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A cross-well seismic survey was acquired in the Chester 16 reef from September 9 to 14, 2018, to attempt to locate 85,000 tonnes of carbon dioxide (CO 2 ) that were injected into the A-1 Carbonate and Brown Niagaran Formations between February 2013 and September 2018.
The 2022 Hunga eruption was a global event recorded by all three Comprehensive Test Ban Treaty Organization (CTBTO) International Monitoring System (IMS) geophysical waveform sensor technologies: seismic, infrasound, and hydroacoustic. Large volcanic eruptions are rare and additionally present an opportunity to test seismoacoustic detection, location, and identification methods for nuclear explosion monitoring.
SUMMARY We present an analysis of combining translational and rotational seismic data in an inversion for the time-variable source time functions corresponding to the components of the seismic moment tensor. We conduct a series of numerical experiments where the data are simulated by a combination of an underground explosion and a co-located double couple shear source and recorded on surface-mounted seismometers within 1–2 km of the source. The experiments are designed to mimic explosion seismology experiments, and thus the data are in the 1–10 Hz frequency range and contain very few surface waves. We use a Monte Carlo method to propagate Earth model uncertainty into the estimates of seismic source parameters. In our experiments, we find that the uncertainty of the estimated seismic source parameters increases when we add rotational seismic motions to the inversion when using a constant number of data channels. In this case, the increased degree of uncertainty in the final results is most likely due to the near-surface Earth model uncertainty that we introduce in our simulations. However, for a fixed number of seismic stations, adding rotational seismic motions to the inversion acts to decrease the uncertainty of the estimated seismic source parameters, most likely due to the increase in the number of data channels used in the inversion.
Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. Additionally, the results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.
Seismic signals from 1993 show a series of magnitude (Mw) 3.7 or less seismic events in Rock Valley on the Nevada National Security Site (NNSS). Historic synthetic aperture radar images of that location were found that could provide interferometric synthetic aperture radar (InSAR) measures of the ground height during 1993. Given this historic SAR imagery, we explore answering the question if ground movement from the 1993 Rock Valley earthquake activity could be sensed by remote sensing means. Finding earthquake surface movement would assist in locating the Rock Valley fault and the 1993 earthquake hypocenter where the Source Physics Experiment Phase III series of experiments will be conducted. In this report, we show that InSAR can sense very small height differences, and for the European Radar Satellite-1 InSAR collections during 1992 and 1993 over Rock Valley earth surface movements were measured with 8 mm uplift and 12.5 mm subsidence over isolated areas. One of these earth movement areas coincides with an InSAR image pair coherence drop between March 5, 1993 and June 18, 1993. The coherence drop is over an approximately 13 square km area south southeast of Skull Mountain centered at 36° 43' 30" N latitude and 116° 05' 00" W longitude. Measured small surface movement and a loss of InSAR coherence may be caused by the series of earthquakes. The location of these InSAR detections may also coincide with water drainage or erosion displacement. There are no records to disambiguate the earthquake and erosion earth surface motion possibilities. Therefore, the InSAR findings of earth surface movement by InSAR are inconclusive.
Moment tensors (MTs) have long been used in earthquake and explosion source analysis, and there has been a renewed interest in how they can inform us about the seismic source, particularly in the geophysical monitoring community due to its application in event identification and yield analysis. However, parameter uncertainties in seismic MT inversion are rarely available. The inverse procedure often does not quantify MT model errors such as event location, data noise and Earth model that are essential for estimating solution robustness. To address this need, we propose to adopt the Bayesian probabilistic framework to incorporate uncertainties in MT inversions. In this study, we present the theoretical background of a probabilistic Bayesian framework for MT inversion accounting for model and measurements errors and illustrate the implementation of the method using a synthetic example.
The problem of estimating discontinuous coefficients, including locations of discontinuities, that occur in second order hyperbolic systems typical of those arising in I-D surface seismic problems is discussed. In addition, the problem of identifying unknown parameters that appear in boundary conditions for the system is treated. A spline-based approximation theory is presented, together with related convergence findings and representative numerical examples.
