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At least 775 records · Page 43Linked to original sources
USGS2015

The petroleum geologist and the insurance policy

In a recent study, Hough and Page (2015) presented several lines of evidence suggesting that most of the significant earthquakes in Oklahoma during the twentieth century, including the M w 5.7 El Reno earthquake of 9 April 1952, were likely induced by wastewater injection and possibly secondary oil recovery operations. We undertook an archival search for accounts of this event, which unearthed a newspaper article published immediately following the El Reno earthquake regarding a prominent petroleum geologist in the area who took out a rare earthquake insurance policy less than 60 days before the earthquake struck. In this study we present a historical context for this intriguing coincidence. We present a retrospective of oil industry practices in the early‐ to mid‐twentieth century, gleaned from court records and other industry reports, that potentially bear on the interplay between oil exploration activities and earthquakes, focusing on the Oklahoma City region. We describe events of the day that could plausibly have alerted a geologist to the possibility of induced earthquakes, although there is no indication that the potential for induced earthquakes was widely recognized within the industry at that time.

Oklahoma↗
USGS2016

The Earthquake‐Source Inversion Validation (SIV) Project

Finite‐fault earthquake source inversions infer the (time‐dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake‐source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward‐modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source‐model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake‐source imaging problem.

Seismological Research Letters↗
USGS2016

Demonstration of the Cascadia G‐FAST geodetic earthquake early warning system for the Nisqually, Washington, earthquake

A prototype earthquake early warning (EEW) system is currently in development in the Pacific Northwest. We have taken a two‐stage approach to EEW: (1) detection and initial characterization using strong‐motion data with the Earthquake Alarm Systems (ElarmS) seismic early warning package and (2) the triggering of geodetic modeling modules using Global Navigation Satellite Systems data that help provide robust estimates of large‐magnitude earthquakes. In this article we demonstrate the performance of the latter, the Geodetic First Approximation of Size and Time (G‐FAST) geodetic early warning system, using simulated displacements for the 2001 M w 6.8 Nisqually earthquake. We test the timing and performance of the two G‐FAST source characterization modules, peak ground displacement scaling, and Centroid Moment Tensor‐driven finite‐fault‐slip modeling under ideal, latent, noisy, and incomplete data conditions. We show good agreement between source parameters computed by G‐FAST with previously published and postprocessed seismic and geodetic results for all test cases and modeling modules, and we discuss the challenges with integration into the U.S. Geological Survey’s ShakeAlert EEW system.

Washington↗
USGS2016

Reply to “Comment on ‘Ground motions from the 2015 Mw 7.8 Gorkha, Nepal, earthquake constrained by a detailed assessment of macroseismic data’ by Stacey S. Martin, Susan E. Hough, and Charleen Hung” by Andrea Tertulliani, Laura Graziani, Corrado Castellano, Alessandra Maramai, and Antonio Rossi

We thank Andrea Tertulliani and his colleagues for their interest in our article on the 2015 Gorkha earthquake (Martin, Hough, et al., 2015), and for their comments pertaining to our study (Tertulliani et al., 2016). Indeed, as they note, a comprehensive assessment of macroseismic effects for an earthquake with far‐reaching effects as that of Gorkha is not only critically important but is also an extremely difficult undertaking. In the absence of a widely known web‐based system, employing a well‐calibrated algorithm with which to collect and systematically assess macroseismic information (e.g., Wald et al., 1999; Coppola et al., 2010; Bossu et al., 2015) in the Indian subcontinent, one is left with two approaches to characterize effects of an event such as the Gorkha earthquake: a comprehensive ground‐based survey such as the one undertaken in India following the 2001 Bhuj earthquake (Pande and Kayal, 2003), or an assessment such as Martin, Hough, et al. (2015) akin to other contemporary studies (e.g., Nuttli, 1973; Sieh, 1978; Meltzner and Wald, 1998; Martin and Szeliga, 2010; Ambraseys and Bilham, 2012; Mahajan et al., 2012; Gupta et al., 2013; Singh et al., 2013; Hough and Martin, 2015; Martin and Hough, 2015; Martin, Bradley, et al., 2015; Ribeiro et al., 2015), based primarily upon media reports and other available documentary accounts.

