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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Challenges and Opportunities in Turning Large U.S. Archives of Analog Seismograms into a Modern Usable Resource

Abstract Quantitative seismology is based firmly on the analysis of actual ground motions, and the transition to digital recording in the 1980s enabled sophisticated new capabilities to extract useful results from waveforms. With some effort, these tools can also be applied to analog records. Focusing on assets available within U.S. institutions, we review the necessary steps and the challenges in enabling “data rescue”—that is, preserving the scientific information latent in large analog seismogram archives and making it usable. They include: determining what assets are available (the analog seismogram archives held by various institutions, with associated metadata on instrument responses, station locations, and timing information); developing a consensus on the top level of a triage process (which analog records most definitely should be rescued?); deciding the level of quality needed in copying original seismograms to media suitable for digitizing; assessing the relative merits of scanning and digitizing; and, the need for a community service in distributing scans and digital records, as they accumulate. The necessary level of effort can benefit from practical experience. For example, specific studies have used digitized versions of analog recordings to model earthquake sources and assess seismic hazard. Other studies have used them to gain experience with nuclear explosion signals recorded at regional distances, noting that regional signals enable explosions to be monitored down to levels much lower than those attainable teleseismically. The opportunities presented by large archives of analog seismograms include the insights they present to current and future seismologists studying earthquakes and explosions, into the practical areas of assessing seismic hazard, monitoring for test ban compliance down to low explosion yields—and prompt characterization of actual explosions should they occur, as well the traditional academic pursuit of a better understanding of earthquake physics.

Geochemistry & Geophysics↗
DOE OSTI2016

A Multi­Discipline Approach to Digitizing Historic Seismograms

Retriever Technology has developed and has made available free of charge a seismogram digitization software package called SKATE (Seismogram Kit for Automatic Trace Extraction). We have developed an extensive set of algorithms that process seismogram image files, provide editing tools, and output time series data. The software is available online and free of charge at seismo.redfish.com. To demonstrate the speed and cost effectiveness of the software, we have processed over 30,000 images.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Fast computation of synthetic seismograms within a medium containing remote localized perturbations: a numerical solution to the scattering problem

We derive a fast discrete solution to the scattering problem. This solution allows us to compute accurate synthetic seismograms or waveforms for arbitrary locations of sources and receivers within a medium containing localized perturbations. The key to efficiency is that wave propagation modelling does not need to be carried out in the entire volume that encompasses the sources and the receivers but only within the subvolume containing the perturbations or scatterers. The proposed solution has important applications, for example, it permits the imaging of remote targets located in regions where no sources or receivers are present. Our solution relies on domain decomposition: within a small volume that contains the scatterers, wave propagation is modelled numerically, while in the surrounding volume, where the medium isn't perturbed, the response is obtained through wavefield extrapolation. The originality of this work is the derivation of discrete formulas for representation theorems and Kirchhof–Helmholtz integrals that naturally adapt to the numerical scheme employed for modelling wave propagation. Our solution applies, for example, to finite difference methods or finite/spectral elements methods. The synthetic seismograms obtained with our solution can be considered ‘exact’ as the total numerical error is comparable to that of the method employed for modelling wave propagation. We detail a basic implementation of our solution in the acoustic case using the finite difference method and present numerical examples that demonstrate the accuracy of the method. We show that ignoring some terms accounting for higher order scattering effects in our solution has a limited effect on the computed seismograms and significantly reduces the computational effort. Finally, we show that our solution can be used to compute localized sensitivity kernels and we discuss applications to target oriented imaging. Extension to the elastic case is straightforward and summarized in a dedicated section.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A digital seismogram archive of nuclear explosion signals, recorded at the Borovoye Geophysical Observatory, Kazakhstan, from 1966 to 1996

