ABSTRACT Although the Brune source model describes earthquake moment release as a single pulse, it is widely used in studies of complex earthquakes with multiple episodes of high moment release (i.e., multiple subevents). In this study, we investigate how corner frequency estimates of earthquakes with multiple subevents are biased if they are based on the Brune source model. By assuming complex sources as a sum of multiple Brune sources, we analyze 1640 source time functions of Mw 5.5–8.0 earthquakes in the seismic source characteristic retrieved from deconvolving teleseismic body waves catalog to estimate the corner frequencies, onset times, and seismic moments of subevents. We identify more subevents for strike-slip earthquakes than dip-slip earthquakes, and the number of resolvable subevents increases with magnitude. We find that earthquake corner frequency correlates best with the corner frequency of the subevent with the highest moment release (i.e., the largest subsevent). This suggests that, when the Brune model is used, the estimated corner frequency and, therefore, the stress drop of a complex earthquake is determined primarily by the largest subevent rather than the total rupture area. Our results imply that, in addition to the simplified assumption of a radial rupture area with a constant rupture velocity, the stress variation of asperities, rather than the average stress change of the whole fault, contributes to the large variance of stress-drop estimates.
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This content will become publicly available on May 8, 2024
Spectral Characteristics of Hydraulic Fracturing-Induced Seismicity Can Distinguish between Activation of Faults and Fractures
Abstract Analysis of earthquake spectra can aid in understanding source characteristics like stress drop and rupture complexity. There is growing interest in probing the similarities and differences of fault rupture for natural and human-induced seismic events. Here, we analyze waveform data from a shallow, buried geophone array that recorded seismicity during a hydraulic fracturing operation near Fox Creek, Alberta. Starting from a quality-controlled catalog of 4000 events between magnitude 0 and 3.2, we estimate source-spectral corner frequencies using methods that account for the band-limited nature of the sensor response. The stress-drop values are found to be approximately self-similar, but with a slight magnitude dependence in which larger events have higher stress drop (∼10 MPa). Careful analysis of the relative corner frequencies shows that individual fault and fracture segments experienced systematic variations in relative corner frequency over time, indicating a possible change in the stress state. Clustering analysis of source spectra based on the relative proportion of high- and low-frequency content relative to the Brune model further shows that event complexity evolves over time. In addition, the faults produce earthquakes with systematically larger stress-drop values than the fractures. Combined, these results indicate that the features activated by hydraulic fracturing experience observable changes in source behavior over time and exhibit different properties depending on the orientation, scale, and fabric of the structural feature on which they occur.
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- Award ID(s):
- 2231705
- NSF-PAR ID:
- 10410962
- Date Published:
- Journal Name:
- Seismological Research Letters
- ISSN:
- 0895-0695
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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SUMMARY It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well. Studying these small earthquakes offers the opportunity to better understand the possible causes of rupture complexities. Specifically, if they are random or are related to fault properties. We examine microearthquakes (M < 3) in the Parkfield, California, area that are recorded by a high-resolution borehole network. We quantify earthquake complexity by the deviation of source time functions and source spectra from simple circular (omega-square) source models. We establish thresholds to declare complexity, and find that it can be detected in earthquakes larger than magnitude 2, with the best resolution above M2.5. Comparison between the two approaches reveals good agreement (>90 per cent), implying both methods are characterizing the same source complexity. For the two methods, 60–80 per cent (M 2.6–3) of the resolved events are complex depending on the method. The complex events we observe tend to cluster in areas of previously identified structural complexity; a larger fraction of the earthquakes exhibit complexity in the days following the Mw 6 2004 Parkfield earthquake. Ignoring the complexity of these small events can introduce artefacts or add uncertainty to stress drop measurements. Focusing only on simple events however could lead to systematic bias, scaling artefacts and the lack of measurements of stress in structurally complex regions.
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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
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Abstract Understanding and modeling variability of ground motion is essential for building accurate and precise ground motion prediction equations, which can net site‐specific characterization and reduced hazard levels. Here, we explore the spatial variability in peak ground velocity (PGV) at Sage Brush Flats along the San Jacinto Fault in Southern California. We use data from a dense array (0.6 × 0.6 km2, 1,108 geophones, station spacings 10–30 m) deployed in 2014 for ~1 month. These data offer an opportunity to study small‐scale variability in this region. We examine 38 earthquakes (2 ≤ ML ≤ 4.2) within 200 km of the array. Fault strands and a small basin impact the ground motions, producing PGV variations up to 22% of the mean and a 40% reduction in
P andS wave near‐surface velocities. We find along‐fault rupture directivity, source, and path effects can increase PGVs by 167%. Surface PGV measurements exceed the colocated borehole station (depth at 148 m) PGV by factors of 3–10, confirming the impact on PGV from near‐surface fault structures, basins, topography, and amplifications from soft sediments. Consistently, we find high PGVs within the basin structure. A pair of colocated GaML2.6 events produce repeatable PGV values with similar spatial patterns. The average corner frequencies of these two events are 11–16 Hz, and viable measurements of stress drop can differ by 6.45 MPa. Within this small array, the PGV values are variable implying spatial extrapolation of PGV to regions of known faults and basins, even across a small area, should be done with caution. -
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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.
