Geology topics

Elizabeth S. Cochran

Publications and source records attributed to Elizabeth S. Cochran.

At least 91 records · Page 5Linked to original sources

USGS2017

Strong SH-to-Love wave scattering off the Southern California Continental Borderland

Seismic scattering is commonly observed and results from wave propagation in heterogeneous medium. Yet, deterministic characterization of scatterers associated with lateral heterogeneities remains challenging. In this study, we analyze broadband waveforms recorded by the Southern California Seismic Network and observe strongly scattered Love waves following the arrival of teleseismic SH wave. These scattered Love waves travel approximately in the same (azimuthal) direction as the incident SH wave at a dominant period of ~10 s but at an apparent velocity of ~3.6 km/s as compared to the ~11 km/s for the SH wave. Back-projection suggests that this strong scattering is associated with pronounced bathymetric relief in the Southern California Continental Borderland, in particular the Patton Escarpment. Finite-difference simulations using a simplified 2-D bathymetric and crustal model are able to predict the arrival times and amplitudes of major scatterers. The modeling suggests a relatively low shear wave velocity in the Continental Borderland.

California↗

USGS2017

Source spectral properties of small-to-moderate earthquakes in southern Kansas

The source spectral properties of injection-induced earthquakes give insight into their nucleation, rupture processes, and influence on ground motion. Here we apply a spectral decomposition approach to analyze P -wave spectra and estimate Brune-type stress drop for more than 2000 M L 1.5–5.2 earthquakes occurring in southern Kansas from 2014 to 2016. We find that these earthquakes are characterized by low stress drop values (median ∼0.4MPa) compared to natural seismicity in California. We observe a significant increase in stress drop as a function of depth, but the shallow depth distribution of these events is not by itself sufficient to explain their lower stress drop. Stress drop increases with magnitude from M1.5–M3.5, but this scaling trend may weaken above M4 and also depends on the assumed source model. Although we observe a nonstationary, sequence-specific temporal evolution in stress drop, we find no clear systematic relation with the activity of nearby injection wells.

Kansas↗

USGS2017

Delayed seismicity rate changes controlled by static stress transfer

On 15 June 2010, a M w 5.7 earthquake occurred near Ocotillo, California, in the Yuha Desert. This event was the largest aftershock of the 4 April 2010 M w 7.2 El Mayor-Cucapah (EMC) earthquake in this region. The EMC mainshock and subsequent Ocotillo aftershock provide an opportunity to test the Coulomb failure hypothesis (CFS). We explore the spatiotemporal correlation between seismicity rate changes and regions of positive and negative CFS change imparted by the Ocotillo event. Based on simple CFS calculations we divide the Yuha Desert into three subregions, one triggering zone and two stress shadow zones. We find the nominal triggering zone displays immediate triggering, one stress shadowed region experiences immediate quiescence, and the other nominal stress shadow undergoes an immediate rate increase followed by a delayed shutdown. We quantitatively model the spatiotemporal variation of earthquake rates by combining calculations of CFS change with the rate-state earthquake rate formulation of Dieterich (1994), assuming that each subregion contains a mixture of nucleation sources that experienced a CFS change of differing signs. Our modeling reproduces the observations, including the observed delay in the stress shadow effect in the third region following the Ocotillo aftershock. The delayed shadow effect occurs because of intrinsic differences in the amplitude of the rate response to positive and negative stress changes and the time constants for return to background rates for the two populations. We find that rate-state models of time-dependent earthquake rates are in good agreement with the observed rates and thus explain the complex spatiotemporal patterns of seismicity.

California↗

USGS2017

Aftershocks driven by afterslip and fluid pressure sweeping through a fault-fracture mesh

A variety of physical mechanisms are thought to be responsible for the triggering and spatiotemporal evolution of aftershocks. Here we analyze a vigorous aftershock sequence and postseismic geodetic strain that occurred in the Yuha Desert following the 2010 M w 7.2 El Mayor-Cucapah earthquake. About 155,000 detected aftershocks occurred in a network of orthogonal faults and exhibit features of two distinct mechanisms for aftershock triggering. The earliest aftershocks were likely driven by afterslip that spread away from the main shock with the logarithm of time. A later pulse of aftershocks swept again across the Yuha Desert with square root time dependence and swarm-like behavior; together with local geological evidence for hydrothermalism, these features suggest that the events were driven by fluid diffusion. The observations illustrate how multiple driving mechanisms and the underlying fault structure jointly control the evolution of an aftershock sequence.