Seismologists from Kazakhstan, Russia, and the United States have rescued the Soviet-era archive of nuclear explosion seismograms recorded at Borovoye in northern Kazakhstan during the period 1966–1996. The signals had been stored on about 8000 magnetic tapes, which were held at the recording observatory. After hundreds of man-years of work, these digital waveforms together with significant metadata are now available via the project URL, namely http://www.ldeo.columbia.edu/res/pi/Monitoring/Data/ as a modern open database, of use to diverse communities. Three different sets of recording systems were operated at Borovoye, each using several different seismometers and different gain levels. For some explosions, more than twenty different channels of data are available. A first data release, in 2001, contained numerous glitches and lacked many instrument responses, but could still be used for measuring accurate arrival times and for comparison of the strengths of different types of seismic waves. The project URL also links to our second major data release, for nuclear explosions in Eurasia recorded in Borovoye, in which the data have been deglitched, all instrument responses have been included, and recording systems are described in detail. This second dataset consists of more than 3700 waveforms (digital seismograms) from almost 500 nuclear explosions in Eurasia, many of them recorded at regional distances. It is important as a training set for the development and evaluation of seismological methods of discriminating between earthquakes and underground explosions, and can be used for assessment of three-dimensional models of the Earth’s interior structure.

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

Denoising Seismograms in the Time Domain Using a Deep Learning Model

Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.

P-waves↗
DOE OSTI2012

Development of earthquake early warning system using real time signal of broadband seismogram

Earthquake pose serious threat of live and properties for urban area near subduction zone offshore and active fault on land. Jakarta and Bandung is an example of big city that no system of Earthquake early warning (EEW) event very high urbanization, and has many important infra structure in the area. The capital city is potentially high risk ground shaking. EEW can be usefull tool for reducing earthquake hazard, if spatial relation between cities and earthquake source is favorable for such warning and their citizens are properly trained to response early warning message. An EEW and rapid response system can provide the critical information needed to minimized lost of live and property and direct rescue. Earthquake ground shaking with magnitude M>6.0 from zone of Megathrust, southern of West Java should potentially damage in the area of west java especially Bandung and Jakarta City. This research development of EEW parameter such as amplitude displacement (Pd), rapid magnitude determination (M) and Peak ground Velocity (PGV). We explore the practical approach to EEW with the use of Broadband seismogram signal. Time effective EEW which epicenter from megathrust zone has potential to provide EEW in the area of west java such as Jakarta first ground shaking more or less 60 second later and strong shaking 118 second after EEW Alarm on CISI Station. EEW notification at potentially damage in the area of west java can be predicted from the characteristic of Pd > 0.5 cm, M> 6 and PGV > 10 cm/sec. GIS as a tool for presentation of hazard mapping in the affected area.

58 GEOSCIENCES↗
DOE OSTI2025

Simulating High-Frequency Seismograms in Realistic Earth Models to Better Understand Source Discrimination Based on Differential Magnitudes ( M L− M c)

Discriminating low-yield underground nuclear explosions from small earthquakes is a key task in monitoring nuclear test ban treaties. P/S amplitude ratios have been an effective discriminant for moderate-sized events recorded at regional distances, but it is unclear if they are as effective in discriminating small seismic events recorded at local distances (<150 km). The difference between local magnitude (M L ) and coda duration magnitude (M c ) has been proposed as a new discriminant that may complement P/S amplitude ratios at local distances. Here, in this work, we calculate high-frequency (up to ∼4 Hz) synthetic seismograms at epicentral distances of 0–30 km in realistic models of the Salt Lake basin (Utah, United States) to better understand how variations in source type and depth affect M L −M c values. The Earth models incorporate simplified 1D and deterministic 3D structures, small-wavelength stochastic velocity perturbations, and surface topography. Coda waves are enhanced for the more complicated models compared to the base 1D model, but still underpredict observed durations by about a factor of two, which results in overprediction of amplitude to duration ratios (i.e., M L −M c values) for a near-surface explosion and a 7 km deep earthquake. For both source types, the predicted M L and M c values decrease as source depth increases, and M L −M c shows only minor variation with depth; however, M L −M c is on average ∼0.5 units smaller for explosions than earthquakes. This finding may imply that M L −M c has sensitivity to source type, in addition to being a depth discriminant, but more modeling is needed given the limitations of the current study. Future modeling should incorporate higher-frequency (≳5 Hz) simulations over a larger distance range (0–150 km), where M L and M c are commonly measured, while honoring low shear velocities (<300 m/s) near the surface and sampling a wider range of earthquake and explosion source mechanisms.

