Earthquake Science Center Seminars

Each large continental earthquake is a unique opportunity to get a privileged insight in earthquake mechanics. One way to go is to document in detail surface ruptures by combining remote sensing studies and field observations. As resolution increases, quantification of the deformation on- and off-fault enlarges our understanding of earthquake rupture processes. In addition, although the number of large continental earthquakes well documented remains small, in case of strike-slip events it becomes now possible to point to some generic pattern in surface rupture that can inform us on how continental strike-slip faults might be structured.

While small earthquakes are expected to produce weak shaking, ground motion is highly variable and there are outlier earthquakes that generate more shaking than expected - sometimes significantly more. We explore datasets of M0.5-M8.3 earthquakes to determine the relative impact of common, smaller magnitude earthquakes that rarely produce strong ground motion to rare, large earthquakes that always cause strong shaking. We find that the natural variability of ground motion, combined with the Gutenberg-Richter magnitude-frequency relationship, ensures that most occurrences of any ground motion comes from earthquakes of smaller magnitude than expected, often >2 magnitude units smaller. This holds even for very strong shaking (>20%g), suggesting that M<7 earthquakes could be a significant source of damage.

While small earthquakes are expected to produce weak shaking, ground motion is highly variable and there are outlier earthquakes that generate more shaking than expected - sometimes significantly more. We explore datasets of M0.5-M8.3 earthquakes to determine the relative impact of common, smaller magnitude earthquakes that rarely produce strong ground motion to rare, large earthquakes that always cause strong shaking. We find that the natural variability of ground motion, combined with the Gutenberg-Richter magnitude-frequency relationship, ensures that most occurrences of any ground motion comes from earthquakes of smaller magnitude than expected, often >2 magnitude units smaller. This holds even for very strong shaking (>20%g), suggesting that M<7 earthquakes could be a significant source of damage.

In the past handful of years, significant strides have been made to better understand the seismotectonic setting of the Western Canada Sedimentary Basin in Alberta. In this talk, I summarize these understandings. First, increased monitoring efforts in Alberta begins in 2006, when the Canadian Rockies and Alberta Network (CRANE) was first deployed and then bolstered by the Regional Alberta Observatory for Earthquake Studies Network (RAVEN). It was through this enhanced monitoring that some of the first cases of induced seismicity were recognized in Alberta: the Rocky Mountain House Seismogenic Zone, Brazeau River Cluster, Cardston Earthquake Swarm, the events near Fox Creek, and the events near Red Deer. In this talk we focus in on the events related to hydraulic fracturing of the Duvernay Formation. We discuss a seismological overview of the phenomenon recorded from these events, a conceptual understanding of the geological conditions susceptible to these events, operational controls impacting the likelihood and productivity of earthquakes, and regulatory controls enacted. Overall, the learnings from induced events in Alberta could be useful for other jurisdictions that are also encountering similar scenarios.

We will have a series of 10-15 minute AGU preview talks.

Fred Pollitz (USGS): "Observations and models of crustal deformation transients following the 2019 Ridgecrest, California, earthquake sequence"

Evan Hirakawa (USGS): "Kinematic Rupture and 3D Wave Propagation Simulations of the Mw7.1 Ridgecrest Earthquake"

Jean Soubestre (INVOLCAN): "CovNet: an automatic seismic network-based method for the detection and location of seismo-volcanic signals"

Sara McBride (USGS): "Social Science and ShakeAlert"

I assess the potential for artificial neural networks to capture complex relationships among input parameters in ground-motion prediction equations (GMPEs) that may be difficult to describe in traditional empirical regressions. I construct a suite of GMPEs for California using an artificial neural network model with data from the PEER NGA West2 ground-motion database. I consider different parameterizations for capturing the spatial variations in ground motion associated with the earthquake mechanism, site characterization, and distance from the rupture. For the inputs associated with each effect, I assess how the neural network weights the combination of parameters, the effect on the uncertainty in the resulting GMPE, and compare the functional form to traditional empirical regression-based GMPEs. For example, complex variations in amplitude associated with hanging wall/footwall effects can be captured using a combination of Joyner-Boore distance and mean rupture distance. The artificial neural network provides a generalized form that remains the same for all of these different parameterizations, thereby facilitating exploration of how to best represent complex spatial variations of ground-motion amplitude in GMPEs.

