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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗
NASA NTRS1980

Regional analysis of earthquake occurrence and seismic energy release

The historic temporal variation in earthquake occurrence and seismic energy release on a regional basis throughtout the world were studied. The regionalization scheme employed divided the world into large areas based either on seismic and tectonic considerations (Flinn-Engdahl Scheme) or geographic (longitude and latitude) criteria. The data set is the wide earthquake catalog of the National Geophysical Solar-Terrestrial Data Center. An apparent relationship exists between the maximum energy released in a limited time within a seismic region and the average or background energy per year averaged over a long time period. In terms of average or peak energy release, the most seismic regions of the world during the 50 to 81 year period ending in 1977 were Japanese, Andean South American, and the Alaska-Aleutian Arc regions. The year to year fluctuations in regional seismic energy release are greater, by orders of magnitude, than the corresponding variations in the world-wide seismic energy release. The b values of seismic regions range from 0.7 to 1.4 where earthquake magnitude is in the range 6.0 to 7.5.

Cohen, S. C.↗
NASA NTRS1984

Seismic Analysis Capability in NASTRAN

Seismic analysis is a technique which pertains to loading described in terms of boundary accelerations. Earthquake shocks to buildings is the type of excitation which usually comes to mind when one hears the word seismic, but this technique also applied to a broad class of acceleration excitations which are applied at the base of a structure such as vibration shaker testing or shocks to machinery foundations. Four different solution paths are available in NASTRAN for seismic analysis. They are: Direct Seismic Frequency Response, Direct Seismic Transient Response, Modal Seismic Frequency Response, and Modal Seismic Transient Response. This capability, at present, is invoked not as separate rigid formats, but as pre-packaged ALTER packets to existing RIGID Formats 8, 9, 11, and 12. These ALTER packets are included with the delivery of the NASTRAN program and are stored on the computer as a library of callable utilities. The user calls one of these utilities and merges it into the Executive Control Section of the data deck to perform any of the four options are invoked by setting parameter values in the bulk data.

Butler, T. G.↗
NASA NTRS1989

Monte Carlo simulations of the diurnal variation in seismic detection rate of sporadic meteoroid impacts on the moon

The rate of detection of meteoroid impacts on the moon by the lunar seismic network shows a characteristic diurnal variation. Assuming that these meteoroids have a flux and a preimpact orbital distribution similar to that of fireballs observed by terrestrial camera networks, one can compute the expected diurnal variation for a given set of parameters that describe the seismic wave generation and transmission on the moon. An iterative process to match the theoretical variation with the observed one has led us to the following results: (1) the majority of the detected impact events occur within a closer range of the network than was believed earlier. This results in higher meteoroid flux estimates from lunar seismic data that agree with the terrestrially measured flux. (2) For meteoroid masses smaller than 1000 g, seismic amplitude is approximately proportional to the one-fifth power of the impact speed; for larger masses it is approximately proportional to the eight-fifth power, provided that the terrestrial meteor data used for analysis are not biased. (3) Seismic efficiency of meteoroids smaller than 1000 g is significantly less than that of large meteoroids. (4) Using orbits of fireballs that represent meteorites, we predict that the share of meteorites among the detected impacts is approximately 15 percent assuming that seismic efficiency of the high-density meteorites is the same as that of average meteoroids. A greatly increased seismic efficiency for these high-density objects is not likely.

Oberst, J.↗
NASA NTRS1991

Martian seismicity

The design and ultimate success of network seismology experiments on Mars depends on the present level of Martian seismicity. Volcanic and tectonic landforms observed from imaging experiments show that Mars must have been a seismically active planet in the past and there is no reason to discount the notion that Mars is seismically active today but at a lower level of activity. Models are explored for present day Mars seismicity. Depending on the sensitivity and geometry of a seismic network and the attenuation and scattering properties of the interior, it appears that a reasonable number of Martian seismic events would be detected over the period of a decade. The thermoelastic cooling mechanism as estimated is surely a lower bound, and a more refined estimate would take into account specifically the regional cooling of Tharsis and lead to a higher frequency of seismic events.

