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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Analysis of seismic moment tensors and in situ stress during Enhanced Geothermal System development at The Geysers geothermal field, California

Seismicity in the vicinity of an Enhanced Geothermal System (EGS) demonstration project in the Northwest Geysers at the Prati 32 (P-32) injection well and the Prati State 31 (PS-31) production well is investigated to determine earthquake focal mechanisms, moment magnitudes and in situ stress of events that occur before and during reservoir stimulation starting 2011 October 6. We present a catalogue of 167 waveform-based seismic moment tensors ranging in moment magnitude from 0.6 to 3.9. The moment tensor catalogue is subsequently used to invert for the stress tensor and to investigate possible temporal stress changes resulting from fluid injection. We find an approximate 15-degree counter-clockwise rotation of the least compressive stress σ3 during injection. More remarkable is a change in orientation of the maximum compressive stress σ1 from subhorizontal to vertical when injection operations temporarily cease. The orientation of σ1 returns to subhorizontal when injection operations resume. It is found that there was a systematic reduction in the stress shape factor, R, as the injected water volume increases, indicating an evolution towards a more transtensional stress state.

58 GEOSCIENCES↗
DOE OSTI2017

Decentralized Interleaving of Paralleled Dc-Dc Buck Converters

We present a decentralized control strategy that yields switch interleaving among parallel-connected dc-dc buck converters. The proposed method is based on the digital implementation of the dynamics of a nonlinear oscillator circuit as the controller. Each controller is fully decentralized, i.e., it only requires the locally measured output current to synthesize the pulse width modulation (PWM) carrier waveform and no communication between different controllers is needed. By virtue of the intrinsic electrical coupling between converters, the nonlinear oscillator-based controllers converge to an interleaved state with uniform phase-spacing across PWM carriers. To the knowledge of the authors, this work presents the first fully decentralized strategy for switch interleaving in paralleled dc-dc buck converters.

14 SOLAR ENERGY↗
DOE OSTI2022

Making Invisible Visible: Data-Driven Seismic Inversion With Spatio-Temporally Constrained Data Augmentation

Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of obtaining data through expensive physical experiments, instruments, and simulations, data augmentation techniques for scientific applications have emerged as a new direction for obtaining scientific data recently. However, existing data augmentation techniques originating from computer vision yield physically unacceptable data samples that are not helpful for the domain problems that we are interested in. In this article, we develop new data augmentation techniques based on convolutional neural networks. Specifically, our generative models leverage different physics knowledge (such as governing equations, observable perception, and physics phenomena) to improve the quality of the synthetic data. To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO 2 leakage data. Our interest is to invert for subsurface velocity models associated with very small CO 2 leakage. We validate the performance of our methods using comprehensive numerical tests. Here via comparison and analysis, we show that data-driven seismic imaging can be significantly enhanced by using our data augmentation techniques. Particularly, the imaging quality has been improved by 15% in test scenarios of general-sized leakage and 17% in small-sized leakage when using an augmented training set obtained with our techniques.

58 GEOSCIENCES↗
DOE OSTI2020

Time Resolution Measurements of EJ-232Q With Single- and Dual-Sided Readouts

In view of its importance to applications in high energy physics, nuclear security, and time-of-flight PET, the time resolution of 0.5% benzophenone-quenched EJ-232Q plastic scintillators of various lengths was studied using a fast waveform digitizer and fast PMTs. The scintillator sizes were 5 mm × 5 mm × 10, 25, 50, 75, or 100 mm. First, the timing measurements were performed by using a single PMT reading out one end. The degradation in time resolution with increasing scintillator length was studied. The irradiation geometry was also observed to have a non-negligible impact on the time resolution due to the variation of depth-of-interaction positions, especially for the scintillators with a high aspect ratio. Second, two PMTs were employed for a dual-sided readout. This readout together with the mean time method was demonstrated to be an effective approach to improve the timing performance since the depth-of-interaction-related effect was considerably mitigated. A time resolution of 79 ± 1 ps (full-width at half-maximum) has been achieved for the 5 × 5 × 10 mm 3 scintillator. The 5 × 5 × 100 mm 3 scintillator can still provide a time resolution as good as 172 ± 1 ps. Here, the energy range used for each was between 340 keVee and 450 keVee. In addition, the time information from individual PMTs in a dual-sided readout was able to show a time resolution almost identical to that determined with the mean-time-based technique after correcting for the depth-of-interaction variation for the 100 mm long scintillator.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

