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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Convolutional Neural Networks for Signal Detection

Currently, traditional methods such as short-term average/long-term average (STA/LTA) are used to detect arrivals in three-component seismic waveform data. Accurately establishing the identity and arrival of these waves is helpful in detecting and locating seismic events. Convolutional Neural Networks (CNNs) have been shown to significantly improve performance at local distances. This work will expand the use of CNNs to more remote distances and lower magnitudes. Sandia National Labs (SNL) will explore the advantages and limits of a particular approach and investigate requirements for expanding this technique to different types, distances, and magnitudes of events in the future. The team will describe detailed performance results of this method tuned on a curated dataset from Utah with its expert-defined arrival picks.

58 GEOSCIENCES↗
NASA NTRS2019

The Seismic Experiment for Interior Structure (SEIS): Experiment Data Distribution

The six sensors of SEIS (The Seismic Experiment for Interior Structure) [- one of three primary instruments on NASA's Mars Lander Insight] cover a broad range of the seismic bandwidth, from 0.01 hertz to 50 hertz, with possible extension to longer periods. Data are transmitted in the form of three continuous VBB (Very Broad-Band) components at 2 samples per second (sps), an estimation of the short period (SP) energy content from the SP at 1 sps, and a continuous compound VBB/SP vertical axis at 10 sps. The continuous streams are augmented by requested event data with sample rates from 20 to 100 sps. SEIS data products are downlinked from the spacecraft in raw CCSDS (Consultative Committee for Space Data Systems) packets and converted to both the Standard for the Exchange of Earthquake Data (SEED) format files and ASCII tables (GeoCSV) for analysis and archiving. Metadata are available in dataless SEED and StionXML. Time series data (waveforms) are available in miniseed and GeoCSV. Data are distributed according to FDSN (Federation of Digital Seismograph Networks - http://www.fdsn.org) formats and interfaces. Wind, pressure and temperature data from the Auxiliary Payload Sensor Suite (APSS) will also be available in SEED format, and can be used for decorrelation and diagnostic purposes on SEIS.

Pardo, Constanza↗
DOE OSTI2022

Utah FORGE - Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study

This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model was developed using RMS velocities of the seismic reflection survey and seismic velocity logs from borehole measurements as an input model. To improve the accuracy of the model in the shallow subsurface, travel times phase arrivals of the direct propagating P-waves were determined from the seismic reflection data, using PhaseNet, a deep-neural-network-based seismic arrival time picking method. The travel times were subsequently inverted using the input velocity model. The seismic resolution study used borehole and surface seismic sensors as well as the seismicity observed during the April 2022 stimulation experiment to estimate the seismic resolution in the activated fracture reservoir. The data contain a 3D P- and S-wave velocity model for the larger FORGE area.

15 GEOTHERMAL ENERGY↗
NASA NTRS1978

Passive seismic experiment - A summary of current status

The data set obtained from the four-station Apollo seismic network including signals from approximately 11,800 events, is surveyed. Some refinement of the lunar model will result, but its gross features remain the same. Attention is given to the question of a small, molten lunar core, the answer to which remains dependent on analysis of signals from a far side impact. Seventy three sources of repeating, deep moonquakes have been identified, thirty nine of which have been accurately located. Concentrated at depths from 800 to 1000 km, the periodicities of these events have led to the hypothesis that they are generated by tidal stresses. Lunar seismic data has also indicated that the meteoroid population is ten times lower than originally determined from earth based observations. Lunar seismic activity is much lower and mountainous masses show no sign of sinking, in contrast to earth, as a result of the lunar crust being four times thicker. While much work remains to be done, significant correlation between terrestrial and lunar observations can be seen.

Latham, G. V.↗
DOE OSTI2022

A deep learning-enhanced framework for multiphysics joint inversion

Joint inversion has drawn considerable attention due to the availability of multiple geophysical data sets, ever-increasing computational resources, the development of advanced algorithms, and its ability to reduce inversion uncertainty. A key issue of joint inversion is to develop effective strategies to link different geophysical data in a unified mathematical framework, in which the information obtained from different models can complement each other. We have developed a deep learning-enhanced joint inversion framework to simultaneously reconstruct different physical models by fusing different types of geophysical data. Traditionally, structure similarity constraints are pursued by joint inversion algorithms using manually crafted formulations (e.g., cross gradient). The constraint is constructed by a deep neural network (DNN) during the learning process. The framework is designed to combine the DNN and a traditional independent inversion workflow and improve the joint inversion result iteratively. The network can be easily extended to incorporate multiphysics without structural changes. Numerical experiments on the joint inversion of 2D DC resistivity data and seismic traveltime are used to validate our method. In addition, this learning-based framework demonstrates excellent generalization abilities when tested on data sets using different geologic structures. It also can handle different sensing configurations and nonconforming discretization.