Geophysical Research Letters↗

USGS2017

Low stress drops observed for aftershocks of the 2011 Mw 5.7 Prague, Oklahoma, earthquake

In November 2011, three M w ≥ 4.8 earthquakes and thousands of aftershocks occurred along the structurally complex Wilzetta fault system near Prague, Oklahoma. Previous studies suggest that wastewater injection induced a M w 4.8 foreshock, which subsequently triggered a M w 5.7 mainshock. We examine source properties of aftershocks with a standard Brune-type spectral model and jointly solve for seismic moment ( M 0 ), corner frequency ( f 0 ), and kappa ( κ ) with an iterative Gauss-Newton global downhill optimization method. We examine 934 earthquakes with initial moment magnitudes ( M w ) between 0.33 and 4.99 based on the pseudospectral acceleration and recover reasonable M 0 , f 0 , and κ for 87 earthquakes with M w 1.83–3.51 determined by spectral fit. We use M 0 and f 0 to estimate the Brune-type stress drop, assuming a circular fault and shear-wave velocity at the hypocentral depth of the event. Our observations suggest that stress drops range between 0.005 and 4.8 MPa with a median of 0.2 MPa (0.03–26.4 MPa with a median of 1.1 MPa for Madariaga-type), which is significantly lower than typical eastern United States intraplate events (>10 MPa). We find that stress drops correlate weakly with hypocentral depth and magnitude. Additionally, we find the stress drops increase with time after the mainshock, although temporal variation in stress drop is difficult to separate from spatial heterogeneity and changing event locations. The overall low median stress drop suggests that the fault segments may have been primed to fail as a result of high pore fluid pressures, likely related to nearby wastewater injection.

Oklahoma↗

USGS2017

Poroelastic properties of the Arbuckle Group in Oklahoma derived from well fluid level response to the 3 September 2016 M w 5.8 Pawnee and 7 November 2016 M w 5.0 Cushing earthquakes

The Arbuckle Group (Arbuckle) is a basal sedimentary unit that is the primary target for saltwater disposal in Oklahoma. Thus, the reservoir characteristics of the Arbuckle, including how the poroelastic properties change laterally and over time are of significant interest. We report observations of fluid level changes in two monitoring wells in response to the 3 September 2016 M w 5.8 Pawnee and the 7 November 2016 M w 5.0 Cushing earthquakes. We investigate the relationship between static strain resulting from these events and the fluid level changes observed in the wells. We model the fluid level response by estimating static strains from a set of earthquake source parameters and spatiotemporal poroelastic properties of the Arbuckle in the neighborhood of the monitoring wells. Results suggest that both the direction of the observed fluid level step and the amplitude can be predicted from the computed volumetric strain change and a reasonable set of poroelastic parameters. Modeling results indicate that poroelastic parameters differ at the time of the Pawnee and Cushing earthquakes, with a moderately higher Skempton’s coefficient required to fit the response to the Cushing earthquake. This may indicate that dynamic shaking resulted in physical alteration of the Arbuckle at distances up to ∼50 km from the Pawnee earthquake.

Oklahoma↗

USGS2017

Quake warnings, seismic culture

Since 1990, nearly one million people have died from the impacts of earthquakes. Reducing those impacts requires building a local seismic culture in which residents are aware of earthquake risks and value efforts to mitigate harm. Such efforts include earthquake early warning (EEW) systems that provide seconds to minutes notice of pending shaking. Recent events in Mexico provide an opportunity to assess performance and perception of an EEW system and highlight areas for further improvement. We have learned that EEW systems, even imperfect ones, can help people prepare for earthquakes and build local seismic culture, both beneficial in reducing earthquake-related losses.

