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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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

GRAIL Refinements to Lunar Seismic Structure

A method to enhance and detect subtle seismic arrivals typically used in terrestrial seismology, is to stack seismograms that have been time shifted to the predicted arrival time of a hypothetical phase of interest. We previously applied this array processing approach to the Apollo lunar seismic data, providing the first direct constraint on the size and state of the Moon's core. The method used travel time predictions made from pre-existing estimates of the crust and mantle velocities and densities and assumed that each of the Moons layers ia a uniform shell with no lateral variation or heterogeneity. In reality the structural properties of the Moon are likely inhomogeneous and vary both laterally and with depth.

Weber, Renee C.↗
NASA NTRS2018

Lessons Learned from Recent Rapid Imaging of Earthquake Ruptures with Satellite Geodesy

Rapid determination of the location and extent of earthquake ruptures at the surface and at depth is helpful for disaster response, as it allows prediction of the likely area of major damage from the earthquake and can help with rescue and recovery planning. The Caltech-Jet Propulsion Laboratory (JPL) Advanced Rapid Imaging and Analysis (ARIA) project has responded to many recent large earthquakes to process geodetic data and help determine the location and extent of ruptures. With the increasing availability of near real-time data from the Global Positioning System (GPS) and other global navigation satellite system receivers in active tectonic regions, and with the shorter repeat times of many recent and newly launched radar satellites, geodetic data can now be obtained quickly after earthquakes or other disasters. We have been building an ARIA data system that can ingest, catalog, and process geodetic data and combine it with seismic analysis to estimate the fault rupture locations and slip distributions for large earthquakes that are on or near land.

Simons, Mark↗
DOE OSTI2024

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗
DOE OSTI2017

Final report of a scalable, automated, semipermanent seismic array (SASSA) method for detecting CO 2 extent during geologic CO 2 injection

The scalable, automated, semipermanent seismic array (SASSA) project led and managed by the Energy & Environmental Research Center (EERC) was designed as a 3-year proof-of-concept study to evaluate and demonstrate an innovative application of the seismic method. The concept was to use a sparse surface array of 96 nodal seismic sensors paired with a single, remotely operated active seismic source at a fixed location to monitor for CO 2 saturation changes in a subsurface reservoir by processing the data for time-lapse changes at individual, strategically chosen reservoir reflection points. The combination of autonomous equipment and modern processing algorithms was used to apply the seismic method in a manner different from the normal paradigm of collecting a spatially dense data set to produce an image. It was used instead to monitor individual, strategically chosen reservoir reflection points for detectable signal character changes that could be attributed to the passing of a CO 2 saturation front or, possibly, changes in reservoir pressure. Data collection occurred over the course of 1 year at an oil field undergoing CO 2 injection for enhanced oil recovery (EOR) and focused on four overlapping “five-spot” EOR injector–producer patterns. Selection, procurement, configuration, installation, and testing of project equipment and collection of five baseline data sets were completed in advance of CO 2 injection within the study area. Weekly remote data collection produced 41 incremental time-lapse records for each of the 96 nodes. Validation was provided by two methods: 1) a conventional 2-D seismic line acquired through the center of the study area before injection started and again after the project ended and processed in a time-lapse manner and 2) by CO 2 saturation maps created from reservoir simulations based on injection and production history matching. Interpreted results were encouraging but mixed, with indications of changes likely due to the presence of CO 2 on some node reflection points where and when effects would be expected and noneffects where no CO 2 was expected, while results at some locations where simulation outputs suggested CO 2 should be present were ambiguous. Acquisition noise impacted interpretation of data at several locations. Many lessons learned were generated by the study to inform and improve results on a follow-up study. The ultimate aim of the project was to evaluate whether deployment of a SASSA technology can provide a useful and cost-effective monitoring solution for future CO 2 injection projects. The answer appears to be affirmative, with the expectation that lessons learned applied to future iterations, together with technology advances, will likely result in significant improvements.

58 GEOSCIENCES↗
DOE OSTI2015

A microseismic workflow for managing induced seismicity risk as CO 2 storage projects

It is well established that fluid injection has the potential to induce earthquakes—from microseismicity to large, damaging events—by altering state-of-stress conditions in the subsurface. While induced seismicity has not been a major operational issue for carbon storage projects to date, a seismicity hazard exists and must be carefully addressed. Two essential components of effective seismic risk management are (1) sensitive microseismic monitoring and (2) robust data interpretation tools. This report describes a novel workflow, based on advanced processing algorithms applied to microseismic data, to help improve management of seismic risk. This workflow has three main goals: (1) to improve the resolution and reliability of passive seismic monitoring, (2) to extract additional, valuable information from continuous waveform data that is often ignored in standard processing, and (3) to minimize the turn-around time between data collection, interpretation, and decision-making. These three objectives can allow for a better-informed and rapid response to changing subsurface conditions.