Phillips, Roger J.↗
NASA NTRS2011

Towards Simulating a Realistic Planetary Seismic Wavefield: The Contribution of the Megaregolith and Low-Velocity Waveguides

Lunar seismograms are distinctly different from their terrestrial counterparts. The Apollo lunar seismometers recorded moonquakes without distinct P- or S-wave arrivals; instead waves arrive as a diffuse coda that decays over several hours making the identification of body waves difficult. The unusual character of the lunar seismic wavefield is generally tied to properties of the megaregolith: it consists of highly fractured and broken crustal rock, the result of extensive bombardment of the Moon. The megaregolith extends several kilometers into the lunar crust, possibly into the mantle in some regions, and is covered by a thin coating of fine-scale dust. These materials possess very low seismic velocities that strongly scatter the seismic wavefield at high frequencies. Directly modeling the effects of the megaregolith to simulate an accurate lunar seismic wavefield is a challenging computational problem, owing to the inherent 3-D nature of the problem and the high frequencies (greater than 1 Hz) required. Here we focus on modeling the long duration code, studying the effects of the low velocities found in the megaregolith. We produce synthetic seismograms using 1-D slowness integration methodologies, GEMINI and reflectivity, and a 3-D Cartesian finite difference code, Wave Propagation Program, to study the effect of thin layers of low velocity on the surface of a planet. These codes allow us generate seismograms with dominant frequencies of approximately 1 Hz. For background lunar seismic structure we explore several models, including the recent model of Weber et al., Science, 2011. We also investigate variations in megaregolithic thickness, velocity, attenuation, and seismogram frequency content. Our results are compared to the Apollo seismic dataset, using both a cross correlation technique and integrated envelope approach to investigate coda decay. We find our new high frequency results strongly support the hypothesis that the long duration of the lunar seismic codes is generated by the presence of the low velocity megaregolith, and that the diffuse arrivals are a combination of scattered energy and multiple reverberations within this layer. The 3-D modeling indicates the extreme surface topography of the Moon adds only a small contribution to scattering effects, though local geology may play a larger role. We also study the effects of the megaregolith on core reflected and converted phases and other body waves. Our analysis indicates detection of core interacting arrivals with a polarization filter technique is robust and lends the possibility of detecting other body waves from the Moon.

Schmerr, Nicholas C.↗
NASA NTRS2020

A New Crater Near Insight: Implications for Seismic Impact Detectability on Mars

A new 1.5 m diameter impact crater was discovered on Mars only ~40 km from the InSight lander. Context camera images constrained its formation between 21 February and 6 April 2019; follow-up High Resolution Imaging Science Experiment images resolved the crater. During this time period, three seismic events were identified in InSight data. We derive expected seismic signal characteristics and use them to evaluate each of the seismic events. However, none of them can definitively be associated with this source. Atmospheric perturbations are generally expected to be generated during impacts; however, in this case, no signal could be identified as related to the known impact. Using scaling relationships based on the terrestrial and lunar analogs and numerical modeling, we predict the amplitude, peak frequency, and duration of the seismic signal that would have emanated from this impact. The predicted amplitude falls near the lowest levels of the measured seismometer noise for the predicted frequency. Hence, it is not surprising this impact event was not positively identified in the seismic data. Finding this crater was a lucky event as its formation this close to InSight has a probability of only ~0.2, and the odds of capturing it in before and after images are extremely low. We revisit impact-seismic discriminators in light of real experience with a seismometer on the Martian surface. Using measured noise of the instrument, we revise our previous prediction of seismic impact detections downward, from ~a few to tens, to just ~2 per Earth year, still with an order of magnitude uncertainty.

