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DOE OSTI2017

Implications for elastic energy storage in the Himalaya from the Gorkha 2015 earthquake and other incomplete ruptures of the Main Himalayan Thrust

Rupture in the 2015 M7.8 Gorkha earthquake nucleated at the downdip edge of the Main Himalayan Thrust (MHT) near the transition from interseismic locking to aseismic creep beneath the Tibetan plateau, and propagated incompletely towards the Main Frontal Thrusts (MFT). Despite the imposition of a substantial static strain in the mid-décollement, afterslip on the MHT within a year of the earthquake had decayed to negligible levels. Earthquakes that incompletely rupture the MHT (7 < Mw < 7.9) have been relatively common in the past two centuries, and as a consequence heterogeneous patches of stored elastic strain must exist throughout the Himalaya similar to that emplaced by the Gorkha earthquake. We show that these patches of stored strain are not dissipated by creep or by subsequent updip earthquakes, with the possible exceptions of a sequence of moderate earthquakes to the west of the great 1950 Assam earthquake, and to the east of the Kangra 1905 earthquake. It is thus considered likely that mid-décollement strain newly imposed by the Gorkha earthquake, and other recent incomplete ruptures will be incorporated in the rupture of a future much larger earthquake. Incomplete ruptures (i.e. those that nucleate downdip but fail to rupture the frontal thrusts) appear to occur preferentially in parts of the central Himalaya characterized by relatively narrow transition regions of interseismic decoupling (<30 km downdip). Assuming uniform strain at failure these narrow zones are unable to store large amounts of strain energy compared to wide zones of interseismic decoupling. Since the transition from fully locked to a fully creeping rheology depends partly on temperature, to first order the width of the interseismic decoupling transition zone depends on the local dip of the MHT. Where the decoupling zone is narrow (25 km) moderate earthquakes (6 < Mw < 7) are observed to occur at intervals of a few hundred years. Where the transition zone is wide (e.g. Kashmir and Assam, 150 km) great earthquakes nucleate at long time intervals (millennia). Because the cumulative moment release of moderate earthquakes in regions of narrow seismic decoupling is insufficient to keep up with plate convergence, we conclude that megaquakes that eventually sweep through these regions are augmented by the heterogenous fossil strain of former incomplete ruptures. Because great earthquakes in the central Himalaya are inferred to nucleate from moderate earthquakes near the base of the MHT, the preparation zones of these moderate earthquakes may provide opportunities for forecasting the approach of future great earthquakes.

58 GEOSCIENCES↗

DOE OSTI2024

Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure

Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology

58 GEOSCIENCES↗

DOE OSTI2015

Relocation of the 2010-2013 near the north coast of Papua earthquake sequence using Modified Joint Hypocenter Determination (MJHD) method

The accuracy of earthquake hypocenter position is necessary to analyze the tectonic conditions. This study aims to: (1) relocate the mainshock and aftershocks of the large earthquakes in Papua region i.e. June 16, 2010, April 21, 2012 and April 06, 2013 earthquake (2) determine the true fault plane, (3) estimate the area of the fracture, and (4) analyze the advantages and disadvantages of relocation with MJHD method in benefits for tectonic studies. This study used Modified Joint Hypocenter Determination (MJHD) method. Using P arrival phase data reported by the BMKG and openly available from website repogempa.bmkg.go.id, we relocated the mainshock of this large significant earthquake and its aftershocks. Then we identified the prefered fault planes from the candidate fault planes provided by the global CMT catalogue. The position of earthquakes was successfully relocated. The earthquakes mostly were clustered around the mainshock. Earthquakes that not clustered around mainshock are considered to be different mechanism from the mainshock. Relocation results indicate that the mainshock fault plane of June 16, 2010 earthquake is a field with strike 332o, dip 80o and −172o slip, the mainshock fault plane of April 21, 2012 earthquake is a field with strike 82o, dip 84o and 2o slip, the mainshock fault plane of April 06, 2013 earthquake is a field with strike 339o, dip 56o and −137o slip. Fault plane area estimated by cross section graphical method is an area of 2816.0 km2 (June 16, 2010), 906.2 km2 (April 21, 2012) and 1984.3 km2 (April 06, 2013). MJHD method has the advantage that it can calculate a lot of earthquakes simultaneously and has a station correction to account for lateral heterogeneity of the earth. This method successfully provides significant changes to improve the position of the depth of earthquakes that most of the hypocenter depth manually specified as a fixed depth (± 10 km). But this method cannot be sure that the hypocenters derived from the same earthquake mechanism.

