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At least 523 records · Page 29

International Monitoring System Correlation Detection at the North Korean Nuclear Test Site at Punggye-ri with Insights from the Source Physics Experiment

Seismic waveform correlation offers the prospect of greatly reducing event detection thresholds when compared with more conventional processing methods. Correlation is applicable for seismic events that in some sense repeat, that is they have very similar waveforms. A number of recent studies have shown that correlated seismic signals may form a significant fraction of seismicity at regional distances. For the particular case of multiple nuclear explosions at the same test site, regional distance correlation also allows very precise relative location measurements and could offer the potential to lower thresholds when multiple events exist. Using the Comprehensive Nuclear-Test-Ban Treaty (CTBT) International Monitoring System (IMS) seismic array at Matsushiro, Japan (MJAR), Gibbons and Ringdal (2012) were able to create a multichannel correlation detector with a very low false alarm rate and a threshold below magnitude 3.0. They did this using the 2006 or 2009 Democratic People’s Republic of Korea (DPRK) nuclear explosion as a template to search through a data stream from the same station to find a match via waveform correlation. In this paper, we extend the work of Gibbons and Ringdal (2012) and measure the correlation detection threshold at several other IMS arrays. We use this to address three main points. First, we show the IMS array station at Mina, Nevada (NVAR), which is closest to the Nevada National Security Site (NNSS), is able to detect a chemical explosion that is well under 1 ton with the right template. Second, we examine the two IMS arrays closest to the North Korean (DPRK) test site (at Ussuriysk, Russian Federation [USRK] and Wonju, Republic of Korea [KSRS]) to show that similarly low thresholds are possible when the right templates exist. We also extend the work of Schaff et al. (2012) and measure the correlation detection threshold at the nearest Global Seismic Network (GSN) three-component station (MDJ) at Mudanjiang, Heilongjiang Province, China, from the New China Digital Seismograph Network (IC). To conclude, we use these results to explore the recent claim by Zhang and Wen (2015) that the DPRK conducted “…a low-yield nuclear test…” on 12 May 2010.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Adaptive Self-Tuning of Signal Detection Parameters

The quality of automatic detections from sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings, yet achieving superior automatic detection of events is closely related to these parameters. We present an automated sensor tuning (AST) system that tunes effective parameter settings for each sensor detector to the current state of the environment by leveraging cooperation within a neighborhood of sensors. After a stabilization period, the AST algorithm can adapt in near real-time to changing conditions and automatically self-tune a signal detector to identify (detect) only signals from events of interest. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Our current work focuses on reducing false signal detections early in the seismic signal processing pipeline, which leads to fewer false events and has a significant impact on reducing analyst time and effort. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections from a seismic sensor network monitoring the Mount Erebus Volcano in Antarctica, we show that AST increases the probability of detection while decreasing false alarms.

58 GEOSCIENCES↗

Observing Tsunamis in the Ionosphere Using Ground Based GPS Measurements

Ground-based Global Positioning System (GPS) measurements of ionospheric Total Electron Content (TEC) show variations consistent with atmospheric internal gravity waves caused by ocean tsunamis following recent seismic events, including the Tohoku tsunami of March 11, 2011. We observe fluctuations correlated in time, space, and wave properties with this tsunami in TEC estimates processed using JPL's Global Ionospheric Mapping Software. These TEC estimates were band-pass filtered to remove ionospheric TEC variations with periods outside the typical range of internal gravity waves caused by tsunamis. Observable variations in TEC appear correlated with the Tohoku tsunami near the epicenter, at Hawaii, and near the west coast of North America. Disturbance magnitudes are 1-10% of the background TEC value. Observations near the epicenter are compared to estimates of expected tsunami-driven TEC variations produced by Embry Riddle Aeronautical University's Spectral Full Wave Model, an atmosphere-ionosphere coupling model, and found to be in good agreement. The potential exists to apply these detection techniques to real-time GPS TEC data, providing estimates of tsunami speed and amplitude that may be useful for future early warning systems.

total electron content (TEC)↗

Applying Waveform Correlation to Mining Blasts Using a Global Sparse Network

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment that uses waveform templates recorded by multiple International Monitoring System stations of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization for up to 10 years prior to the time period of interest to detect and identify mining blasts that occur during single weeks of study. We discuss approaches for template selection, threshold setting, and event detection that are specialized for mining blasts and a sparse, global network. We apply the approaches to two different weeks of study for each of two geographic regions, Wyoming and Scandinavia, to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to develop an intuition about potential reduction in analyst workload.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Impact of Three-Phase Relative Permeability and Hysteresis Models on Forecasts of Storage Associated With CO 2 -EOR