Seismological Research Letters↗
USGS2016

Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States

The U.S. Geological Survey (USGS) has produced a one‐year (2016) probabilistic seismic‐hazard assessment for the central and eastern United States (CEUS) that includes contributions from both induced and natural earthquakes that are constructed with probabilistic methods using alternative data and inputs. This hazard assessment builds on our 2016 final model ( Petersen et al. , 2016 ) by adding sensitivity studies, illustrating hazard in new ways, incorporating new population data, and discussing potential improvements. The model considers short‐term seismic activity rates (primarily 2014–2015) and assumes that the activity rates will remain stationary over short time intervals. The final model considers different ways of categorizing induced and natural earthquakes by incorporating two equally weighted earthquake rate submodels that are composed of alternative earthquake inputs for catalog duration, smoothing parameters, maximum magnitudes, and ground‐motion models. These alternatives represent uncertainties on how we calculate earthquake occurrence and the diversity of opinion within the science community. In this article, we also test sensitivity to the minimum moment magnitude between M 4 and M 4.7 and the choice of applying a declustered catalog with b =1.0 rather than the full catalog with b =1.3. We incorporate two earthquake rate submodels: in the informed submodel we classify earthquakes as induced or natural, and in the adaptive submodel we do not differentiate. The alternative submodel hazard maps both depict high hazard and these are combined in the final model. Results depict several ground‐shaking measures as well as intensity and include maps showing a high‐hazard level (1% probability of exceedance in 1 year or greater). Ground motions reach 0.6 g horizontal peak ground acceleration (PGA) in north‐central Oklahoma and southern Kansas, and about 0.2 g PGA in the Raton basin of Colorado and New Mexico, in central Arkansas, and in north‐central Texas near Dallas–Fort Worth. The chance of having levels of ground motions corresponding to modified Mercalli intensity (MMI) VI or greater earthquake shaking is 2%–12% per year in north‐central Oklahoma and southern Kansas and New Madrid similar to the chance of damage at sites in high‐hazard portions of California caused by natural earthquakes. Hazard is also significant in the Raton basin of Colorado/New Mexico; north‐central Arkansas; Dallas–Fort Worth, Texas; and in a few other areas. Hazard probabilities are much lower (by about half or more) for exceeding MMI VII or VIII. Hazard is 3‐ to 10‐fold higher near some areas of active‐induced earthquakes than in the 2014 USGS National Seismic Hazard Model (NSHM), which did not consider induced earthquakes. This study in conjunction with the LandScan TM Database (2013) indicates that about 8 million people live in areas of active injection wells that have a greater than 1% chance of experiencing damaging ground shaking (MMI≥VI) in 2016. The final model has high uncertainty, and engineers, regulators, and industry should use these assessments cautiously to make informed decisions on mitigating the potential effects of induced and natural earthquakes.

Seismological Research Letters↗
USGS2017

Global Positioning System data collection, processing, and analysis conducted by the U.S. Geological Survey Earthquake Hazards Program

The U.S. Geological Survey Earthquake Science Center collects and processes Global Positioning System (GPS) data throughout the western United States to measure crustal deformation related to earthquakes and tectonic processes as part of a long‐term program of research and monitoring. Here, we outline data collection procedures and present the GPS dataset built through repeated temporary deployments since 1992. This dataset consists of observations at ∼1950 locations. In addition, this article details our data processing and analysis procedures, which consist of the following. We process the raw data collected through temporary deployments, in addition to data from continuously operating western U.S. GPS stations operated by multiple agencies, using the GIPSY software package to obtain position time series. Subsequently, we align the positions to a common reference frame, determine the optimal parameters for a temporally correlated noise model, and apply this noise model when carrying out time‐series analysis to derive deformation measures, including constant interseismic velocities, coseismic offsets, and transient postseismic motion.

