record↗
NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗
DOE OSTI2020

High-pressure elastic properties of dolomite melt supporting carbonate-induced melting in deep upper mantle

Deeply subducted carbonates likely cause low-degree melting of the upper mantle and thus play an important role in the deep carbon cycle. However, direct seismic detection of carbonate-induced partial melts in the Earth’s interior is hindered by our poor knowledge on the elastic properties of carbonate melts. Here we report the first experimentally determined sound velocity and density data on dolomite melt up to 5.9 GPa and 2046 K by in-situ ultrasonic and sink-float techniques, respectively, as well as first-principles molecular dynamics simulations of dolomite melt up to 16 GPa and 3000 K. Using our new elasticity data, the calculated V P /V S ratio of the deep upper mantle (~180–330 km) with a small amount of carbonate-rich melt provides a natural explanation for the elevated V P /V S ratio of the upper mantle from global seismic observations, supporting the pervasive presence of a low-degree carbonate-rich partial melt (~0.05%) that is consistent with the volatile-induced or redox-regulated initial melting in the upper mantle as argued by petrologic studies. This carbonate-rich partial melt region implies a global average carbon (C) concentration of 80–140 ppm. by weight in the deep upper mantle source region, consistent with the mantle carbon content determined from geochemical studies.

58 GEOSCIENCES↗
DOE OSTI2023

Economic and operational investigation of CO 2 sequestration through enhanced oil recovery in unconventional reservoirs in Colorado, USA

The ongoing CCUS commercial projects are highly relied on the support of government incentives due to massive capital investment. Here, this study analyzes the economics of carbon capture utilization and sequestration (CCUS) projects, shows a state-wide CCUS deployment exercise, followed by simulation results of enhanced oil recovery (EOR) based CO 2 storage in unconventional reservoirs. The comprehensive economic analysis of capture, transportation, sequestration costs, enhanced 45Q tax credits, and EOR revenue implies the practicality of CO 2 -EOR to offset the high CCUS costs. With the economics understanding, we study the top CO 2 sources, existing CO 2 pipelines, and sequestration sinks in the state of Colorado, USA. This paper next presents results from EOR simulation in one section of the unconventional Denver-Julesburg (DJ) Basin Niobrara and Codell reservoirs. The simulation model is based on a geological static model, incorporated with hydraulic fracture stimulation, history matched to production, and calibrated to the microseismic and time-lapse surface seismic data. The CO 2 -EOR simulation results show that oil production can be increased and more CO 2 stored with: a longer primary production period; the presence of a shut-in period; higher injection rates; and multi-well injectors. The modeling results show that about 7–10 Mscf of CO 2 will be stored when recovering 1 stb of EOR oil. By adding the enhanced oil revenue and the carbon credits together, it is estimated that the most economic case can generate $\$13$ MM when oil price is assumed to be $\$80$/stb, and the EOR oil revenue is 3.4 times greater than that generated from 45Q incentives. It corresponds to the scenario that a five-year primary production is followed by CO 2 injection into four wells with the sequence of injection (4 MMscf/day for 6 months), shut-in (6 months) and production (12 months). The best practices in this study will provide valuable insights for similar CCUS projects in other unconventional fields. Furthermore, this study defines a term named “Carbon Neutrality Index (CNI)” by comparing the amount of CO 2 stored with that burned by EOR oil. The CNI value of 0 indicates the enhanced oil is carbon neutral; a negative CNI value implies there is a net reduction in carbon emission. The 4-year huff-n-puff (HnP) simulation leads to a positive CNI value, indicating that the EOR oil generated in this process is not carbon neutral yet.

03 NATURAL GAS↗
DOE OSTI2020

Analysis of Fault Zone Resonance Modes Recorded by a Dense Seismic Array Across the San Jacinto Fault Zone at Blackburn Saddle