Geological CO 2 sequestration in conjunction with enhanced oil recovery (CO 2 -EOR) includes complex multiphase flow processes compared to CO 2 storage in deep saline aquifers. Two of the most critical factors affecting multiphase flow in CO 2 -EOR are three-phase relative permeability and associated hysteresis, both of which are difficult to measure and are usually represented by numerical interpolation models. The purpose of this research is to improve understanding of (1) the relative impacts of different three-phase relative permeability models and hysteresis models on CO 2 trapping mechanisms, and (2) uncertainty associated with these two factors. Four different three-phase relative permeability models and three hysteresis models were applied to simulations of an active CO 2 -EOR site, the SACROC unit located in western Texas. To eliminate potential bias of deterministic parameters, we utilized a sequential Gaussian simulation technique to generate 50 realizations to describe heterogeneity of porosity and permeability, based on data obtained from well logs and seismic survey. Simulation results of forecasted CO 2 storage suggested that (1) the choice of three-phase relative permeability model and hysteresis model led to noticeable impacts on forecasted CO 2 sequestration capacity; (2) impacts of three-phase relative permeability models and hysteresis models on CO 2 trapping are small during the CO 2 -EOR injection period, and increase during the post-EOR CO 2 injection period; (3) the specific choice of hysteresis model is more important relative to the choice of three-phase relative permeability model; and (4) using the recommended three-phase WAG (Water-Alternating-Gas) hysteresis model may increase the impact of three-phase relative permeability models and uncertainty due to heterogeneity.

42 ENGINEERING↗

Big Data Seismology

The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our ability to resolve 4D Earth structure are fundamentally limited by data volume. Currently, Big Data Seismology is an emergent revolution involving the use of large, data-dense inquiries that is providing new opportunities to make fundamental advances in these areas. This article reviews recent scientific advances enabled by Big Data Seismology through the context of three major drivers: the development of new data-dense sensor systems, improvements in computing, and the development of new types of techniques and algorithms. Each driver is explored in the context of both global and exploration seismology, alongside collaborative opportunities that combine the features of long-duration data collections (common to global seismology) with dense networks of sensors (common to exploration seismology). The review explores some of the unique challenges and opportunities that Big Data Seismology presents, drawing on parallels from other fields facing similar issues. Finally, recent scientific findings enabled by dense seismic data sets are discussed, and we assess the opportunities for significant advances made possible with Big Data Seismology. This review is designed to be a primer for seismologists who are interested in getting up-to-speed with how the Big Data revolution is advancing the field of seismology.

58 GEOSCIENCES↗

Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply scattered or reflected waves. However, a challenge arises when multiply scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural or induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (TNN also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The TNN with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. Furthermore, these results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗

Summary: SEE4GEO

The seismoelectric effects technique (SEE) is a new and innovative approach for geothermal subsurface imaging and monitoring at reservoir scale. The objective of this project is to assess SEE in terms of data acquisition, cost and quality, and to determine its capability in comparison with classical imaging and monitoring techniques, particularly decoupled seismic and electromagnetic methods. This will be achieved by (1) development of a fast, true 3D numerical package, handling SEE imaging and subsurface properties characterization, including resistivity and permeability, (2) laboratory experiments performed in a controlled environment to define optimal deployment design, data quality, and inform field deployment, and (3) field surveys to ultimately test and draw lessons for practical use of SEE technology. There is a relatively extensive body of work in the literature on SEE, and members of this consortium have been involved in theoretical and numerical development of SEE modeling as well as laboratory experiments. Nevertheless, to our knowledge few, if any, documented efforts have been specifically targeting the use of SEE for geothermal subsurface imaging and monitoring. The strength and originality of our proposal rely on an integrated approach leveraging numerical, laboratory and field experiments, to properly document the practical use of SEE. Through this process, SEE in-hand technology for the geothermal industry will be able to progress from a TRL 1 to TRL 3.

