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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.
We present a computationally efficient method to approximate the probability distribution of seismic Green's functions given the uncertainty of an Earth model. The method is based on the Karhunen-Loève (KL) theorem and an approximation of the Green's function (or seismogram) covariance. Using Monte Carlo (MC) simulations as a control case, we demonstrate that our KL-based method can accurately reproduce a probability distribution of seismograms that results from an uncertain Earth model for a MC-derived seismogram covariance. We then describe a method to estimate the covariance of the seismograms resulting from those Earth models that is not based on MC simulations. We use the estimated Green's function covariance in conjunction with our KL-based method to produce a Green's function probability distribution, and compare that distribution to a Green's function probability distribution produced using a MC finite difference method. We find that the Green's function probability distribution approximated using our KL-based method generally mimics that produced using the MC simulations, especially for direct-arriving body waves. However the accuracy of the KL-based method generally decreases for later times in the simulated Green's function distribution.
This report is a preliminary test plan of the seismic shake table test. The final report will be developed when all decisions regarding the test hardware, instrumentation, and shake table inputs are made. A new revision of this report will be issued in spring of 2022. The preliminary test plan documents the free-field ground motions that will be used as inputs to the shake table, the test hardware, and instrumentation. It also describes the facility at which the test will take place in late summer of 2022.
Geophysical waveforms collected from Arctic regions provides data required for monitoring global security targets. Some seismic instruments deployed on Scandinavian and Greenlandic sites provide waveform data, but these installations include specific challenges: Sea ice and glacial ice generates waveform interference; Meltwater generates narrowband interference, resembling tonal noise.
This report documents the updated seismic shake table test plan. The report describes the shake table inputs (ground motions), test hardware, shake table facility, friction experiment, and proposed instrumentation.
As significantly more focus is placed on carbon sequestration as a means to help mitigate the progression of climate change, the need to adequately characterize an injection target for its induced seismicity potential becomes more apparent. In the Iron Mountain project in Southern Utah, a single fault is identified in the Neck of the Desert near Iron Mountain. The dip of the fault is unknown, and the geomechanical stability of the fault (i.e., distribution of Coulomb failure functions (CFFs)) is highly dependent upon the dip. For some dips, such as 15 degrees, the hazard from injection is low. For other dips, such as 75 degrees, the hazard is high. Another key consideration is the depth of penetration of the fault. Should the fault not penetrate the stress and pressure perturbed region from injection, it will not be induced to fail. Thus, understanding the dip and the depth of penetration of the fault will greatly improve our understanding of the likelihood of inducing an earthquake.
Seismology is the study of earthquakes. It involves looking at the origin and propagation of seismic waves through the Earth to study the interior.
This project has developed and demonstrated a new technology for large-volume and targeted comminution of rock in low permeability formations to enhance recovery from unconventional oil and gas (UOG) resources. The technology is based on a strategically designed interaction of multiple induced seismic pulses that assist the hydraulic fracturing process to enhance shear and multi-planar crack formation. This greatly increased rock stimulation, through bulk comminution, is expected to cause significant increase in permeability leading to enhancement of recovery factors for sub- surface fluids. The proposed technology is especially applicable for enhanced recovery in emerging UOG plays, such as ductile shales that are resistant to opening-mode fracturing by conventional hydraulic fracturing processes. The project combines an integrated experimental and computation approach to develop and demonstrate a modular technology that can be easily implement in the field to augment current practices. The effort integrates a fundamental scientific understanding of dynamic material response under constraint and damage-induced permeability and porosity enhancements at multiple length scales, along with models of comminution due to the local release of kinetic energy associated with high shear strain rate of dynamic deformation. The results will be validated through small-scale experiments and then implemented in a lab-scale field test to demonstrate the developed technology. The project involves collaboration between a solid mechanician, a materials scientist, and a petroleum engineering geo-mechanician. It builds on a successful history of success and collaboration that includes both fundamental scientific exploration and technology development.
This project aims to improve field-scale Carbon Capture and Storage (CCS) assessments by enhancing petrophysical and geophysical log predictions through machine learning and neural networks. In our work during EY23, we applied Conditional Variational Autoencoders (CVAEs) to predict compressional velocity (Vp) and assess CO2 saturation levels in geological formations at the Illinois Basin Decatur Project (IBDP). In another task, we improved full-waveform inversion (FWI) methods with machine-learning approaches using lithological constraints. Full-waveform inversion (FWI) of seismic data estimates the elastic properties of subsurface rocks with high spatial resolution.
The goal of this work is to provide a database of quality-checked seismic parameters that can be integrated with the Geologic Framework Model (GFM) for the LYNM-PE1 (Low Yield Nuclear Monitoring – Physical Experiment 1) testbed. We integrated data from geophysical borehole logs, tabletop measurements on collected core, and laboratory measurements. We reviewed for internal consistency among each measurement type, documented the caveats of measurement conditions, and integrated lithologic logs to check the validity of outlier values. The resulting consolidated parameter tables can be used as inputs for modeling and analysis codes and are designed to interface with the GFM, which is being actively developed.