Hutchings, Sean J. [Univ. of Utah, Salt Lake City,↗
DOE OSTI2022

Seismic strain energy partitioning: estimating the strain energy of seismic body waves.

This report details a method to estimate the energy content of various types of seismic body waves. The method is based on the strain energy of an elastic wavefield and Hooke’s Law. We present a detailed derivation of a set of equations that explicitly partition the seismic strain energy into two parts: one for compressional (P) waves and one for shear (S) waves. We posit that the ratio of these two quantities can be used to determine the relative contribution of seismic P and S waves, possibly as a method to discriminate between earthquakes and buried explosions. We demonstrate the efficacy of our method by using it to compute the strain energy of synthetic seismograms with differing source characteristics. Specifically, we find that explosion-generated seismograms contain a preponderance of P wave strain energy when compared to earthquake-generated synthetic seismograms. Conversely, earthquake-generated synthetic seismograms contain a much greater degree of S wave strain energy when compared to explosion-generated seismograms.

58 GEOSCIENCES↗
DOE OSTI2017

Seismic classification through sparse filter dictionaries

We tackle a multi-label classi cation problem involving the relation between acoustic- pro le features and the measured seismogram. To isolate components of the seismo- grams unique to each class of acoustic pro le we build dictionaries of convolutional lters. The convolutional- lter dictionaries for the individual classes are then combined into a large dictionary for the entire seismogram set. A given seismogram is classi ed by computing its representation in the large dictionary and then comparing reconstruction accuracy with this representation using each of the sub-dictionaries. The sub-dictionary with the minimal reconstruction error identi es the seismogram class.

58 GEOSCIENCES↗
DOE OSTI2021

An efficient method to estimate the probability density of seismic Green's functions

We present a computationally efficient method to approximate the probability distribution of seismic Green's functions given the uncertainty of an Earth model. The method is based on the Karhunen-Loève (KL) theorem and an approximation of the Green's function (or seismogram) covariance. Using Monte Carlo (MC) simulations as a control case, we demonstrate that our KL-based method can accurately reproduce a probability distribution of seismograms that results from an uncertain Earth model for a MC-derived seismogram covariance. We then describe a method to estimate the covariance of the seismograms resulting from those Earth models that is not based on MC simulations. We use the estimated Green's function covariance in conjunction with our KL-based method to produce a Green's function probability distribution, and compare that distribution to a Green's function probability distribution produced using a MC finite difference method. We find that the Green's function probability distribution approximated using our KL-based method generally mimics that produced using the MC simulations, especially for direct-arriving body waves. However the accuracy of the KL-based method generally decreases for later times in the simulated Green's function distribution.

58 GEOSCIENCES↗
DOE OSTI2022

Observations of Mantle Seismic Anisotropy Using Array Techniques: Shear-Wave Splitting of Beamformed SmKS Phases

Shear-wave splitting measurements are commonly used to resolve seismic anisotropy in both the upper and lowermost mantle. Typically, such techniques are applied to SmKS phases that have reflected (m-1) times off the underside of the core-mantle boundary before being recorded. Practical constraints for shear-wave splitting studies include the limited number of suitable phases as well as the large fraction of available data discarded because of poor signal-to-noise ratios (SNRs) or large measurement uncertainties. Array techniques such as beamforming are commonly used in observational seismology to enhance SNRs, but have not been applied before to improve SmKS signal strength and coherency for shear wave splitting studies. Here, we investigate how a beamforming methodology, based on slowness and backazimuth vespagrams to determine the most coherent incoming wave direction, can improve shear-wave splitting measurement confidence intervals. Through the analysis of real and synthetic seismograms, we show that (a) the splitting measurements obtained from the beamformed seismograms (beams) reflect an average of the single-station splitting parameters that contribute to the beam; (b) the beams have (on average) more than twice as large SNRs than the single-station seismograms that contribute to the beam; (c) the increased SNRs allow the reliable measurement of shear wave splitting parameters from beams down to average single-station SNRs of 1.3. Beamforming may thus be helpful to more reliably measure splitting due to upper mantle anisotropy. Moreover, here we show that beamforming holds potential to greatly improve detection of lowermost mantle anisotropy by demonstrating differential SKS–SKKS splitting analysis using beamformed USArray data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Toward tsunami early warning system in Indonesia by using rapid rupture durations estimation

