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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars

Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.

Geochemistry & Geophysics↗
DOE OSTI2024

Seismic Monitoring near Ithaca, New York, Reveals Nonuniform Distribution of Microseismicity in an Intraplate Region

Abstract Cornell University intends to use a deep direct-use geothermal system to heat its Ithaca, New York, campus. In preparation for this project, the Cornell Seismic Network has been monitoring the background seismicity in this intraplate region since 2019. From January 2020 to June 2023, 95 events were detected within 20 km of the proposed geothermal well site, with local magnitudes ranging from −1.02 to 0.56. None of these events appear in regional or national catalogs. Events locate in a narrow geographic band, with one-fourth exhibiting multimodal hypocentral probability peaks both near the surface and at 1–4 km depth. We relocate events with a joint hypocenter and 1D velocity model inversion, in addition to a fully nonlinear method, and then compare observations with synthetic waveforms. Together, these approaches provide strong evidence for >95% of events locating at the surface or within the 3-km-thick sedimentary sequence. We explore how anthropogenic activity and regional topographic stress may contribute to frequent surficial events. This information is critical for characterizing the background microseismicity for comparison during future geothermal operations. Ithaca’s geology of Paleozoic sediments overlying Precambrian crystalline basement is typical of many continental interiors, so these results also provide insight into intraplate microseismicity patterns.

Geochemistry & Geophysics↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗
DOE OSTI2025

Array-Based Seismic Measurements of OSIRIS-REx’s Re-Entry

The return home of the OSIRIS-REx spacecraft in September 2023 marked only the fifth time that an artificial object entered the Earth’s atmosphere at interplanetary velocities. Although rare, such events serve as valuable analogs for natural meteoroid re-entries; enabling study of hypersonic dynamics, shock wave generation, and acoustic-to-seismic coupling. Here, in this study, we report on the signatures recorded by a dense (100 m scale) 11-station array located almost directly underneath the capsule’s point of peak atmospheric heating in northern Nevada. Seismic data are presented, which allow inferences to be made about the shape of the shock wave’s footprint on the surface, the capsule’s trajectory, and its flight parameters.

58 GEOSCIENCES↗
DOE OSTI2026

Variability in Performance of a Machine Learning Seismicity Catalog: Central Italy, 2016–2017

Machine learning (ML) catalogs contain many more earthquakes than routine catalogs, but their performance in phase picking and earthquake detection has not been fully evaluated. We develop station‐level detection probabilities using logistic regression and combine them across a seismic network to compute spatial magnitude‐of‐completeness fields. We apply this approach to two catalogs from the 2016–2017 Central Italy sequence that were constructed from the same seismic network, one routine and one ML‐based. At the station level, the ML picker increases detection sensitivity by identifying smaller magnitude events and detecting earthquakes at greater distances. Spatially, the magnitude of completeness decreases substantially, with median values shifting from 1.6 to 0.5 for P waves and from 1.7 to 0.5 for S waves. However, the ML catalog also shows greater variability in station‐level performance than the routine catalog. These results demonstrate that ML‐based improvements in detectability are widespread but spatially nonuniform, highlighting their benefits, their limitations, and the potential for further improvements.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Multi-Event Explosive Seismic Source for the 2022 M w 6.3 Hunga Tonga Submarine Volcanic Eruption

The eruption of the Hunga Tonga–Hunga Ha’apai submarine volcano on 15 January 2022 produced a variety of geophysical responses, including a significant seismic signal. We study the seismic source process of this event by inverting for moment tensors (MTs) using regional surface waves (Rayleigh, Love). By comparing inversion results for the eruption with eight nearby earthquakes, we show that it is possible to discriminate MT source types. Our inversion yields a shallow explosive source for the eruption and reveals the importance of trade-offs among depth, magnitude, and source type. We illustrate these trade-offs by representing the misfit variations over the eigenvalue lune. Finally, we invert for the source-time function of the sequence of explosions that occurred in the first minutes of the eruption. The multi-event source-time function comprises four subevents spanning ~270 s, with a total magnitude estimate of M w 6.34 ± 0.10.

