MCE Ph.D. Thesis Seminar
Modeling of Nucleation and Dynamic Rupture on Heterogeneous Frictional Interfaces with Applications to Foreshocks
Abstract: While many large earthquakes are preceded by observable foreshocks, the mechanisms responsible for the occurrence of these smaller-scale seismic events remain uncertain. One physical explanation of foreshocks with growing support is that they are produced by the interaction of slow slip, due to the nucleation of the upcoming mainshock, with fault patches of different properties. Having a better understanding of how earthquakes nucleate on heterogeneous faults would increase our capacity to forecast potentially hazardous events.
With this motivation in mind, we seek to understand what conditions produce isolated microseismicity within the nucleating region of the mainshock and to study the mechanics of the resulting events. Inspired by the suggestion from laboratory experiments that foreshocks occur on asperities, i.e. local deviations from planarity that are flattened by the overall compression, we explore the behavior of asperity-type patches of higher compressive stress embedded in the larger seismogenic region of a rate-and-state fault model by conducting 3D numerical simulations of their slip over long-term sequences of aseismic and seismic slip. Our models do produce smaller-scale seismicity during the aseismic nucleation of much larger seismic events, and we explore their properties as well as the separation in length scales needed to produce them. These foreshock-like events have stress drops that are consistent with laboratory and field observations and approximately constant, despite the highly elevated compression assigned to the source patches. Two main factors contributing to the reasonable stress drops are the significant extent of the rupture into the region surrounding the patch and the aseismic stress release just prior to the seismic event.
We also investigate the seismologically derived properties of the asperity-type events using the spectral analysis commonly applied to natural microseismic events. We find that the seismological methods cannot adequately capture the properties of the simulated events. In part, the seismological estimates of their stress drops are significantly different from the actual stress drops determined from the on-fault stress changes. This is because our sources have more complex features than the standard models from which the current seismological methods have been built, including heterogeneous stress change over the rupture area with much larger initial stress change, and heterogeneous rupture speed. We identify features in the far-field seismograms of the asperity-type sources that differ from the standard models and can be potentially characteristic of the asperity-type sources.
Our asperity-type models of microseismicity sources provide insight into the conditions conducive for generating foreshocks on both natural and laboratory faults and the properties of the resulting events. The conclusions provided jointly by the two perspectives in this study -- dynamically simulating the behavior of seismic sources within heterogeneous fault models and seismologically analyzing their far-field source spectra -- have important implications that warrant further study. Topics for future research include the interaction among smaller-scale seismic events and their role in the mainshock nucleation process, the effect of timing on their source properties, and relation to the so-called seismic nucleation phase of the subsequent mainshock.
Existing Earthquake Early Warning (EEW) algorithms use waveform analysis for earthquake detections, estimation of source parameters (i.e., magnitude and hypocenter location), and prediction of peak ground motions at sites near the source. The latency of warning delivery due to data collection significantly restricts the usefulness of the system, especially for users in the vicinity of the earthquake source, as the warning may not arrive before the strong shaking. This presentation discusses several methods to reduce the warning latency, while maintaining reliability and robustness, so that the warning time can be maximized for users to take appropriate actions to reduce causalities and economic losses.
Firstly, we incorporated the seismicity forecast information from Epidemic-Type Aftershock Sequence (ETAS) model into EEW as prior information, under the Bayesian probabilistic inference framework. Similar to human's decision making process, the Bayesian approach updates the probability of the estimations as more information becomes available. This allows us to reduce the required time for reliable earthquake signal detection from at least 3 seconds to 0.5 second. Furthermore, the initial error of hypocenter location estimation is reduced by 58%. The performance of the algorithm is further improved during aftershock sequences and swarm earthquakes.
Secondly, we introduce the use of multidimensional (KD tree) data structure to organize seismic database, so that the querying time can be reduced for the nearest neighbor search during earthquake source parameter estimation. The processing time of KD tree is approximately 15% of the processing time of linear exhaustive search, which allows the potential use of large seismic databases in real-time.EEW is an interdisciplinary subject that involves collaboration among different scientific and engineering communities. Only by optimizing the warning time, such a unified system could be successful in taking protective actions before, during, and after earthquake natural disasters.
Contact: Carolina Oseguera at 626-395-4271 firstname.lastname@example.org