A systematic study has been conducted of oceanic intraplate seismicity in the 1964-1983 period occurring in lithosphere younger than 35 million years. Detailed findings are presented on the stress in young lithosphere, depth of seismicity, intraplate events in fracture zones, seismicity distributions, and regional concentrations of seismicity. It is concluded that there is no evidence of a general transition from tensional to compressive stresses at any particular age of the lithosphere. Extensional events are located mostly in the Indian Ocean and have tensional axes oriented at large angles to the spreading direction. Compressional axes of thrust faulting events show a weak preferred orientation parallel to the spreading direction. Normal faulting events occur at greater depths and temperatures than thrust faulting events. Differential thermal contraction along fracture zones is not a significant source of intraplate seismicity.
Two events of magnitude (m b ) 3.6–3.8 occurred in southern North Korea (NK) on 27 June 2019 and 11 May 2020. Although these events were located ~330–400 km from the known nuclear test site, the fact that they occurred within the territory of NK, a country with a recent history of underground nuclear tests, made them events of interest for the monitoring community. In this work, we used P/Lg ratios from regional stations to categorize seismic events that occurred in NK from 2006 to May 2020, including these two recent events, the six declared NK nuclear tests, and the cavity collapse and triggered earthquakes that followed the 3 September 2017 nuclear explosion. We were able to separate the cavity collapse from the population of nuclear explosions. However, based on P/Lg ratios, the distinction between the earthquakes and the cavity collapse is ambiguous. The performed discriminant analyses suggest that combining Pg/Lg and Pn/Lg ratios results in improved discriminant power compared with any of the ratio types alone. We used the two ratio types jointly in a quadratic discriminant function and successfully classified the six declared nuclear tests and the triggered earthquakes that followed the September 2017 explosion. Our analyses also confirm that the recent southern events of June 2019 and May 2020 are both tectonic earthquakes that occurred naturally.
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.
This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.
Here we present a series of simple shear numerical simulations of dynamic recrystallization of two-phase nonlinear viscous materials that represent temperate ice. First, we investigate the effect of the presence of water on the resulting microstructures and, second, how water influences on P wave (V p ) and fast S wave (V s ) velocities. Regardless the water percentage, all simulations evolve from a random fabric to a vertical single maximum. For a purely solid aggregate, the highest V p quickly aligns with the maximum c-axis orientation. At the same time, the maximum c-axis development reduces V s in this orientation. When water is present, the developed maximum c-axis orientation is less intense, which results in lower V p and V s . At high percentage of water, V p does not align with the maximum c-axis orientation. If the bulk modulus of ice is assumed for the water phase (i.e., implying that water is at high pressure), we find a remarkable decrease of V s while V p remains close to the value for purely solid ice. These results suggest that the decrease in V s observed at the base of the ice sheets could be explained by the presence of water at elevated pressure, which would reside in isolated pockets at grain triple junctions. Under these conditions water would not favor sliding between ice grains. However, if we consider that deformation dominates over recrystallization, water pockets get continuously stretched, allowing water films to be located at grain boundaries. This configuration would modify and even overprint the maximum c-axis-dependent orientation and the magnitude of seismic anisotropy.
Here, this study analyzed the Democratic People’s Republic of Korea’s (DPRK) fourth (DPRK4, 6 January 2016 M w 4.49) and sixth (DPRK6, 7 September 2017 M w 5.2) declared nuclear tests, employing a joint seismic and Interferometric Synthetic Aperture Radar (InSAR) inversion to improve understanding of these events and enhance moment tensor (MT) inversion capabilities. The recent efforts have focused on employing seismic waveform and InSAR geodetic deformation data separately to analyze these and the previous nuclear tests (e.g., Chiang et al., 2018; Myers et al., 2018; Wang et al., 2018). Building upon our previous work (Chi-Durán et al., 2021), we performed a joint regional waveform, first-motion (FM) polarity, and surface displacement inversion, which demonstrated improved source-type discrimination, a revised MT solution with reduced scalar moment uncertainty, and an independently constrained location. In this article, we build on the previous results for DPRK6 by including an analysis using a four-layered velocity model with free-surface topography to compute the near-source static deformation Green’s functions. The model consists of a 50 m basalt layer (V P = 2.07 km/s, V S = 1.2 km/s), a 250 m stratified volcanic deposit layer (V P = 1.73 km/s, V S = 1.0 km/s), a 700 m weathered granodiorite layer (V P = 2.5 km/s, V S = 1.3 km/s), and a granodiorite half-space (V P = 5.35 km/s, V S = 3.09 km/s). The half-space shares the velocity of the regional MDJ2 velocity model (Ford et al., 2010), which has proven effective for waveform inversion in the region. This model considers the range of reported values for various lithologies and weathering effects. Our findings show that using the layered velocity model enhances the recovery of source location and depth for both the explosions by improving fits and reducing uncertainties. The joint inversion also improves source-type discrimination and better constrains the scalar seismic moment necessary for downstream yield estimation.