58 GEOSCIENCES↗

Seismoelectric Effects for Geothermal Resources Assessment and Monitoring (SEE4GEO)

The seismoelectric effects technique (SEE) is a new and innovative approach for geothermal subsurface imaging and monitoring at reservoir scale. The objective of this project is to assess SEE in terms of data acquisition, cost and quality, and to determine its capability in comparison with classical imaging and monitoring techniques, particularly decoupled seismic and electromagnetic methods. This will be achieved by (1) development of a fast, true 3D numerical package, handling SEE imaging and subsurface properties characterization, including resistivity and permeability, (2) laboratory experiments performed in a controlled environment to define optimal deployment design, data quality, and inform field deployment, and (3) field surveys to ultimately test and draw lessons for practical use of SEE technology. There is a relatively extensive body of work in the literature on SEE, and members of this consortium have been involved in theoretical and numerical development of SEE modeling as well as laboratory experiments. Nevertheless, to our knowledge few, if any, documented efforts have been specifically targeting the use of SEE for geothermal subsurface imaging and monitoring. The strength and originality of our proposal rely on an integrated approach leveraging numerical, laboratory and field experiments, to properly document the practical use of SEE. Through this process, SEE in-hand technology for the geothermal industry will be able to progress from a TRL 1 to TRL 3.

58 GEOSCIENCES↗

Data for Monitoring Fracture Saturation with Internal Transportable Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply-scattered or reflected waves. However, a challenge arises when multiply-scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The twin neural network with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. These results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗

The evolution of seafloor venting from hydrate-sealed gas reservoirs

Here we use 3D seismic data to show that three rows of seafloor gas mounds can be traced downward to leak points that lie at the hydrate-gas contact within three individual dipping coarse-grained sand bodies in the Terrebonne Basin, Walker Ridge block 313, northern Gulf of Mexico. We predict the overpressure within the sand bodies by assuming that the gas pressure at the vent points equal the least principal stress. We interpret that free gas accumulates at the base of the hydrate stability zone, trapped by the overlying sand which has a high methane hydrate saturation. The free gas accumulates until the gas pressure at the base of the hydrate stability zone reaches the least principal stress in the overlying mudrock, whereupon hydraulic fractures form and fluids are vented to the surface. The warm rising fluids and perhaps localized exothermic formation of hydrate raise the local salinity and temperature. This process progressively shifts the base of the hydrate stability zone to shallower depths and dissociates the hydrate seal within the sand, which creates new leak points and results in the observed migration of the seafloor vents. Within the southwest corner of the Terrebonne Basin, this process has repeated multiple times within the Blue, Orange, and Green sands. Here this study shows how the hydrate stability zone can influence the location of fluid expulsion and in turn be affected by the warm, rising, saline fluids sealed by hydrate.

58 GEOSCIENCES↗

Structural algorithm to reservoir reconstruction using passive seismic data (synthetic example)

Using of passive seismic observations to detect a reservoir is a new direction of prospecting and exploration of hydrocarbons. In order to identify thin reservoir model we applied the modification of Gaussian elimination method in conditions of incomplete synthetic data. Because of the singularity of a matrix conventional method does not work. Therefore structural algorithm has been developed by analyzing the given model as a complex model. Numerical results demonstrate of its advantage compared with usual way of solution. We conclude that the gas reservoir is reconstructed by retrieving of the image of encasing shale beneath it.

58 GEOSCIENCES↗

Fluoroethylenepropylene ferroelectret films with cross-tunnel structure for piezoelectric transducers and micro energy harvesters

Layered fluoroethylenepropylene (FEP) ferroelectret films with cross-tunnel structure were fabricated from sheets of FEP films by template-patterning followed by a fusion-bonding process and contact charging. The typical piezoelectric d{sub 33} coefficients, measured by a quasi-static method of samples not annealed, are in the range of 1000–3700 pC/N. The resonance behavior of the samples is analyzed by dielectric spectroscopy which also yields Young's modulus. Microphones built with such films exhibit a somewhat decreasing frequency response up to 1 kHz, an increase of the responses due to diffraction effects at higher frequencies, and eventually a peak probably due to a thickness resonance at about 40 kHz. Annealing at 125 °C indicates that the sensitivity stabilizes at about 40% of the original value. From this data, stable dynamic d{sub 33} coefficients of up to 300 pC/N can be calculated. A micro energy harvesting generator utilizing these films and based on the excitation of thickness vibrations is also described. With an active area of 4.3 cm{sup 2} and a seismic mass of 69.5 g, power up to 0.5 μW referred to an acceleration of 1 g can be generated at a frequency of 120 Hz.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The interpretation of crustal dynamics data in terms of plate motions and regional deformation near plate boundaries