We present observations and modeling of spatial eigen-functions of resonating waves within fault zone waveguide, using data recorded on a dense seismic array across the San Jacinto Fault Zone (SJFZ) in southern California. The array consists of 5-Hz geophones that cross the SJFZ with ~10-30 m spacing at the Blackburn Saddle near the Hemet Stepover. Wavefield snapshots after the S wave arrival are consistent for more than 50 near-fault events, suggesting that this pattern is controlled by the fault zone structure rather than source properties. Data from example event with high signal to noise ratio shows three main frequency peaks at ~1.3 Hz, ~2.0 Hz, and ~2.8 Hz in the amplitude spectra of resonance waves averaged over stations near the fault. The data are modeled with analytical expressions for eigen-functions of resonance waves in a low-velocity layer (fault zone) between two quarter-spaces. Using a grid search-based method, we investigate the possible width of the waveguide, location within the array, and shear wave velocities of the media that fit well the resonance signal at ~1.3 Hz. The results indicate a ~300 m wide damaged fault zone layer with ~65% S wave velocity reduction compared to the host rock. The SW edge of the low-velocity zone is near the mapped fault surface trace, indicating that the damage zone is asymmetrically located at the regionally faster NE crustal block. The imaging resolution of the fault zone structure can be improved by modeling fault zone resonance modes and trapped waves together.

58 GEOSCIENCES↗
DOE OSTI2020

The Value of Information From Horizontal Distributed Acoustic Sensing Compared to Multicomponent Geophones Via Machine Learning

Abstract Faults play an important role in recharging many geothermal reservoirs, and seismic information can image the locations of these faults. The value of information (VOI) metric is used to objectively quantify and compare the value of two types of seismic receiver data via a machine learning approach. The demonstrated VOI methodology is novel by including spatial models from seismic data and obtaining the information statistics from machine learning. Our two-dimensional numerical experiments compare images created from sparsely spaced (80 m), two-component geophone sampling to high spatial resolution (1 m), single-component DAS. We used a three-fold cross validation of a U-Net convolutional neural networks to achieve average classification statistics. The results suggest that when horizontal sources are utilized, geophones and DAS identify reflectors and non-reflectors at roughly the same rate. The average F1 score for horizontal DAS is 0.939 and 0.931 for geophones. For images created from a vertical source, DAS performed marginally better (F1 = 0.919) than geophones (F1 = 0.877). Our transferrable methodology can provide guidance on which acquisition scenarios can improve images of important structures in the subsurface and present an efficient method for obtaining reliability statistics from high-dimensional, spatial data.

Energy & Fuels↗
DOE OSTI2025

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗
DOE OSTI2023

A Fusion of Geothermal and InSAR Data with Machine Learning for Enhanced Deformation Forecasting at the Geysers

The Geysers geothermal field in California is experiencing land subsidence due to the seismic and geothermal activities taking place. This poses a risk not only to the underlying infrastructure but also to the groundwater level which would reduce the water availability for the local community. Because of this, it is crucial to monitor and assess the surface deformation occurring and adjust geothermal operations accordingly. In this study, we examine the correlation between the geothermal injection and production rates as well as the seismic activity in the area, and we show the high correlation between the injection rate and the number of earthquakes. This motivates the use of this data in a machine learning model that would predict future deformation maps. First, we build a model that uses interferometric synthetic aperture radar (InSAR) images that have been processed and turned into a deformation time series using LiCSBAS, an open-source InSAR time series package, and evaluate the performance against a linear baseline model. The model includes both convolutional neural network (CNN) layers as well as long short-term memory (LSTM) layers and is able to improve upon the baseline model based on a mean squared error metric. Then, after getting preprocessed, we incorporate the geothermal data by adding them as additional inputs to the model. This new model was able to outperform both the baseline and the previous version of the model that uses only InSAR data, motivating the use of machine learning models as well as geothermal data in assessing and predicting future deformation at The Geysers as part of hazard mitigation models which would then be used as fundamental tools for informed decision making when it comes to adjusting geothermal operations.

Yazbeck, Joe (ORCID:0000000302235260)↗
DOE OSTI2022

On various mechanisms of shear wave generation from underground chemical explosions in hard rocks

Significant shear waves observed during underground explosions can make them look similar to natural earthquakes. In the near field, they can be caused by the source geometry and emplacement conditions, heterogeneous and anisotropic properties of the rock mass, relaxation of a non-uniform in situ stress around the source after the departure of the shock wave as well as by activation of nearby faults. Here, the stress relaxation mechanism is important at depth when the difference in main principal stresses becomes significant. Another mechanism of shear motion generation is due to explosive gas flow from the source cavity into the cracks initiated by the shock wave and joints connected to the cavity. Also, the shock wave from the explosion can cause weakening of the rock either due to permanent damage or shock-induced liquefaction at saturated joints. Numerical modelling of underground chemical explosions in hard rock at various confinement stresses has been conducted to compare various mechanisms of shear wave generation and their seismic characteristics with that of a simple fault rupture process observed during an earthquake.