Indonesia has Indonesian Tsunami Early Warning System (Ina-TEWS) since 2008. The Ina-TEWS has used automatic processing on hypocenter; Mwp, Mw (mB) and Mj. If earthquake occurred in Ocean, depth < 70 km and magnitude > 7, then Ina-TEWS announce early warning that the earthquake can generate tsunami. However, the announcement of the Ina-TEWS is still not accuracy. Purposes of this research are to estimate earthquake rupture duration of large Indonesia earthquakes that occurred in Indian Ocean, Java, Timor sea, Banda sea, Arafura sea and Pasific ocean. We analyzed at least 330 vertical seismogram recorded by IRIS-DMC network using a direct procedure for rapid assessment of earthquake tsunami potential using simple measures on P-wave vertical seismograms on the velocity records, and the likelihood that the high-frequency, apparent rupture duration, T{sub dur}. T{sub dur} can be related to the critical parameters rupture length (L), depth (z), and shear modulus ({mu}) while T{sub dur} may be related to wide (W), slip (D), z or {mu}. Our analysis shows that the rupture duration has a stronger influence to generate tsunami than Mw and depth. The rupture duration gives more information on tsunami impact, Mo/{mu}, depth and size than Mw and other currently used discriminants. We show more information which known from the rupture durations. The longer rupture duration, the shallower source of the earthquake. For rupture duration greater than 50 s, the depth less than 50 km, Mw greater than 7, the longer rupture length, because T{sub dur} is proportional L and greater Mo/{mu}. Because Mo/{mu} is proportional L. So, with rupture duration information can be known information of the four parameters. We also suggest that tsunami potential is not directly related to the faulting type of source and for events that have rupture duration greater than 50 s, the earthquakes generated tsunami. With available real-time seismogram data, rapid calculation, rupture duration discriminant can be completed within 4-5 min after an earthquake occurs and thus can aid in effective, accuracy and reliable tsunami early warning for Indonesia region.

58 GEOSCIENCES↗
DOE OSTI2016

Global adjoint tomography: first-generation model

We present the first-generation global tomographic model constructed based on adjoint tomography, an iterative full-waveform inversion technique. Synthetic seismograms were calculated using GPU-accelerated spectral-element simulations of global seismic wave propagation, accommodating effects due to 3-D anelastic crust & mantle structure, topography & bathymetry, the ocean load, ellipticity, rotation, and self-gravitation. Fréchet derivatives were calculated in 3-D anelastic models based on an adjoint-state method. The simulations were performed on the Cray XK7 named ‘Titan’, a computer with 18 688 GPU accelerators housed at Oak Ridge National Laboratory. The transversely isotropic global model is the result of 15 tomographic iterations, which systematically reduced differences between observed and simulated three-component seismograms. Our starting model combined 3-D mantle model S362ANI with 3-D crustal model Crust2.0. We simultaneously inverted for structure in the crust and mantle, thereby eliminating the need for widely used ‘crustal corrections’. We used data from 253 earthquakes in the magnitude range 5.8 ≤ M w ≤ 7.0. We started inversions by combining ~30 s body-wave data with ~60 s surface-wave data. The shortest period of the surface waves was gradually decreased, and in the last three iterations we combined ~17 s body waves with ~45 s surface waves. We started using 180 min long seismograms after the 12th iteration and assimilated minor- and major-arc body and surface waves. The 15th iteration model features enhancements of well-known slabs, an enhanced image of the Samoa/Tahiti plume, as well as various other plumes and hotspots, such as Caroline, Galapagos, Yellowstone and Erebus. Furthermore, we see clear improvements in slab resolution along the Hellenic and Japan Arcs, as well as subduction along the East of Scotia Plate, which does not exist in the starting model. Point-spread function tests demonstrate that we are approaching the resolution of continental-scale studies in some areas, for example, underneath Yellowstone. Here, this is a consequence of our multiscale smoothing strategy in which we define our smoothing operator as a function of the approximate Hessian kernel, thereby smoothing gradients less wherever we have good ray coverage, such as underneath North America.