58 GEOSCIENCES↗
DOE OSTI2019

Insights into Permafrost and Seasonal Active-Layer Dynamics from Ambient Seismic Noise Monitoring

Widespread permafrost thaw in response to changing climate conditions has the potential to dramatically impact ecosystems, infrastructure, and the global carbon budget. Ambient seismic noise techniques allow passive subsurface monitoring that could provide new insights into permafrost vulnerability and active–layer processes. Using nearly 2 years of continuous seismic data recorded near Fairbanks, Alaska, we measured relative velocity variations that showed a clear seasonal cycle reflecting active–layer freeze and thaw. Relative to January 2014, velocities increased up to 3% through late spring, decreased to –8% by late August, then gradually returned to the initial values by the following winter. Velocities responded rapidly (over ~2 to 7 days) to discrete hydrologic events and temperature forcing and indicated that spring snowmelt and infiltration events from summer rainfall were particularly influential in propagating thaw across the site. Velocity increases during the fall zero–curtain captured the re–freezing process and incremental ice formation. Looking across multiple frequency bands (3–30 Hz), negative relative velocities began at higher frequencies earlier in the summer then shifted lower when active–layer thaw deepened, suggesting a potential relationship between frequency and thaw depth; however, this response was dependent on interstation distance. Bayesian tomography returned 2–D time–lapse images identifying zones of greatest velocity reduction concentrated in the western side of the array, providing insight into the spatial variability of thaw progression, soil moisture, and drainage. Furthermore, this study demonstrates the potential of passive seismic monitoring as a new tool for studying site–scale active–layer and permafrost thaw processes at high temporal and spatial resolution.

58 GEOSCIENCES↗
DOE OSTI2021

Intelligent Monitoring System for Real-time Geologic Storage, Optimization, and Reservoir Management

The objective of the subtask was to develop a near-real-time monitoring system for seismic data at the Decatur, IL, geologic carbon sequestration (GCS) site and specifically include fiber-optic cable derived distributed acoustic signal (DAS) data in the process. Owing to the large volumes of data, we opted to utilize existing deep borehole conventional seismic sensors for detection and pull DAS and shallow borehole seismic data once a detection has been made. Unfortunately, the horizontal fiber-optic cables did not yield microseismic signals for use in locating events near the GCS site. Various stacking and filtering approaches were tested without any coherent detection becoming apparent. We attribute the insensitivity to local microseismic events to a lack of coupling in downhole, vertical cable and the non-ideal alignment of the horizontal fiber-optic cable to the vertically polarized seismic energy. Despite the inability to detect and utilize the DAS data from the fiber-optic cables, we developed a general processing framework that enables easy adaptation for future deployment of fiber-optic cables with better suited alignment at Decatur or elsewhere.

Kaven, J. Ole↗
DOE OSTI2021

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗
DOE OSTI2020

Generating Uncertainty Distributions for Seismic Signal Onset Times

Signal arrival-time estimation plays a critical role in a variety of downstream seismic analyses, including location estimation and source characterization. Any arrival-time errors propagate through subsequent data-processing results. In this article, we detail a general framework for refining estimated seismic signal arrival times along with full estimation of their associated uncertainty. Using the standard short-term average/long-term average threshold algorithm to identify a search window, we demonstrate how to refine the pick estimate through two different approaches. In both cases, new waveform realizations are generated through bootstrap algorithms to produce full a posteriori estimates of uncertainty of onset arrival time of the seismic signal. The onset arrival uncertainty estimates provide additional data-derived information from the signal and have the potential to influence seismic analysis along several fronts.

58 GEOSCIENCES↗
DOE OSTI2017

Scalable Metadata Management for a Large Multi-Source Seismic Data Repository

In this work, we implemented the key metadata management components of a scalable seismic data ingestion framework to address limitations in our existing system, and to position it for anticipated growth in volume and complexity. We began the effort with an assessment of open source data flow tools from the Hadoop ecosystem. We then began the construction of a layered architecture that is specifically designed to address many of the scalability and data quality issues we experience with our current pipeline. This included implementing basic functionality in each of the layers, such as establishing a data lake, designing a unified metadata schema, tracking provenance, and calculating data quality metrics. Our original intent was to test and validate the new ingestion framework with data from a large-scale field deployment in a temporary network. This delivered somewhat unsatisfying results, since the new system immediately identified fatal flaws in the data relatively early in the pipeline. Although this is a correct result it did not allow us to sufficiently exercise the whole framework. We then widened our scope to process all available metadata from over a dozen online seismic data sources to further test the implementation and validate the design. This experiment also uncovered a higher than expected frequency of certain types of metadata issues that challenged us to further tune our data management strategy to handle them. Our result from this project is a greatly improved understanding of real world data issues, a validated design, and prototype implementations of major components of an eventual production framework. This successfully forms the basis of future development for the Geophysical Monitoring Program data pipeline, which is a critical asset supporting multiple programs. It also positions us very well to deliver valuable metadata management expertise to our sponsors, and has already resulted in an NNSA Office of Defense Nuclear Nonproliferation commitment to a multi-year project for follow-on work.