58 GEOSCIENCES↗
DOE OSTI2020

Probing Slow Earthquakes With Deep Learning

Abstract Slow earthquakes may trigger failure on neighboring locked faults that are stressed sufficiently to break, and slow slip patterns may evolve before a nearby great earthquake. However, even in the clearest cases such as Cascadia, slow earthquakes and associated tremor have only been observed in intermittent and discrete bursts. By training a convolutional neural network to detect known tremor on a single seismic station in Cascadia, we isolate and identify tremor and slip preceding and following known larger slow events. The deep neural network can be used for the detection of quasi‐continuous tremor, providing a proxy that quantifies the slow slip rate. Furthermore, the model trained in Cascadia recognizes tremor in other subduction zones and also along the San Andreas Fault at Parkfield, suggesting a universality of waveform characteristics and source processes, as posited from experiments and theory.

58 GEOSCIENCES↗
NASA NTRS1990

Preliminary analysis of measured sound propagation over various seasonal snow covers

Measurements of acoustic pulse propagation in the 5 to 500-Hz frequency band were conducted under various snow cover conditions during the 1989 to 1990 winter in New Hampshire. The objective was to determine the effect of snow cover thickness and other snow properties on the absorption of acoustic pulses. Blank pistol shots were used as the source of the acoustic waves, and geophones and microphones in an 80 m-long linear array served as receivers. Snow thicknesses ranged from 0.05 to 0.35 m, and densities varied from 100 to 350 kg m(sup -3) during the 10 separate measurement days. Preliminary analysis indicates that the peak pulse amplitude decayed in proportion to approx. gamma (sup -1.7) for most conditions and that the acoustic-to-seismic ratios varied from about 4 to 15 x 10(exp -6) m s(sup -1) Pa(sup -1). Theoretical waveforms were calculated for propagation in a homogeneous atmosphere using Attenborough's model of ground impedance. An automatic fitting procedure for the normalized experimental and theoretical waveforms was used to determine the effective flow resistivity of the snow covers, and gave values of 10 to 35 kN s m(sup -4), in agreement with earlier results.

Albert, Donald G.↗
DOE OSTI2024

Seismic Resilience of Large Power Transformer Bushings & Non-SF6 Industrial Base Scan Review

Large (high voltage) power transformers (LPT), and more specifically, their bushings, are known to be susceptible to seismic failure. With bushing failure, a transformer will have to be replaced, which has a considerable lead time, adding to the power outage duration. Cost-efficient, proven solutions are not currently available to mitigate this risk, which can persist for the more than 30-year life of a particular transformer. This work will focus on developing and demonstrating a hardware solution to address seismic vulnerabilities and reduce outage risks from LPT failure. Sulfur Hexafluoride (SF6) is a specialty gas with excellent electrical insulation properties which has been used extensively in the power industry. This gas is unfortunately also one of the most potent greenhouse gases known to humanity. A 2014 report by the Intergovernmental Panel on Climate Change found that SF6 has a global warming potential (GWP) 23,000 times higher than Carbon Dioxide, and has the highest GWP of all gases assessed (Myhre 2013). SF6 is almost exclusively man-made and is produced for use as an insulator in high voltage electrical equipment. This makes the production and use of SF6 one of the leading sources of anthropogenic climate change. To fully eliminate the environmental impacts of SF6, alternative technology is needed. The ideal replacement would be a technology that can fulfil the same role as SF6, at the same cost or cheaper, but without adverse environmental effects. Currently, no technology fits this description, however several promising technologies have begun to enter the market. An industry scan was performed to assess the state of industry adoption and manufacturing capability for SF6-free alternative technologies for use at the high-voltage level, and the primary barriers to broader adoption.

10 SYNTHETIC FUELS↗
NASA NTRS1998

Ionospheric Signature of Surface Mine Blasts from Global Positioning System Measurements

