Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Seismic Data Compression”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Applying Compression-Based Metrics to Seismic Data in Support of Global Nuclear Explosion Monitoring

The analysis of seismic data for evidence of possible nuclear explosion testing is a critical global security mission that relies heavily on human expertise to identify and mark seismic signals embedded in background noise. To assist analysts in making these determinations, we adapted two compression distance metrics for use with seismic data. First, we demonstrated that the Normalized Compression Distance (NCD) metric can be adapted for use with waveform data and can identify the arrival times of seismic signals. Then we tested an approximation for the NCD called Sliding Information Distance (SLID), which can be computed much faster than NCD. We assessed the accuracy of the SLID output by comparing it to both the Akaike Information Criterion (AIC) and the judgments of expert seismic analysts. Our results indicate that SLID effectively identifies arrival times and provides analysts with useful information that can aid their analysis process.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2015

Elastic-Waveform Inversion with Compressive Sensing for Sparse Seismic Data

Accurate velocity models of compressional- and shear-waves are essential for geothermal reservoir characterization and microseismic imaging. Elastic-waveform inversion of multi-component seismic data can provide high-resolution inversion results of subsurface geophysical properties. However, the method requires seismic data acquired using dense source and receiver arrays. In practice, seismic sources and/or geophones are often sparsely distributed on the surface and/or in a borehole, such as 3D vertical seismic profiling (VSP) surveys. We develop a novel elastic-waveform inversion method with compressive sensing for inversion of sparse seismic data. We employ an alternating-minimization algorithm to solve the optimization problem of our new waveform inversion method. We validate our new method using synthetic VSP data for a geophysical model built using geologic features found at the Raft River enhanced-geothermal-system (EGS) field. We apply our method to synthetic VSP data with a sparse source array and compare the results with those obtained with a dense source array. Our numerical results demonstrate that the velocity models produced with our new method using a sparse source array are almost as accurate as those obtained using a dense source array.

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 OSTI2021

A Consensus Equilibrium Approach for 3-D Land Seismic Shots Recovery

Physical and budget constraints often result in inadequate sampling for accurate subsurface imaging. Preprocessing approaches, such as missing trace interpolation, are typically employed to enhance seismic data in such cases. The compressed sensing (CS) framework has been applied for modeling missing seismic data, which is estimated by sparsity-based computational algorithms. While existing work mainly focuses on recovering missing traces resulting from receiver subsampling, source subsampling has greater economical advantages, as sources are more expensive than receivers. Moreover, stronger image models different from sparsity have not been explored for source recovery. This work presents a consensus equilibrium (CE) approach to recover missing seismic shots, which enables to incorporate various regularization operators modeling different data priors. Here, simulation results from a real 3-D land seismic dataset demonstrate that the CE approach provides more accurate estimations of the linear and hyperbolic events in the recovered shots, compared with pure sparsity-based reconstructions.

58 GEOSCIENCES↗
DOE OSTI2022

Deep compressed seismic learning for fast location and moment tensor inferences with natural and induced seismicity

Fast detection and characterization of seismic sources is crucial for decision-making and warning systems that monitor natural and induced seismicity. However, besides the laying out of ever denser monitoring networks of seismic instruments, the incorporation of new sensor technologies such as Distributed Acoustic Sensing (DAS) further challenges our processing capabilities to deliver short turnaround answers from seismic monitoring. In response, this work describes a methodology for the learning of the seismological parameters: location and moment tensor from compressed seismic records. In this method, data dimensionality is reduced by applying a general encoding protocol derived from the principles of compressive sensing. The data in compressed form is then fed directly to a convolutional neural network that outputs fast predictions of the seismic source parameters. Thus, the proposed methodology can not only expedite data transmission from the field to the processing center, but also remove the decompression overhead that would be required for the application of traditional processing methods. An autoencoder is also explored as an equivalent alternative to perform the same job. We observe that the CS-based compression requires only a fraction of the computing power, time, data and expertise required to design and train an autoencoder to perform the same task. Implementation of the CS-method with a continuous flow of data together with generalization of the principles to other applications such as classification are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Effect of Carbon on the Volume of Solid Iron at High Pressure: Implications for Carbon Substitution in Iron Structures and Carbon Content in the Earth’s Inner Core

