Real-time inversions for finite fault slip models and rupture geometry based on high-rate GPS data
Real-time inversions for finite fault slip models and rupture geometry based on high-rate GPS data
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DOI：
10.1002/2013jb010622
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发表时间：
2014-04-01
影响因子：
3.9
通讯作者：
Gomberg, Joan S.
中科院分区：
文献类型：
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作者：
Minson, S. E.;Murray, Jessica R.;Gomberg, Joan S.
我们提出了一种反演策略，能够使用实时高速率GPS数据，同时解决分布式滑动模型和断层几何结构在真实的时间作为一个破裂展开。我们采用贝叶斯推理找到最佳的断层几何形状和可能的滑动模型的分布，该几何形状使用一个简单的解析解。通过采用分析贝叶斯方法，我们可以解决这个复杂的反演问题（包括计算我们的结果的不确定性）在真实的时间。此外，由于分布式滑移和断层几何形状的联合反演可以在真实的时间内计算，因此获得震源模型所需的时间不依赖于计算成本。相反，所需的时间由破裂的持续时间和信息从源传播到接收器所需的时间来控制。我们应用我们的建模方法，称为贝叶斯证据为基础的断层方向和实时地震滑动，2011年东北冲地震，2003年十胜冲地震，和一个模拟的海沃德断层地震。在这三种情况下，反演恢复的幅度，空间分布的滑动，和断层几何形状在真实的时间。由于我们的反演依赖于从实时高速率GPS数据估计的静态偏移，我们还提出了在真实的时间估计准静态偏移的各种方法的性能测试。我们发现，原始的高速率时间序列是最好的数据，用于确定的时刻震级的事件，但稍微平滑的原始时间序列有助于稳定断层几何反演。
We present an inversion strategy capable of using real-time high-rate GPS data to simultaneously solve for a distributed slip model and fault geometry in real time as a rupture unfolds. We employ Bayesian inference to find the optimal fault geometry and the distribution of possible slip models for that geometry using a simple analytical solution. By adopting an analytical Bayesian approach, we can solve this complex inversion problem (including calculating the uncertainties on our results) in real time. Furthermore, since the joint inversion for distributed slip and fault geometry can be computed in real time, the time required to obtain a source model of the earthquake does not depend on the computational cost. Instead, the time required is controlled by the duration of the rupture and the time required for information to propagate from the source to the receivers. We apply our modeling approach, called Bayesian Evidence-based Fault Orientation and Real-time Earthquake Slip, to the 2011 Tohoku-oki earthquake, 2003 Tokachi-oki earthquake, and a simulated Hayward fault earthquake. In all three cases, the inversion recovers the magnitude, spatial distribution of slip, and fault geometry in real time. Since our inversion relies on static offsets estimated from real-time high-rate GPS data, we also present performance tests of various approaches to estimating quasi-static offsets in real time. We find that the raw high-rate time series are the best data to use for determining the moment magnitude of the event, but slightly smoothing the raw time series helps stabilize the inversion for fault geometry.