A particularly detailed set of observations in the vicinity of an intraplate, thrust earthquake (M 7.4) in Argentina, indicate a cyclic pattern of deformation very similar to that reported previously for interplate earthquakes. This deformation cycle, which may be characteristic of many seismically active areas, consists of: (1) steady strain accumulation, possibly punctuated by strain reversals; (2) coseismic strain release; (3) a period of continued strain release due to afterslip (persisting for perhaps a year or so); and (4) rapid postseismic strain accumulation which decreases exponentially and grades into steady strain accumulation. Deformation associated with three earthquakes in the U.S. (1940, M7.1 Imperial Valley California; 1964, M8.4 Alaska; 1959, M7.5 Hebgen Lake, Montana) are interpreted in light of this general earthquake cycle and are used to investigate the mechanics of strain release for these events. These examples indicate that large postseismic movements can occur for strike-slip, thrust, and normal fault events, and both viscoelastic relaxation and postseismic after-slip must be incorporated in models of earthquake related deformation. The mechanics of the strain release process revealed by these examples has implications for estimating earthquake repeat times from geodetic observations near active faults.

Solomon, Sean C.↗

Robust inverse scattering full waveform seismic tomography for imaging complex structure

Seismic tomography becomes important tool recently for imaging complex subsurface. It is well known that imaging complex rich fault zone is difficult. In this paper, The application of time domain inverse scattering wave tomography to image the complex fault zone would be shown on this paper, especially an efficient time domain inverse scattering tomography and their run in cluster parallel computer which has been developed. This algorithm is purely based on scattering theory through solving Lippmann Schwienger integral by using Born's approximation. In this paper, it is shown the robustness of this algorithm especially in avoiding the inversion trapped in local minimum to reach global minimum. A large data are solved by windowing and blocking technique of memory as well as computation. Parameter of windowing computation is based on shot gather's aperture. This windowing technique reduces memory as well as computation significantly. This parallel algorithm is done by means cluster system of 120 processors from 20 nodes of AMD Phenom II. Benchmarking of this algorithm is done by means Marmoussi model which can be representative of complex rich fault area. It is shown that the proposed method can image clearly the rich fault and complex zone in Marmoussi model even though the initial model is quite far from the true model. Therefore, this method can be as one of solution to image the very complex mode.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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

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

58 GEOSCIENCES↗

The deep structure of lunar basins - Implications for basin formation and modification

Models for the crustal structure in the vicinity of nine impact basins, from an inversion of gravity and topographic data from the lunar nearside are presented. The models display a low-density nonmare crustal layer and a mare basalt layer, both of variable thicknesses. Assuming that topography in mare areas is isostatically compensated before the emplacement of mare basalts and that compensation of mare basalt units may be neglected, a decomposition of the gravity anomaly into contributions from Moho relief and mare fill is permitted. Minimum values for mare basalt thicknesses are obtained but because mare basalts and mantle material are similar in density, the thicknesses of the nonmare crust are estimated. An important constraint is the crustal thickness inferred from the Apollo 12 and 14 landing sites from seismic observations. The crustal thickness model indicates that the crust is thinner beneath each of the major nearside basins than in surrounding areas. New bounds on the volume of material ejected from each basin are derived. The geological implications of structural differences among basins for the processes of basin formation and modification are evaluated as functions of time on the moon.

Bratt, S. R.↗

Preliminary result of P-wave speed tomography beneath North Sumatera region

The structure of P-wave speed beneath the North Sumatra region was determined using P-wave arrival times compiled by MCGA from time periods of January 2009 to December 2012 combining with PASSCAL data for February to May 1995. In total, there are 2,246 local earthquake events with 10,666 P-wave phases from 63 stations seismic around the study area. Ray tracing to estimate travel time from source to receiver in this study by applying pseudo-bending method while the damped LSQR method was used for the tomographic inversion. Based on assessment of ray coverage, earthquakes and stations distribution, horizontal grid nodes was set up of 30×30 km2 for inside the study area and 80×80 km2 for outside the study area. The tomographic inversion results show low Vp anomaly beneath Toba caldera complex region and around the Sumatra Fault Zones (SFZ). These features are consistent with previous study. The low Vp anomaly beneath Toba caldera complex are observed around Mt. Pusuk Bukit at depths of 5 km down to 100 km. The interpretation is these anomalies may be associated with ascending hot materials from subduction processes at depths of 80 km down to 100 km. The obtained Vp structure from local tomography will give valuable information to enhance understanding of tectonic and volcanic in this study area.

58 GEOSCIENCES↗