Understanding the effect of carbon on the density of hcp (hexagonal-close-packed) Fe-C alloys is essential for modeling the carbon content in the Earth’s inner core. Previous studies have focused on the equations of state of iron carbides that may not be applicable to the solid inner core that may incorporate carbon as dissolved carbon in metallic iron. Carbon substitution in hcp-Fe and its effect on the density have never been experimentally studied. We investigated the compression behavior of Fe-C alloys with 0.31 and 1.37 wt % carbon, along with pure iron as a reference, by in-situ X-ray diffraction measurements up to 135 GPa for pure Fe, and 87 GPa for Fe-0.31C and 109 GPa for Fe-1.37C. The results show that the incorporation of carbon in hcp-Fe leads to the expansion of the lattice, contrary to the known effect in body-centered cubic (bcc)-Fe, suggesting a change in the substitution mechanism or local environment. The data on axial compressibility suggest that increasing carbon content could enhance seismic anisotropy in the Earth’s inner core. The new thermoelastic parameters allow us to develop a thermoelastic model to estimate the carbon content in the inner core when carbon is incorporated as dissolved carbon hcp-Fe. The required carbon contents to explain the density deficit of Earth’s inner core are 1.30 and 0.43 wt % at inner core boundary temperatures of 5000 K and 7000 K, respectively.

58 GEOSCIENCES↗
DOE OSTI2021

Utah FORGE: Seismic Velocity Models, February 2021

This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. The paper summary follows: We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2-5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ~22 degrees to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity. Reference: Zhang, H. and K. L. Pankow (2021). High-resolution Bayesian spatial auto-correlation (SPAC) pseudo-3D Vs model of Utah FORGE site with a dense geophone array, Geophys. Res. Int, https://doi.org/10.1093/gji/ggab049

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

CODAS Data from Oliktok Point, Beaufort Sea, Alaska

Cryosphere/Ocean Distributed Acoustic Sensing (CODAS) data collected from the Beaufort Sea, Alaska, using ~37.4 km of dark telecommunications fiber located at Oliktok Point, Alaska. Data were collected with a Silixa iDAS, using 10 m gauge length, 2 m spatial resolution, and 1000 Hz sample rate. Provided here are the DAS-recorded time series for the rapid refreeze event described in Baker & Abbott (2022) (see link below). This covers a date range of 2021-11-10 15:00 UTC to 2021-11-11 17:00 UTC. Data have been decimated to 100 Hz and 20 m (i.e., every 10th channel for 1831 channels, total), as used in Baker & Abbott (2022). Data have been extracted from raw format into 1-hour long .sac* files and organized into directories by channel number, spanning channels 100 to 18400. Time series units are nano-strainrate (nm/m/s). For distribution, data have been compressed into .zip files containing all time series files for 100 channels. *For information on the Seismic Analysis Code (SAC) file format: https://seiscode.iris.washington.edu/projects/sac

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Screening IMS Seismic Detections using Dynamic Correlation Processor: Progress report for 2020

LLNL completed the FY20 workplan entailing application of the Dynamic Correlation Processor (DCP) to International Monitoring System (IMS) primary seismic data in 2019 and 2020. The effective analysis period was curtailed to January 1 through November 12, 2019 due to a data compression change that rendered later data unusable. Fixing the data compression error is a priority for our data source, and we plan to extend the period of data analysis when the fix is implemented. We found that the percentage overlap between detections generated by the International Data Centre (IDC) DFX software and detections generated by DCP varied widely by station. Overlap is 30-40% at some stations, suggesting that a large percentage of DFX detections could be screened (removed) from the detection-event association algorithm. However, detection overlap was much lower, a few percent, at many stations and the percentage overlap was low at stations known to have many mines and other local sources of seismicity. Unexpectedly low detection overlap at many stations prompted us to examine results for the ARCES station in detail. There is considerable mine activity near ARCES, but our initial FY20 analysis found only ~2% DCP/DFX detection overlap. Differences in the pre-processing (e.g. beam recipes) used by DCP and DFX appear to be the cause of low detection overlap at ARCES. DCP uses wideband filters to improve detector robustness and the IDC uses narrow-band pre-filtering to improve sensitivity. After reprocessing ARCES using the IDC beam recipe, DCP/DFX overlap increased to ~74%. This result shows that we must reprocess the IMS network using the IDC station-specific beam recipes if we are to effectively screen DFX detections and improve automatic event building performance at the IDC.