Science↗

USGS2016

Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence

The seismic spectrum can be constructed by assuming a Brune spectral model and estimating the parameters of seismic moment ( M 0 ), corner frequency ( f c ), and high-frequency site attenuation ( κ ). Using seismic data collected during the 2010–2011 Canterbury, New Zealand, earthquake sequence, we apply the non-linear least-squares Gauss–Newton method, a deterministic downhill optimization technique, to simultaneously determine the M 0 , f c , and κ for each event-station pair. We fit the Brune spectral acceleration model to Fourier-transformed S-wave records following application of path and site corrections to the data. For each event, we solve for a single M 0 and f c , while any remaining residual kappa, κ r "> κ r κr , is allowed to differ per station record to reflect varying high-frequency falloff due to path and site attenuation. We use a parametric forward modeling method, calculating initial M 0 and f c values from the local GNS New Zealand catalog M w, GNS magnitudes and measuring an initial κ r "> κ r κr using an automated high-frequency linear regression method. Final solutions for M 0 , f c , and κ r "> κ r κr are iteratively computed through minimization of the residual function, and the Brune model stress drop is then calculated from the final, best-fit f c . We perform the spectral fitting routine on nested array seismic data that include the permanent GeoNet accelerometer network as well as a dense network of nearly 200 Quake Catcher Network (QCN) MEMs accelerometers, analyzing over 180 aftershocks M w,GNS ≥ 3.5 that occurred from 9 September 2010 to 31 July 2011. QCN stations were hosted by public volunteers and served to fill spatial gaps between existing GeoNet stations. Moment magnitudes determined using the spectral fitting procedure ( M w,SF ) range from 3.5 to 5.7 and agree well with M w,GNS , with a median difference of 0.09 and 0.17 for GeoNet and QCN records, respectively, and 0.11 when data from both networks are combined. The majority of events are calculated to have stress drops between 1.7 and 13 MPa (20th and 80th percentile, correspondingly) for the combined networks. The overall median stress drop for the combined networks is 3.2 MPa, which is similar to median stress drops previously reported for the Canterbury sequence. We do not observe a correlation between stress drop and depth for this region, nor a relationship between stress drop and magnitude over the catalog considered. Lateral spatial patterns in stress drop, such as a cluster of aftershocks near the eastern extent of the Greendale fault with higher stress drops and lower stress drops for aftershocks of the 2011 M w,GNS 6.2 Christchurch mainshock, are found to be in agreement with previous reports. As stress drop is arguably a method-dependent calculation and subject to high spatial variability, our results using the parametric Gauss–Newton algorithm strengthen conclusions that the Canterbury sequence has stress drops that are more similar to those found in intraplate regions, with overall higher stress drops that are typically observed in tectonically active areas.

Christchurch↗

USGS2016

3-D P- and S-wave velocity structure and low-frequency earthquake locations in the Parkfield, California region

To refine the 3-D seismic velocity model in the greater Parkfield, California region, a new data set including regular earthquakes, shots, quarry blasts and low-frequency earthquakes (LFEs) was assembled. Hundreds of traces of each LFE family at two temporary arrays were stacked with time–frequency domain phase weighted stacking method to improve signal-to-noise ratio. We extend our model resolution to lower crustal depth with LFE data. Our result images not only previously identified features but also low velocity zones (LVZs) in the area around the LFEs and the lower crust beneath the southern Rinconada Fault. The former LVZ is consistent with high fluid pressure that can account for several aspects of LFE behaviour. The latter LVZ is consistent with a high conductivity zone in magnetotelluric studies. A new Vs model was developed with S picks that were obtained with a new autopicker. At shallow depth, the low Vs areas underlie the strongest shaking areas in the 2004 Parkfield earthquake. We relocate LFE families and analyse the location uncertainties with the NonLinLoc and tomoDD codes. The two methods yield similar results.