58 GEOSCIENCES↗

DOE OSTI2022

Earthquake Phase Association Using a Bayesian Gaussian Mixture Model

Earthquake phase association algorithms aggregate picked seismic phases from a network of seismometers into individual seismic events and play an important role in earthquake monitoring and research. Dense seismic networks and improved phase picking methods produce massive seismic phase datasets, particularly for earthquake swarms and aftershocks occurring closely in time and space, making phase association a challenging problem. Here, we present a new association method, the Gaussian Mixture Model Association (GaMMA), that combines the Gaussian mixture model with earthquake location, origin time, and magnitude estimation. We treat earthquake phase association as an unsupervised clustering problem in a probabilistic framework, where each earthquake corresponds to a cluster of P and S phases with a hyperbolic moveout of arrival times and a decay of amplitude with distance. We use the multivariate Gaussian distribution to model the collection of phase picks of an event; and the mean of the multivariate Gaussian distribution is given by the predicted arrival time and amplitude from the causative event. We carry out the pick assignment to each earthquake and determine earthquake source parameters (i.e., earthquake location, origin time, and magnitude) under the maximum likelihood criterion using the Expectation-Maximization algorithm. The GaMMA method does not require typical association steps of other algorithms, such as grid-search or supervised training. The results for both synthetic tests and for the 2019 Ridgecrest earthquake sequence show that GaMMA effectively associates phases from a temporally and spatially dense earthquake sequence while producing useful estimates of earthquake location and magnitude.

58 GEOSCIENCES↗

DOE OSTI2022

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗

DOE OSTI2023

Dynamic Rupture Simulations of the Mw7.2 1992 Landers,California, Earthquake

An important part of the simulation technique implemented in the Recipe is the earthquake rupture characterization based on established empirical scaling relationships between source parameters and seismic moment. The scaling relationships used in the rupture characterization are derived from recorded data and are tested against dynamic and kinematic rupture models of crustal earthquakes. Currently, a revised three-stage source scaling relationship between the source rupture area and seismic moment of inland crustal earthquakes, initially proposed by Irikura and Miyake, is being used. Recent analysis of results obtained with the Recipe for the 2016 M7.1 Kumamoto earthquake performed by several researchers, including the PI, Arben Pitarka, indicate that in order to reproduce the near-fault long-period ground motions and the permanent displacements, observed during surface-rupturing earthquakes, the recipe needs modifications to the kinematic rupture parametrization in the shallow crustal weak zone. In particular, improvements are required in characterizing the slip rate function at shallow depths, above the sesimogenic zone. The main objective of this research project was the development of a dynamic rupture model for the Mw7.2 1992 Landers, California earthquake. The dynamic rupture model was used to derive kinematic rupture parameters, such as slip, slip-rate, rupture time distributions, and slip rate functions in the weak (0-4km) and seismogenic crustal zones. In addition to the knowledge gained from the dynamic rupture modeling of Chi-chi, Ridgecrest, Kumamoto and other crustal earthquakes, studied by the PI, the rupture characterization of the Landers earthquake can be helpful in updating the conventional recipe for broadband ground motion simulations of crustal earthquakes with shallow rupture. The project emphasizes the need for performing physics-based earthquake rupture modeling which ultimately will inform further improvements of rupture characterization. In particular, the modeling of rupture dynamics for recorded earthquakes, and numerical simulations for different rupture scenarios, provides physical constrains on slip evolution in time and space, used in adjustments of empirical source scaling relationships for large crustal earthquakes.