Seismological Research Letters↗
USGS2017

A synoptic view of the Third Uniform California Earthquake Rupture Forecast (UCERF3)

Probabilistic forecasting of earthquake‐producing fault ruptures informs all major decisions aimed at reducing seismic risk and improving earthquake resilience. Earthquake forecasting models rely on two scales of hazard evolution: long‐term (decades to centuries) probabilities of fault rupture, constrained by stress renewal statistics, and short‐term (hours to years) probabilities of distributed seismicity, constrained by earthquake‐clustering statistics. Comprehensive datasets on both hazard scales have been integrated into the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3). UCERF3 is the first model to provide self‐consistent rupture probabilities over forecasting intervals from less than an hour to more than a century, and it is the first capable of evaluating the short‐term hazards that result from multievent sequences of complex faulting. This article gives an overview of UCERF3, illustrates the short‐term probabilities with aftershock scenarios, and draws some valuable scientific conclusions from the modeling results. In particular, seismic, geologic, and geodetic data, when combined in the UCERF3 framework, reject two types of fault‐based models: long‐term forecasts constrained to have local Gutenberg–Richter scaling, and short‐term forecasts that lack stress relaxation by elastic rebound.

Seismological Research Letters↗
USGS2017

The Station Information System (SIS): A centralized seismic station repository for populating, managing, and distributing metadata

Creating, maintaining, and archiving accurate station metadata is critical for successful seismic network operations, data discovery, and research. The Station Information System (SIS) is a centralized repository of seismic station equipment inventory, instrument response, and site information of stations operated by regional seismic networks (RSNs) of the Advanced National Seismic System (ANSS; Filson and Arabasz, 2017 ). It has a web‐based user interface that enables the creation and manipulation of the corresponding metadata. The system can track the installation, maintenance, and removal of equipment from a site, which often results in the creation of new metadata epochs. SIS also computes the overall response, including gain, of a data channel by combining the responses of the underlying hardware components. SIS distributes this information in standard formats such as Federation of Digital Seismic Networks StationXML and dataless Standard for the Exchange of Earthquake Data. SIS can also be used to manage inventory of field equipment such as power, telemetry, or Global Positioning System antenna, as well as links to other site‐related repositories external to SIS to give the network operator the most complete view of a site and the overall network. This article summarizes the main features in SIS. We present its basic infrastructure, holdings, workflow, and how RSNs retrieve data from it. We also explain the reasoning to pursue one centralized repository and why it supports the goals of SIS and the ANSS. We demonstrate that by providing the ANSS network operator with a comprehensive site view, SIS enables the production of high‐quality metadata, a necessary prerequisite for producing high‐quality seismic data.

Seismological Research Letters↗
USGS2018

2018 one‐year seismic hazard forecast for the central and eastern United States from induced and natural earthquakes

This article describes the U.S. Geological Survey (USGS) 2018 one‐year probabilistic seismic hazard forecast for the central and eastern United States from induced and natural earthquakes. For consistency, the updated 2018 forecast is developed using the same probabilistic seismicity‐based methodology as applied in the two previous forecasts. Rates of earthquakes across the United States M ≥ 3.0 "> M ≥ 3.0 grew rapidly between 2008 and 2015 but have steadily declined over the past 3 years, especially in areas of Oklahoma and southern Kansas where fluid injection has decreased. The seismicity pattern in 2017 was complex with earthquakes more spatially dispersed than in the previous years. Some areas of west‐central Oklahoma experienced increased activity rates where industrial activity increased. Earthquake rates in Oklahoma (429 earthquakes of M ≥ 3 "> M ≥ 3 and 4 M ≥ 4 "> M ≥ 4 ), Raton basin (Colorado/New Mexico border, six earthquakes M ≥ 3 "> M ≥ 3 ), and the New Madrid seismic zone (11 earthquakes M ≥ 3 "> M ≥ 3 ) continue to be higher than historical levels. Almost all of these earthquakes occurred within the highest hazard regions of the 2017 forecast. Even though rates declined over the past 3 years, the short‐term hazard for damaging ground shaking across much of Oklahoma remains at high levels due to continuing high rates of smaller earthquakes that are still hundreds of times higher than at any time in the state’s history. Fine details and variability between the 2016–2018 forecasts are obscured by significant uncertainties in the input model. These short‐term hazard levels are similar to active regions in California. During 2017, M ≥ 3 "> M ≥ 3 earthquakes also occurred in or near Ohio, West Virginia, Missouri, Kentucky, Tennessee, Arkansas, Illinois, Oklahoma, Kansas, Colorado, New Mexico, Utah, and Wyoming.