Geochemistry & Geophysics↗
NASA NTRS1993

Geophysical inferences of thermal-chemical structures in the lower mantle

Lateral variations of the temperature field in the lower mantle have been reconstructed using new results in mineral physics and seismic tomographic data. We show that, with the application of high-pressure experimental values of thermal expansivity and of sound velocities, the slow seismic anomalies in the lower mantle under the Pacific and Africa can be converted into realistic-looking plume structures with large dimensions of 0(1000 km). The outer fringes of the plumes have an excess temperature of around 400 K. In the core of the plumes are found tonguelike structures with extremely high thermal anomalies. These values can exceed 1200 K and are too high to be explained on the basis of thermal anomalies alone. We suggest that these major plumes in the deep mantle may be driven by both thermal and chemical buoyancies or that enhanced conductive heat-transfer may be important there.

Yuen, D. A.↗
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 OSTI2024

DE-FE0029488 - North Dakota Integrated Carbon Capture and Storage Complex Feasibility Study Public Data

Data from award DE-FE0029488 - North Dakota Integrated Carbon Capture and Storage Complex Feasibility Study performed by the Energy & Environmental Research Center including the following: - 2D Seismic {Input data, sgy files, maps, logs, and descriptors} - Core Petrophysics {Core analysis of plugs from the two stratigraphic test wells (Flemmer-1 [API 33-057-00039] and BNI-1 [API 33-065-00018])} - North Dakota Oil and Gas File No 37380 Files - North Dakota Oil and Gas File No 37672 Files - Well Testing Data {Summary of well testing methods and results from the stratigraphic test wells (Flemmer-1 and BNI-1)} Additional References: https://www.netl.doe.gov/sites/default/files/2017-12/Wesley-Peck-_Mastering-the-Subsurface_CarbonSAFE-Phase-II_August-2017-final.pdf Peck, W.D., Ayash, S.C., Klapperich, R.J., Gorecki, C.D. (2019) The North Dakota integrated carbon storage complex feasibility study, International Journal of Greenhouse Gas Control, Volume 84, 2019, Pages 47-53, https://doi.org/10.1016/j.ijggc.2019.03.001

Carbon Storage↗
DOE OSTI2023

Detectable Changes in U1a Data [Slides]

This is an update presentation on U1a data analytics for the Advanced Data Analytics for Proliferation Detection Tech Exchange Meeting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data-driven time-scale separation of ODE right-hand sides using dynamic mode decomposition and time delay embedding

Multi-physics simulation often involves multiple different scales. The ARKODE ODE solver package in the SUNDIALS library addresses multi-scale problems with a multi-rate time-integrator that can work with a right-hand side that has fast scale and slow scale components. In this report, we use dynamic mode decomposition and time delay embedding to extract the fast and slow components of the right-hand sides of a simple ODE from data. We then use the extracted components to solve the ODE with ARKODE. Finally, to move towards a real-world use case, we attempt to extract fast and slow scale dynamics from synthetic seismic modeling data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

A model of convergent plate margins based on the recent tectonics of Shikoku, Japan

A viscoelastic finite element plate tectonic model is applied to displacement data for the island of Shikoku, Japan. The flow properties and geometry of the upper portions of the earth are assumed known from geophysical evidence, and the loading characteristics are determined from the model. The nature of the forces acting on the Philippine Sea plate, particularly in the vicinity of the Nankai trough, is determined. Seismic displacement data related to the 1946 Nankaido earthquake are modeled in terms of a thick elastic plate overlying a fluidlike substratum. The sequence of preseismic and seismic displacements can be explained in terms of two independent processes operating on elastic lithospheric plates: a strain accumulation process caused by vertical downward forces acting on or within the lithosphere in the vicinity of the trench, and a strain release process caused by plate failure along a preexisting zone on weakness. This is a restatement of Reid's elastic rebound theory in terms of elastic lithospheric plates.

