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

Three-dimensional paganica fault morphology obtained from hypocenter clustering (L'Aquila 2009 seismic sequence, Central Italy)
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DOI:
10.1016/j.tecto.2021.228756
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发表时间:
2021-02
期刊:
影响因子:
2.9
通讯作者:
B. Brunsvik;G. Morra;G. Cambiotti;L. Chiaraluce;R. D. Stefano;P. Gori;D. Yuen
B. Brunsvik;G. Morra;G. Cambiotti;L. Chiaraluce;R. D. Stefano;P. Gori;D. Yuen
中科院分区:
地球科学2区
文献类型:
--
作者:
B. Brunsvik;G. Morra;G. Cambiotti;L. Chiaraluce;R. D. Stefano;P. Gori;D. Yuen

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在地震模拟中,由于缺乏可以约束断层形态的数据,通常假定断层平面是平坦的。然而,结合三维断层形态对于模拟一些现象很重要,例如计算主震引起的应力变化。我们利用一种数据分析方法,利用应用于地震序列震源的无监督聚类技术揭示断层的三维破裂形态。我们将这种方法应用于2009年4月6日发生MW6.1级主震的拉奎拉地震序列。我们使用了一个包含大约50,000个重新定位事件的数据集,其中大多数是微地震,其完整程度达到0.7级。聚类将地震区分为发生在三个主要的地震群以及其他较小的断层段。然后我们用样条曲线表示帕加尼卡主断层系统的形态(造成最大的主震)。该方法有望在监测地震序列的情况下,稳定快速地获得三维破裂形态。三维模型以交互式方式在线呈现,并在交互式Jupyter Notebook (https://bit.ly/2MnCFdj)中呈现处理过程。
In seismic modelling, fault planes are normally assumed to be flat due to the lack of data which can constrain fault morphology. However, incorporating 3D fault morphology is important for modelling several phenomena, for example calculating mainshock induced stress changes. We utilize a data-analytical method to unveil the 3D rupture morphology of faults using unsupervised clustering techniques applied to earthquake hypocenters in seismic sequences. We apply this method to the 2009 L'Aquila seismic sequence which involved a MW6.1 mainshock on April 6th. We use a dataset of about 50,000 relocated events, mostly microearthquakes, reaching magnitude of completeness equal to 0.7. Clustering distinguishes the earthquakes as occurring in three main clusters along with other minor fault segments. We then represent the morphology of the main Paganica fault system (responsible for the largest mainshock) using splines. This method shows promise as a step toward robustly and quickly obtaining 3D rupture morphologies where earthquake sequences have been monitored. The 3D model is presented interactively online, and the processing is presented in an interactive Jupyter Notebook (https://bit.ly/2MnCFdj).