58 GEOSCIENCES↗
DOE OSTI2020

Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves

Ultrasonic transmission is sensitive to the spatial variation in mechanical properties of materials due to the presence of cracks/fractures. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-informed unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing. Novelty of the work involves the assignment of both statistically consistent and physically consistent clusters to the measurements of shear waveforms acquired across the one axial and two frontal planes. Physically consistent/relevant information is incorporated by considering the travel time of the peak of spectral energy and transmission coefficient of the transmitted waveform. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. Finally, the proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.

42 ENGINEERING↗
DOE OSTI2013

Anisotropic parameter estimation using velocity variation with offset analysis

Seismic anisotropy is defined as velocity dependent upon angle or offset. Knowledge about anisotropy effect on seismic data is important in amplitude analysis, stacking process and time to depth conversion. Due to this anisotropic effect, reflector can not be flattened using single velocity based on hyperbolic moveout equation. Therefore, after normal moveout correction, there will still be residual moveout that relates to velocity information. This research aims to obtain anisotropic parameters, ε and δ, using two proposed methods. The first method is called velocity variation with offset (VVO) which is based on simplification of weak anisotropy equation. In VVO method, velocity at each offset is calculated and plotted to obtain vertical velocity and parameter δ. The second method is inversion method using linear approach where vertical velocity, δ, and ε is estimated simultaneously. Both methods are tested on synthetic models using ray-tracing forward modelling. Results show that δ value can be estimated appropriately using both methods. Meanwhile, inversion based method give better estimation for obtaining ε value. This study shows that estimation on anisotropic parameters rely on the accuracy of normal moveout velocity, residual moveout and offset to angle transformation.

58 GEOSCIENCES↗
DOE OSTI2015

3D Seismic Experimentation and Advanced Processing/Inversion Development for Investigations of the Shallow Subsurface

The work plan for this project was to develop and apply advanced seismic reflection and wide-angle processing and inversion techniques to high resolution seismic data for the shallow subsurface to seismically characterize the shallow subsurface at hazardous waste sites as an aid to containment and cleanup activities. We proposed to continue work on seismic data that we had already acquired under a previous DoE grant, as well as to acquire additional new datasets for analysis. The project successfully developed and/or implemented the use of 3D reflection seismology algorithms, waveform tomography and finite-frequency tomography using compressional and shear waves for high resolution characterization of the shallow subsurface at two waste sites. These two sites have markedly different near-surface structures, groundwater flow patterns, and hazardous waste problems. This is documented in the list of refereed documents, conference proceedings, and Rice graduate theses, listed below.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Evolution of southern Caribbean plate boundary, vicinity of Trinidad and Tobago

The tectonic evolution of the southeastern corner of the Caribbean is examined, using field data from the El Pilar fault zone of Trinidad and offshore seismic data. It is found that the dominant process in the region's tectonic evolution is strike-slip motion on at least five major fault systems in a 250-km wide east-west-trending plate-boundary zone extending from Grenada in the north to the Orinoco River in the south. The geological effects of this evolution over the past 30 m y are described.

Robertson, Paul↗
NASA NTRS1995

Stresses and Strains within the "Stable" North American Plate

This paper presents a final report on "Stresses and Strains within the "Stable" North American Plate". The topics include: 1) Strain rates near the New Madrid seismic zone; 2) Signal Processing of intermediate term data; and 3) Transform fault stresses and strains. The paper also includes graphs of the stress and strain distributions.

Engeln, Joe↗
DOE OSTI2020

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained), S-wave velocity (km/s), and S-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained). The Updated_MEQ_catalog text file contains event origin time, x(m), y(m), z(m), error in x (m), error in y (m), error in z (m), and RMS misfit (millisecond). The 3D_seismic_P-wave_velocity_model animation file shows slices of the 3D P-wave velocity model. The 3D_seismic_S-wave_velocity_model animation file shows slices of the 3D S-wave velocity model. The Interactive_MEQ_locations API file is an interactive visualization of the updated microseismic event locations. The visualization allows users to view the event locations by dragging, rotating, and zooming in. References: Chai, C., Maceira, M., Santos-Villalobos, H. J., Venkatakrishnan, S. V., Schoenball, M., and EGS Collab Team, 2020, Automatic Seismic Phase Picking Using Deep Learning for the EGS Collab Project, in PROCEEDINGS, 45th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California, 45, 1266-1276.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog from Double-Difference Seismic Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained), S-wave velocity (km/s), and S-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained). The Updated_MEQ_catalog text file contains event origin time, x(m), y(m), z(m), error in x (m), error in y (m), error in z (m), and RMS misfit (millisecond). The 3D_seismic_P-wave_velocity_model animation file shows slices of the 3D P-wave velocity model. The 3D_seismic_S-wave_velocity_model animation file shows slices of the 3D S-wave velocity model. The Interactive_MEQ_location_comparison API file is an interactive visualization of the updated microseismic event locations and the original seismic catalog. The visualization allows users to view and compare the event locations by dragging, rotating, and zooming in. An updated version of 3D_seismic_velocity_model and associated animations were included, which were calculated with a more strict assumption for quality indicators.

15 GEOTHERMAL ENERGY↗
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↗