The effectiveness of an Earthquake Early Warning System (EEWS) in lowering the risk of earthquake casualties depends to a large extent on the seismic vulnerability of buildings. In California, the potential casualty count is mitigated by the high safety standards of construction. Furthermore, in the near-field of a major earthquake, where the shaking is most intense, there may be little or no earthquake warning; or there may be few people at risk. However, rather than 'drop-cover-hold', there is a distinct injury mitigation benefit in Californians using the precious seconds of early warning to find an optimal place under which to 'duck-cover-hold'. Assessment of the effectiveness of an EEWS requires use of a catastrophe earthquake model, which can estimate the EEWS casualty and injury reduction on a scenario by scenario basis. In this presentation, with focus on the San Francisco Bay Area and the Los Angeles region, the potential benefits of an EEWS for several earthquake events in California will be shown and discussed (see Fig.1). Taking a thirty-year time frame, the results confirm the expectation that the long-term safety investment in installing and operating a California EEWS would be warranted by the number of lives saved and the reduced injury toll and fire loss following an earthquake.

Earthquake ruptures commonly exceed anticipated lengths and magnitudes, involving more faults or fault segments than expected from inadequate recurrence models. The inadequacy of both physics-based and empirical models of rupture recurrence is due in part to the relatively short record of modern observations. In order to improve both our understanding of rupture propagation and our collection of empirical rupture parameters, we revisit pre-modern earthquakes using techniques we have recently developed to map and measure coseismic displacement and to digitally analyze their analog waveforms.

In this talk, I will describe analyses of three historic earthquakes from the nascent years of [analog] instrumental seismology: the 1889 Chilik, Kazakhstan, M=8.3, 1911 Sarez, Tajikistan, M=7.3, and 1932 Changma, China, M=7.6 earthquakes. Each of these events is well preserved in the semi-arid to arid environments of Central Asia, permitting us to use newly developed tools to measure coseismic deformation and map the ruptures in high resolution. We also employ newly developed methods to analyze digitized waveforms from analog teleseismic records of these events, relating the observed rupture complexity to seismogenic features of the earthquakes.

By pairing seismological and geomorphological analysis of these earthquakes we gain a modern picture of events that were previously only sparsely mapped, overlooked, or not previously evaluated with contemporary questions on seismic behavior in mind.

With an increasing number of strong-motion records over the last decade, it has become clear that there are significant differences in ground-motion scaling even within relatively small regions such as California. These differences are typically not modeled in ground-motion prediction equations (GMPEs); they are based on the so-called ergodic assumption. By including the systematic source, path and site effects in fully non-ergodic GMPEs it is possible to reduce the value of the aleatory variability by about 30-40%. This requires the estimation of the systematic effects for every possible source/site combination, together with their epistemic uncertainty. If a non-ergodic GMPE is used in seismic hazard analysis, it is very important to propagate the epistemic uncertainty of the systematic effects to obtain the full hazard distribution.

In this talk, I will describe how non-ergodic adjustment terms can be estimated for California. The adjustment terms are estimated using a Gaussian process framework, which allows one to keep track of the associated uncertainties. The underlying assumption is that the systematic effects are spatially correlated, which can be exploited to estimate the distribution of these terms at non-observed locations. The impact of incorporating the non-ergodic adjustment into seismic hazard calculations is shown for a few example sites. For sites that have abundant data in their vicinity, the non-ergodic hazard changes compared to the ergodic one; while for sites with sparse data the mean hazard stays the same, but there is a large increase in the epistemic uncertainty range of the hazard distribution. Finally, I outline how one can apply non-ergodic hazard analysis in regions with very sparse data.

Over the past decade, the seismicity rate in the Central United States has increased by more than an order of magnitude. The vast majority of these earthquakes has been induced by oil and gas operations, principally wastewater disposal, hydraulic fracturing, and hydrocarbon production. As many of these induced earthquakes have occurred in regions that historically had little to no documented seismicity, these induced earthquakes have dramatically altered the seismic hazard; recent seismic hazard assessments for Oklahoma are comparable to those estimated for California and New Madrid. This presentation will focus on the evolution of induced seismicity in Kansas, Oklahoma, and Texas. With the large number of induced earthquakes, we have a unique opportunity to learn about earthquake processes and characterize the subsurface in areas using methods that were previously not feasible. Through advancements in our abilities to identify seismogenic faults, estimate the state of stress, and determining the geologic/industrial parameters that control the occurrence of induced earthquakes, we hope to gain a better understanding of the induced earthquakes and mitigate future hazard.