California↗

USGS2016

Along-strike variations in fault frictional properties along the San Andreas Fault near Cholame, California from joint earthquake and low-frequency earthquake relocations

Recent observations of low‐frequency earthquakes (LFEs) and tectonic tremor along the Parkfield–Cholame segment of the San Andreas fault suggest slow‐slip earthquakes occur in a transition zone between the shallow fault, which accommodates slip by a combination of aseismic creep and earthquakes (<15  km depth), and the deep fault, which accommodates slip by stable sliding (>35  km depth). However, the spatial relationship between shallow earthquakes and LFEs remains unclear. Here, we present precise relocations of 34 earthquakes and 34 LFEs recorded during a temporary deployment of 13 broadband seismic stations from May 2010 to July 2011. We use the temporary array waveform data, along with data from permanent seismic stations and a new high‐resolution 3D velocity model, to illuminate the fine‐scale details of the seismicity distribution near Cholame and the relation to the distribution of LFEs. The depth of the boundary between earthquakes and LFE hypocenters changes along strike and roughly follows the 350°C isotherm, suggesting frictional behavior may be, in part, thermally controlled. We observe no overlap in the depth of earthquakes and LFEs, with an &sim;5  km separation between the deepest earthquakes and shallowest LFEs. In addition, clustering in the relocated seismicity near the 2004 M w 6.0 Parkfield earthquake hypocenter and near the northern boundary of the 1857 M w 7.8 Fort Tejon rupture may highlight areas of frictional heterogeneities on the fault where earthquakes tend to nucleate.

California↗

USGS2015

Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network

We present and describe strong-motion data observations from the 2015 M 7.8 Gorkha, Nepal, earthquake sequence collected using existing and new Quake-Catcher Network (QCN) and U.S. Geological Survey NetQuakes sensors located in the Kathmandu Valley. A comparison of QCN data with waveforms recorded by a conventional strong-motion (NetQuakes) instrument validates the QCN data. We present preliminary analysis of spectral accelerations, and peak ground acceleration and velocity for earthquakes up to M 7.3 from the QCN stations, as well as preliminary analysis of the mainshock recording from the NetQuakes station. We show that mainshock peak accelerations were lower than expected and conclude the Kathmandu Valley experienced a pervasively nonlinear response during the mainshock. Phase picks from the QCN and NetQuakes data are also used to improve aftershock locations. This study confirms the utility of QCN instruments to contribute to ground-motion investigations and aftershock response in regions where conventional instrumentation and open-access seismic data are limited. Initial pilot installations of QCN instruments in 2014 are now being expanded to create the Nepal–Shaking Hazard Assessment for Kathmandu and its Environment (N-SHAKE) network.

Seismological Research Letters↗

USGS2015

Using a modified time-reverse imaging technique to locate low-frequency earthquakes on the San Andreas Fault near Cholame, California

We present a new method to locate low-frequency earthquakes (LFEs) within tectonic tremor episodes based on time-reverse imaging techniques. The modified time-reverse imaging technique presented here is the first method that locates individual LFEs within tremor episodes within 5 km uncertainty without relying on high-amplitude P-wave arrivals and that produces similar hypocentral locations to methods that locate events by stacking hundreds of LFEs without having to assume event co-location. In contrast to classic time-reverse imaging algorithms, we implement a modification to the method that searches for phase coherence over a short time period rather than identifying the maximum amplitude of a superpositioned wavefield. The method is independent of amplitude and can help constrain event origin time. The method uses individual LFE origin times, but does not rely on a priori information on LFE templates and families.We apply the method to locate 34 individual LFEs within tremor episodes that occur between 2010 and 2011 on the San Andreas Fault, near Cholame, California. Individual LFE location accuracies range from 2.6 to 5 km horizontally and 4.8 km vertically. Other methods that have been able to locate individual LFEs with accuracy of less than 5 km have mainly used large-amplitude events where a P-phase arrival can be identified. The method described here has the potential to locate a larger number of individual low-amplitude events with only the S-phase arrival. Location accuracy is controlled by the velocity model resolution and the wavelength of the dominant energy of the signal. Location results are also dependent on the number of stations used and are negligibly correlated with other factors such as the maximum gap in azimuthal coverage, source–station distance and signal-to-noise ratio.

