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DOE OSTI2021

Three-dimensional paganica fault morphology obtained from hypocenter clustering (L'Aquila 2009 seismic sequence, Central Italy)

In seismic modelling, fault planes are normally assumed to be flat due to the lack of data which can constrain fault morphology. However, incorporating 3D fault morphology is important for modelling several phenomena, for example calculating mainshock induced stress changes. Here we utilize a data-analytical method to unveil the 3D rupture morphology of faults using unsupervised clustering techniques applied to earthquake hypocenters in seismic sequences. We apply this method to the 2009 L'Aquila seismic sequence which involved a M W 6.1 mainshock on April 6th. We use a dataset of about 50,000 relocated events, mostly microearthquakes, reaching magnitude of completeness equal to 0.7. Clustering distinguishes the earthquakes as occurring in three main clusters along with other minor fault segments. We then represent the morphology of the main Paganica fault system (responsible for the largest mainshock) using splines. This method shows promise as a step toward robustly and quickly obtaining 3D rupture morphologies where earthquake sequences have been monitored. The 3D model is presented interactively online, and the processing is presented in an interactive Jupyter Notebook (https://bit.ly/2MnCFdj).

58 GEOSCIENCES↗

DOE OSTI2021

Joint impedance and facies inversion of time-lapse seismic data for improving monitoring of CO 2 incidentally stored from CO 2 EOR

Time-lapse seismic monitoring is an effective and proven technology for mapping the distribution of CO 2 in a subsurface reservoir. When injected CO 2 displaces other reservoir fluids, porous-medium properties are changed and thus the seismic impedance changes, causing time-lapse seismic amplitude differences in the injection zones. The analysis and interpretation of images created from these amplitude differences can provide information about reservoir architecture and the CO 2 migration within the reservoir. Incorporating seismic inversion and rock physics into the interpretation of time-lapse seismic data can considerably improve the modeling and monitoring to detect and assess the location of CO 2 over time. The joint inversion method presented in this paper has an integral representation of the geology in the inversion algorithm using elastic facies, which provides information about the spatial distribution of the geologic heterogeneities controlling the movement of fluids in the reservoir. The method was successfully applied to time-lapse seismic data from a mature oil field undergoing CO 2 enhanced oil recovery. The estimated seismic acoustic impedances and facies reflect the characteristics of individual geologic facies and fluid conditions of the reservoir subject to CO 2 injection. Finally, the probabilities estimated by the joint impedance and facies inversion for the reservoir's litho-fluid facies can be used for forecasting CO 2 saturation and pressure changes within the target reservoir.

4D seismic↗

DOE OSTI2020

Advanced High-Performance Computational Modeling of the Seismic Response of High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSS

New methods for predicting the amplitude and variability of ground shaking from earthquakes (and explosions) are needed for seismic hazard analysis for buildings, nuclear power plants, and critical infrastructure at the NNSS. We are comparing existing 1-D and new 3-D geophysical methods for estimating the shear-wave velocity structure in the upper 30 meters of the ground surface (Vs30), which plays a major role in ground motion amplification and seismic response of buildings. We evaluate the performance of these methodologies at the U1a Complex at the NNSS and develop simple 1-D and high-resolution 3-D Vs30 models. We then emplace these high-resolution models into a background seismic velocity model. We will collaborate with Lawrence Livermore National Laboratory (LLNL) to conduct numerical modeling of the ground shaking at the NNSS using their high-performance computing technology and state-of-the-art ground motion simulation methodology. The primary work that was completed in FY 2019 was to acquire the seismic systems and familiarize staff at the NNSS with their use. We also worked on developing a collection plan with the Device Assembly Facility (DAF) at the NNSS, but due to time constraints and other ongoing projects at the DAF, we had to use U1a as a backup. We were able to coordinate the seismic survey, and we will complete the collection of seismic data in FY 2020. Additionally, during FY 2019, we completed the geologic framework model (GFM) for the U1a Complex and modeled the Yucca fault. LLNL worked with us through FY 2019 to prepare the data files for their modeling software and tested the software for reliability. In FY 2020 we will develop the end-to-end capability so that any facility could easily be modeled and the expected shaking from a local earthquake understood. The work in FY 2020 will include building fault models from the GFM and finalizing the velocity model analysis. The final simulations will be run for multiple rupture models, and final assessments will demonstrate the seismic hazard at the U1a Complex.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗

DOE OSTI2024

Cyclic Injection Leads to Larger and More Frequent Induced Earthquakes under Volume-Controlled Conditions

As carbon storage technologies advance globally, methods to understand and mitigate induced earthquakes become increasingly important. Although the physical processes that relate increased subsurface pore pressure changes to induced earthquakes have long been known, reliable methods to forecast and control induced seismic sequences remain elusive. Suggested reservoir engineering scenarios for mitigating induced earthquakes typically involve modulation of the injection rate. Some operators have implemented periodic shutdowns (i.e., effective cycling of injection rates) to allow reservoir pressures to equilibrate (e.g., Paradox Valley) or shut-in wells after the occurrence of an event of concern (e.g., Basel, Switzerland). Other proposed scenarios include altering injection rates, actively managing pressures through coproduction of fluids, and preinjection brine extraction. Here, in this work, we use 3D physics-based earthquake simulations to understand the effects of different injection scenarios on induced earthquake rates, maximum event magnitudes, and postinjection seismicity. For comparability, the modeled injection considers the same cumulative volume over the project’s operational life but varies the schedule and rates of fluid injected. Simulation results show that cyclic injection leads to more frequent and larger events than constant injection. Furthermore, with intermittent injection scenario, a significant number of events are shown to occur during pauses in injection, and the seismicity rate remains elevated for longer into the postinjection phase compared to the constant injection scenario.

58 GEOSCIENCES↗

DOE OSTI2021

A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage (Task 5 Report Field Scale Stress Modeling)

This report describes research accomplishments achieved with funding provided through Department of Energy (DOE) Contract DE-FE0031686, for the project “A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage.” The purpose of this DOE funding is to develop non-invasive methods to obtain important information about subsurface stresses. The overall research goal of the project was to develop and improve methods for determining the spatial distribution of stresses, including magnitude and orientation of the three principal stress components in the subsurface, based on new methods that extract stress information from seismic data combined with well measurements, extended with well tests and logs, and unified in a numerical model that permits computation of the full stress tensor throughout the domains under investigation.

58 GEOSCIENCES↗

NASA NTRS1977

Aerospace technology can be applied to exploration 'back on earth'

Applications of aerospace technology to petroleum exploration are described. Attention is given to seismic reflection techniques, sea-floor mapping, remote geochemical sensing, improved drilling methods and down-hole acoustic concepts, such as down-hole seismic tomography. The seismic reflection techniques include monitoring of swept-frequency explosive or solid-propellant seismic sources, as well as aerial seismic surveys. Telemetry and processing of seismic data may also be performed through use of aerospace technology. Sea-floor sonor imaging and a computer-aided system of geologic analogies for petroleum exploration are also considered.

Jaffe, L. D.↗

NASA NTRS1982

Inverting travel times with a triplication

A method based on the use of constrained spline fits is used to overcome the difficulties arising when body-wave data in the form of T-delta are reduced to the tau-p form in the presence of cusps. In comparison with unconstrained spline fits, the method proposed here tends to produce much smoother models which lie approximately in the middle of the bounds produced by the extremal method. The method is noniterative and, therefore, computationally efficient. The method is applied to the lunar seismic data, where at least one triplication is presumed to occur in the P-wave travel-time curve. It is shown, however, that because of an insufficient number of data points for events close to the antipode of the center of the lunar network, the present analysis is not accurate enough to resolve the problem of a possible lunar core.

Jarosch, H. S.↗

DOE OSTI2020

Numerical Modeling of Anisotropic Elastic-Wave Sensitivity Propagation for Optimal Design of Time-Lapse Seismic Surveys

