Fault damage zones can influence various aspects of the earthquake cycle, such as the recurrence intervals and magnitudes of large earthquakes. Hence, our research aims to develop a novel method to image fault damage zones using high-frequency P-waves reflected within them. Previous studies have demonstrated that fault damage zones can amplify high-frequency waves along directions close to fault strike. The associated frequency band of the amplified secondary peak may be used to estimate the width and velocity contrast of the fault damage zone. Here we use the stacked P-wave velocity spectra of M1.5–3 earthquakes in the Parkfield region to identify the azimuthal variation in high-frequency energy. Our preliminary results show that for 62% of the Parkfield clusters, stations close to the fault strike record more high-frequency energies around 10–20 Hz. The frequency band is lower than what we observed for the 2019 Ridgecrest earthquakes region, and corresponds to a fault zone velocity reduction of ~50% assuming a fault zone width of 200m. We also observe along-strike differences in our results, where clusters along some fault sections show greater azimuthal variation than clusters in other sections.
Moreover, to account for the possible effects of site conditions underneath the stations, we will quantify their effects using the spectra of regional earthquakes. We will compute the root-mean-square spectra at different frequency bands for each event, and calculate the average deviation in spectra at each station. We can then generate an empirical correction term for each station as a function of frequency. By applying these corrections to the stacked P-wave velocity spectra of our earthquake clusters, we can separate the contribution of site effects from fault zone structures. Our results demonstrate that the new method can be applied to search for fault damage zone structures in different tectonic regions with broadband stations in order to enhance our understanding of the co-evolution of fault zones and earthquake cycle.
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Localization and coalescence of seismicity before large earthquakes
SUMMARY We examine localization processes of low magnitude seismicity in relation to the occurrence of large earthquakes using three complementary analyses: (i) estimated production of rock damage by background events, (ii) evolving occupied fractional area of background seismicity and (iii) progressive coalescence of individual earthquakes into clusters. The different techniques provide information on different time scales and on the spatial extent of weakened damaged regions. Techniques (i) and (ii) use declustered catalogues to avoid the occasional strong fluctuations associated with aftershock sequences, while technique (iii) examines developing clusters in entire catalogue data. We analyse primarily earthquakes around large faults that are locked in the interseismic periods, and examine also as a contrasting example seismicity from the creeping Parkfield section of the San Andreas fault. Results of analysis (i) show that the M > 7 Landers 1992, Hector Mine 1999, El Mayor-Cucapah 2010 and Ridgecrest 2019 main shocks in Southern and Baja California were preceded in the previous decades by generation of rock damage around the eventual rupture zones. Analysis (ii) reveals localization (reduced fractional area) 2–3 yr before these main shocks and before the M > 7 Düzce 1999 earthquake in Turkey. Results with technique (iii) indicate that individual events tend to coalesce rapidly to clusters in the final 1–2 yr before the main shocks. Corresponding analyses of data from the Parkfield region show opposite delocalization patterns and decreasing clustering before the 2004 M6 earthquake. Continuing studies with these techniques, combined with analysis of geodetic data and insights from laboratory experiments and model simulations, might improve the ability to track preparation processes leading to large earthquakes.