Seismological Research Letters↗
USGS2018

Improving earthquake rupture forecasts using California as a guide

This article discusses ways in which earthquake rupture forecast models might be improved. Because changes are most easily described in the context of specific models, the third Uniform California Earthquake Rupture Forecast (UCERF3) and its presumed successor, UCERF4, is used as a basis for discussion. Virtually all of the issues and possible improvements discussed are nevertheless general and should therefore be applicable to other regions as well. Two common themes are a need for better epistemic uncertainty representation and the potential utility of physics‐based simulators. Given the large number of possible improvements, coupled with challenges in defining the potential value of each, which will vary among uses, community feedback is invaluable in terms of setting priorities. We should also strive to define more objective valuation metrics.

Seismological Research Letters↗
USGS2019

#EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm

Communicating probabilities of natural hazards to varied audiences is a notoriously difficult task. Many of these challenges were encountered during the 2016 Bombay Beach, California, swarm of ~100 2≤M≤4.3 earthquakes, which began on 26 September 2016 and lasted for several days. The swarm’s proximity to the southern end of the San Andreas fault caused concern that a larger earthquake could be triggered. Within 1–2 days, different forecast models were used to evaluate the likelihood of a larger event with two agencies (the U.S. Geological Survey [USGS] and the California Governor’s Office of Emergency Services) releasing probabilities and forecasts for larger earthquakes. Our research explores communication and news media efforts, as well as how people on a microblogging social media site (Twitter) responded to these forecasts. Our findings suggest that news media used a combination of information sources, basing their articles on what they learned from social media, as well as using information provided by government agencies. As the swarm slowed down, there is evidence of the continued interplay between news media and social media, with the USGS issuing revised probability reports and scientists from the USGS and other institutions participating in media interviews. In reporting on the swarm, news media often used language more generally than the scientists; terms such as probability, likelihood, chance, and possibility were used interchangeably. Knowledge of how news media used scientific information from the 2016 Bombay Beach forecasts can assist local, state, and federal agencies in developing effective communication strategies to respond to future earthquakes.

California↗
USGS2020

The 2019 Ridgecrest, California, earthquake sequence ground motions: Processed records and derived intensity metrics

Following the 2019 Ridgecrest, California, earthquake sequence, we compiled ground‐motion records from multiple data centers and processed these records using newly developed ground‐motion processing software that performs quality assurance checks, performs standard time series processing steps, and computes a wide range of ground‐motion metrics. In addition, we compute station and waveform metrics such as the time‐averaged shear‐wave velocity to 30 m depth ( ⁠ V S 30 "> V S 30 ⁠ ), finite‐rupture distances, and spectral accelerations. This data set includes 22,708 records from 133 events from 4 July 2019 (UTC) to 18 October 2019 with a magnitude range from 3.6 to 7.1. We expect that the rapid collection and dissemination of this information will facilitate detailed studies of these ground motions. In this article, we describe the data selection, processing steps, and how to access the data.

California↗
USGS2020

The U.S. Geological Survey’s Rapid Seismic Array Deployment for the 2019 Ridgecrest Earthquake Sequence

Rapid seismic deployments following large earthquakes capture ephemeral near‐field recordings of aftershocks and ambient noise that can provide valuable data for seismological studies. The U.S. Geological Survey installed 19 temporary seismic stations following the 4 July 2019 M w 6.4 and 6 July 2019 (UTC) M w 7.1 earthquakes near the city of Ridgecrest, California. The stations record the aftershock sequence beginning two days after the mainshock and are expected to remain in the field through approximately January 2020. The deployment augments the permanent seismic network in the area to improve azimuthal coverage and provide additional near‐field observations. This article summarizes the motivation and goals of the deployment; details of station installation, instrumentation, and configurations; and initial data quality and observations from the network. We expect these data to be useful for a range of studies including detailing near‐field variability in strong ground motions, determining stress drops and rupture directivity of small events, imaging the fault zone, documenting the evolution of crustal properties within and outside of the fault zone, and others.

