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DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗

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↗

DOE OSTI2021

Hydraulic fracture mapping using wavelet-based fusion of wave transmission and emission measurements

Fracture characterization is essential to hydrocarbon and geothermal exploration and production as well as carbon geo-sequestration. Active and passive measurements have been extensively applied to map fractures across various scales. Active and passive methods have inherent advantages and limitations that complement each other. Here, in this study, to improve the mapping of embedded fractures and the surrounding geomechanically altered regions, we integrate active shear-wave transmission measurement with passive acoustic-emission measurement collected during a lab-scale hydraulic-fracturing experiment. The proposed data fusion leverages the advantages of the two modalities of measurements, while minimizing their individual limitations. Polarized shear-wave transmission (active) measurement was collected before and after the hydraulic fracturing, and the acoustic emission (passive) measurement was collected during hydraulic fracturing. Two sets of two-dimensional maps of fracture and fracture-induced damage in axial, median and frontal planes were obtained by separately processing active and passive measurements. These 2D maps are then fed to wavelet-based image fusion technique to integrate the two sources of information for the reliable mapping/imaging of the embedded fractures and the surrounding geomechanically altered regions.

58 GEOSCIENCES↗

NASA NTRS1992

Differential shear wave attenuation and its lateral variation in the North Atlantic region

A digital data base of over 150 seismograms and a spectral radio technique are used to measure SS-S differential attenuation in the North Atlantic region. Differential attenuation is positively correlated with SS-S travel time residual, and both differential attentuation and travel time residual decrease with increasing seafloor age. Models are developed for seismic Q in which lateral variations include contributions from the asthenospheric low-Q zone as well as from lithospheric cooling. The Q models obtained under this assumption are in good agreement with those obtained from surface wave studies and are therefore preferred over those models with lateral variations confined to the upper 125 km. Systematic long-wavelength (1000-7000 km) variations in differential attenuation, corrected for seafloor age, are evident along the axis of the Mid-Atlantic Ridge. These variations can be qualitatively correlated with long-wavelength variations in SS-S differential travel time residuals and are attributed to along-axis differences in upper mantle temperature.

Sheehan, Anne F.↗

NASA NTRS2015

Possible Space-Based Gravitational-Wave Observatory Mission Concept

The existence of gravitational waves was established by the discovery of the Binary Pulsar PSR 1913+16 by Hulse and Taylor in 1974, for which they were awarded the 1983 Nobel Prize. However, it is the exploitation of these gravitational waves for the extraction of the astrophysical parameters of the sources that will open the first new astronomical window since the development of gamma ray telescopes in the 1970's and enable a new era of discovery and understanding of the Universe. Direct detection is expected in at least two frequency bands from the ground before the end of the decade with Advanced LIGO and Pulsar Timing Arrays. However, many of the most exciting sources will be continuously observable in the band from 0.1-100 mHz, accessible only from space due to seismic noise and gravity gradients in that band that disturb ground-based observatories. This poster will discuss a possible mission concept, Space-based Gravitational-wave Observatory (SGO-Mid) developed from the original Laser Interferometer Space Antenna (LISA) reference mission but updated to reduce risk and cost.

Livas, Jeffrey C.↗

DOE OSTI2025

Microseismicity Modulation Due To Changes in Geothermal Production at San Emidio, Nevada, USA

Brief cessations of geothermal production can induce seismicity, a phenomenon that has drawn increasing attention in recent years. Such observations are rare, and the underlying mechanism requires careful analysis. In April 2022, a dense seismic and hydrologic monitoring system was deployed at the San Emidio geothermal field, Nevada, to accompany a planned power plant shutdown. Using the dense seismic array data, we detected and located ∼1,800 microseismic events (MSEs) and developed a high-resolution tomographic P-wave velocity model. We observed substantially increased microseismicity during shutdown. Most MSEs occurred on pre-existing normal faults, which are contained within extremely low-velocity zones that are likely damaged, fluid-filled, and hydraulically connected to nearby production wells. Hydrologic data show rapid fluid pressure increases of <60 kPa following the shutdown. We suggest that the cessation of production rapidly increased fluid pressures along pre-existing fault zones, activating critically stressed fault patches and fractures and producing microseismicity.