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- NSF-PAR ID:
- 10271605
- Date Published:
- Journal Name:
- Geophysical Journal International
- Volume:
- 223
- Issue:
- 1
- ISSN:
- 0956-540X
- Page Range / eLocation ID:
- 561 to 583
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Fault damage zones can influence various aspects of the earthquake cycle, such as the recurrence intervals and magnitudes of large earthquakes. The properties and structure of fault damage zones are often characterized using dense arrays of seismic stations located directly above the faults. However, such arrays may not always be available. Hence, our research aims to develop a novel method to image fault damage zones using broadband stations at relatively larger distances. Previous kinematic simulations and a case study of the 2003 Big Bear earthquake sequence demonstrated that fault damage zones can act as effective waveguides, amplifying high-frequency waves along directions close to fault strike via multiple reflections within the fault damage zone. The amplified high-frequency energy can be observed using the stacked P-wave spectra of earthquake clusters with highly-similar waveforms (Huang et al., 2016). We attempt to identify the high-frequency peak associated with fault zone waves in stacked spectra by conducting a large-scale study of small earthquakes (M1.5–3). We use high quality broadband data from seismic stations at hypocentral distances of 20-100km in the 2004 Parkfield and 2019 Ridgecrest earthquake regions. First, we group earthquakes in clusters by their locations and their waveform similarity, and then stack their velocity spectra to average the source effects of individual earthquakes. We applied our method to the 2019 Ridgecrest earthquake sequence, and our preliminary results show that stations close to the fault strike tend to record more high-frequency energies around the characteristic frequency of fault zone reflections. The frequency bands in which amplified high-frequency energies are observed may be used to estimate the width and velocity contrast of the fault damage zone. We aim to develop a robust and versatile method that can be used to search for fault damage zone structures and estimate their material properties, in order to shed light on earthquake source processes.more » « less
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SUMMARY Precisely constraining the source parameters of large earthquakes is one of the primary objectives of seismology. However, the quality of the results relies on the quality of synthetic earth response. Although earth structure is laterally heterogeneous, particularly at shallow depth, most earthquake source studies at the global scale rely on the Green's functions calculated with radially symmetric (1-D) earth structure. To avoid the impact of inaccurate Green's functions, these conventional source studies use a limited set of seismic phases, such as long-period seismic waves, broad-band P and S waves in teleseismic distances (30° < ∆ < 90°), and strong ground motion records at close-fault stations. The enriched information embedded in the broad-band seismograms recorded by global and regional networks is largely ignored, limiting the spatiotemporal resolution. Here we calculate 3-D strain Green's functions at 30 GSN stations for source regions of 9 selected global earthquakes and one earthquake-prone area (California), with frequency up to 67 mHz (15 s), using SPECFEM3D_GLOBE and the reciprocity theorem. The 3-D SEM mesh model is composed of mantle model S40RTS, crustal model CRUST2.0 and surface topography ETOPO2. We surround each target event with grids in horizontal spacing of 5 km and vertical spacing of 2.0–3.0 km, allowing us to investigate not only the main shock but also the background seismicity. In total, the response at over 210 000 source points is calculated in simulation. The number of earthquakes, including different focal mechanisms, centroid depth range and tectonic background, could further increase without additional computational cost if they were properly selected to avoid overloading individual CPUs. The storage requirement can be reduced by two orders of magnitude if the output strain Green's functions are stored for periods over 15 s. We quantitatively evaluate the quality of these 3-D synthetic seismograms, which are frequency and phase dependent, for each source region using nearby aftershocks, before using them to constrain the focal mechanisms and slip distribution. Case studies show that using a 3-D earth model significantly improves the waveform similarity, agreement in amplitude and arrival time of seismic phases with the observations. The limitations of current 3-D models are still notable, dependent on seismic phases and frequency range. The 3-D synthetic seismograms cannot well match the high frequency (>40 mHz) S wave and (>20 mHz) Rayleigh wave yet. Though the mean time-shifts are close to zero, the standard deviations are notable. Careful calibration using the records of nearby better located earthquakes is still recommended to take full advantage of better waveform similarity due to the use of 3-D models. Our results indicate that it is now feasible to systematically study global large earthquakes using full 3-D earth response in a global scale.
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Abstract We attempt to clarify processes associated with the 2019 Ridgecrest earthquake sequence by analyzing space‐time variations of seismicity, potency values, and focal mechanisms of earthquakes leading to and during the sequence. Over the 20 years before the
M w 7.1 mainshock, the percentage of normal faulting events decreased gradually from 25% to below 10%, indicating a long‐term increase of shear stress. TheM w 6.4 andM w 7.1 ruptures terminated at areas with strong changes of seismic velocity or intersections with other faults producing arresting barriers. The aftershocks are characterized by highly diverse focal mechanisms and produced volumetric brittle deformation concentrated in a 5–10 km wide zone around the main ruptures. Early aftershocks of theM w 7.1 event extended over a wide area below typical seismogenic depth, consistent with a transient deepening of the brittle‐ductile transition. The Ridgecrest earthquake sequence produced considerable rock damage in the surrounding crust including below the nominal seismogenic zone. -
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/gji/ggaa315