California↗
USGS2020

Documentation of Surface Fault Rupture and Ground‐Deformation Features Produced by the 4 and 5 July 2019 Mw 6.4 and Mw 7.1 Ridgecrest Earthquake Sequence

The M w "> M w Mw 6.4 and M w "> M w Mw 7.1 Ridgecrest earthquake sequence occurred on 4 and 5 July 2019 within the eastern California shear zone of southern California. Both events produced extensive surface faulting and ground deformation within Indian Wells Valley and Searles Valley. In the weeks following the earthquakes, more than six dozen scientists from government, academia, and the private sector carefully documented the surface faulting and ground‐deformation features. As of December 2019, we have compiled a total of more than 6000 ground observations; approximately 1500 of these simply note the presence or absence of fault rupture or ground failure, but the remainder include detailed descriptions and other documentation, including tens of thousands of photographs. More than 1100 of these observations also include quantitative field measurements of displacement sense and magnitude. These field observations were supplemented by mapping of fault rupture and ground‐deformation features directly in the field as well as by interpreting the location and extent of surface faulting and ground deformation from optical imagery and geodetic image products. We identified greater than 68 km of fault rupture produced by both earthquakes as well as numerous sites of ground deformation resulting from liquefaction or slope failure. These observations comprise a dataset that is fundamental to understanding the processes that controlled this earthquake sequence and for improving earthquake hazard estimates in the region. This article documents the types of data collected during postearthquake field investigations, the compilation effort, and the digital data products resulting from these efforts.

California↗
USGS2020

Capturing, preserving and digitizing legacy seismic data from the Montserrat Volcano Observatory analog seismic network, July 1995 – December 2004

An eruption of the Soufrière Hills Volcano (SHV) on the eastern Caribbean island of Montserrat began on 18 July 1995 and continued until February 2010. Within nine days of the eruption onset, an existing four‐station analog seismic network (ASN) was expanded to 10 sites. Telemetered data from this network were recorded, processed, and archived locally using a system developed by scientists from the U.S. Geological Survey (USGS) Volcano Disaster Assistance Program (VDAP). In October 1996, a digital seismic network (DSN) was deployed with the ability to capture larger amplitude signals across a broader frequency range. These two networks operated in parallel until December 2004, with separate telemetry and acquisition systems (analysis systems were merged in March 2001). Although the DSN provided better quality data for research, the ASN featured superior real‐time monitoring tools and captured valuable data including the only seismic data from the first 15 months of the eruption. These successes of the ASN have been rather overlooked. This article documents the evolution of the ASN, the VDAP system, the original data captured, and the recovery and conversion of more than 230,000 seismic events from legacy SUDS, Hypo71, and Seislog formats into Seisan database with waveform data in miniSEED format. No digital catalog existed for these events, but students at the University of South Florida have classified two-thirds of the 40,000 events that were captured between July 1995 and October 1996. Locations and magnitudes were recovered for ~10,000 of these events. Real-time seismic amplitude measurement, seismic spectral amplitude measurement, and tiltmeter data were also captured. The result is that the ASN seismic dataset is now more discoverable, accessible, and reusable, in accordance with FAIR data principles. These efforts could catalyze new research on the 1995–2010 SHV eruption. Furthermore, many observatories have data in these same legacy data formats and might benefit from procedures and codes documented here.

