Three-dimensional paganica fault morphology obtained from hypocenter clustering (L'Aquila 2009 seismic sequence, Central Italy)

Brunsvik, Brennan; Morra, Gabriele; Cambiotti, Gabriele; Chiaraluce, L.; Stefano, Raffaele Di; Gori, Pasquale De; Yuen, David A.

doi:10.1016/j.tecto.2021.228756

Cited by 5 publications

(12 citation statements)

References 63 publications

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“…This is also consistent with observations of Brunsvik et al. (2021), which notes greater angular mismatch between the Paganica fault of the L’Aquila mainshock and smaller magnitude aftershocks near the rupture plane. Other processes in the vicinity of the mainshock rupture planes, such as dynamic rupture propagation and fluid flow, are likely to alter the stress state for those aftershocks.…”

Section: Discussionsupporting

confidence: 93%

“…For the L'Aquila earthquake sequence, incorporation of smaller magnitude events as uniform slip patches decreased the percentage of triggered aftershocks. Brunsvik et al (2021) noted similar findings for the L'Aquila earthquake sequence. Meier et al (2014) also concluded that incorporating smaller magnitude events with earthquake scaling relationships introduced too much uncertainty for stress calculations.…”

Section: Coseismic Slip Distributions Aftershock Data Sets and Region...supporting

confidence: 71%

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Implications of Receiver Plane Uncertainty for the Static Stress Triggering Hypothesis

et al. 2022

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Static stress transfer from major earthquakes is commonly invoked as the primary mechanism for triggering aftershocks, but evaluating this mechanism depends on aftershock rupture plane orientations and hypocenter locations, which are often subject to significant observational uncertainty. We evaluate static stress change for an unusually large data set comprising hundreds to thousands of aftershocks following the 1997 Umbria‐Marche, 2009 L’Aquila (Italy), and 2019 Ridgecrest (California) earthquake sequences. We compare failure stress resolved on aftershock focal mechanism planes and planes that are optimally oriented (OOPs) in the regional and earthquake perturbed stress field. Like previous studies, we find that failure stress resolved on OOPs overpredicts the percentage (>70%) of triggered aftershocks relative to that predicted from observed aftershock rupture planes (∼50%–65%) from focal mechanisms solutions, independent of how nodal plane ambiguity is resolved. Further, observed aftershock nodal planes appear statistically different from OOPs. Observed rupture planes, at least for larger magnitude events (M > 3), appear to align more closely with pre‐existing tectonic structures. The inferred observational uncertainty associated with nodal plane ambiguity, plane orientation, and, to second order, hypocentral location yields a broad range of aftershocks potentially triggered by static stress changes, ranging from slightly better than random chance to nearly any aftershock promoted, particularly those further than 5 km from the causative fault. Dynamic stresses, afterslip, pore fluids, and other sources of unresolved small‐scale heterogeneity in the post‐mainshock stress field may also contribute appreciably to aftershock occurrence closer to the mainshock.

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Section: Discussionsupporting

confidence: 93%

Section: Coseismic Slip Distributions Aftershock Data Sets and Region...supporting

confidence: 71%

Implications of Receiver Plane Uncertainty for the Static Stress Triggering Hypothesis

et al. 2022

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“…There are often some background earthquakes between faults, which may affect the fitting accuracy of the fault plane. The spectral clustering algorithm has obvious advantages in screening seismic clusters related to the fault plane [31]. It is based on the spectral graph theory, which has the advantages of clustering in the arbitrary shape of sample space and converging to the optimal global solution compared with the traditional clustering algorithm.…”

Section: The Geometric Features Of Fault Planementioning

confidence: 99%

“…(3) After obtaining the earthquake clusters highly related to faults, they can be spatially interpolated, and the most suitable 3D fault plane can be fitted. In order to facilitate calculation, the fault plane fitting method similar to Brunsvik et al (2021) [31] was adopted in this study, and the strike, dip, and normal direction pointing to the hanging (3) After obtaining the earthquake clusters highly related to faults, they can be spatially interpolated, and the most suitable 3D fault plane can be fitted. In order to facilitate calculation, the fault plane fitting method similar to Brunsvik et al (2021) [31] was adopted in this study, and the strike, dip, and normal direction pointing to the hanging wall of the fault plane were selected as the three coordinate axes of the local coordinate system.…”

Section: The Geometric Features Of Fault Planementioning

confidence: 99%

“…For example, automatic detection of rupture using source location [22], earthquake relocation [23], automatic acquisition and application of source mechanism [24,25], seismic probabilistic hazard analysis [26], fault geometry based on source information [27][28][29][30], etc. In addition, 3D visualization technology has also been deeply applied in structural geology, fault plane fitting, and the 3D structure of the lithosphere [31]. However, relatively few studies on automatic modeling are based on multiple data [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Three-Dimensional Modeling of the Xichang Crust in Sichuan, China by Machine Learning

et al. 2022

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Seismicity and distribution of earthquakes can provide active fault structural information on the crust at a regional scale. The morphology of faults can be derived from the epicentral distribution of micro-earthquakes. In this study, we combined both the relocated earthquake catalogue and related preliminary geophysical information for 3D modeling of the crust in the Xichang area, Sichuan province, China. The fault morphology and deep crustal structure were automatically extracted by the machine learning approach, such as the supervised classification and cluster analysis methods. This new 3D crustal model includes the seismic velocity distribution, fault planes in 3D and 3D seismicity. There are many earthquake clusters located in the folded basement and low-velocity zone. Our model revealed the topological relation between the folded basement and faults. Our work show the crustal model derived is supported by the earthquake clusters which in turn controls the morphological characteristics of the crystalline basement in this area. Our use of machine learning techniques can not only be used to predict the refined fault geometry, but also to combine the seismic velocity structure with the known geological information. This 3D crustal model can also be used for geodynamic analysis and simulation of strong motionseismic waves.

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Hypocenter‐Based 3D Imaging of Active Faults: Method and Applications in the Southwestern Swiss Alps

2023

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Three-dimensional paganica fault morphology obtained from hypocenter clustering (L'Aquila 2009 seismic sequence, Central Italy)

Cited by 5 publications

References 63 publications

Implications of Receiver Plane Uncertainty for the Static Stress Triggering Hypothesis

Implications of Receiver Plane Uncertainty for the Static Stress Triggering Hypothesis

Three-Dimensional Modeling of the Xichang Crust in Sichuan, China by Machine Learning

Hypocenter‐Based 3D Imaging of Active Faults: Method and Applications in the Southwestern Swiss Alps

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