58 GEOSCIENCES↗
DOE OSTI2025

Seismic Tremors From Sea‐Landfast Ice Interactions Near Utqiaġvik, Alaska

The mechanical state of Arctic landfast sea ice remains poorly constrained due to limited observations. This study investigates interactions between drifting sea ice and the coastal landfast ice near Utqiaġvik, Alaska by integrating data from broadband seismometer, Distributed Acoustic Sensing, and marine radar. We find that decreases in sea ice velocity, marking transitions from drift to compressive contact, coincide with increased seismic energy. Tremor characteristics vary seasonally with ice conditions. In January, dense ice packs produced sustained harmonic tremors with gliding and U-shaped spectral features, consistent with repetitive stick-slip motion at the ice–ice or ice–ground interface under velocity-weakening friction. In April, smaller fragmented floes generated short-lived, chaotic tremors linked to brittle failure and spatially dispersed impacts. These findings demonstrate that seismic tremors encode the mechanical properties of interacting ice, offering a new tool to distinguish ice regimes and monitor evolving Arctic coastal dynamics under climate change.

58 GEOSCIENCES↗
DOE OSTI2016

Surface uplift and time-dependent seismic hazard due to fluid injection in eastern Texas

Observations that unequivocally link seismicity and wastewater injection are scarce. We show that wastewater injection in eastern Texas causes uplift, detectable in radar interferometric data up to >8 kilometers from the wells. Using measurements of uplift, reported injection data, and a poroelastic model, we computed the crustal strain and pore pressure. We infer that an increase of >1 megapascal in pore pressure in rocks with low compressibility triggers earthquakes, including the 4.8–moment magnitude event that occurred on 17 May 2012, the largest earthquake recorded in eastern Texas. Seismic activity increased even while injection rates declined, owing to diffusion of pore pressure from earlier periods with higher injection rates. Finally, induced seismicity potential is suppressed where tight confining formations prevent pore pressure from propagating into crystalline basement rocks.

58 GEOSCIENCES↗
DOE OSTI2016

Reducing Disk Storage of Full-3D Seismic Waveform Tomography (F3DT) Through Lossy Online Compression

Full-3D seismic waveform tomography (F3DT) is the latest seismic tomography technique that can assimilate broadband, multi-component seismic waveform observations into high-resolution 3D subsurface seismic structure models. The main drawback in the current F3DT implementation, in particular the scattering-integral implementation (F3DT-SI), is the high disk storage cost and the associated I/O overhead of archiving the 4D space-time wavefields of the receiver- or source-side strain tensors. The strain tensor fields are needed for computing the data sensitivity kernels, which are used for constructing the Jacobian matrix in the Gauss-Newton optimization algorithm. In this study, we have successfully integrated a lossy compression algorithm into our F3DT SI workflow to significantly reduce the disk space for storing the strain tensor fields. The compressor supports a user-specified tolerance for bounding the error, and can be integrated into our finite-difference wave-propagation simulation code used for computing the strain fields. The decompressor can be integrated into the kernel calculation code that reads the strain fields from the disk and compute the data sensitivity kernels. During the wave-propagation simulations, we compress the strain fields before writing them to the disk. To compute the data sensitivity kernels, we read the compressed strain fields from the disk and decompress them before using them in kernel calculations. Experiments using a realistic dataset in our California statewide F3DT project have shown that we can reduce the strain-field disk storage by at least an order of magnitude with acceptable loss, and also improve the overall I/O performance of the entire F3DT-SI workflow significantly. The integration of the lossy online compressor may potentially open up the possibilities of the wide adoption of F3DT-SI in routine seismic tomography practices in the near future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Complicated Link Between Material Properties and Microfracture Density for an Underground Explosion in Granite