Guo, Hao [University of Wisconsin-Madison, WI (Uni↗

DOE OSTI2023

Infrasound Detections of Low-Magnitude Earthquakes: Preliminary Results of the West Texas Acoustic Experiment

Infrasound observations have grown increasingly important for the monitoring of earthquakes. While large earthquakes generate infrasound that can be detected thousands of kilometers away, there are few near-field observations of infrasound generated by low-magnitude events. We describe preliminary results of the West Texas Acoustic Experiment, during which infrasound sensors collected continuous data in the Permian Basin for a six-month period spanning January—June 2023. During this time, more than 1000 earthquakes with magnitudes between 1.2 and 4.2 occurred within 50 km of the network. We used spectral analysis, array processing, and manual inspection of waveforms to evaluate arrivals of infrasound signals following 84 events with magnitudes between 2.5 and 4.2. Here, we describe eight such events and the infrasound signals associated with each. We find detections of seismic-to-acoustic infrasound signals associated with seven events. We also find strong evidence of a laterally-propagating, purely acoustic wave generated by an M2.9 earthquake.

58 GEOSCIENCES↗

DOE OSTI2026

Seismic velocity modeling and earthquake relocations for the southern Nevada National Security Site (NNSS), with a focus on Rock Valley

The Rock Valley Direct Comparison (RV/DC) is the third phase of the Source Physics Experiment (SPE; Snelson et al., 2014), a project aimed at improving seismic discrimination between explosive sources and natural earthquakes. Phases I and II of SPE focused on studying the generation of shear waves in endmember geologies (granite and alluvium, respectively), while Phase III aims to detonate a chemical explosion co-located with the source region of the 1993 Rock Valley earthquake sequence, located in the Rock Valley Fault Zone (RVFZ), in the southern portion of the Nevada Test Site (now the Nevada National Security Site, or NNSS).

58 GEOSCIENCES↗

DOE OSTI2020

Crustal Structure of the Mesopotamian Plain, East of Iraq

The crustal structure of Iraq was investigated through analyzing teleseismic data from 12 new seismic stations. Three seismic stations are located within the Zagros Fold-Thrust Belt, and nine are within the Mesopotamian Plain. Joint inversion of P wave receiver function and Rayleigh wave dispersion data were employed to resolve S wave velocity structure models beneath each station. Combining these models with available Moho depths within and around the study area reveals that the Moho depth is smoothly increasing from the Arabian platform toward the Zagros Mountains. Further, an exceptional deeper root is observed near the eastern edge of the Mesopotamian Plain where sedimentary pile is the thickest. This root was interpreted as a structure inherited from the successive Mesozoic rifting of the NE Arabian platform enhanced by sedimentary loading and progressive subsidence. A low-velocity uppermost mantle was observed beneath the Arabian Foredeep attesting the existence of a low-strength lithospheric mantle beneath the region southwest from the Zagros deformation front. The weak rheology of the uppermost mantle may have allowed local sinking of the crust and deepening of the Moho boundary due to vertical loading and the Late Miocene lateral contraction.

58 GEOSCIENCES↗

DOE OSTI2021

Seismic Visibility of Eclogite in the Earth’s Upper Mantle—Implications From High Pressure‐Temperature Single‐Crystal Elastic Properties of Omphacite