Bischke, R. E.↗
DOE OSTI2026

Regularization by denoising diffusion models for solving inverse PDE problems with application to full waveform inversion

Partial differential equation (PDE)-governed inverse problems are fundamental across various scientific and engineering applications; yet they face significant challenges due to nonlinearity, ill-posedness, and sensitivity to noise. Here, we introduce a computational framework, regularization by denoising using diffusion models for partial differential equations (RED-DiffEq), by integrating physics-driven inversion and data-driven learning. RED-DiffEq leverages pretrained diffusion models as a regularization mechanism for PDE-governed inverse problems. We apply RED-DiffEq to solve the full waveform inversion problem in geophysics, a challenging seismic imaging technique that seeks to reconstruct high-resolution subsurface velocity models from seismic measurement data. Our method shows enhanced accuracy and robustness compared to benchmark methods. Additionally, it exhibits strong generalization and domain decomposition capacity, enabling the inversion of more complex velocity models with larger domains than those used in training the diffusion model. Our framework can also be directly applied to diverse PDE-governed inverse problems.

Shan, Siming [Yale University, New Haven, CT (Unit↗
DOE OSTI2022

Seismic Waveform Inversion Capability on Resource-Constrained Edge Devices

Seismic full wave inversion (FWI) is a widely used non-linear seismic imaging method used to reconstruct subsurface velocity images, however it is time consuming, has high computational cost and depend heavily on human interaction. Recently, deep learning has accelerated it’s use in several data-driven techniques, however most deep learning techniques suffer from overfitting and stability issues. In this work, we propose an edge computing-based data-driven inversion technique based on supervised deep convolutional neural network to accurately reconstruct the subsurface velocities. Deep learning based data-driven technique depends mostly on bulk data training. In this work, we train our deep convolutional neural network (DCN) (UNet and InversionNet) on the raw seismic data and their corresponding velocity models during the training phase to learn the non-linear mapping between the seismic data and velocity models. The trained network is then used to estimate the velocity models from new input seismic data during the prediction phase. The prediction phase is performed on a resource-constrained edge device such as Raspberry Pi. Raspberry Pi provides real-time and on-device computational power to execute the inference process. In addition, we demonstrate robustness of our models to perform inversion in the presence on noise by performing both noise-aware and no-noise training and feeding the resulting trained models with noise at different signal-to-noise (SNR) ratio values. We make great efforts to achieve very feasible inference times on the Raspberry Pi for both models. Specifically, the inference times per prediction for UNet and InversionNet models on Raspberry Pi were 22 and 4 s respectively whilst inference times for both models on the GPU were 2 and 18 s which are very comparable. Finally, we have designed a user-friendly interactive graphical user interface (GUI) to automate the model execution and inversion process on the Raspberry Pi.

Manu, Daniel (ORCID:0000000154982677)↗
NASA NTRS1974

Lunar near-surface structure

Seismic refraction data obtained at the Apollo 14, 16, and 17 landing sites permit a compressional wave velocity profile of the lunar near surface to be derived. Beneath the regolith at the Apollo 14 Fra Mauro site and the Apollo 16 Descartes site is material with a seismic velocity of about 300 m/sec, believed to be brecciated material or impact-derived debris. Considerable detail is known about the velocity structure at the Apollo 17 Taurus-Littrow site. Seismic velocities of 100, 327, 495, 960, and 4700 m/sec are observed. The depth to the top of the 4700-m/sec material is 1385 m, compatible with gravity estimates for the thickness of mare basaltic flows, which fill the Taurus-Littrow valley. The observed magnitude of the velocity change with depth and the implied steep velocity-depth gradient of more than 2 km/sec/km are much larger than have been observed on compaction experiments on granular materials and preclude simple cold compaction of a fine-grained rock powder to thicknesses of the order of kilometers.

Cooper, M. R.↗
DOE OSTI2024

Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage

The project Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The South Carolina Research Foundation and partners evaluated the feasibility of CCS in the Jurassic/ Triassic (J / TR) saline formations of the buried Mesozoic South Georgia Rift (SGR) Basin that extends from South Carolina into Georgia. The J / TR sequence, based on preliminary assessment of limited geologic and geophysical data, appears to have both the appropriate areal extent and multiple horizons to permanently and safely store CO2 The presence of several igneous rock layers within the sequence may potentially provide adequate seals to prevent upward CO2 migration into the Coastal Plain aquifer systems. Approximately 81 kilometers of 2-D seismic reflection data were collected by Bay Geophysical, Inc. to explore a portion of the SGR located in southern Georgia. The 81 kilometers were divided into two lines approximately 40.5 kilometers each, with Line 1 intersecting Georgia well GGS 3457. Line 2 intersects Line 1 at the southern portion of Line 1 to maximize the extent of coverage away from GGS-3457 (a deep well drilled in the 1980s for oil and gas exploration). This well had a set of usable logs, including gamma and neutron logs that provided promising results related to CO2 storage. Results showed sandstone with porosity values greater than 10 percent and a thickness of 120 meters. The design of the seismic shot was to extrapolate information away from the well and to better define the extent of the SGR and the necessary reservoir and caprock for a successful CO2 injection. A numerical simulation model of CO2 Injection and migration was developed based on the geology log for the GGS-3457 well. The simulation model was used to investigate the feasibility of injecting 30 million metric tons of CO2 into SGR J / TA sediments and integrity of the diabase layers as seals to prevent CO2 migration.