Geophysical techniques are often implemented as quick and inexpensive ways to locate and characterize fractures in the subsurface, which is important for a number of geoscience fields. Seismic velocities are the most widely used proxies for identification of fractures, but the correlation is not always well-defined. In this study we present material property data: unconfined compressive strength (UCS), bulk density (ρ), Young's modulus (E), Poisson's ratio (ν), P wave velocity (V p ), and S wave velocity (V s ), in conjunction with microfracture densities measured on samples of granite collected before and after underground chemical explosions. Results indicate the relationship between fractures and material properties is complex, even in this single-lithology environment. We interpret that this complexity arises from varying fracture mechanisms (e.g. dilation-inducing fractures vs compression-inducing fractures) in different parts of the core, due to differences in stress conditions. Additional complexity may result from chemical interactions between the fresh fractures and the fluids in the area. Water content appears to have a significant, if not dominant, role in the unconfined compressive strength (UCS) of the samples. We suggest caution when using elastic property measurements as a proxy for fracturing in areas of explosion-induced damage, or in other areas where a variety of mechanisms induce fracturing.

58 GEOSCIENCES↗
DOE OSTI2018

Unconfined Compression Results on Core from Borehole U-15n#10, NNSS, in support of SPE

The Nevada National Security Site (NNSS) serves as the geologic setting for a Source Physics Experiment (SPE) program. The SPE provides ground truth data to create and improve strong ground motion and seismic S-wave generation and propagation models. The NNSS was chosen as the test bed because it provides a variety of geologic settings ranging from relatively simple to very complex. Each series of SPE testing will comprise the setting and firing of explosive charges (source) placed in a central borehole at varying depths and recording ground motions in instrumented boreholes located in two rings around the source, positioned at different radii. Modeling using advanced simulation codes will be performed both before and after each test to predict ground response and to improve models based on acquired field data, respectively. A key component in the predictive capability and ultimate validation of the models is the full understanding of the intervening geology between the source and the instrumented boreholes including the geomechanical behavior of the site's rock/structural features. This memorandum reports on an initial phase of unconfined compression testing from corehole U-15n#10. Specimens tested came from the U-15n#10 core hole, which was drilled at -60° to the horizontal in granitic rock (quartz monzonite) after the second SPE shot (SPE-2). Figure 1 illustrates at the surface, the core hole was approximately 90 feet from the central SPE borehole. Corehole U 15n#10 intersects the central SPE borehole (U-15n) at a core depth of 170 feet (approximately 150 feet vertical depth) which is within the highly damaged zone of SPE-2. The U-15n#10 location is the site of the first, second and third SPE's, in Area 15 of the NNSS.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Unconfined Compression Results on Core from Boreholes U-15n#12 and U-15n#13, NNSS in support of SPE

The Nevada National Security Site (NNSS) serves as the geologic setting for a Source Physics Experiment (SPE) program. The SPE provides ground truth data to create and improve strong ground motion and seismic S-wave generation and propagation models. The NNSS was chosen as the test bed because it provides a variety of geologic settings ranging from relatively simple to very complex. Each series of SPE testing will comprise the setting and firing of explosive charges (source) placed in a central borehole at varying depths and recording ground motions in instrumented boreholes located in two rings around the source, positioned at different radii. Modeling using advanced simulation codes will be performed both before and after each test to predict ground response and to improve models based on acquired field data, respectively. A key component in the predictive capability and ultimate validation of the models is the full understanding of the intervening geology between the source and the instrumented boreholes including the geomechanical behavior of the site's rock/structural features. This report summarizes unconfined compression testing (UCS) from coreholes U-15n#12 and U-15n#13 and compares those datasets to UCS results from coreholes U-15n and U-15n#10. U-15n#12 corehole was drilled at -60° to the horizontal and U-15n#13 was drilled vertically in granitic rock (quartz monzonite) after the third SPE shot. Figure 1 illustrates at the surface, U 15n#12 and U-15n#13 coreholes were approximately 30 meters and 10 meters from the central SPE borehole (U-15n) respectively. Corehole U-15n#12 intersects the central SPE borehole (U 15n) at a core depth of 174 feet (approximately 150 feet vertical depth). The location of U 15n#12 and U-15n#13 is the site of the first, second and third SPE's, in Area 15 of the NNSS.

58 GEOSCIENCES↗