58 GEOSCIENCES↗
DOE OSTI2022

ccp137/SUGAR

This package (SUrface-wave Grader with ARtificial intelligence or SUGAR) automatically assigns a quality score to surface-wave seismograms (SAC format) using a trained artificial neural network model (included). Specifically, the python script 01_apply_ann.py calculates probability scores for a list of SAC files. You may consider seismograms with probability scores larger than 0.5 as acceptable data. Note no scores will be given to seismograms that do not pass an initial check (e.g., insufficient number of data points). See https://doi.org/10.1002/essoar.10507941.3 for more details.

Chai, Chengping [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2017

Multiobjective Optimization of Regional and Teleseismic Data to Constrain the Source of the 12 September 2016 Mw 5.4 Earthquake in South Korea

In this paper, we propose a new approach for source inversion with automatic criteria for the station selection process and using a multiobjective optimization scheme combining teleseismic body-wave and regional surface-wave observations. To illustrate the approach, we determine the source parameters of the 12 September 2016 M w 5.4 South Korea earthquake, as well as its foreshock (same day) and its main aftershock on 19 September 2016. Available teleseismic (short period and broadband) and regional (broadband) seismograms from the Incorporated Research Institutions for Seismology International–Federation of Digital Seismograph Networks (IRIS-FDSN) webservice are selected (see Data and Resources). First, all teleseismic data with signal-to-noise ratio (SNR) above 2 in the 0.3–1.5 Hz frequency band are selected and a cepstrum function is blindly applied to help detect reflected wave arrivals inside a P coda. This method allows the identification of records with weak P-coda and clear depth phase (pP, sP) arrivals and can be used to select an optimal set of teleseismic seismograms to be used for the inversion. Second, regional seismograms are selected according to the fit between their observed and theoretical dispersion curves extracted from local 1D velocity model. Depending on the epicentral distance, two frequency bands are proposed for regional data: 15–50 s for epicentral distances smaller than 2° and 30–80 s otherwise. Finally, we explore the space parameters from exhaustive grid searches for the two objective functions Tf and Rf for teleseismic and regional data, respectively. We show that the seismic moment parameters can be exclusively derived from Rf and can be fixed for Tf. However, the depth parameter is not sensitive to Rf and can be simultaneously inverted from both. The selection of the optimal solution satisfying both cost functions uses the optimum Pareto front that allows a decrease in epistemic uncertainty. Lastly, we discuss the advantage of this approach for improving the characterization of moderate earthquake sources in areas with limited regional instrumentation.

58 GEOSCIENCES↗
DOE OSTI2021

Challenges and Potential of Waveform Modeling for Crustal Scale Predictions

Waveform modeling is crucial to improving our understanding of observed seismograms. Forward simulation of wavefields provides quantitative methods of testing interactions between complicated source functions and the propagation medium. Here, we discuss three experiments designed to improve under standing of high frequency seismic wave propagation. First, we compare observed and predicted travel times of crustal phases for a set of real observed earthquakes with calculations and synthetic seismograms. Second, we estimate the frequency content of a series of nearly co-located earthquakes of varying magnitude for which we have a relatively well- known 1D velocity model. Third, we apply stochastic perturbations on top of a 3D tomographic model and qualitatively assess how those variations map to differences in the seismograms. While different in scope and aim, these three vignettes illustrate the current state of crustal scale waveform modeling and the potential for future studies to better constrain the structure of the crust.

58 GEOSCIENCES↗