Reliable subsurface time-lapse seismic monitoring is crucial for many geophysical applications, such as enhanced geothermal system characterization, geologic carbon utilization and storage, and conventional and unconventional oil/gas reservoir characterization, etc. In this work, we develop an elastic-wave sensitivity propagation method for optimal design of cost-effective time-lapse seismic surveys considering the fact that most of subsurface geologic layers and fractured reservoirs are anisotropic instead of isotropic. For anisotropic media, we define monitoring criteria using qP- and qS-wave sensitivity energies after decomposing qP- and qS-wave components from the total elastic-wave sensitivity wavefield using a hybrid time- and frequency-domain approach. Geophones should therefore be placed at locations with significant qP- and qS-wave sensitivity energies for cost-effective time-lapse seismic monitoring in an anisotropic geology setting. Our numerical modeling results for a modified anisotropic Hess model demonstrate that, compared with the isotropic case, subsurface anisotropy changes the spatial distributions of elastic-wave sensitivity energies. Consequently, it is necessary to consider subsurface anisotropies when designing the spatial distribution of geophones for cost-effective time-lapse seismic monitoring. This finding suggests that it is essential to use our new anisotropic elastic-wave sensitivity modeling method for optimal design of time-lapse seismic surveys to reliably monitor the changes in subsurface reservoirs, fracture zones or target monitoring regions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Team has shared the following files from the project: - 149 microearthquakes (MEQs) between 2012 and 2013 at Newberry EGS sites, 'Normalized Waveform Inputs.npz' are normalized waveforms. - labels of 149 MEQs: Processed Waveform Inputs.npz - location labels of 149 MEQs: Location Data.npz Note: .npz is the python file format by NumPy that provides storage of array data.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Impact of representative ground motion level on seismic PSA with the boundary between overestimation and underestimation

One commonly used approach in seismic probabilistic safety assessment (PSA) is the discrete method. This method follows the standard PSA framework and can be applied to various models, such as multi-unit models, while reducing computational costs using standard software. However, due to the inability to subdivide intervals infinitely, the discrete method approximates with a finite number of subintervals. In practice, different numbers of subintervals are applied, and the representative ground motion level is selected based on expert judgment. When employing a smaller number of subintervals, it is important to take caution to prevent underestimation. This study analyzes the impact of the representative ground motion level on seismic risk. It confirms that underestimation can occur with a small number of subintervals depending on the representative ground motion level. This study also proposes a method for determining the boundary of underestimation and overestimation. The method is demonstrated through examples, providing a mathematical foundation for selecting appropriate representative ground motion levels. By avoiding underestimation, this research helps prevent the oversight of significant risk contributors and enhances the understanding of seismic risk.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Locating Seismic Events with Local-Distance Data

As the seismic monitoring community advances toward detecting, identifying, and locating ever-smaller natural and anthropogenic events, the need is constantly increasing for higher resolution, higher fidelity data, models, and methods for accurately characterizing events. Local-distance seismic data provide robust constraints on event locations, but also introduce complexity due to the significant geologic heterogeneity of the Earth’s crust and upper mantle, and the relative sparsity of data that often occurs with small events recorded on regional seismic networks. Identifying the critical characteristics for improving local-scale event locations and the factors that impact location accuracy and reliability is an ongoing challenge for the seismic community. Using Utah as a test case, we examine three data sets of varying duration, finesse, and magnitude to investigate the effects of local earth structure and modeling parameters on local-distance event location precision and accuracy. We observe that the most critical elements controlling relocation precision are azimuthal coverage and local-scale velocity structure, with tradeoffs based on event depth, type, location, and range.

42 ENGINEERING↗

DOE OSTI2023

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO 2 plume monitoring

Continuous seismic monitoring for quantifying CO 2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO 2 distribution by estimating seismic velocity changes, but recent studies find that CO 2 -induced attenuation is an important complement to seismic velocity for tracking the CO 2 plumes and even quantifying the CO 2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO 2 leakage case and a realistic Frio-II CO 2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. Here, by assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

58 GEOSCIENCES↗

DOE OSTI2022

Analysis of Data Fusion Between Waveform Events and Radionuclide Detections Reported in 2021 by the International Data Centre