I. J. Daubar↗
DOE OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗
DOE OSTI2024

Probing the evolution of fault properties during the seismic cycle with deep learning

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy. We use raw seismic records as input to a 7 layer CNN model to perform the classification. Here we show that DL models successfully distinguish seismic waves pre/post mainshock in accord with lab and theoretical expectations of progressive changes in crack density prior to abrupt change at failure and gradual postseismic recovery. Performance is lower for band-pass filtered seismograms (below 10 Hz) suggesting that DL models learn from the evolution of subtle changes in elastic wave attenuation. Tests to verify that our results indeed provide a proxy for fault properties included DL models trained with the wrong mainshock time and those using seismic waves far from the Norcia mainshock; both show degraded performance. Our results demonstrate that DL models have the potential to track the evolution of fault zone properties during the seismic cycle. If this result is generalizable it could improve earthquake early warning and seismic hazard analysis.

58 GEOSCIENCES↗
DOE OSTI2025

Seafloor Seismic Noise Patterns Across the Pacific Basin

Seismic hazard monitoring and global tomography efforts are improved by recording signals at a variety of distances and azimuths to maximize subsurface sampling. Although seismic networks provide good to excellent coverage on land, seafloor stations are still sparse. Inclusion of ocean-based data would greatly improve the global coverage of seismic networks, but the use of seafloor seismic data to complement land-based detection and characterization of events is complicated by the generally much higher ambient noise level in the ocean compared to that observed on land. This noise is driven primarily by sea surface waves and tides, but how seismic noise levels vary with location in the oceans is not well described. Here, in this work, we analyze the relationship between ocean surface wave height and seismic noise in the 0.4–4 Hz frequency band at ocean-bottom seismometer deployments across the Pacific basin. We find that a noise-to-responsiveness ratio (NRR)—the median noise level at a station divided by its sea surface wave height responsiveness—correlates negatively with detection success for large teleseismic earthquakes. Stations that are close to land, with relatively shallow ocean and low wind speed, often have lower NRR than open-ocean stations, but the connection between geographic location and earthquake detection success is imperfect.

58 GEOSCIENCES↗
DOE OSTI2024

Assessing the Value of Seismic Amplitude Versus Offset (AVO) Attributes for CO2 Storage Project Using a Bayesian Network Model for Decision Support

Attributes versus offset (AVO) are a set of measurements to analyze how the characteristics of reflected seismic waves change as a function of the offset. It can be useful for monitoring CO2 storage sites because the presence of leaked CO2 into the overlying aquifer can change the properties of the rocks and pore fluids composition that can alter the way seismic waves reflect and their amplitudes. The time-lapse changes in AVO attributes derived from repeat seismic surveys can help identify anomalies or shifts in the subsurface that could potentially be used as an indicator for CO2 leak detection. Our study leverages multiple seismic attributes derived from synthetic seismic data and Bayesian network model to quantify the probability of leak detection in the overlying aquifer above the storage reservoir. It helps to quantify the value of individual seismic attributes at multiple monitoring periods based upon their sensitivities.

Kumar, Abhash↗
NASA NTRS1971

Air-coupled seismic waves at long range from Apollo launchings.

Microphones and seismographs were co-located in arrays on Skidaway Island, Georgia, for the launchings of Apollo 13 and 14, 374 km to the south. Simultaneous acoustic and seismic waves were recorded for both events at times appropriate to the arrival of the acoustic waves from the source. The acoustic signal is relatively broadband compared to the nearly monochromatic seismic signal; the seismic signal is much more continuous than the more pulse-like acoustic signal; ground loading from the pressure variations of the acoustic waves is shown to be too small to account for the seismic waves; and the measured phase velocities of both acoustic and seismic waves across the local instrument arrays differ by less than 6 per cent and possibly 3 per cent if experimental error is included. It is concluded that the seismic waves are generated by resonant coupling to the acoustic waves along some 10 km of path on Skidaway Island.

Donn, W. L.↗
NASA NTRS1972

Active seismic experiment

The Apollo 16 active seismic experiment (ASE) was designed to generate and monitor seismic waves for the study of the lunar near-surface structure. Several seismic energy sources are used: an astronaut-activated thumper device, a mortar package that contains rocket-launched grenades, and the impulse produced by the lunar module ascent. Analysis of some seismic signals recorded by the ASE has provided data concerning the near-surface structure at the Descartes landing site. Two compressional seismic velocities have so far been recognized in the seismic data. The deployment of the ASE is described, and the significant results obtained are discussed.