58 GEOSCIENCES↗

NASA NTRS2010

Validating of Atmospheric Signals Associated with some of the Major Earthquakes in Asia (2003-2009)

The recent catastrophic earthquake in Haiti (January 2010) has provided and renewed interest in the important question of the existence of precursory signals related to strong earthquakes. Latest studies (VESTO workshop in Japan 2009) have shown that there were precursory atmospheric signals observed on the ground and in space associated with several recent earthquakes. The major question, still widely debated in the scientific community is whether such signals systematically precede major earthquakes. To address this problem we have started to validate the anomalous atmospheric signals during the occurrence of large earthquakes. Our approach is based on integration analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, Radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. We performed hind-cast detection over three different regions with high seismicity Taiwan, Japan and Kamchatka for the period of 2003-2009. We are using existing thermal satellite data (Aqua and POES); in situ atmospheric data (NOAA/NCEP); and ionospheric variability data (GPS/TEC and DEMETER). The first part of this validation included 42 major earthquakes (M greater than 5.9): 10 events in Taiwan, 15 events in Japan, 15 events in Kamchatka and four most recent events for M8.0 Wenchuan earthquake (May 2008) in China and M7.9 Samoa earthquakes (Sep 2009). Our initial results suggest a systematic appearance of atmospheric anomalies near the epicentral area, 1 to 5 days prior to the largest earthquakes, that could be explained by a coupling process between the observed physical parameters, and the earthquake preparation processes.

Ouzounov, D. P.↗

NASA NTRS2012

Multi-Parameter Observation and Detection of Pre-Earthquake Signals in Seismically Active Areas

The recent large earthquakes (M9.0 Tohoku, 03/2011; M7.0 Haiti, 01/2010; M6.7 L Aquila, 04/2008; and M7.9 Wenchuan 05/2008) have renewed interest in pre-anomalous seismic signals associated with them. Recent workshops (DEMETER 2006, 2011 and VESTO 2009 ) have shown that there were precursory atmospheric /ionospheric signals observed in space prior to these events. Our initial results indicate that no single pre-earthquake observation (seismic, magnetic field, electric field, thermal infrared [TIR], or GPS/TEC) can provide a consistent and successful global scale early warning. This is most likely due to complexity and chaotic nature of earthquakes and the limitation in existing ground (temporal/spatial) and global satellite observations. In this study we analyze preseismic temporal and spatial variations (gas/radon counting rate, atmospheric temperature and humidity change, long-wave radiation transitions and ionospheric electron density/plasma variations) which we propose occur before the onset of major earthquakes:. We propose an Integrated Space -- Terrestrial Framework (ISTF), as a different approach for revealing pre-earthquake phenomena in seismically active areas. ISTF is a sensor web of a coordinated observation infrastructure employing multiple sensors that are distributed on one or more platforms; data from satellite sensors (Terra, Aqua, POES, DEMETER and others) and ground observations, e.g., Global Positioning System, Total Electron Content (GPS/TEC). As a theoretical guide we use the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model to explain the generation of multiple earthquake precursors. Using our methodology, we evaluated retrospectively the signals preceding the most devastated earthquakes during 2005-2011. We observed a correlation between both atmospheric and ionospheric anomalies preceding most of these earthquakes. The second phase of our validation include systematic retrospective analysis for more than 100 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. Calculated false alarm ratio for the for the same month over the entire period of analysis (2003-2009) is less than 10% and was d as the earthquakes. The commonalities in detecting atmospheric/ionospheric anomalies show that they may exist over both land and sea in regions of maximum stress (i.e., along plate boundaries) Our results indicate that the ISTF model could provide a capability to observe pre-earthquake atmospheric/ionospheric signals by combining this information into a common framework.

Ouzounov, D.↗

DOE OSTI2023

Real-Time Fault Tracking and Ground Motion Prediction for Large Earthquakes With HR-GNSS and Deep Learning

Earthquake early warning (EEW) systems aim to forecast the shaking intensity rapidly after an earthquake occurs and send warnings to affected areas before the onset of strong shaking. The system relies on rapid and accurate estimation of earthquake source parameters. However, it is known that source estimation for large ruptures in real-time is challenging, and it often leads to magnitude underestimation. In a previous study, we showed that machine learning, HR-GNSS, and realistic rupture synthetics can be used to reliably predict earthquake magnitude. This model, called Machine-Learning Assessed Rapid Geodetic Earthquake model (M-LARGE), can rapidly forecast large earthquake magnitudes with an accuracy of 99%. Here, we expand M-LARGE to predict centroid location and fault size, enabling the construction of the fault rupture extent for forecasting shaking intensity using existing ground motion models. We test our model in the Chilean Subduction Zone with thousands of simulated and five real large earthquakes. The result achieves an average warning time of 40.5 s for shaking intensity MMI4+, surpassing the 34 s obtained by a similar GNSS EEW model. Our approach addresses a critical gap in existing EEW systems for large earthquakes by demonstrating real-time fault tracking feasibility without saturation issues. This capability leads to timely and accurate ground motion forecasts and can support other methods, enhancing the overall effectiveness of EEW systems. Additionally, the ability to predict source parameters for real Chilean earthquakes implies that synthetic data, governed by our understanding of earthquake scaling, is consistent with the actual rupture processes.