58 GEOSCIENCES↗
DOE OSTI2017

Streamline-Based Time-Lapse-Seismic-Data Integration Incorporating Pressure and Saturation Effects

In this paper, we present an efficient history-matching technique that simultaneously integrates 4D repeat seismic surveys with well-production data. This approach is particularly well-suited for the calibration of the reservoir properties of high-resolution geologic models because the seismic data are a really dense but sparse in time, whereas the production data are finely sampled in time but spatially averaged. The joint history matching is performed by use of streamline-based sensitivities derived from either finite-difference or streamline-based flow simulation. For the most part, earlier approaches have focused on the role of saturation changes, but the effects of pressure have largely been ignored. Here, we present a streamline-based semianalytic approach for computing model-parameter sensitivities, accounting for both pressure and saturation effects. The novelty of the method lies in the semianalytic sensitivity computations, making it computationally efficient for high-resolution geologic models. The approach is implemented by use of a finite-difference simulator incorporating the detailed physics. Its efficacy is demonstrated by use of both synthetic and field applications. Lastly, for both the synthetic and the field cases, the advantages of incorporating the time-lapse variations are clear, seen through the improved estimation of the permeability distribution, the pressure profile, the evolution of the fluid saturation, and the swept volumes.

58 GEOSCIENCES↗
DOE OSTI2023

New Insights from Legacy Seismic Data regarding Basalt Elevations and Variability on the Hanford Site

Migration of groundwater contaminants in the Gable Gap area of the Hanford Site in southeastern Washington State is strongly influenced by the distribution and permeability of basalts that lie beneath an unconfined aquifer. Locally, folding and faulting of the Columbia River Basalt associated with the Yakima fold and thrust belt followed by erosion due to the Lake Missoula floods resulted in a complex basalt surface that represents either an impermeable lower boundary to the unconfined aquifer system or localized regions of increased permeability that potentially promote communication between the unconfined aquifer system and deeper, confined aquifer systems. Paleo-channels carved into the basalt by floodwaters are thought to provide preferential flow paths for groundwater contaminants. In 2011, a seismic landstreamer campaign was carried out to image the basalt surface and produced pre-stack depth migrated p-wave reflection images. The reflection images identified two large troughs that may represent paleo-channels and several areas of possible faulting. Here, the streamer data are re-analyzed using refraction travel-time and Rayleigh wave dispersion analyses to obtain images of compressional and shear wave velocities within the suprabasalt sediment sections and the upper basalt surface. The combined interpretation of reflection and seismic velocity images shows complexity in the basalt velocity and elevation, which varies by 50 m or more within the study area. These results, along with other ongoing geophysical investigations, will be used to inform the site geologic model and potentially guide placement of future boreholes needed to quantify vertical flow between the confined and unconfined aquifers.

58 GEOSCIENCES↗
DOE OSTI2013

Seismic Soil-Structure Interaction Analyses of a Deeply Embedded Model Reactor – SASSI Analyses

This report summarizes the SASSI analyses of a deeply embedded reactor model performed by BNL and CJC and Associates, as part of the seismic soil-structure interaction (SSI) simulation capability project for the NEAMS (Nuclear Energy Advanced Modeling and Simulation) Program of the Department of Energy. The SASSI analyses included three cases: 0.2 g, 0.5 g, and 0.9g, all of which refer to nominal peak accelerations at the top of the bedrock. The analyses utilized the modified subtraction method (MSM) for performing the seismic SSI evaluations. Each case consisted of two analyses: input motion in one horizontal direction (X) and input motion in the vertical direction (Z), both of which utilized the same in-column input motion. Besides providing SASSI results for use in comparison with the time domain SSI results obtained using the DIABLO computer code, this study also leads to the recognition that the frequency-domain method should be modernized so that it can better serve its mission-critical role for analysis and design of nuclear power plants.

