Earthquake Science Center Seminars

The crustal stresses and pore fluid pressures at depth are difficult to quantify directly, and the downhole measurements of in-situ stress are generally limited to a few km depth. The Nobeoka Thrust, southwestern Japan is an on-land example of an ancient megasplay fault and provides an excellent record of deformation and fluid flow at seismogenic depths. In this study, we present (1) temporal stress changes for the seismic period of the Nobeoka Thrust and (2) spatial heterogeneity of the pore fluid pressure and rock strength by using the minor faults and mineral veins around the fault zone in the Nobeoka Thrust.

Minor faults can be observed from drillcores that intersected the Nobeoka thrust. The orientation clusters detected by the stress tensor inversion are characterized by the temporal changes for the orientations of the sigma 1 and sigma 3 principal stress axes that involve alternation between horizontal and vertical. The findings are probably due to a change in stress state before and after earthquakes that occurred on the fault; similar changes have been observed in active tectonic settings, such as the 2011 Tohoku-Oki earthquake (Japan).

Many quartz veins that filled mode I cracks can be observed in the hanging wall and footwall of the Nobeoka Thrust. Inversion for stress orientation suggests that normal faulting dominated in both the hanging wall and footwall, with similar stress axis orientations in both. The orientation of sigma 3 for the estimated stress regime is parallel to the slip direction of the Nobeoka Thrust. The detected normal-faulting-type stress regimes likely resulted from postseismic stress buildup after megathrust earthquakes. We propose two possible explanations for the variations of vein attitudes: (a) spatial variations in pore fluid pressure are directly responsible for these variations, or (b) these variations are controlled by differences in rock strength between the hanging wall and footwall.

Inputs into seismic hazard models include 1) fault slip rates, 2) their uncertainties, and 3) off-fault deformation rates. Fault slip rates can be estimated by modeling fault systems, based on space geodetic measurements of active surface ground displacement, such as Global Navigation Satellite Systems (GNSS) and interferometric synthetic aperature radar (InSAR). Geodetic slip rate estimates may vary widely due to measurement and epistemic (model) uncertainties, presenting a challenge for both estimating slip rates and accurately characterizing uncertainties: models may vary in the number of faults represented and the precise location of those faults. I address this ambiguity in California in two ways.

First, I address the potential role of fault system geometry in the eastern California shear zone with an L1 regularization method that allows for an algorithmic assessment of the best-fitting block model geometry based on geodetic observations. This approach permits fault system geometries with many densely spaced active faults (analogous to distributed interseismic deformation), and so is uniquely capable of addressing the nature of on- vs. off-fault tectonic deformation. Second, I combine 33 published geodetic slip rate estimates on a georeferenced grid and find an average standard deviation on slip rate of ~1.5 mm/yr, which I consider proxy for model uncertainties in geodetic slip rates. Both approaches independently assess geodetic constraints on fault slip, and systematically identify regions that may require more careful consideration in terms of modeling the complex set of faults in California.

Since the classic papers by Aki (1967, JGR) and Brune (1970, JGR), a basic axiom in seismology is that for all earthquakes the Fourier amplitude spectra of the source moment rate have a similar shape characterized by 1) a low-frequency asymptote f0 proportional to seismic moment, 2) spectral decay of the high-frequencies as f-2 and 3) a single corner fc (intersection of the low- and high-frequency asymptotes) such that the seismic moment is proportional to fc3. We (Archuleta and Chen, 2016, GRL) have recently found an apparent moment rate function that accurately predicts the scaling with magnitude of peak ground acceleration (PGA), peak ground velocity (PGV), peak Wood-Anderson displacement and the ratio of PGA/2?PGV (a dominant).

The moment rate function is characterized by two time constants that scale with seismic moment: 1) a time to reach the peak moment rate and 2) a time for the total duration. The source spectrum is not the classic Aki-Brune spectrum. While the new source is also flat at low-frequencies and has a f-2 decay at high frequencies, there is an intermediate trend where the spectral amplitudes decay like f-1. Thus, the spectrum has two corners?a lower frequency one associated with the total duration and a higher frequency one associated with the time to reach the peak moment rate. We show that if an earthquake occurs where the medium has typical attenuation observed in tectonically active areas (e.g., western US, Japan, Taiwan), the higher corner will be masked and in all likelihood never recovered. However, in regions with low attenuation, e.g., parts of eastern US or stable craton areas, the second corner should be observed. The presence of the second corner has direct implications about stress drop. It is a possible explanation for the difference between seismologically determined stress drops and stress parameters used to predict peak ground motions. The scalable moment rate function might be explained by different physical models of t he earthquake source, but our preference is an asperity model first described by McGarr (BSSA, 1981) and later by Boatwright (BSSA, 1988).