58 GEOSCIENCES↗

DOE OSTI2016

The evaluation of the earthquake hazard using the exponential distribution method for different seismic source regions in and around Ağrı

The aim of this study; were determined of the earthquake hazard using the exponential distribution method for different seismic sources of the Ağrı and vicinity. A homogeneous earthquake catalog has been examined for 1900-2015 (the instrumental period) with 456 earthquake data for Ağrı and vicinity. Catalog; Bogazici University Kandilli Observatory and Earthquake Research Institute (Burke), National Earthquake Monitoring Center (NEMC), TUBITAK, TURKNET the International Seismological Center (ISC), Seismological Research Institute (IRIS) has been created using different catalogs like. Ağrı and vicinity are divided into 7 different seismic source regions with epicenter distribution of formed earthquakes in the instrumental period, focal mechanism solutions, and existing tectonic structures. In the study, the average magnitude value are calculated according to the specified magnitude ranges for 7 different seismic source region. According to the estimated calculations for 7 different seismic source regions, the biggest difference corresponding with the classes of determined magnitudes between observed and expected cumulative probabilities are determined. The recurrence period and earthquake occurrence number per year are estimated of occurring earthquakes in the Ağrı and vicinity. As a result, 7 different seismic source regions are determined occurrence probabilities of an earthquake 3.2 magnitude, Region 1 was greater than 6.7 magnitude, Region 2 was greater than than 4.7 magnitude, Region 3 was greater than 5.2 magnitude, Region 4 was greater than 6.2 magnitude, Region 5 was greater than 5.7 magnitude, Region 6 was greater than 7.2 magnitude, Region 7 was greater than 6.2 magnitude. The highest observed magnitude 7 different seismic source regions of Ağrı and vicinity are estimated 7 magnitude in Region 6. Region 6 are determined according to determining magnitudes, occurrence years of earthquakes in the future years, respectively, 7.2 magnitude was in 158 years, 6.7 magnitude was in 70 years, 6.2 magnitude was in 31 years, 5.7 magnitude was in 13 years, 5.2 magnitude was in 6 years.

58 GEOSCIENCES↗

DOE OSTI2015

Seismic design of a nuclear waste repository against an earthquake induced rock shear load - 15346

Concepts for isolation of spent nuclear fuel have been studied by organizations in countries that employ nuclear power. These concepts typically involve a deep geological repository in bedrock, with processed radioactive waste encased in deposition canisters emplaced in underground excavations and surrounded by clay-based buffer. This multi-barrier approach is intended to provide long-term isolation of the waste package from the biosphere. According to many statistics, there is a tendency toward increasing numbers of earthquakes in the Korean peninsula each year. If an earthquake induced rock shear load occurs at a repository site, the engineered barrier system (EBS) can be sheared, resulting in a pressure increased in the buffer material. This is expected to result in damage to the canisters. Therefore, because the damage, which can be fatal to a disposal canister, can be given in case an earthquake occurs, the method protecting the canisters safely is needed. In this paper, 'an earthquake-resistance type buffer' was proposed using a method for protection from earthquake damage. To aid in achieving this objective, we have developed a technique for estimating the behavior of the EBS affected by earthquake induced rock shear using an analysis method, such as finite element method. As a first step, experimental tests are performed for understanding the behavior of the buffer material. Comparing the results of the numerical simulations to the experimental results can be used to verity the reliability of the analysis model. Then we developed the real scale analysis model of a nuclear waste repository. The main parameter having an effect on the earthquake-resistant performance was analyzed and an earthquake-resistance proof type buffer was designed. To improve the earthquake-resistance performance, we designed the buffer by putting the low- density buffer between the canister and buffer. The simulation results show that the earthquake-resistant performance was improved by about 65%. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization

Abstract Accurate earthquake location and magnitude estimation play critical roles in seismology. Recent deep learning frameworks have produced encouraging results on various seismological tasks (e.g., earthquake detection, phase picking, seismic classification, and earthquake early warning). Many existing machine learning earthquake location methods utilize waveform information from a single station. However, multiple stations contain more complete information for earthquake source characterization. Inspired by recent successes in applying graph neural networks (GNNs) in graph‐structured data, we develop a Spatiotemporal Graph Neural Network (STGNN) for estimating earthquake locations and magnitudes. Our graph neural network leverages geographical and waveform information from multiple stations to construct graphs automatically and dynamically by adaptive message passing based on graphs' edges. Using a recent graph neural network and a fully convolutional neural network as baselines, we apply STGNN to earthquakes recorded by the Southern California Seismic Network from 2000 to 2019 and earthquakes collected in Oklahoma from 2014 to 2015. STGNN yields more accurate earthquake locations than those obtained by the baseline models and performs comparably in terms of depth and magnitude prediction, though the ability to predict depth and magnitude remains weak for all tested models. Our work demonstrates the potential of using GNNs and multiple stations for better automatic estimation of earthquake epicenters.

58 GEOSCIENCES↗

NASA NTRS2011

Atmospheric Signals Associated with Major Earthquakes. A Multi-Sensor Approach

We are studying the possibility of a connection between atmospheric observation recorded by several ground and satellites as earthquakes precursors. Our main goal is to search for the existence and cause of physical phenomenon related to prior earthquake activity and to gain a better understanding of the physics of earthquake and earthquake cycles. The recent catastrophic earthquake in Japan in March 2011 has provided a renewed interest in the important question of the existence of precursory signals preceding strong earthquakes. We will demonstrate our approach based on integration and analysis of several atmospheric and environmental parameters that were found associated with earthquakes. These observations include: thermal infrared radiation, radon! ion activities; air temperature and humidity and a concentration of electrons in the ionosphere. We describe a possible physical link between atmospheric observations with earthquake precursors using the latest Lithosphere-Atmosphere-Ionosphere Coupling model, one of several paradigms used to explain our observations. Initial results for the period of2003-2009 are presented from our systematic hind-cast validation studies. We present our findings of multi-sensor atmospheric precursory signals for two major earthquakes in Japan, M6.7 Niigata-ken Chuetsu-oki of July16, 2007 and the latest M9.0 great Tohoku earthquakes of March 11,2011

Ouzounov, Dimitar↗

DOE OSTI2017

Source characteristics and geological implications of the January 2016 induced earthquake swarm near Crooked Lake, Alberta

On 2016 January 12, an intraplate earthquake with an initial reported local magnitude (M L ) of 4.8 shook the town of Fox Creek, Alberta. While there were no reported damages, this earthquake was widely felt by the local residents and suspected to be induced by the nearby hydraulic-fracturing (HF) operations. We determine the earthquake source parameters using moment tensor inversions, and then detect and locate the associated swarm using a waveform cross-correlation based method. The broad-band seismic recordings from regional arrays suggest a moment magnitude (M) 4.1 for this event, which is the largest in Alberta in the past decade. Similar to other recent M ~ 3 earthquakes near Fox Creek, the 2016 January 12 earthquake exhibits a dominant strike-slip (strike = 184°) mechanism with limited non-double-couple components (~22 per cent). This resolved focal mechanism, which is also supported by forward modelling and P-wave first motion analysis, indicates an NE–SW oriented compressional axis consistent with the maximum compressive horizontal stress orientations delineated from borehole breakouts. Further detection analysis on industry-contributed recordings unveils 1108 smaller events within 3 km radius of the epicentre of the main event, showing a close spatial-temporal relation to a nearby HF well. The majority of the detected events are located above the basement, comparable to the injection depth (3.5 km) on the Duvernay shale Formation. The spatial distribution of this earthquake cluster further suggests that (1) the source of the sequence is an N–S-striking fault system and (2) these earthquakes were induced by an HF well close to but different from the well that triggered a previous (January 2015) earthquake swarm. Reactivation of pre-existing, N-S oriented faults analogous to the Pine Creek fault zone, which was reported by earlier studies of active source seismic and aeromagnetic data, are likely responsible for the occurrence of the January 2016 earthquake swarm and other recent events in the Crooked Lake area.