2-D seismic↗
DOE OSTI2020

A method to fuse multiphysics waveforms and improve predictive explosion detection: theory, experiment and performance

Natural and human-made sources of transient energy often emit multiple geophysical signatures that include mechanical and electromagnetic waveforms. We present a constructive method to fuse and evaluate statistics that we derive from such multiphysics waveforms that improves our capability to detect small, near-ground explosions over similar methods that consume single signature waveforms. Our method advances Fisher's Combined Probability Test (Fisher's Method) to operate under both hypotheses of a binary test on noisy data and provide researchers with the density functions required to forecast the ability of Fisher's Method to screen fused explosion signatures from noise. We apply this method against 12 d, multisignature explosion and noise records to show (1) that a fused multiphysics waveform statistic that combines radio, acoustic and seismic waveform data can identify explosions roughly 0.8 magnitude units lower than an acoustic emission, STA/LTA detector for the same detection probability and (2) that we can quantitatively predict how this fused, multiphysics statistic performs with Fisher's Method. Our work thereby offers a baseline method for predictive waveform fusion that supports multiphenomenological explosion monitoring (multiPEM) and is applicable to any binary testing problem in observational geophysics.

58 GEOSCIENCES↗
NASA NTRS1993

Plate tectonics and crustal deformation around the Japanese Islands

We analyze over a century of geodetic data to study crustal deformation and plate motion around the Japanese Islands, using the block-fault model for crustal deformation developed by Matsu'ura et al. (1986). We model the area including the Japanese Islands with 19 crustal blocks and 104 faults based on the distribution of active faults and seismicity. Geodetic data are used to obtain block motions and average slip rates of faults. This geodetic model predicts that the Pacific plate moves N deg 69 +/- 2 deg W at about 80 +/- 3 mm/yr relative to the Eurasian plate which is much lower than that predicted in geologic models. Substantial aseismic slip occurs on the subduction boundaries. The block containing the Izu Peninsula may be separated from the rigid part of the Philippine Sea plate. The faults on the coast of Japan Sea and the western part of the Median Tectonic Line have slip rates exceeding 4 mm/yr, while the Fossa Magna does not play an important role in the tectonics of the central Japan. The geodetic model requires the division of northeastern Japan, contrary to the hypothesis that northeastern Japan is a part of the North American plate. Owing to rapid convergence, the seismic risk in the Nankai trough may be larger than that of the Tokai gap.

Hashimoto, Manabu↗
NASA NTRS1985

Kinematics of a large-scale intraplate extending lithosphere: The Basin-Range

Upper lithospheric structure of the Cordilleran Basin Range (B-R) is characterised by an E-W symmetry of velocity layering. The crust is 25 km thick on its eastern active margin, thickening to 30 km within the central portion and thinning to approx. 25 km on the west. Pn velocities of 7.8 to 7.9 km/s characterize the upper mantle low velocity cushion, 7.4 km/s to 7.5 km/s, occurs at a depth of approx. 25 km in the eastern B-R and underlies the area of active extension. An upper-crustal low-velocity zone in the eastern B-R shows a marked P-wave velocity inversion of 7% at depths of 7 to 10 km also in the area of greatest extension. The seismic velocity models for this region of intraplate extension suggest major differences from that of a normal, thermally underformed continental lithosphere. Interpretations of seismic reflection data demonstrate the presence of extensive low-angle reflections in the upper-crust of the eastern B-R at depths from near-surface to 7 to 10 km. These reflections have been interpreted to represent low-angle normal fault detachments or reactivated thrusts. Seismic profiles across steeply-dipping normal faults in unconsolidated sediments show reflections from both planar to downward flatening (listric) faults that in most cases do not penetrate the low-angle detachments. These faults are interpreted as late Cenozoic and cataclastic mylonitic zones of shear displacement.

Smith, R. B.↗