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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Big Data Seismology

The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our ability to resolve 4D Earth structure are fundamentally limited by data volume. Currently, Big Data Seismology is an emergent revolution involving the use of large, data-dense inquiries that is providing new opportunities to make fundamental advances in these areas. This article reviews recent scientific advances enabled by Big Data Seismology through the context of three major drivers: the development of new data-dense sensor systems, improvements in computing, and the development of new types of techniques and algorithms. Each driver is explored in the context of both global and exploration seismology, alongside collaborative opportunities that combine the features of long-duration data collections (common to global seismology) with dense networks of sensors (common to exploration seismology). The review explores some of the unique challenges and opportunities that Big Data Seismology presents, drawing on parallels from other fields facing similar issues. Finally, recent scientific findings enabled by dense seismic data sets are discussed, and we assess the opportunities for significant advances made possible with Big Data Seismology. This review is designed to be a primer for seismologists who are interested in getting up-to-speed with how the Big Data revolution is advancing the field of seismology.

58 GEOSCIENCES↗
NASA NTRS1993

Seismology and space-based geodesy

The potential of space-based geodetic measurement of crustal deformation in the context of seismology is explored. The achievements of seismological source theory and data analyses, mechanical modeling of fault zone behavior, and advances in space-based geodesy are reviewed, with emphasis on realizable contributions of space-based geodetic measurements specifically to seismology. The fundamental relationships between crustal deformation associated with an earthquake and the geodetically observable data are summarized. The response and spatial and temporal resolution of the geodetic data necessary to understand deformation at various phases of the earthquake cycle is stressed. The use of VLBI, SLR, and GPS measurements for studying global geodynamics properties that can be investigated to some extent with seismic data is discussed. The potential contributions of continuously operating strain monitoring networks and globally distributed geodetic observatories to existing worldwide modern digital seismographic networks are evaluated in reference to mutually addressable problems in seismology, geophysics, and tectonics.

Tralli, David M.↗
DOE OSTI2022

Editorial: Advances in Ocean Bottom Seismology

Among the physical sciences, seismology is relatively young; with the continued advances in instrumental technologies and computer capacity, ours has to be one of the most rapidly evolving subject areas within the Earth Sciences writ large. Exploration of the Earth by way of seismic observation and modeling is expanding not only in the range of capabilities - from reservoir scale to whole-Earth sensing - but in recent decades seismology has resolutely marched from the Earth’s continents and sea shores into the oceans, which cover nearly 75% of the Earth and have until recently hindered our ability to more fully explore the planet.

58 GEOSCIENCES↗
NASA NTRS2013

Saturn Ring Seismology: Interpreting the Seismogram

Marley (1990) and Marley and Porco (1993) proposed that f-mode oscillations of Saturn could excite resonant density and bending waves in the inner C-ring. They hypothesized that certain wave features discovered by Rosen et al. (1991) that were not associated with known satellite resonances could be the result of such resonant interactions with the planetary oscillation modes. They also predicted that if this was the case the waves would be found to be density (and not bending) waves by Cassini and predicted the azimuthal wave number of the C-ring waves m. Employing Cassini VIMS stellar occultation data Hedman and Nicholson (2013) have now confirmed the predictions and demonstrated that at least some of the C-ring features identified by Rosen et al. are indeed likely caused by resonant oscillation modes of Saturn. Given this context we have taken a fresh look at the Saturn ring seismology. First we propose that an apparent bending wave denoted 'j' by Rosen may be a second order outer vertical resonance with the l=3, m=2 f-mode of Saturn and discuss the locations of other plausible second order resonances in the rings. Since only a handful of ring resonances have been identified, measuring even one or two additional planetary mode frequencies would substantially assist the process of inverting mode frequencies to constrain Saturn interior's structure. Using the available mode frequencies, modern inversion technique employed in stellar seismology, and a recent set of Saturn interior models we provide an initial estimation of what available mode frequencies are telling us about the interior structure of the planet. Since the f-modes are confined relatively closely to the planetary surface, most of the observed modes probe only the outermost layers of the planet that are already comparatively well understood. However the l = 2 mode does probe relatively deeply into the planet and we will discuss the potential the measurement of this mode frequency has for placing new constraints on the interior structure.