Abstract Identifying and locating the geochemical and geophysical heterogeneities in the Earth’s interior is one of the most important and challenging tasks for the deep Earth scientists. Subducted oceanic crust metamorphizes into the dense eclogite in the upper mantle and is considered as a major cause of geochemical and geophysical heterogeneities in the deep Earth. In order to detect eclogitic materials inside the Earth, precise measurements of the high pressure‐temperature single‐crystal elasticity of major minerals in eclogite are thus exceedingly important. Omphacite, a Na,Al‐bearing clinopyroxene, constitutes up to 75 vol% of eclogite. In the present study, we performed the first high pressure‐temperature single‐crystal elasticity measurements of omphacite using Brillouin spectroscopy. Utilizing the finite‐strain approach, we obtained the following thermoelastic parameters for omphacite: K S0 ’ = 4.5(1), G 0 ’ = 1.53(5), ∂K S0 /∂ T = −0.029(5) GPa/K, ∂G 0 /∂ T = −0.013(5) GPa/K, with K S0 = 123(3) GPa, G 0 = 74(2) GPa, and ρ 0 = 3.34(1) g/cm 3 . We found that the seismic velocities of undeformed eclogite are similar to pyrolite at the depths of 200–300 and 410–500 km, thus eclogite is seismically invisible at these depths. Combined with the lattice‐preferred orientations of the omphacite in naturally deformed eclogites, we also modeled seismic anisotropy of eclogite at various pressure‐temperature conditions. A 10 km thick subducted eclogitic crust can result in ∼0.2 s shear wave splitting in the Earth’s upper mantle.

Hao, Ming↗

DOE OSTI2026

WaveDP

We developed a robust deep learning model designed to effectively reduce background noise and measure signal arrival times from seismic waveforms. This model processes a 57-second, three-component seismogram to predict the probability of Primary (P) and Secondary (S) waves for each timestamp, while also generating a denoised seismogram. Training was conducted using the benchmark STEAD dataset, which includes globally distributed earthquake signals recorded at local distances ranging from 0 to 350 kilometers.

Chai, Chengping [Oak Ridge National Laboratory (OR↗

DOE OSTI2025

A Deep Learning-Aided Workflow for Decoding the Stress Regime of Southern Nevada

The Rock Valley fault zone in southern Nevada has a notable history of seismic activity and is the site of a future direct comparison experiment of explosion and earthquake sources. This study aims to gain insight into regional tectonic processes by leveraging recent advances in seismic monitoring capabilities to elucidate the local stress regime. A crucial step in this investigation is the accurate determination of P-wave first-motion polarities, which play a vital role in resolving earthquake focal mechanisms of small earthquakes. Here, we deploy a deep learning-based method for automatic determination of first-motion polarities to vastly expand the polarity dataset beyond what has been reviewed by human analysts. By the integrating P-wave polarities with new measurements of S/P amplitude ratios, we obtain robust focal mechanism estimates for 1306 earthquakes with a local magnitude of 1 and above occurring between 2010 and 2023 in southern Nevada. We then use the focal mechanism catalog to examine the regional stress orientation, confirming an overall trans-tensional stress regime with smaller scale complexities illuminated by individual earthquake sequences. These findings demonstrate how detailed analyses of small earthquakes can provide fundamental information for understanding earthquake processes in the region and inform future experiments at the Nevada National Security Site.

58 GEOSCIENCES↗

DOE OSTI2021

Using onset times from frequent geophysical surveys to understand reservoir fluid flow and to estimate flow properties

Seismic characterization of flow properties is a difficult prospect, due to the indirect relationship between permeability and seismic velocity and attenuation. At best, seismic time-lapse changes can detect the effects of saturation and pressure changes in a reservoir due to fluid flow. Even in this case, the interpretation of the seismic observation in terms of the state of the reservoir depends intimately on the properties of the rock physics model, which are usually poorly known. The onset time, the calendar time of geophysical changes, provides an alternative datum for characterizing properties such as reservoir permeability. The main advantage of an onset time is that it is sensitive to the flow properties of the reservoir yet insensitive to the details of the rock physics model. Two examples of the utility of onset times are discussed: The use of travel time shifts induced by the injection of carbon dioxide between two wells, and the time-lapse time shifts for elastic waves propagating through a reservoir undergoing enhanced oil recovery. In both examples, the onset times are mapped into permeability estimates using a trajectory-based approach akin to seismic tomography.