OFDM Radar Space-Time Adaptive Processing by Exploiting Spatio-Temporal Sparsity

We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. We observe that the target and interference spectra are inherently sparse in the spatio-temporal domain. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data and produces an equivalent performance as the other existing STAP techniques. In addition, the use of an OFDM signal increases the frequency diversity of our system, as different scattering centers of a target resonate at different frequencies, and thus improves the target detectability. First, we formulate a realistic sparse-measurement model for an OFDM radar considering both the clutter and jammer as the interfering sources. Then, we apply a residual sparse-recovery technique based on the LASSO estimator to estimate the target and interference covariance matrices, and subsequently compute the optimal STAP-filter weights. Our numerical results demonstrate a comparative performance analysis of the proposed sparse-STAP algorithm with four other existing STAP methods. Furthermore, we discover that the OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.

adaptive waveform design.↗
DOE OSTI2017

Multistep inversion workflow for 3D long-offset damped elastic waves in the Fourier domain

We present a new workflow for imaging damped three-dimensional elastic wavefields in the Fourier domain. The workflow employs a multiscale imaging approach, in which offset lengths are laddered, where frequency content and damping of the data are changed cyclically. Thus, the inversion process is launched using short-offset and low-frequency data to recover the long spatial wavelength of the image at a shallow depth. Increasing frequency and offset length leads to the recovery of the fine-scale features of the model at greater depths. For the fixed offset, we employ (in the imaging process) a few discrete frequencies with a set of Laplace damping parameters. The forward problem is solved with a finite-difference frequency-domain method based on a massively parallel iterative solver. The inversion code is based upon the solution of a least squares optimisation problem and is solved using a nonlinear gradient method. It is fully parallelised for distributed memory computational platforms. Our full-waveform inversion workflow is applied to the 3D Marmousi-2 and SEG/EAGE Salt models with long-offset data. The maximum inverted frequencies are 6 Hz for the Marmousi model and 2 Hz for the SEG/EAGE Salt model. The detailed structures are imaged successfully up to the depth approximately equal to one-third of the maximum offset length at a resolution consistent with the inverted frequencies.

3D full waveform inversion↗
DOE OSTI2022

Flicker: A review of temporal light modulation stimulus, responses, and measures

Flicker has been an important lighting system consideration for over a century. More precise terms are temporal light modulation (TLM) as the stimulus, and responses to TLM as the unwanted visual, cognitive, or physiological consequences. As lighting technology evolved, different forms of TLM emerged, and so did responses to them. Today, some LED systems – encompassing the LED, driver, and control – can result in TLM causing severe unwanted effects, while other LED systems produce no unwanted effects at all. LED systems can deliver a much wider range of luminous waveforms than conventional lighting systems, some exhibiting very high modulation depths. More than any light source before, they can elicit perceptions of the phantom array. Direct flicker effects at modulation frequencies less than about 80 Hz and the stroboscopic effect at frequencies greater than 80 Hz are fairly well understood, but the phantom array effect needs more exploration and characterisation. This review focuses on the technology and research history that led to current metrics for quantifying TLM and human responses to TLM. Notably, visually impaired individuals may exhibit alterations in their response to TLM, but such a discussion is beyond the intent of this review. Thus, the focus is on individuals with normal visual function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Joint physics-based and data-driven time-lapse seismic inversion: Mitigating data scarcity