California↗

USGS2015

Stress- and structure-controlled anisotropy in a region of complex faulting—Yuha Desert, California

We examine shear velocity anisotropy in the Yuha Desert, California using aftershocks of the 2010 M7.2 El Mayor-Cucapah earthquake. The Yuha Desert is underlain by a complex network of right- and left-lateral conjugate faults, some of which experienced triggered slip during the El Mayor-Cucapah earthquake. An automated method that implements multiple measurement windows and a range of bandpass filters is used to estimate the fast direction ( ϕ ) and delay time ( δt ) of the split shear waves. We find an average ϕ oriented approximately north–south suggesting it is primarily controlled by the regional maximum compressive stress direction. However, the spatial variability in ϕ reveals that the fault structures that underlie the Yuha Desert also influence the measured splitting parameters. We infer that the northeast- and northwest-oriented ϕ reflect shear fabric subparallel to the conjugate fault structures. We do not observe a simple correlation between δt and hypocentral distance. Instead, the observed spatial variation in δt suggests that near-source variation in anisotropic strength may be equal to or more important than effects local to the station. No temporal variation in splitting parameters is observed during the 70-day period following the main shock. In this region of complex faulting, we observe a spatially variable pattern of anisotropy that is both stress- and structure-controlled. This study suggests that shear fabric can form even along short, discontinuous fault strands with minimal offset.

California↗

USGS2015

Improved rapid magnitude estimation for a community-based, low-cost MEMS accelerometer network

Immediately following the M w 7.2 Darfield, New Zealand, earthquake, over 180 Quake‐Catcher Network (QCN) low‐cost micro‐electro‐mechanical systems accelerometers were deployed in the Canterbury region. Using data recorded by this dense network from 2010 to 2013, we significantly improved the QCN rapid magnitude estimation relationship. The previous scaling relationship ( Lawrence et al. , 2014 ) did not accurately estimate the magnitudes of nearby (<35 km) events. The new scaling relationship estimates earthquake magnitudes within 1 magnitude unit of the GNS Science GeoNet earthquake catalog magnitudes for 99% of the events tested, within 0.5 magnitude units for 90% of the events, and within 0.25 magnitude units for 57% of the events. These magnitudes are reliably estimated within 3 s of the initial trigger recorded on at least seven stations. In this report, we present the methods used to calculate a new scaling relationship and demonstrate the accuracy of the revised magnitude estimates using a program that is able to retrospectively estimate event magnitudes using archived data.

Bulletin of the Seismological Society of America↗

USGS2015

On the reliability of Quake-Catcher Network earthquake detections

Over the past two decades, there have been several initiatives to create volunteer‐based seismic networks. The Personal Seismic Network, proposed around 1990, used a short‐period seismograph to record earthquake waveforms using existing phone lines ( Cranswick and Banfill, 1990 ; Cranswick et al. , 1993 ). NetQuakes ( Luetgert et al. , 2010 ) deploys triaxial Micro‐Electromechanical Systems (MEMS) sensors in private homes, businesses, and public buildings where there is an Internet connection. Other seismic networks using a dense array of low‐cost MEMS sensors are the Community Seismic Network ( Clayton et al. , 2012 ; Kohler et al. , 2013 ) and the Home Seismometer Network ( Horiuchi et al. , 2009 ). One main advantage of combining low‐cost MEMS sensors and existing Internet connection in public and private buildings over the traditional networks is the reduction in installation and maintenance costs ( Koide et al. , 2006 ). In doing so, it is possible to create a dense seismic network for a fraction of the cost of traditional seismic networks ( D’Alessandro and D’Anna, 2013 ; D’Alessandro, 2014 ; D’Alessandro et al. , 2014 ).

Seismological Research Letters↗

USGS2015

The Red Atrapa Sismos (Quake Catcher Network in Mexico): assessing performance during large and damaging earthquakes.