Accurately locating seismoacoustic sources with geophysical observations helps to monitor natural and anthropogenic phenomena. Sparsely deployed infrasound arrays can readily locate large sources thousands of kms away, but small events typically produce signals observable at only local to regional distances. At such distances, accurate location efforts rely on observations across smaller regional or temporary deployments which often consist of single-channel infrasound sensors that cannot record direction of arrival. Event locations can also be aided by inclusion of ground coupled airwaves (GCA). This study demonstrates how we can robustly locate a catalog of seismoacoustic events using infrasound, GCA, and seismic arrival times at local to near-regional distances. We employ a probabilistic location framework using simplified forward models. Our results indicate that both single-channel infrasound and GCA arrival times can provide accurate estimates of event location in the absence of array-based observations even when using simple models. However, one must carefully choose model uncertainty bounds to avoid underestimation of confidence intervals.
In this report we discuss training a deep learning seismic signal detection model on 3-component stations from the International Monitoring System (IMS) using the PhaseNet architecture. Using 14 years of associated signals from the International Data Centre’s (IDC) Late Event Bulletin (LEB), we auto-curated training data consisting of signal windows containing associated arrivals, and noise windows that contain no LEB-associated signals. We trained several models using different waveform window durations (30 seconds and 100 seconds), with and without bandpass filtering. We evaluated the effectiveness of our models using associated signals from the Unconstrained Global Event Bulletin (UGEB) and found that several of our models outperformed the signal detections from the IDC’s Selected Event List 3 (SEL3) arrival table. The SEL3 bulletin evaluated on the UGEB dataset with 100-second waveform windows registered a precision and recall of .15 and .48, respectively, versus .19 and .59 for our filtered-data model. For the 30-second waveform window dataset, the SEL3 bulletin achieved a precision and recall of .31 and .47, respectively, versus .32 and .60 for our filtered-data model. Finally, our models detected signals from all source-to-receiver distances, suggesting it is feasible to use a single PhaseNet model for the IMS network.
The purpose of the enclosed calculations is to determine the required seismic anchorage for the relocation of the Multi-Axis SYS-MA-YLS Workstation and its auxiliary equipment into B226. Analysis of the equipment frames are excluded from the scope of this safety note; it is assumed that they are capable of transferring the load demands to the anchorage detailed in this package.
Sandia National Laboratories has fabricated a Seismic Sensor Temperature Testbed (SSTT) suitable for exposing sensors under test to a range of reasonably stable temperatures while a co-located reference sensor is maintained at room temperature. The testbed has proven sufficiently quiet to allow recording of high-coherence signals from regional earthquakes in the passband of the seismometers, allowing a direct comparison of signals between the sensors under test and the reference sensor.
The Arc Weld Robotic Arm & Enclosure is adequately anchored by the details shown on sheets SKS-01 through SKS-03. Two different Hilti anchors have been provided to allow for installation flexibility. Existing documentation shows that the existing enclosure base has been anchored with 5/8”Ø Kwik Bolt TZ’s. As a result, it is believed that the existing holes are sized for that 5/8”Ø anchor. The first option is to install a 5/8”Ø Kwik Bolt TZ2, similarly to the existing conditions. The second option is to use a threaded insert anchor. Since the largest allowable diameter of HIS-N insert is 1/2”Ø based on the slab thickness, 2”x2” square plate washers with a 9/16”Ø hole will need to be installed on the top of the existing enclosure base plates to reduce the diameter of the existing holes. This is required for the anchorage to provide proper restraint in a seismic event.
This a presentation for the 2024 Signal Processing Applied to Nonproliferation (SPAN) 2024 workshop. It discusses seismic research conducted at the Redmond Mine as part of the NA-22 STILGAR project.
Within the NIF (National Ignition Facility) sustainment project, LLNL is replacing all 1,728 blast shields with new ones. Before the new blast shield glass can be installed on NIF, it must pass through the AMOL (Amplifier Main Optics Loop). The AMOL process involves cleaning and coating the glass, assembling it into a Line Replaceable Unit (LRU), and performing testing and inspection. This work will be conducted in the OPFX cleanroom facility (Building 391, Room 1250) and requires several pieces of custom equipment. One key piece of equipment within the loop is the Handling Frame Assembly Table (see Figure 1.1). Its purpose is to assist operators in installing the blast shield glass into handling frames (1014442709) (see Figure 1.2). The table is also used to store handling frame assembly components. The primary components stored are the L-frames (1015208271), which are kept in a drawer underneath the table (see Figure 1.3). The purpose of this safety note is to ensure that the system does not pose a risk of injury to personnel during a seismic event. The system owner is OMST Engineering & Maintenance.
A series of large damaging explosions involving fireworks storage occurred near Esparto, Yolo County California on July 1, 2025. Three explosions were located and reported by the University of California Berkeley Seismology Laboratory (UCB/BSL) and the United States Geological Survey (USGS). Analysis of local distance (< 30 km) seismic recordings of the first blast indicates that there were actually three explosions with later blasts delayed by about 3 and 30 seconds. We measured the first arriving P-wave amplitudes on four of these events with good signal-to-noise ratios.