Seismogram↗
NASA NTRS2015

Planetary Seismology

Of the many geophysical means that can be used to probe a planet's interior, seismology remains the most direct. In addition to Earth, seismometers have been installed on Venus, Mars, and the Moon. Given that the seismic data gathered on the Moon (now over 40 years ago) revolutionized our understanding of the Moon and are still being used today to produce new insight into the state of the lunar interior, it is no wonder that many future missions, both real and conceptual, plan to take seismometers to other planets. To best facilitate the return of high-quality data from these instruments, as well as to further our understanding of the dynamic processes that modify a planet's interior, various modeling approaches are used to quantify parameters such as the amount and distribution of seismicity, tidal deformation, and seismic structure of the terrestrial planets. In addition, recent advances in wavefield modeling have permitted a renewed look at seismic energy transmission and the effects of attenuation and scattering, as well as the presence and effect of a core, on recorded seismograms. In this talk I will discuss some of these methods and review the history of planetary seismology.

planetary seismology↗
DOE OSTI2021

Deep convolutional autoencoders as generic feature extractors in seismological applications

The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event discrimination (i.e., earthquake vs. noise waveforms, earthquake vs. explosion waveforms), and phase picking. These tests involve training an autoencoder, either undercomplete or overcomplete, on a large amount of earthquake waveforms, and then using the trained encoder as a feature extractor with subsequent application layers (either a fully connected layer, or a convolutional layer plus a fully connected layer) to make the decision. By comparing the performance of these newly designed models against the baseline models trained from scratch, we conclude that the autoencoder feature extractor approach may only outperform the baseline under certain conditions, such as when the target problems require features that are similar to the autoencoder encoded features, when a relatively small amount of training data is available, and when certain model structures and training strategies are utilized. The model structure that works best in all these tests is an overcomplete autoencoder with a convolutional layer and a fully connected layer to make the estimation.

58 GEOSCIENCES↗
DOE OSTI2020

Seismology in the Cloud: A New Streaming Workflow

Data-intensive research in seismology is experiencing a recent boom, driven in part by large volumes of available data and advances in the growing field of data science. However, there are significant barriers to processing large data volumes, such as long retrieval times from data repositories, complex data management, and limited computational resources. New tools and platforms have reduced the barriers to entry for scientific cluster computing, including the maturation of the commercial cloud as an accessible instrument for research. Here, we build a customized research cluster in the cloud to test a new workflow for large-scale seismic analysis, in which data are processed as a stream (retrieved on-the-fly and acted upon without storing), with data from the Incorporated Research Institutions for Seismology Data Management Center. We use this workflow to deploy a spectral peak detection algorithm over 5.6 TB of compressed continuous seismic data from 2074 stations of the USArray Transportable Array EarthScope network. Using a 50-node cluster in the cloud, we completed the noise survey in 80 hr, with an average data throughput of 1.7 GB per minute. By varying cluster sizes, we find the scaling of our analysis to be sublinear, due to a combination of algorithmic limitations and data center response times. The cloud-based streaming workflow represents an order-of-magnitude increase in acquisition and processing speed compared to a traditional download-store-process workflow, and offers the additional benefits of employing a flexible, accessible, and widely used computing architecture. It is limited, however, due to its reliance on Internet transfer speeds and data center service capacity, and may not work well for repeated analyses or those for which even higher data throughputs are needed. These research applications will require a new class of cloud-native approaches in which both data and analysis are in the cloud.