In carbon capture and sequestration (CCS), developing rapid and effective imaging techniques is crucial for real-time monitoring of the spatial and temporal dynamics of CO 2 propagation during/after injection. With continuing improvements in computational power and data storage, data-driven techniques based on machine learning (ML) have been effectively applied to seismic inverse problems. In particular, ML helps alleviate the ill-posedness and high computational cost of full-waveform inversion (FWI). However, such data-driven inversion techniques require massive high-quality training data sets to ensure prediction accuracy, which hinders their application to time-lapse monitoring of CO 2 sequestration. We propose an efficient “hybrid” time-lapse workflow that combines physics-based FWI and data-driven ML inversion. The scarcity of the available training data is addressed by developing a new data-generation technique with physics constraints. The method is vali dated on a synthetic CO 2 -sequestration model based on the Kimberlina storage reservoir in California. The proposed approach is shown to synthesize a large volume of high-quality, physically realistic training data, which is critically important in accurately characterizing the CO 2 movement in the reservoir. In conclusion, the developed hybrid methodology can also simultaneously predict the variations in velocity and saturation and achieve high spatial resolution in the presence of realistic noise in the data.

58 GEOSCIENCES↗
DOE OSTI2022

Assessing the Effectiveness of Generalized Likelihood Ratio Test Detector Schemes in Seismic Event Detection and the Avoidance of Nontarget Signals

Cross-correlation techniques have played a long-standing and pivotal role in seismic event monitoring. However, the performance of correlation-based detectors is challenged by nuisance seismicity, or nontarget signals. Such detections are a problem when the mission is to automatically map events to the correct source region. Using aftershocks of the 2014 $M_w$ 6.0 South Napa, California, earthquake, we demonstrate the effectiveness of utilizing a dynamic correlation processor framework in a generalized likelihood ratio test (GLRT) detector configuration to minimize nontarget detections. A GLRT maximizes a detection statistic with respect to one or more unknown parameters. In this case, the detection statistic is a template signal match against the waveform in a window sliding over a data stream, and the unknown parameter is an index variable indicating group membership of the template event or events. Detected events are assigned to the event group that yields the largest detection statistic. In this work, our results show that a GLRT detector will outperform a suite of independently operating correlation and subspace detectors in terms of having a lower nontarget detection rate at a given missed detection rate. We also show that a GLRT detector composed of a few high-rank subspace detectors has a slightly higher nontarget detection rate, but a significantly lower missed detection rate, than a GLRT detector composed of many low-rank subspace detectors. The high-rank GLRT configuration produced impressive results even with marginal data (single channel, single station, and very low time bandwidth product), which bodes well for the utility of building efficient aftershock classification systems and global monitoring systems at larger scales. However, future work is required to assess performance at the regional scale and to assess the performance of the system at detecting target events not used in the detector template creation.

58 GEOSCIENCES↗
DOE OSTI2017

Continued Data Acquisition Development

This task focused on improving techniques for integrating data acquisition of secondary particles correlated in time with detected cosmic-ray muons. Scintillation detectors with Pulse Shape Discrimination (PSD) capability show the most promise as a detector technology based on work in FY13. Typically PSD parameters are determined prior to an experiment and the results are based on these parameters. By saving data in list mode, including the fully digitized waveform, any experiment can effectively be replayed to adjust PSD and other parameters for the best data capture. List mode requires time synchronization of two independent data acquisitions (DAQ) systems: the muon tracker and the particle detector system. Techniques to synchronize these systems were studied. Two basic techniques were identified: real time mode and sequential mode. Real time mode is the preferred system but has proven to be a significant challenge since two FPGA systems with different clocking parameters must be synchronized. Sequential processing is expected to work with virtually any DAQ but requires more post processing to extract the data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2019

Overlapping localized exponential time differencing methods for diffusion problems

The localized exponential time differencing (ETD) based on overlapping domain decomposition has been recently introduced for extreme-scale phase field simulations of coarsening dynamics, which displays excellent parallel scalability in supercomputers. This paper serves as the first step toward building a solid mathematical foundation for this approach. We study the overlapping localized ETD schemes for a model time-dependent diffusion equation discretized in space by the standard central difference. Two methods are proposed and analyzed for solving the fully discrete localized ETD systems: the first one is based on Schwarz iteration applied at each time step and involves solving stationary problems in the subdomains at each iteration, while the second one is based on the Schwarz waveform relaxation algorithm in which time-dependent subdomain problems are solved at each iteration. The convergences of the associated iterative solutions to the corresponding fully discrete localized ETD solution and to the exact semidiscrete solution are rigorously proved. Finally, numerical experiments are also carried out to confirm theoretical results and to compare the performance of the two methods.