The Quake‐Catcher Network (QCN) is an expanding seismic array made possible by thousands of participants who volunteered time and resources from their computers to record seismic data using low‐cost accelerometers (http://qcn.stanford.edu/; last accessed December 2014). Sensors based on Micro‐Electromechanical Systems (MEMS) technology have rapidly improved over the last few years due to the demand of the private sector (e.g., automobiles, cell phones, and laptops). For strong‐motion applications, low‐cost MEMS accelerometers have promising features due to an increasing resolution and near‐linear phase and amplitude response ( Cochran, Lawrence, Christensen, and Jakka, 2009 ; Clayton et al. , 2011 ; Evans et al. , 2014 ). Each volunteer computer monitors ground motion and communicates using the Berkeley Open Infrastructure for Network Computing (BOINC, Anderson, 2004 ). Using a standard short‐term average, long‐term average (STLA) algorithm ( Earle and Shearer, 1994 ; Cochran, Lawrence, Christensen, Chung, 2009 ; Cochran, Lawrence, Christensen, and Jakka, 2009 ), volunteer computer and sensor systems detect abrupt changes in the acceleration recordings. Each time a possible trigger signal is declared, a small package of information containing sensor and ground‐motion information is streamed to one of the QCN servers ( Chung et al. , 2011 ). Trigger signals, correlated in space and time, are then processed by the QCN server to look for potential earthquakes.

Seismological Research Letters↗

USGS2015

A century of oilfield operations and earthquakes in the greater Los Angeles Basin, southern California

Most of the seismicity in the Los Angeles Basin (LA Basin) occurs at depth below the sediments and is caused by transpressional tectonics related to the big bend in the San Andreas fault. However, some of the seismicity could be associated with fluid extraction or injection in oil fields that have been in production for almost a century and cover &sim; 17% of the basin. In a recent study, first the influence of industry operations was evaluated by analyzing seismicity characteristics, including normalized seismicity rates, focal depths, and b -values, but no significant difference was found in seismicity characteristics inside and outside the oil fields. In addition, to identify possible temporal correlations, the seismicity and available monthly fluid extraction and injection volumes since 1977 were analyzed. Second, the production and deformation history of the Wilmington oil field were used to evaluate whether other oil fields are likely to experience similar surface deformation in the future. Third, the maximum earthquake magnitudes of events within the perimeters of the oil fields were analyzed to see whether they correlate with total net injected volumes, as suggested by previous studies. Similarly, maximum magnitudes were examined to see whether they exhibit an increase with net extraction volume. Overall, no obvious previously unidentified induced earthquakes were found, and the management of balanced production and injection of fluids appears to reduce the risk of induced-earthquake activity in the oil fields.

California↗

USGS2014

Investigation of the high-frequency attenuation parameter, κ (kappa), from aftershocks of the 2010 M w 8.8 Maule, Chile earthquake

The Bío Bío region of Chile experienced a vigorous aftershock sequence following the 2010 February 27 M w 8.8 Maule earthquake. The immediate aftershock sequence was captured by two temporary seismic deployments: the Quake Catcher Network Rapid Aftershock Mobilization Program (QCN RAMP) and the Incorporated Research Institutions for Seismology CHile Aftershock Mobilization Program (IRIS CHAMP). Here, we use moderate to large aftershocks ( M L ≥ 4.0) occurring between 2010 March 1 and June 30 recorded by QCN RAMP and IRIS CHAMP stations to determine the spectral decay parameter, kappa ( κ ). First, we compare waveforms and κ estimates from the lower-resolution QCN stations to the IRIS CHAMP stations to ensure the QCN data are of sufficient quality. We find that QCN stations provide reasonable estimates of κ in comparison to traditional seismic sensors and provide valuable additional observations of local ground motion variation. Using data from both deployments, we investigate the variation in κ for the region to determine if κ is influenced primarily by local geological structure, path attenuation, or source properties (e.g. magnitude, mechanism and depth). Estimates of κ for the Bío Bío region range from 0.0022 to 0.0704 s with a mean of 0.0295 s and are in good agreement with κ values previously reported for similar tectonic environments. κ correlates with epicentral distance and, to a lesser degree, with source magnitude. We find little to no correlation between the site kappa, κ 0 , and mapped geology, although we were only able to compare the data to a low-resolution map of surficial geology. These results support an increasing number of studies that suggest κ observations can be attributed to a combination of source, path and site properties; additionally, measured κ are often highly scattered making it difficult to separate the contribution from each of these factors. Thus, our results suggest that contributions from the site, path and source should be carefully considered when interpreting κ values.

Bío Bío Region↗