58 GEOSCIENCES↗

NASA NTRS2010

Seismic Constraints on Interior Solar Convection

We constrain the velocity spectral distribution of global-scale solar convective cells at depth using techniques of local helioseismology. We calibrate the sensitivity of helioseismic waves to large-scale convective cells in the interior by analyzing simulations of waves propagating through a velocity snapshot of global solar convection via methods of time-distance helioseismology. Applying identical analysis techniques to observations of the Sun, we are able to bound from above the magnitudes of solar convective cells as a function of spatial convective scale. We find that convection at a depth of r/R(solar) = 0.95 with spatial extent l < 30, where l is the spherical harmonic degree, comprise weak flow systems, on the order of 15 m/s or less. Convective features deeper than r/R(solar) = 0.95 are more difficult to image due to the rapidly decreasing sensitivity of helioseismic waves.

Hanasoge, Shravan M.↗

DOE OSTI2023

Emulation of seismic-phase traveltimes with machine learning

SUMMARY We present a machine learning (ML) method for emulating seismic-phase traveltimes that are computed using a global-scale 3-D earth model and physics-based ray tracing. Accurate traveltime predictions based on 3-D earth models are known to reduce the bias of event location estimates, increase our ability to assign phase labels to seismic detections and associate detections to events. However, practical use of 3-D models is challenged by slow computational speed and the unwieldiness of pre-computed lookup tables that are often large and have prescribed computational grids. In this work, we train a ML emulator using pre-computed traveltimes, resulting in a compact and computationally fast way to approximate traveltimes that are based on a 3-D earth model. Our model is trained using approximately 850 million P-wave traveltimes that are based on the global LLNL-G3D-JPS model, which was developed for more accurate event location. The training-set consists of traveltimes between 10 393 global seismic stations and randomly sampled event locations that provide a prescribed, distance-dependent geographic sample density for each station. Prediction accuracy is dependent on event-station distance and whether the station was included in the training set. For stations included in the training set the mean absolute deviation (MAD) of the difference between traveltimes computed using ray tracing through the 3-D model and the ML emulator for local, regional, and teleseismic distances are 0.090, 0.125 and 0.121 s, respectively. For tested station locations not included in the training set, MAD values for the three distance ranges increase to 0.173, 0.219 and 0.210 s, respectively. Empirical traveltime residuals for a global reference data are indistinguishable when ML emulation or the 3-D model is used to compute traveltimes. This result holds regardless of whether the recording station is used in ML training or not.

58 GEOSCIENCES↗

DOE OSTI2022

Crustal and uppermost mantle structure of Cape Verde from ambient noise tomography

SUMMARY We present a seismic ambient noise tomography of the Cape Verde archipelago, located in the Atlantic Ocean, approximately 600 km west of Senegal. We used 38 seismic broad-band stations that continuously recorded for 10 months, in order to construct the first 3-D model of Sv-wave velocities for the crust and uppermost mantle beneath the Cape Verde region. We started by computing phase cross-correlations for vertical component recordings using all possible inter-island station pairs. Next, a time–frequency phase-weighted stack was applied to obtain robust Rayleigh-wave group-velocity dispersion curves in the period band between 10 and 24 s. Group-velocity maps at different periods are obtained by inverting the dispersion curves. We then inverted the group-velocity maps to obtain the 3-D shear wave velocity structure of the crust and uppermost mantle beneath Cape Verde. The final 3-D model extends from 8 km down to 23 km and has a lateral resolution of about 50 km. The crust in the southwestern sector, encompassing Fogo, presents lower S-wave velocities that may be caused by the presence of melt pockets and/or hydrothermal fluids circulation. The uppermost mantle beneath the northwestern sector is characterized by higher S-wave velocities in agreement with previous results obtained from Ps and Sp receiver functions. Those high-velocity anomalies can reflect non-altered crust or remnants of magma chambers or solidified basaltic intrusions, which fed the volcanism in these islands. Our maps revealed the presence of crustal underplating across the entire archipelago, yet stronger beneath the groups Santo Antão—São Vicente—São Nicolau and Fogo—Santiago—Maio.