Many questions remain on the detailed morphology of convection patterns in the earth's mantle. In particular, the existence of deep mantle plumes has been the subject of debate ever since they were proposed to explain the presence of hotspot volcanoes. With the advent of numerical methods for accurate seismic wavefield computations, it is now possible to apply the tools of waveform tomography to better detect structures in the deep mantle, previously "hidden" by wavefront healing effects not captured by approximate wave propagation methods. Taking advantage of these new tools, we have recently constructed a global shear velocity model of the mantle, which shows better focused, finer scale structures both in the upper and in the lower mantle, and in particular vertically elongated structures that form discrete columns rooted at the base of the mantle, positioned in the vicinity of some 25 major hotspots. At least some of the roots of these fat plumes contain large quasi-circular "ultra-low velocity zones", as I will illustrate in the case of Hawaii and Iceland. The vertical conduits are quite straight from the base of the mantle to 1000 km depth, but wider (500-1000 km) than expected from the standard "plume" model. Their character changes above this depth, as they seem to become narrower and meander across the upper mantle, where they interact with secondary scale convection set off by plate motions. I will also discuss the significance of the apparent rheological boundary around 1000 km depth.

In this talk, we introduce the trial to improve the estimation quality of the stress drop using the residual evaluation of the corner frequency estimation process, and show the estimated stress drop of potentially induced earthquakes in Oklahoma. In the last several years, disposal of wastewater increases the seismic activity in central United States, especially in Oklahoma. The similarity or difference of the source characteristics between induced and natural earthquakes would contribute to hazard assessment. While stress drop is one of the most important source parameter, accurate estimation was very difficult. The process in the stress drop estimation need to obtain the corner frequency by comparing the spectral ratio of the co-located event pair and the theoretical model. The accuracy of the corner frequency strongly affects the stress drop estimation since stress drop has proportional relationship to the cube of the corner frequency.

We formed clusters of co-located events which occurred from 2016 March 1st to August 31. The spectral ratios between the smaller events (Mw < 4.0) and the larger event (Mw > 4.0) in each cluster were calculated to remove path effects. Spectral ratios of the all components of 4 stations with 100 Hz sampling frequency were stacked. We analyzed 5.12 seconds from 2.5 times after the S wave arrival time after applied the band-pass filter of 0.1 to 40 Hz. Corner frequencies and moment ratio of each event pair were searched by the least square fitting with Brune model.

To improve the accuracy of the results, we evaluate the quality of the fitting process by using the residuals between the best fitted curve and data. The residual on each data point at each grid search trial demonstrated the large uncertainty of higher corner frequency estimation (search range of a larger event: 0.1 to 40 Hz, smaller event: 0.1 to 60 Hz). We selected the events with the size and shape of the small residual region around the best fitted point. The event pairs which has small residual region show a rounded compact shape around the best fitted point were defined as a good quality, and utilized them for the stress drop calculation. Comparing to the results without the selection, stress drops of selected data in the same cluster showed small variation in three clusters; thus, the quality control with residual would be effective. Estimated stress drops were 1-10 MPa for the smaller eGf events and 6-63 MPa for the larger events. This result is consistent with the stress drop estimated in other regions of central United States as well as natural earthquakes.

Near-surface structure is important in understanding earthquake and volcano hazards. It is directly related to the level of ground shaking, and its temporal change can track magma migration. We introduce a novel technique to constrain near-surface seismic wave speed based upon the polarization measurements of teleseismic body-wave arrivals.

Polarization analysis of three-component seismic data has been widely used until about two decades ago for detection and identification of different types of seismic arrivals (e.g., compressional, shear, and surface waves). Today, we have good understanding of the expected polarization for any given seismic phase arrival based upon a reference seismic model such as IASP91, and deviations from the predicted polarization provide constraints on the near-surface wave speeds.