We investigate and analyze site specific systematics for the MAGIS-100 atomic interferometry experiment at Fermi National Accelerator Laboratory. As atom interferometers move out of the laboratory environment passive and active mitigation for noise sources must be implemented. To inform the research and development of the experiment design, we measure ambient temperature, humidity, and vibrations of the installation site. We find that temperature fluctuations will necessitate enclosures for critical subsystems and a temperature controlled laser room for the laser system. We also measure and analyze the vibration spectrum above and below ground for the installation site. The seismic vibration effect of gravity gradient noise is also modeled using input from a low-noise seismometer at multiple locations and a mitigation scheme is studied using a stochastic simulation and characterized by a suppression factor.
The problem of estimating discontinuous coefficients, including locations of discontinuities, that occur in second-order hyperbolic systems typical of those arising in one-dimensional surface seismic problems, is considered. The problem of identifying unknown parameters that appear in boundary conditions for the system is addressed. A spline-based approximation theory is presented as well as related convergence findings and representative numerical examples.
As the United States transitions toward a clean energy economy, an opportunity exists for redeveloping the more than 17,000 mine land sites located across the nation with clean energy technologies, which have a combined potential for generating more than 85 GW of clean electricity. This report provides an overview of the potential of demonstrating and deploying clean energy projects on current and former mine land. Clean energy project refers to a project that demonstrates one or more of the following technologies: solar; microgrids; geothermal; direct air capture; fossil-fueled electricity generation with carbon capture, utilization, and sequestration; energy storage, including pumped storage hydropower and compressed air energy storage; and advanced nuclear technologies. The report discusses the following technologies and their potential for creating jobs and generating tax revenue that would result in direct and indirect benefits to the local economy: Solar photovoltaics (PV) is being developed on current and former mine land in various parts of the world, including the United States. This approach is attractive because it requires limited infrastructure investment and would utilize the bare surfaces of mines and tailing ponds. Solar resource availability may be greater in the southern regions, including the Interior and Appalachian Basins and the southwestern United States. However, since some mine land sites include areas of significant change in elevation, the deployment of PV on mine land may require sophisticated planning to account for shading and irradiance, or may require regrading of the areas. PV does not create significant environmental risks and generally does not face public resistance; Geothermal systems are often spatially and genetically associated with ore deposits, and in some cases, they have been discovered while in search for epithermal mineral resources. Numerous diverse geothermal applications have been employed at mine land around the world, including power generation, mineral extraction from geothermal brines, process heating, direct use for other mining operations, and direct use for non-mining operations and subsurface energy storage, including geothermal heat pumps. Case studies highlighting these applications provide key lessons relating to identifying drivers and barriers to geothermal resource deployment and can be used to create screening tools for identifying the types and locations of mine land most amenable to utilizing geothermal resources; Carbon capture, utilization, and sequestration technologies include direct air capture (DAC) and enhanced weathering. DAC technologies include air contactors, regeneration systems, and CO 2 compression systems. Captured CO 2 can be converted to valuable feedstocks or possibly injected into abandoned subsurface mines where it would be absorbed by alkaline rock waste and mine tailings or by the porous minerals along the walls of the mine. DAC systems can be coupled with energy sources such as wind, solar, grid, or geothermal. Many DAC systems require a source of water or steam; however, some are expected to be net producers of water. Local impacts of DAC systems are expected to be low, and are related to land footprint, material disposal, and upstream impacts of energy and material production; Compressed air energy storage is an established energy storage technology in salt caverns. It has the potential for implementation in underground mines by pressurizing and storing