58 GEOSCIENCES↗
DOE OSTI2017

Decentralized Interleaving of Paralleled Dc-Dc Buck Converters: Preprint

We present a decentralized control strategy that yields switch interleaving among parallel connected dc-dc buck converters without communication. The proposed method is based on the digital implementation of the dynamics of a nonlinear oscillator circuit as the controller. Each controller is fully decentralized, i.e., it only requires the locally measured output current to synthesize the pulse width modulation (PWM) carrier waveform. By virtue of the intrinsic electrical coupling between converters, the nonlinear oscillator-based controllers converge to an interleaved state with uniform phase-spacing across PWM carriers. To the knowledge of the authors, this work represents the first fully decentralized strategy for switch interleaving of paralleled dc-dc buck converters.

14 SOLAR ENERGY↗
DOE OSTI2019

Analysis of Cygnus Electrical Signals

The United States initiated the Subcritical Experiment (SCE) program to support a stockpile stewardship mission shortly after the 1992 moratorium on underground nuclear testing was established. Many SCE’s are conducted at the Nevada National Security Site (NNSS) in Nevada. Cygnus is a high-energy radiation generating device (RGD) located and operated at the NNSS and is a primary diagnostic for the SCE program. The Cygnus Dual Beam Radiographic Facility consists of two identical radiographic sources, Cygnus 1 and Cygnus 2. From creation of the high power V-I drive to energy transport and X-ray conversion at the rod-pinch diode, the Cygnus machines utilize the following components: oil-filled Marx generator, water-filled pulse-forming line (PFL), water-filled coaxial transmission line (CTL), three-cell vacuum induction voltage adder (IVA), and rod-pinch diode. The diode pulse has the following electrical specifications: 2.25 MV, 60 kA, 60 ns. Each source has the following X-ray specifications: 1 mm diameter, 4 rad at 1 m, and 50 ns radiation pulse. SCEs are both single-event and high-value; therefore, a high level of performance in reliability and reproducibility are key issues of Cygnus. Prior to executing such a SCE, there are a formidable number of shots (e.g., each of the two Cygnus RGDs charging and discharging properly into the rod-pinch diode load) that must be executed to determine reliability and reproducibility of the Cygnus RGDs. For every shot on Cygnus, voltages and currents along the machine are recorded and analyzed. In this paper we summarize attributes of the voltage and current waveforms at different locations using distribution plots. These distribution plots are used to quantify the reliability and reproducibility for Cygnus. This analysis methodology will provide a standard to trouble shoot results of individual Cygnus shots, and also to monitor long term Cygnus performance. Accordingly, this type of extensive analysis will contribute to optimized Cygnus performance on SCEs.

42 ENGINEERING↗
DOE OSTI2019

A progressive deep transfer learning approach to cycle-skipping mitigation in FWI, In SEG Technical Program Expanded Abstracts 2019, pp. 2348-2352. Society of Exploration Geophysicists, 2019.

To effectively mitigate the cycle-skipping phenomenon in full waveform inversion (FWI), we developed an inception-based deep learning neural network to reconstruct the absent low frequency data by exploiting the subsurface low wavenumber information buried in the acquired high frequency data. Two unique features of our deep learning network for the low frequency data reconstruction are 1) Dual Data Feed; 2) Progressive Transfer Learning. With the Dual Data Feed feature, not only the high frequency data, but also the corresponding Beat Tone data are fed into the neural network, significantly reducing the network complexity and the network training cost. The Progressive Transfer Learning technique enables us to initiate the deep learning network with only one training dataset. Unlike other deep learning approaches in this category, our training dataset is not fixed. Instead, the training dataset and the network accuracy are progressively enhanced in an iterative manner within the Progressive Transfer Learning workflow. The numerical experiments validated that the low frequency data reconstructed by this progressive transfer learning network are sufficiently accurate for a successful FWI inversion without suffering from the cycle-skipping without any priori geological information.