This approach is applied to the High-Sensitivity Seismograph Network (Hi-net) in Japan, where the results are benchmarked against the in-situ measurements of the P and S wave speeds that are available at most stations. The polarization-based estimates and the well measurements show good agreement, confirming the efficacy of the new method. This technique provides reliable, non-invasive, and inexpensive estimates of near-surface elastic properties at various locations, and can be expanded in the depth dimension by examining the frequency dependence and in the time dimension by analyzing earthquakes from different time periods.

Data mining methods have often been used to explore the similarities of individual seismic events that comprise an earthquake sequence. A relatively new example is PageRank (Google?s initial search algorithm), which can be used for measuring connectivity between two seismograms.

PageRank was originally developed for webpage search engines and was subsequently adapted for use in seismology to detect low-frequency earthquakes (Aguiar and Beroza, 2014). PageRank links seismograms directly through cross correlation and indirectly when two seismograms have a high correlation coefficient (CC) with one another but only one of those has a high CC with a 3rd seismogram. We expand on this initial application of PageRank by using it to define signal-correlation topology for micro-earthquakes in a geothermal environment, including the identification of signals that are connected to the largest number of other signals.

We have focused on the Newberry Volcano in the Deschutes National Forest in Central Oregon, which has been stimulated two times using high-pressure fluid injection to study the Enhanced Geothermal Systems (EGS) technology. Initial locations of the 2012 stimulation found that events occurred in two distinct depth ranges and microseismicity did not clearly outline subsurface structures (Foulger and Julian, 2013). We explored the spatial and temporal development of the 2012 events to better understand how the stimulation modifies stress, fractures rock, and affects permeability. By applying PageRank, we created signal families and simultaneously relocated events within families using the Bayesloc approach (Myers et al., 2007). After relocation, event families are tightly clustered spatially, and some events determined to be linked by PageRank but not spatially clustered in the initial locations are indeed relocated to the same cluster. We also found that signal similarity (linkage) at several stations, not just one or two, is needed to confidently determine if events are in close proximity to one another.

Indirect linkage of signals using PageRank is a reliable way to increase the number of events that are confidently determined to be located close to one another and have a similar focal mechanism. We are currently analyzing the second stimulation, performed in 2014, and will compare these results to clusters found in the initial stimulation. This will allow us to determine whether changes in the state of stress and/or changes in the generation of subsurface fracture networks can be detected using PageRank topology. Ultimately, automating and applying this method in real time could be used in adaptive approaches to enhance production at well-instrumented geothermal sites. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.LLNL-ABS-720039.

Surface deformation from large magnitude earthquakes provide vital insight into faulting mechanics and the rupture process at depth. However, our understanding of the surface deformation close to fault ruptures (< 2 km) remains limited. GPS data are commonly too sparse to capture complex surface motion, while Interferometric Synthetic Aperture Radar (InSAR) typically decorrelates in such regions due to high phase gradients, and traditional field surveys usually cannot constrain diffuse, off-fault deformation. Sub-pixel correlation of optical images taken before and after earthquakes, however, is well optimized to retrieve the full surface displacement close to the earthquake rupture, providing a complementary technique to other geodetic methods. In this talk I will present optical correlation results that reveal the near-field deformation pattern of the 1992 Mw 7.3 Landers and 1999 Mw 7.1 Hector Mine earthquakes in high spatial resolution. I will demonstrate how such measurements can deepen our understanding of fault zone deformation, from how the magnitude of distributed, inelastic strain may vary between fault systems to how fault slip is distributed with depth. These results have important implications for understanding the dynamics of rupture, diffuse deformation in continental regions, and reliably estimating geologic slip rates for our understanding of plate kinematics.

Science is a powerful tool for understanding our world and predicting our future. Research into the mechanics of geohazards is invaluable in hazard assessments and disaster risk reduction. But that science doesn't help society until it's translated into effective disaster communication. How we talk about the science of disasters is essential to saving lives.

Mika McKinnon is a landslide researcher and science communicator. Her experiences are on all sides of disaster communication: the interviewed expert source scrambling to find the right words, the nosey journalist on under the relentless time-crunch of online news, and the curious public trying to understand local disasters. These are her lessons learned for best practices (and mishaps to avoid!) in disaster communication.