Kovach, R. L.↗
NASA NTRS1976

Seismic structure of the moon - A summary of current status

A seismic model of the moon, refined from previous models with the aid of new data and analyses for seismic events recorded by four Apollo lunar seismic stations and a gravimeter, is outlined. The current model has five zones. The crust is 55-60 km thick. The surface is covered by regolith of varying thicknesses and low seismic velocity. The seismic Q's are extremely high. The upper mantle, 250 km thick, is characterized by seismic velocities close to those of the earth's upper mantle, and shear wave Q of about 4000. Tidally controlled deep moonquakes are concentrated near the boundary of the middle mantle, 600-700 km thick. A lower mantle extending to an undetermined depth is characterized by high attenuation of shear waves. The existence of a low-velocity core is only tentatively proposed.

Nakamura, Y.↗
NASA NTRS1981

Seismic energy release of the moon

Lunar seismicity is investigated by calculating various source parameters for a number of shallow and deep-focus moonquakes. The seismic moment, seismic energy release, annual seismic energy release, stress drop, and body-wave magnitude are determined for the largest shallow moonquakes and for large deep-focus events. It is found that the shallow events dominate the lunar seismic energy release, that tidal dissipation may account for the energy release by the deep-focus events, and that the stress drops for the deep-focus events are comparable to or smaller than the calculated tidal stresses. A comparison of the results with terrestrial data indicates that the seismic characteristics of a planet are controlled more by tectonic style and state than by the relative magnitude of the driving forces.

Goins, N. R.↗
NASA NTRS1983

Seismic properties of the crust and uppermost mantle of North America

Seismic refraction profiles for the North American continent were compiled. The crustal models compiled data on the upper mantle seismic velocity (P sub n), the crustal thickness (H sub c) and the average seismic velocity of the crystalline crust (V sub p). Compressional wave parameters were compared with shear wave data derived from surface wave dispersion models and indicate an average value for Poisson's ratio of 0.252 for the crust and of 0.273 for the uppermost mantle. Contour maps illustrate lateral variations in crustal thickness, upper mantle velocity and average seismic velocity of the crystalline crust. The distribution of seismic parameters are compared with a smoothed free air anomaly map of North America and indicate that a complidated mechanism of isostatic compensation exists for the North American continent. Several features on the seismic contour maps also correlate with regional magnetic anomalies.

Braile, L. W.↗
NASA NTRS1991

Martian seismicity through time from surface faulting

An objective of future Mars missions involves emplacing a seismic network on Mars to determine the internal structure of the planet. An argument based on the relative geologic histories of the terrestrial planets suggests that Mars should be seismically more active than the Moon, but less active than the Earth. The seismicity is estimated which is expected on Mars through time from slip on faults visible on the planets surface. These estimates of martian seismicity must be considered a lower limit as only structures produced by shear faulting visible at the surface today are included (i.e., no provision is made for buried structures or non-shear structures); in addition, the estimate does not include seismic events that do not produce surface displacement (e.g., activity associated with hidden faults, deep lithospheric processes or volcanism) or events produced by tidal triggering or meteorite impacts. Calibration of these estimates suggests that Mars may be many times more seismically active than the Moon.

Golombek, M. P.↗
NASA NTRS1991

Scientific Rationale and Requirements for a Global Seismic Network on Mars

Following a brief overview of the mission concepts for a Mars Global Network Mission as of the time of the workshop, we present the principal scientific objectives to be achieved by a Mars seismic network. We review the lessons for extraterrestrial seismology gained from experience to date on the Moon and on Mars. An important unknown on Mars is the expected rate of seismicity, but theoretical expectations and extrapolation from lunar experience both support the view that seismicity rates, wave propagation characteristics, and signal-to-noise ratios are favorable to the collection of a scientifically rich dataset during the multiyear operation of a global seismic experiment. We discuss how particular types of seismic waves will provide the most useful information to address each of the scientific objectives, and this discussion provides the basis for a strategy for station siting. Finally, we define the necessary technical requirements for the seismic stations.

Solomon, Sean C.↗