a large amount of air using electrical compressors when excess electricity is available. When a need for discharge emerges, the air is used to spin turbines and produce the necessary volume of electricity. Abandoned or unused mine openings, including shafts, adits, access tunnels, and mined workings of any orientation, offer potential for vast amounts of compressed air energy storage if the site characteristics meet operational requirements; Pumped hydropower storage can be implemented in surface and subsurface mines. In surface mine applications, both reservoirs may be located in a mine pit or artificial reservoirs made of excavated materials. In subsurface mines, the lower reservoir may be implemented by waterproofing and flooding mine shafts and tunnels. The water is then pumped from the lower reservoir to the upper reservoir during periods of low load and high production, and it is discharged through the turbines during periods of peak demand. The potential environmental damages associated with acidity of mine water or the presence of toxic chemicals incentivizes the development of closed-loop technologies, in which water circulates inside the pumped hydropower facility without being discharged into the external water basins; Advanced nuclear energy technologies include small modular reactors, which can be deployed locally to produce electricity and heat. Such units require seismic stability and a supply of cooling water, but population constraints may exist in some areas. Therefore, remote mine land could represent an optimal location for siting advanced nuclear energy technologies.
Some areas of research in the SeaRISE project are briefly discussed. They are as follows: (1) Radar Sounding serves multiple purposes. The most general and obvious is mapping ice thickness and the surface and bedrock topography of the ice sheet. (2) The purpose of Seismic Shooting, in addition to water depth measurements on floating ice, is to provide information about the internal physical characteristics of the ice sheet, the rock beneath it, and the interface between the two. (3) Passive Seismic monitoring of microearthquakes can be used to study brittle fracture within the ice or the rock beneath it. Common parameters available from these studies are fault location, orientation, and displacement, as well as the size of the rupture area, stress drop, and energy released. (4) There is a large contrast in Electrical Resistivity between ice or permafrost on the one hand and liquid water or wet rock on the other hand. Thus, electrical resistivity profiles have the ability of revealing the depth to the melting point, whether it is found at the base of the ice or in the subglacial rock. (5) Gravity anomalies, especially combined with seismic measurements, are an effective tool for determining deeper crustal structure. Anomalies averaged over extensive areas are useful also for their potential to reveal isostatic imbalance, which is a measure of average glacial change over the last several hundred years.
Abstract To‐date, only two UIC Class VI permits have been issued by the US Environmental Protection Agency. We illustrate a four‐phase workflow to first identify regional storage resources and then down‐select sites to yield permit‐ready locations that can accept and store large volumes of CO 2 . Specific permit requirements should guide objectives and define deliverables of respective workflow phases. In the first phase we used available regional data and screened structure and injection zones to locate resources that match CO 2 volumes planned to be captured. Available data were also used to assess presence and depth of usable groundwater, the key resource being protected via permitting. We then used advanced, closed‐form, analytical solutions (EASiTool) to estimate CO 2 injectivity into each hydrologically connected injection compartment. In the second phase we acquired and conditioned additional wireline logs and leased available seismic datasets. We interpreted the depositional systems from wireline well‐log character and mapped sandbody geometry to interpolate injection and confining‐zone distribution. Using available data, we mapped faults and locations of freshwater and overpressure (or other capacity‐limiting geologic parameters) in more detail. In the third phase, we used the augmented geologic data to develop a static model for the selected area, extracted the areas of highest interest, and generated and ran dynamic (flow) models. In a fourth phase, we reduced major uncertainties identified in earlier phases. Our case study indicates that to complete preparation of a permit application requires (1) improved lithologic characterization information (thicknesses and horizontal and vertical connectivity) and (2) better definition of poorly defined local faults. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.