42 ENGINEERING↗
DOE OSTI2013

Report on the NDC Capacity Building and Regional Seismic Travel Time Workshop and Training

Drs. Stephen Myers and Michael Begnaud represented the U.S. at the National Data Center Capacity Building and Regional Seismic Travel Time Workshop and Training, which was held at the Instituto Nacional de Prevención Sísmica (INPRES) in San Juan, Argentina from 14 to 18 October 2013. This report focuses on the Regional Seismic Travel Time (RSTT) half of the workshop.

58 GEOSCIENCES↗
DOE OSTI2014

B341 Seismic Evaluation

The Seismic Evaluation of Building 341 located at Lawrence Livermore National Laboratory in Livermore, California has been completed. The subject building consists of a main building, Increment 1, and two smaller additions; Increments 2 and 3. Based on our evaluation the building does not meet a Life Safety performance level for the BSE- 1E earthquake ground shaking hazard. The BSE-1E is the recommended seismic hazard level for evaluation of existing structures and is based on a 20% probability of exceedence in 50 years.

42 ENGINEERING↗
DOE OSTI2014

Seismic and hydroacoustic analysis relevant to MH370

The vicinity of the Indian Ocean is searched for open and readily available seismic and/or hydroacoustic stations that might have recorded a possible impact of MH370 with the ocean surface. Only three stations are identified: the IMS hydrophone arrays H01 and H08, and the Geoscope seismic station AIS. Analysis of the data from these stations shows an interesting arrival on H01 that has some interference from an Antarctic ice event, large amplitude repeating signals at H08 that obscure any possible arrivals, and large amplitude chaotic noise at AIS precludes any analysis at higher frequencies of interest. The results are therefore rather inconclusive but may point to a more southerly impact location within the overall Indian Ocean search region. The results would be more useful if they can be combined with any other data that are not readily available.

58 GEOSCIENCES↗
DOE OSTI2015

Fully Autonomous Multiplet Event Detection: Application to Local-Distance Monitoring of Blood Falls Seismicity

We apply a fully autonomous icequake detection methodology to a single day of high-sample rate (200 Hz) seismic network data recorded from the terminus of Taylor Glacier, ANT that temporally coincided with a brine release episode near Blood Falls (May 13, 2014). We demonstrate a statistically validated procedure to assemble waveforms triggered by icequakes into populations of clusters linked by intra-event waveform similarity. Our processing methodology implements a noise-adaptive power detector coupled with a complete-linkage clustering algorithm and noise-adaptive correlation detector. This detector-chain reveals a population of 20 multiplet sequences that includes ~150 icequakes and produces zero false alarms on the concurrent, diurnally variable noise. Our results are very promising for identifying changes in background seismicity associated with the presence or absence of brine release episodes. We thereby suggest that our methodology could be applied to longer time periods to establish a brine-release monitoring program for Blood Falls that is based on icequake detections.

42 ENGINEERING↗
DOE OSTI2016

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, and finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where uncertainty is added to the system through noise in the measurements.

58 GEOSCIENCES↗
DOE OSTI2017

Scalable Metadata Management for a Large Multi-Source Seismic Data Repository

In this work, we implemented the key metadata management components of a scalable seismic data ingestion framework to address limitations in our existing system, and to position it for anticipated growth in volume and complexity. We began the effort with an assessment of open source data flow tools from the Hadoop ecosystem. We then began the construction of a layered architecture that is specifically designed to address many of the scalability and data quality issues we experience with our current pipeline. This included implementing basic functionality in each of the layers, such as establishing a data lake, designing a unified metadata schema, tracking provenance, and calculating data quality metrics. Our original intent was to test and validate the new ingestion framework with data from a large-scale field deployment in a temporary network. This delivered somewhat unsatisfying results, since the new system immediately identified fatal flaws in the data relatively early in the pipeline. Although this is a correct result it did not allow us to sufficiently exercise the whole framework. We then widened our scope to process all available metadata from over a dozen online seismic data sources to further test the implementation and validate the design. This experiment also uncovered a higher than expected frequency of certain types of metadata issues that challenged us to further tune our data management strategy to handle them. Our result from this project is a greatly improved understanding of real world data issues, a validated design, and prototype implementations of major components of an eventual production framework. This successfully forms the basis of future development for the Geophysical Monitoring Program data pipeline, which is a critical asset supporting multiple programs. It also positions us very well to deliver valuable metadata management expertise to our sponsors, and has already resulted in an NNSA Office of Defense Nuclear Nonproliferation commitment to a multi-year project for follow-on work.