Soufrière Hills Volcano↗
USGS2020

Installation and performance of the Albuquerque Seismological Laboratory small-aperture posthole array

The Global Seismographic Network (GSN) has been used extensively by seismologists to characterize large earthquakes and image deep earth structure. Although the network’s original design goals have been met, the seismological community has suggested that the incorporation of small-aperture seismic arrays at select sites may improve performance of the network and enable new observations. As a pilot study for this concept, we have created a 500 m aperture, nine-element broadband seismic array around the GSN station ANMO (Albuquerque, New Mexico) at the U.S. Geological Survey Albuquerque Seismological Laboratory (ASL). The array was formed by supplementing the secondary borehole seismometer (90 m depth) at ANMO with eight additional 2.6 m posthole sites. Each station’s seismometer was oriented using a fiber optic gyroscope to within 2.0° of north. Data quality, particularly on the vertical components, is excellent with median power levels closely tracking the secondary sensor at ANMO at frequencies lower than 1 Hz. Horizontal component data are more variable at low frequencies (< 0:02 Hz), with the type of installation and local geography appearing to strongly influence the amount of tilt-induced noise. Throughout the article, we pose several fundamental questions related to the variability and precision of seismic wavefield measurements that we seek to address with data from this array. In addition, we calculate the array response and show a few examples of using the array to obtain back azimuths of a local event and a continuous narrowband noise source. The apparent velocity of the event across the array is then used to infer the local P-wave velocity at the ASL. Near real-time data collected from the array along with collocated meteorological, magnetic, and infrasound data are freely available in near-real time from the Incorporated Research Institutions for Seismology Data Management Center.

New Mexico↗
USGS2021

Preface to the Focus Section on the 2020 Intermountain West earthquakes

The Intermountain West region of the United States extends from the eastern margin of the Sierra Nevada and Cascade Mountains in the west to the Rocky Mountains in the east. The region is characterized by dextral shear along the eastern margin of the Sierra Nevada and nearly east-west extension in the Basin and Range. This region experienced four significant earthquake sequences in the first half of 2020. The most significant mainshocks were the 18 March 2020 Mw 5.7 earthquake north of Magna, Utah (a suburb of Salt Lake City), the 31 March 2020 Mw 6.5 earthquake northwest of Stanley, Idaho, the 15 May 2020 Mw 6.5 earthquake in the Monte Cristo Range, northwest of Tonopah, Nevada, and the 24 June 2020 Mw 5.8 earthquake near Lone Pine, California. The 15 articles appearing in this focus section explore timely and important topics associated with these sequences, including kinematic rupture models, near-field ground motions, aftershock statistics, geologic observations, seismic hazard implications, and seismotectonics. It is noteworthy that the efforts to record and characterize these earthquake sequences took place during travel and work restrictions necessitated by the COVID-19 pandemic.

Seismological Research Letters↗
USGS2021

lsforce: A Python-based single-force seismic inversion framework for massive landslides

We present an open‐source Python package, lsforce, for performing single‐force source inversions of long‐period (tens to hundreds of seconds) seismic signals. Although the software is designed primarily for landslides, it can be used for any single‐force seismic source. The package allows users to produce estimates of the three‐component time series of forces exerted on the Earth by a landslide with postprocessing options to estimate the trajectory of its center of mass. Green’s functions for a user‐selected 1D Earth model are obtained automatically from the Incorporated Research Institutions for Seismology Synthetics Engine webservice or can be computed for custom 1D Earth models using Computer Programs in Seismology. lsforce implements the two most commonly used source parameterizations: a fully flexible, high‐resolution approach and a more stable but lower‐resolution method of overlapping triangle sources. Regularization options include a blended zeroth‐, first‐, and second‐order semiautomated Tikhonov regularization scheme, as well as additional optional constraints on start times, end times, and on the sum of forces. Uncertainty due to data selection can be assessed using either a leave‐one‐out approach or a modified jackknife technique that randomly excludes subsets of the data for multiple re‐inversions. Numerous built‐in plotting methods allow for easy quality control and assessment of results. In this article, we briefly outline the theory and methodology, describe our implementation, and demonstrate the usage of lsforce using the well‐studied 28 June 2016 Lamplugh rock avalanche in Alaska. Despite the rapidly increasing prevalence of landslide single‐force inversions in the landslide and seismology literature over the past decade, to our knowledge this is the first open‐source code for performing such inversions.

Seismological Research Letters↗