58 GEOSCIENCES↗
DOE OSTI2020

Seismology on Venus with infrasound observations from balloon and orbit

The study of Venus' evolution is inexorably linked with studying its interior properties, which can be investigated by performing seismic studies on the planet. However, seismology on Venus has long eluded planetary scientists due to technological challenges presented by high surface temperature and pressure, which limit lifetimes of surface-based instrumentation. In this white paper, we present two complementary techniques for performing seismology on Venus by measuring the low-frequency acoustic signature (infrasound) produced by seismic activity through coupling between the solid planet and the atmosphere. These techniques may be implemented with technology available today, without the use of high-temperature electronics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The Scaling and Units of the Elastic Response Term for Rayleigh Waves that is Output by Computer Programs in Seismology (CPS)

We report on the scaling and units of the Rayleigh wave elastic response function A R (ω) that is output from the widely used Computer Programs in Seismology (CPS) to aid in the modeling of ground motion sourced by atmospheric explosions. The program uses mixed units (km, second, km/s, gm/cc) to keep A R (ω) near 10 0 and prevent any numerical underflow or overflow. We compare two models for the response of an elastic half space to the output from CPS. Our application inputs the recommended, mixed unit geological models to determine how researchers must scale this output to obtain physical units for A R (ω) that represents the amplitude scaling for the minimum group velocity (Airy phase) contribution to Rayleigh waves. We determine that a CPS user must scale the output for A R (ω) by 10 -12 (m/km) 2 (g/cc/m 3 /kg) to obtain MKS (meter, kg, second) units and then must multiply this result by the vertical component eigenfunction squared, that is evaluated at the free surface.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗
NASA NTRS1966

General seismology

Seismological instrumentation, earthquake and nuclear explosion detection, and engineering construction applications

RECORDING INSTRUMENT↗
DOE OSTI2024

Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation

This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, discussed the technical objectives of developing a real-time decision-making platform to enhance seismic monitoring and risk management during stimulation activities. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

15 GEOTHERMAL ENERGY↗
NASA NTRS1979

Planetary seismology and interiors

This report briefly summarizes knowledge gained in the area of planetary seismology in the period 1969-1979. Attention is given to the seismic instruments, the seismic environment (noise, characteristics of seismic wave propagation, etc.), and the seismicity of the moon and Mars as determined by the Apollo missions and Viking Lander experiments, respectively. The models of internal structures of the terrestrial planets are discussed, with the earth used for reference.

Toksoz, M. N.↗
NASA NTRS1980

Data User's Note: Apollo seismological investigations

Seismological objectives and equipment used in the passive seismic, active seismic, lunar seismic profiling, and the lunar gravimeter experiments conducted during Apollo 11, 12, 14, 15, 16, and 17 missions are described. The various formats in which the data form these investigations can be obtained are listed an an index showing the NSSDC identification number is provided. Tables show manned lunar landing missions, lunar seismic network statistics, lunar impact coordinate statistics, detonation masses and times of EP's, the ALSEP (Apollo 14) operational history; compressed scale playout tape availability, LSPE coverage for one lunation, and experimenter interpreted events types.

Vostreys, R. W.↗
NASA NTRS1981

Lunar seismology - The internal structure of the moon

It is pointed out that seismology has provided the most detailed information concerning the structure and state of the earth's interior. Beginning in 1969, seismometers were landed on the moon by the Apollo missions, providing the first opportunity to attempt similar studies on another planetary body. In September 1977 the operation of these instruments was terminated. A description is presented of the internal structure of the moon, as determined from the obtained lunar seismic data. The analysis of the lunar data is approached in a systematic fashion, using appropriate techniques to minimize the number of necessary assumptions, extract the maximum amount of structural information, and determine its reliability. The completed lunar seismic network consists of four stations located at the landing sites of Apollo missions 12, 14, 15, and 16. Attention is given to crustal structure, the structure of the lunar mantle, the attenuating region, and the core.

Goins, N. R.↗