58 GEOSCIENCES↗
DOE OSTI2015

On the validation of seismic imaging methods: Finite frequency or ray theory?

Abstract We investigate the merits of the more recently developed finite‐frequency approach to tomography against the more traditional and approximate ray theoretical approach for state of the art seismic models developed for western North America. To this end, we employ the spectral element method to assess the agreement between observations on real data and measurements made on synthetic seismograms predicted by the models under consideration. We check for phase delay agreement as well as waveform cross‐correlation values. Based on statistical analyses on S wave phase delay measurements, finite frequency shows an improvement over ray theory. Random sampling using cross‐correlation values identifies regions where synthetic seismograms computed with ray theory and finite‐frequency models differ the most. Our study suggests that finite‐frequency approaches to seismic imaging exhibit measurable improvement for pronounced low‐velocity anomalies such as mantle plumes.

58 GEOSCIENCES↗
DOE OSTI2014

Large earthquake processes in the northern Vanuatu subduction zone

Abstract The northern Vanuatu (formerly New Hebrides) subduction zone (11°S to 14°S) has experienced large shallow thrust earthquakes with M w > 7 in 1966 ( M S 7.9, 7.3), 1980 ( M w 7.5, 7.7), 1997 ( M w 7.7), 2009 ( M w 7.7, 7.8, 7.4), and 2013 ( M w 8.0). We analyze seismic data from the latter four earthquake sequences to quantify the rupture processes of these large earthquakes. The 7 October 2009 earthquakes occurred in close spatial proximity over about 1 h in the same region as the July 1980 doublet. Both sequences activated widespread seismicity along the northern Vanuatu subduction zone. The focal mechanisms indicate interplate thrusting, but there are differences in waveforms that establish that the events are not exact repeats. With an epicenter near the 1980 and 2009 events, the 1997 earthquake appears to have been a shallow intraslab rupture below the megathrust, with strong southward directivity favoring a steeply dipping plane. Some triggered interplate thrusting events occurred as part of this sequence. The 1966 doublet ruptured north of the 1980 and 2009 events and also produced widespread aftershock activity. The 2013 earthquake rupture propagated southward from the northern corner of the trench with shallow slip that generated a substantial tsunami. The repeated occurrence of large earthquake doublets along the northern Vanuatu subduction zone is remarkable considering the doublets likely involved overlapping, yet different combinations of asperities. The frequent occurrence of large doublet events and rapid aftershock expansion in this region indicate the presence of small, irregularly spaced asperities along the plate interface.

Cleveland, K. Michael↗
DOE OSTI2016

A new algorithm for three‐dimensional joint inversion of body wave and surface wave data and its application to the Southern California plate boundary region

Abstract We introduce a new algorithm for joint inversion of body wave and surface wave data to get better 3‐D P wave ( V p ) and S wave ( V s ) velocity models by taking advantage of the complementary strengths of each data set. Our joint inversion algorithm uses a one‐step inversion of surface wave traveltime measurements at different periods for 3‐D V s and V p models without constructing the intermediate phase or group velocity maps. This allows a more straightforward modeling of surface wave traveltime data with the body wave arrival times. We take into consideration the sensitivity of surface wave data with respect to V p in addition to its large sensitivity to V s , which means both models are constrained by two different data types. The method is applied to determine 3‐D crustal V p and V s models using body wave and Rayleigh wave data in the Southern California plate boundary region, which has previously been studied with both double‐difference tomography method using body wave arrival times and ambient noise tomography method with Rayleigh and Love wave group velocity dispersion measurements. Our approach creates self‐consistent and unique models with no prominent gaps, with Rayleigh wave data resolving shallow and large‐scale features and body wave data constraining relatively deeper structures where their ray coverage is good. The velocity model from the joint inversion is consistent with local geological structures and produces better fits to observed seismic waveforms than the current Southern California Earthquake Center (SCEC) model.

Fang, Hongjian↗