Abstract. In this paper we introduce a method for fault network reconstruction based on the 3D spatial distribution of seismicity. One of the major drawbacks of statistical earthquake models is their inability to account for the highly anisotropic distribution of seismicity. Fault reconstruction has been proposed as a pattern recognition method aiming to extract this structural information from seismicity catalogs. Current methods start from simple large scale models and gradually increase the complexity trying to explain the small scale features. In contrast the method introduced here uses a bottom-up approach, that relies on initial sampling of the small scale features and reduction of this complexity by optimal local merging of substructures. First, we describe the implementation of the method through illustrative synthetic examples. We then apply the method to the probabilistic absolute hypocenter catalog KaKiOS-16, which contains three decades of South Californian seismicity. To reduce data size and increase computation efficiency, the new approach builds upon the previously introduced catalog condensation method that exploits the heterogeneity of the hypocenter uncertainties. We validate the obtained fault network through a pseudo prospective spatial forecast test and discuss possible improvements for future studies. The performance of the presented methodology attests the importance of the non-linear techniques used to quantify location uncertainty information, which is a crucial input for the large scale application of the method. We envision that the results of this study can be used to construct improved models for the spatio-temporal evolution of seismicity.

中文翻译：

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聚集聚类的故障网络重构：在南加州地震中的应用

摘要。在本文中，我们介绍了一种基于地震活动性3D空间分布的故障网络重建方法。统计地震模型的主要缺点之一是它们无法解释地震活动的高度各向异性分布。断层重建已被提出作为一种模式识别方法，旨在从地震活动目录中提取这种结构信息。当前的方法从简单的大型模型开始，并逐渐增加复杂性以试图解释小型特征。相比之下，此处介绍的方法使用了自下而上的方法，该方法依赖于小规模特征的初始采样并通过子结构的最佳局部合并来降低这种复杂性。首先，我们通过说明性的综合示例来描述该方法的实现。然后，我们将该方法应用于概率绝对震源目录KaKiOS-16，其中包含南加州三十年的地震活动。为了减小数据大小并提高计算效率，新方法建立在先前介绍的利用凝震不确定性异质性的目录缩合方法的基础上。我们通过伪前瞻性空间预测测试验证获得的断层网络，并讨论可能的改进措施，以供将来研究。所提出方法的性能证明了用于量化位置不确定性信息的非线性技术的重要性，这是该方法大规模应用的关键输入。我们预想，这项研究的结果可用于构建地震活动时空演化的改进模型。