58 GEOSCIENCES↗
DOE OSTI2018

A Preliminary Explosion Seismic Spectral Model for Saturated/Hard Rock

This short technical report describes a new seismic spectral model for chemical and nuclear explosions in saturated and/or hard rock. Results from the Source Physics Experiments (SPE) indicate that existing explosion spectral models can be poor fits to small and/or over-buried explosions. Here we develop a preliminary improved explosion model to fit both SPE and historic nuclear explosion data. The model is based on revising the Mueller and Murphy (1972) and Denny and Johnson (1991) seismic spectral models. A FORTRAN code was developed to provide the spectral models in SAC format for use in explosion monitoring applications such as detection and yield estimation. This model should be considered preliminary and work is underway to better generalize and expand the model to include explosions in dry porous and/or soft rock media and to better fit explosion S-waves.

58 GEOSCIENCES↗
DOE OSTI2018

Analysis of seismicity at observed at station BCE using subspace detectors

A dynamic correlation processor (DCP) was used to process 90 days of 3-component seismic data recorded by station BCE. Two methods of detector creation were compared. The first attempted to span the signal space with a small number of subspace detectors having minimal projections on one another, and the second used a much larger number of detectors with substantial inter-template projections. After two passes over the data the results were compared, and the second approach was found to have produced more than 3 times the number of detections. For events in common, the average correlation statistic for the second approach was 0.77 compared to a statistic of 0.65 for the first approach. Also, analysis of the detection statistics as a function of SNR showed a strong functional relationship between SNR and correlation statistic for the second approach not found in the first approach. I interpret this to mean that the intra-group variability of signals produced by the second method is due primarily to noise rather than variations in source or path. These results show that (in an environment with large numbers of repeaters) if precise classification is a goal, it is better to operate a DCP with many correlators with substantial inter-template projections and that fully span the signal space. The performance of the DCP was also measured using a small set of “ground truth” picks for BCE from the Chip Brogan catalog. The catalog spanned less than three days out of the 90 days of the experiment and is also incomplete, but the comparison identified 12 signals missed by the DCP because of low SNR. Combining detections by the DCP and picks from the Brogan catalog, identifies 76 unique signals. Of these, the DCP detected 64 (84%) and the Catalog contained between 48/76 (63%) and 48/62 (77%). Analysis of time-of-day and day-of-week statistics was not useful in identifying the signal sources. However, magnitude recurrence statistics were consistent with mining induced seismicity (a preponderance of small sources). Failure of the temporal discriminants may indicate that the events being detected are not coupled in the same way to the mining activity, e.g. secondary failures. Correlation data from explosions at the Nevada test site (NTS) were used to bound the separation of events within groups. Nearly all the NTS correlations with the same passband and time bandwidth product as the detections and having a correlation statistic >= 0.8 are from sources separated by less than 1 km. Even at correlation values of 0.6 nearly all the source separations are less than about 3 km. Because the DCP detectors were formed to span the signal space at a correlation value of 0.9 and because the intra-group variability is most likely due to noise and not source variability, it is likely that the sources associated with each detector are separated by one km or less, and almost certain that the majority are separated by no more than 3 km.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Pararhombi: Parallel Implementation of 3-D Seismic Wave Propagation in Orthorhombic Media

Many earth materials and minerals are seismically anisotropic; however, due to the weakness of anisotropy and for simplicity, the earth is often approximated as an isotropic medium. Specific circumstances, such as in shales, tectonic fabrics, or oriented fractures, for example, require the use of anisotropic simulations in order to accurately model the earth. This report details the development of a new massively parallel 3-D full seismic waveform simulation algorithm within the principle coordinate system of an orthorhombic material, which is a specific form of anisotropy common in layered, fractured media. The theory and implementation of Pararhombi is described along with verification of the code against other solutions.

58 GEOSCIENCES↗