During this project, we assessed the percentage of events reported by the International Data Centre (IDC) that are candidates for evaluation using data fusion methods. We calculated the percentage of waveform (seismic, hydroacoustic, infrasound, SHI) events that may be associated with radionuclide (RN) detections and vice versa. For this task, data fusion means identifying RN detections that may be associated with SHI events. The task of producing a fused SHI and RN bulletin is included in the IDC operational manual. As of 2022, the production of a fused event bulletin remains incomplete, largely because methods for producing the bulletin are under development. Nonetheless, simple methods for data fusion have been developed and preliminary software tools are available at the IDC to associate SHI events and RN detections. This report is a first look at the percentage of SHI events that may be candidates for fusion with RN detections or bulletins. One year of IDC bulletin data (2021) is considered in this report. It is important to note that there were no known nuclear explosions during this time period. Hence, we expect that events during this time period would generate SHI and RN signals. If many SHI events are candidates for fusion with RN data, greater priority should be placed on establishing screening procedures before and/or during the fusion process. By contrast, if the number of candidate events is diminishingly small, then data fusion is not a driver for further development of event or detection screening at the IDC. LLNL reviewed the events reported in the Standard Event Bulletin (SEB) and determined which events are candidates for fusion with the Reviewed Radionuclide Reports (RRR). Much of the work involves establishing a metric or metrics for determining whether a Reviewed Event Bulletin (REB) event is a candidate for data fusion.

58 GEOSCIENCES↗

NASA NTRS2001

Silicon micromachined accelerometer/seismometer and method of making the same

A silicon-based microaccelerometer for seismic application is provided using a low-resonant frequency (10 Hz), large proof mass (1 gram), and high Q suspension to achieve high sensitivity of less than 1 ng with a bandwidth a 0.05 to 50 Hz. The proof mass is cut away from a planar substrate in the form of a disk using abrasive cutting, which disk closely fits but does not touch a surrounding angular frame. The spring of the microaccelerometer between the angular frame and the proof mass is provided from two continuous, 3 microns thick membranes. The fixed capacitive electrodes are provided on separate, subsequently bonded substrates, and movable capacitive plates are provided on the membranes. By fabricating capacitive plates on the separate substrates, the gap between the fixed and movable capacitive plates in the differential capacitive sensor is closely controlled. The use of continuous membranes for the spring produces a shock resistant, robust sensor.

Martin, Richard D.↗

DOE OSTI2024

WHOLESCALE: Microseismic Event Catalog for San Emidio, Nevada 2022

This submission includes a high-precision seismic event catalog estimated from seismic data collected at San Emidio, Nevada from April to May 2022. The catalog lists the precise time, location, and magnitude of microseismic events recorded during this period. Both the seismic data and microseismic event catalog were produced as part of the Water & Hole Observations Leverage Effective Stress Calculations and Lessen Expenses (WHOLESCALE) project. Attached here are the microseismic event catalog, a link to the raw seismic data, and a detailed description of methods used to create the catalog.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Evaluation of the PhaseNet Model Applied to the IMS Seismic Network

Producing a complete and accurate set of signal detections is essential for automatically building and characterizing seismic events of interest for nuclear explosion monitoring. Signal detection algorithms have been an area of research for decades, but still produce large quantities of false detections and misidentify real signals that must be detected to produce a complete global catalog of events of interest. Deep learning methods have shown promising capabilities in effectively characterizing seismic signals for complex tasks such as identifying phase arrival times. We use the PhaseNet model, a UNet-based Neural Network, trained on local distance data from northern California to predict seismic arrivals on data from the International Monitoring System (IMS) global network. We use an analyst-curated bulletin generated from this data set to compare the performance of PhaseNet to that of the Short-Term Average/Long-Term Average (STA/LTA) algorithm. We find that PhaseNet has the potential of outperforming traditional processing methods and recommend the training of a new model with the IMS data to achieve optimal performance.

58 GEOSCIENCES↗

DOE OSTI2025

FY 2025 End of Year Report: Seismic Monitoring of Underground Vibration Sources using Distributed Acoustic Sensing (DAS) and Seismometers

This end-of-year report summarizes progress on using seismic monitoring to detect, associate, and locate anomalous vibration signals that may indicate potential containment breaches. The work focused on four key tasks: 1. Developing a database of continuous waveforms and ground-truth event data from multiple sensing modalities. 2. Refining and implementing detection and association algorithms to generate a catalog of anomalous underground activities. 3. Testing and improving distributed acoustic sensing amplitude-based geolocation methods to build an event location catalog. 4. Testing and refining seismic array polarization-based geolocation methods to build an event location catalog. This report provides a brief recap of results from the FY25 midyear report (Tasks 1 and 2) and presents new findings from geolocation methods (Tasks 3 and 4).

58 GEOSCIENCES↗