58 GEOSCIENCES↗

DOE OSTI2025

Overview of the SCEC/USGS Community Stress Drop Validation Study Using the 2019 Ridgecrest Earthquake Sequence

We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. Here, in this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values.

58 GEOSCIENCES↗

DOE OSTI2016

Location of largest earthquake slip and fast rupture controlled by along-strike change in fault structural maturity due to fault growth

Earthquake slip distributions are asymmetric along strike, but the reasons for the asymmetry are unknown. We address this question by establishing empirical relations between earthquake slip profiles and fault properties. We analyze the slip distributions of 27 large continental earthquakes in the context of available information on their causative faults, in particular on the directions of their long-term lengthening. We find that the largest slips during each earthquake systematically occurred on that half of the ruptured fault sections most distant from the long-term fault propagating tips, i.e., on the most mature half of the broken fault sections. Meanwhile, slip decreased linearly over most of the rupture length in the direction of long-term fault propagation, i.e., of decreasing structural maturity along strike. We suggest that this earthquake slip asymmetry is governed by along-strike changes in fault properties, including fault zone compliance and fault strength, induced by the evolution of off-fault damage, fault segmentation, and fault planarity with increasing structural maturity. We also find higher rupture speeds in more mature rupture sections, consistent with predicted effects of low-velocity damage zones on rupture dynamics. Since the direction(s) of long-term fault propagation can be determined from geological evidence, it might be possible to anticipate in which direction earthquake slip, once nucleated, may increase, accelerate, and possibly lead to a large earthquake. Finally, our results could thus contribute to earthquake hazard assessment and Earthquake Early Warning.

58 GEOSCIENCES↗

DOE OSTI2021

Long Short-Term Memory Networks for Pattern Recognition of Synthetical Complete Earthquake Catalog

Exploring the spatiotemporal distribution of earthquake activity, especially earthquake migration of fault systems, can greatly to understand the basic mechanics of earthquakes and the assessment of earthquake risk. By establishing a three-dimensional strike-slip fault model, to derive the stress response and fault slip along the fault under regional stress conditions. Our study helps to create a long-term, complete earthquake catalog. We modelled Long-Short Term Memory (LSTM) networks for pattern recognition of the synthetical earthquake catalog. The performance of the models was compared using the mean-square error (MSE). Our results showed clearly the application of LSTM showed a meaningful result of 0.08% in the MSE values. Our best model can predict the time and magnitude of the earthquakes with a magnitude greater than Mw = 6.5 with a similar clustering period. These results showed conclusively that applying LSTM in a spatiotemporal series prediction provides a potential application in the study of earthquake mechanics and forecasting of major earthquake events.

58 GEOSCIENCES↗

DOE OSTI2010

Earthquake Response Modeling for a Parked and Operating Megawatt-Scale Wind Turbine

Demand parameters for turbines, such as tower moment demand, are primarily driven by wind excitation and dynamics associated with operation. For that purpose, computational simulation platforms have been developed, such as FAST, maintained by the National Renewable Energy Laboratory (NREL). For seismically active regions, building codes also require the consideration of earthquake loading.Historically, it has been common to use simple building code approaches to estimate the structural demand from earthquake shaking, as an independent loading scenario. Currently, International Electrotechnical Commission (IEC) design requirements include the consideration of earthquake shaking while the turbine is operating. Numerical and analytical tools used to consider earthquake loads forbuildings and other static civil structures are not well suited for modeling simultaneous wind and earthquake excitation in conjunction with operational dynamics. Through the addition of seismic loading capabilities to FAST, it is possible to simulate earthquake shaking in the time domain, which allows consideration of non-linear effects such as structural nonlinearities, aerodynamic hysteresis,control system influence, and transients. This paper presents a FAST model of a modern 900-kW wind turbine, which is calibrated based on field vibration measurements. With this calibrated model, both coupled and uncoupled simulations are conducted looking at the structural demand for the turbine tower. Response is compared under the conditions of normal operation and potential emergency shutdowndue the earthquake induced vibrations. The results highlight the availability of a numerical tool for conducting such studies, and provide insights into the combined wind-earthquake loading mechanism.

17 WIND ENERGY↗