Sources such as atmospheric or buried explosions and shallow earthquakes are known to produce infrasonic pressure waves in the atmosphere. Because of the coupling between neutral particles and electrons at ionospheric altitudes, these acoustic and gravity waves induce variations of the ionospheric electron density. The Global Positioning System (GPS) provides a way of directly measuring the total electron content in the ionosphere and, therefore, of detecting such perturbations in the upper atmosphere. In July and August 1996, three large surface mine blasts (1.5 Kt each) were detonated at the Black Thunder coal mine in eastern Wyoming. As part of a seismic and acoustic monitoring- experiment, we deployed five dual-frequency GPS receivers at distances ranging from 50 to 200 km from the mine and were able to detect the ionospheric perturbation caused by the blasts. The perturbation starts 10 to 15 min after the blast, lasts for about 30 min, and propagates with an apparent horizontal velocity of 1200 meters per second. Its amplitude reaches 3 x 10 (exp 14) el per square meters in the 7-3 min period band, a value close to the ionospheric perturbation caused by the M = 6.7 Northridge earthquake. The small signal-to-noise ratio of the perturbation can be improved by slant-stacking the electron content time-series recorded by the different GPS receivers taking into account the horizontal propagation of the perturbation. The energy of the perturbation is concentrated in the 200 to 300 second period band, a result consistent with previous observations and numerical model predictions. The 300 second band probably corresponds to gravity modes and shorter periods to acoustic modes, respectively. Using a 1-D stratified velocity model of the atmosphere we show that linear acoustic ray tracing fits arrival times at all GPS receivers. We interpret the perturbation as a direct acoustic wave caused by the explosion itself. This study shows that even relatively small subsurface events can produce ionospheric perturbations that are above the detection threshold of the GPS technique. By sensing derivative signals, which can be detected over a relatively broad region, it appears that GPS might be particularly useful for source characterization within the first acoustic quiet zone where infrasound would probably be ineffective. This suggests that dual-frequency GPS monitoring could contribute to Comprehensive Nuclear Test Ban Treaty verification.

Calais, Eric↗
DOE OSTI2020

Beirut Explosion Yield and Mushroom Cloud Height - Effects of the Source Environment

I use crater dimensions to estimate the yield of the August 4th, 2020 Beirut explosion to be equivalent to approximately 1.4 kilotons of TNT with a lower bound of about 0.7 kilotons. Based on the amount of ammonium nitrate reported to have been stored at the Beirut harbor, I assume an upper bound for the yield of 2.75 kilotons. However, it is highly likely that the yield was less than 2.75 kilotons, since reported values for TNT equivalence of ammonium nitrate are typically much less than one hundred percent. The crater-size based yield estimates are based on crater radius estimates from satellite imagery and empirical curves and data for scaled crater radius from past chemical and nuclear explosions. I present evidence that suggests that the relatively large crater radius is due to a high degree of coupling of shock wave energy to the surrounding medium and a reduction of the effective stress because of a high level of saturation of the geologic media beneath the explosion. I provide yield estimates based on seismic body-wave magnitude and crater depth as corroborating evidence. I compare preliminary estimates for the maximum debris cloud height, based on cell phone videos/images, with predicted maximum heights for this yield range from empirical formulas and numerical cloud-rise models. Based on a preliminary analysis of cell phone footage, the observed maximum cloud height appears to be approximately 1600 m. This is much lower than that predicted using standard empirical formulas and buoyant cloud rise models. I present results from a modified buoyant cloud rise model that more accurately predicts the maximum cloud height by allowing for the inclusion of a fixed amount of air and/or water into the fireball at the start of cloud rise. The amount of mass that needs to be added at the start, to reproduce the observed maximum cloud height, is relatively small compared to the total mass entrained during cloud rise. A much greater amount of dry air or debris is required, relative to water, for an equivalent reduction in maximum cloud height. The ammonium nitrate is one possible source for water in the fireball since it was being stored in a very humid environment and ammonium nitrate is known to be hygroscopic. The ground beneath the explosion, especially if it were saturated, and the nearby harbor could also have been sources for water or debris in the fireball.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Tidally Modulated Glacial Slip and Tremor at Helheim Glacier, Greenland

Numerical modeling of ice sheet motion and hence projections of global sea level rise require information about the evolving subglacial environment, which unfortunately remains largely unknown due to its difficulty of access. Here we advance such subglacial observations by reporting multi–year observations of seismic tremor likely associated with glacier sliding at Helheim Glacier. This association is confirmed by correlation analysis between tremor power and multiple environmental forcings on different timescales. Variations of the observed tremor power indicate that different factors affect glacial sliding on different timescales. Effective pressure may control glacial sliding on long (seasonal/annual) timescales, while tidal forcing modulates the sliding rate and tremor power on short (hourly/daily) timescales. Polarization results suggest that the tremor source comes from an upstream subglacial ridge. This observation provides insights on how different factors should be included in ice sheet modeling and how their timescales of variability play an essential role.

54 ENVIRONMENTAL SCIENCES↗