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 by stacking P-wave spectra of earthquake clusters with highly-similar waveforms (Huang et al., 2016), and the frequency band which is amplified may be used to estimate the width and velocity contrast of the fault damage zone.
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 20-80 km in the 2019 Ridgecrest earthquake regions. First, we group the Ridgecrest earthquakes in clusters by their locations and their waveform similarity, and then stack their velocity spectra to average the source effects of individual earthquakes. Our results show that the stations close to the fault strike record more high-frequency energies around the characteristic frequency of fault zone reflections. We find that the increase in the amount of high-frequencies is consistent across clusters with average magnitudes ranging from 1.6-2.4, which suggests that the azimuthal variation in spectra is caused by fault zone amplification rather than rupture directivity. We will apply our method to other fault zones in California, in order to search for fault damage zone structures and estimate their material properties.
more »
« less
Insights on earthquake source processes from the 2019 Ridgecrest earthquake source spectra and its azimuthal variation
The 2019 Ridgecrest, CA earthquake sequence has provided a unique opportunity and a rich dataset to understand earthquake source properties and near-fault structure. Using the high-quality seismic data provided by the SCEC Stress Drop Validation group, we first estimate the corner frequency of M2.0-4.5 earthquakes by applying the spectral ratio method based on empirical Green’s function (Liu et al., 2020). We relate corner frequency estimates to stress drops assuming the Brune source model and circular cracks. Our preliminary results show increasing median stress drops with magnitude for both P and S waves, from 1 MPa for M2.0 events to 10 MPa for M4.0 events, though the limited frequency bandwidth may cause underestimation for small events. The estimated moment magnitude is proportional to the catalog magnitude by a factor of 0.72, which is close to 0.74 estimated by Trugman (2020) for the Ridgecrest earthquake sequence. In the second part of the study, we examine the impact of fault zone structure on the azimuthal variation of the source spectra. Using kinematic simulations and observations of the 2003 Big Bear earthquake sequence, Huang et al. (2016) showed that fault damage zones can act as an effective wave guide and cause high-frequency wave amplification along directions close to fault strike. We use clusters of M1.5-3 earthquakes in the Ridgecrest region to further examine the azimuthal variation of the stacked source spectra and investigate if the near-source structure can affect our corner frequency estimates. We aim to develop robust methods that utilize high-quality seismic data to illuminate earthquake source processes and fault zone properties.
more »
« less
- Award ID(s):
- 1943742
- NSF-PAR ID:
- 10316433
- Date Published:
- Journal Name:
- SSA Annual Meeting
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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
-
more » « less
Abstract The spectra of earthquake waveforms can provide important insight into rupture processes, but the analysis and interpretation of these spectra is rarely straightforward. Here we develop a Bayesian framework that embraces the inherent data and modeling uncertainties of spectral analysis to infer key source properties. The method uses a spectral ratio approach to correct the observed
S ‐wave spectra of nearby earthquakes for path and site attenuation. The objective then is to solve for a joint posterior probability distribution of three source parameters—seismic moment, corner frequency, and high‐frequency falloff rate—for each earthquake in the sequence, as well as a measure of rupture directivity for select target events with good azimuthal station coverage. While computationally intensive, this technique provides a quantitative understanding of parameter tradeoffs and uncertainties and allows one to impose physical constraints through prior distributions on all source parameters, which guide the inversion when data is limited. We demonstrate the method by analyzing in detail the source properties of 14 different target events of magnitude M5 in southern California that span a wide range of tectonic regimes and fault systems. These prominent earthquakes, while comparable in size, exhibit marked diversity in their source properties and directivity, with clear spatial patterns, depth‐dependent trends, and a preference for unilateral directivity. These coherent spatial variations source properties suggest that regional differences in tectonic setting, hypocentral depth or fault zone characteristics may drive variability in rupture processes, with important implications for our understanding of earthquake physics and its relation to hazard. -
more » « less
Abstract Earthquake focal mechanisms, determined with P‐wave polarities and S/P amplitude ratios, are primary data for analyzing fault zone geometry, sense of slip, and the crustal stress field. Solving for the focal mechanisms of small earthquakes is often challenging because phase arrivals and first‐motion polarities are hard to be separated from noise. To overcome this challenge, we implement convolutional‐neural‐network algorithms (Ross, Meier, & Hauksson, 2018, Ross, Meier, Hauksson, & Heaton, 2018,
https://doi.org/10.1029/2017jb015251 ,https://doi.org/10.1785/0120180080 ) to detect additional phases and polarities. Using both existing and these new data, we build a high‐quality focal mechanism catalog of 297,478 events that occurred from 1981 to 2021 in southern California with the HASH method of Hardebeck and Shearer (2002),https://doi.org/10.1785/0120010200 , Hardebeck and Shearer (2003),https://doi.org/10.1785/0120020236 . The new focal mechanism catalog is overall consistent with the standard catalog (Yang et al., 2012,https://doi.org/10.1785/0120110311 ) but includes 40% more focal mechanisms, and is more consistent with moment tensor solutions derived using waveform‐fitting methods. We apply the new catalog to identify changes in focal mechanism properties caused by the occurrences of large mainshocks such as the 2010M w7.2 El Mayor‐Cucapah and 2019M w7.1 Ridgecrest earthquakes. Such changes may be associated with co‐seismic stress drops, post‐seismic deformation processes, and static stress changes on a regional scale. The new high‐resolution catalog will contribute to improved understanding of the crustal stress field, earthquake triggering mechanisms, fault zone geometry, and sense of slip on the faults in southern California. -
The temporal variation of elastic property of the bulk material surrounding the fault is considered an important contribution to the observed co-seismic velocity reduction and interseismic healing. Paglialunga et al. [2021] found that as fault normal stress increases, co-seismic velocity reduction becomes larger because more cracks reopen with higher stress drops. Larger normal stress can lead to smaller nucleation size and contribute to larger co-seismic slip. By contrast, with larger co-seismic velocity reduction and interseismic healing, more slow slip events can propagate in the seismogenic zone [Thakur and Huang, 2021], because the temporal velocity change related to fault zone damage modulates earthquake nucleation. Hence, fault normal stress and temporal damage zone structure evolution have opposite influences on the spatial distribution and recurrence intervals of earthquakes. We conducted 2-D anti-plane fully-dynamic seismic cycle simulations and explored the effects of fault normal stress on seismic cycle when there is coseismic damage and interseismic healing in the fault damage zone. The normal stress is in a range of 40-70 MPa and the co-seismic rigidity reduction is in a range of 5-8%. We find larger normal stress results in larger co-seismic slip and fewer slow slip events, while more co-seismic velocity reduction and interseismic healing leads to more partial ruptures as well as slow slip events. With the increase of both normal stress and seismic velocity change, more regular earthquakes occur and slow slip events gradually disappear. For the selected parameter space, the influence of seismic velocity change is not as significant as the effect of normal stress. However, fault zone maturity or the initial rigidity of fault damage zones should also affect the competitive relationship between normal stress and seismic velocity change, and we will characterize earthquakes and slow-slip events in immature and mature fault damage zones when both on-fault normal stress and off-fault seismic velocity vary over earthquake cycles.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