Carvalho, J. (ORCID:0000000310778994)↗

NASA NTRS2018

Impact-Seismic Investigations of the InSight Mission

Impact investigations will be an important aspect of the InSight mission. One of the scientific goals of the mission is a measurement of the current impact rate at Mars. Impacts will additionally inform the major goal of investigating the interior structure of Mars. In this paper, we review the current state of knowledge about seismic signals from impacts on the Earth, Moon, and laboratory experiments. We describe the generalized physical models that can be used to explain these signals. A discussion of the appropriate source time function for impacts is presented, along with spectral characteristics including the cutoff frequency and its dependence on impact momentum. Estimates of the seismic efficiency (ratio between seismic and impact energies) vary widely. Our preferred value for the seismic efficiency at Mars is 5 × 10−4, which we recommend using until we can measure it during the InSight mission, when seismic moments are not used directly. Effects of the material properties at the impact point and at the seismometer location are considered. We also discuss the processes by which airbursts and acoustic waves emanate from bolides, and the feasibility of detecting such signals. We then consider the case of impacts on Mars. A review is given of the current knowledge of present-day cratering on Mars: the current impact rate, characteristics of those impactors such as velocity and directions, and the morphologies of the craters those impactors create. Several methods of scaling crater size to impact energy are presented. The Martian atmosphere, although thin, will cause fragmentation of impactors, with implications for the resulting seismic signals. We also benchmark several different seismic modeling codes to be used in analysis of impact detections, and those codes are used to explore the seismic amplitude of impactinduced signals as a function of distance from the impact site. We predict a measurement of the current impact flux will be possible within the timeframe of the prime mission (one Mars year) with the detection of ∼ a few to several tens of impacts. However, the error bars on these predictions are large. Specific to the InSight mission, we list discriminators of seismic signals from impacts that will be used to distinguish them from marsquakes. We describe the role of the InSight Impacts Science Theme Group during mission operations, including a plan for possible night-time meteor imaging. The impacts detected by these methods during the InSight mission will be used to improve interior structure models, measure the seismic efficiency, and calculate the size frequency distribution of current impacts.

Ingrid Daubar↗

NASA NTRS2012

Multi-Parameter Observation and Detection of Pre-Earthquake Signals in Seismically Active Areas

The recent large earthquakes (M9.0 Tohoku, 03/2011; M7.0 Haiti, 01/2010; M6.7 L Aquila, 04/2008; and M7.9 Wenchuan 05/2008) have renewed interest in pre-anomalous seismic signals associated with them. Recent workshops (DEMETER 2006, 2011 and VESTO 2009 ) have shown that there were precursory atmospheric /ionospheric signals observed in space prior to these events. Our initial results indicate that no single pre-earthquake observation (seismic, magnetic field, electric field, thermal infrared [TIR], or GPS/TEC) can provide a consistent and successful global scale early warning. This is most likely due to complexity and chaotic nature of earthquakes and the limitation in existing ground (temporal/spatial) and global satellite observations. In this study we analyze preseismic temporal and spatial variations (gas/radon counting rate, atmospheric temperature and humidity change, long-wave radiation transitions and ionospheric electron density/plasma variations) which we propose occur before the onset of major earthquakes:. We propose an Integrated Space -- Terrestrial Framework (ISTF), as a different approach for revealing pre-earthquake phenomena in seismically active areas. ISTF is a sensor web of a coordinated observation infrastructure employing multiple sensors that are distributed on one or more platforms; data from satellite sensors (Terra, Aqua, POES, DEMETER and others) and ground observations, e.g., Global Positioning System, Total Electron Content (GPS/TEC). As a theoretical guide we use the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model to explain the generation of multiple earthquake precursors. Using our methodology, we evaluated retrospectively the signals preceding the most devastated earthquakes during 2005-2011. We observed a correlation between both atmospheric and ionospheric anomalies preceding most of these earthquakes. The second phase of our validation include systematic retrospective analysis for more than 100 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. Calculated false alarm ratio for the for the same month over the entire period of analysis (2003-2009) is less than 10% and was d as the earthquakes. The commonalities in detecting atmospheric/ionospheric anomalies show that they may exist over both land and sea in regions of maximum stress (i.e., along plate boundaries) Our results indicate that the ISTF model could provide a capability to observe pre-earthquake atmospheric/ionospheric signals by combining this information into a common framework.

Ouzounov, D.↗