Finite Element Models of Elastic Earthquake Deformation

Abstract

The Earth's surface deforms in response to earthquake fault dislocations at depth. Deformation models are constructed to interpret the corresponding ground movements recorded by geodetic data such GPS and InSAR, and ultimately characterize the seismic ruptures. Conventional analytical and latest numerical solutions serve similar purpose but with different technical constraints. The former cannot simulate the heterogeneous rock properties and structural complexity, while the latter directly tackles these challenges but requires more computational resources. As demonstrated in the 2015 M7.8 Gorkha, Nepal earthquake and the 2016 M6.2 Amatrice, Italy earthquake, we develop state-of-art finite element models (FEMs) to efficiently accommodate both the material and tectonic complexity of a seismic deformational system in a seamless model environment. The FEM predictions are significantly more accurate than the analytical models embedded in a homogeneous half-space at the 95% confidence level. The primary goal of this chapter is describe a systematic approach to design, construct, execute and calibrate FEMs of elastic earthquake deformation. As constrained by coseismic displacements, FEM-based inverse analyses are employed to resolve linear and nonlinear fault-slip parameters. With such numerical techniques and modeling framework, researchers can explicitly investigate the spatial distribution of seismic fault slip and probe other in-depth rheological processes.

Coseismic Deformation Responses due to Geometrical Structure and Heterogeneity of the Accretionary Wedge: Study Case 2010 Mentawai Earthquake, West Sumatra, Indonesia

“…However, the shallow part of the crust is more complex than a simple homogeneous model. Using a homogeneous elastic half-space model may lead to less accu-rate prediction in the coseismic simulation [3] and may not be sufficient to obtain the Green function especially for a region where the existence of inhomogeneity is large [4]. Zhao et al [5] show that the effect of layered rigidity contributes to at least 20% of the surface deformation.…”

Structural Controls Over the 2019 Ridgecrest Earthquake Sequence Investigated by High‐Fidelity Elastic Models of 3D Velocity Structures

“…For instance, the over‐simplification of the 3D elastic domain as a homogeneous or layered half‐space, a conventional practice in coseismic slip inversion exercises, could result in over‐/under‐prediction of slip‐induced displacement when the approximated crust substantially differs from the actual environment. Thus, the resolved fault‐slip distribution and fit to the geodetic observations could be improved by incorporating more realistic lithological configurations into forward models linking fault dislocations to observed surface deformation (Hearn & Bürgmann, 2005; Kyriakopoulos et al., 2013; Tung, Fielding, et al., 2019; Tung, Katzenstein, et al., 2019; Tung & Masterlark, 2016, 2018b; 2018c; Tung, Masterlark, & Lo, 2018; Williams & Wallace, 2015). In addition to modeling the fault kinematics, the near‐fault elastic variabilities should also be considered for accurately calculating the geodetic slip moment (and moment magnitude) and Coulomb stress changes (Das et al., 2019; King et al., 1994; Langenbruch & Shapiro, 2014; Tung, Fielding, et al., 2019; Tung, Katzenstein, et al., 2019).…”

“…The left-bottom inlet shows the location of the proximal major faults, namely, the San Andreas Fault and Garlock Fault as well as the Eastern California shear zone and nearby significant events over the past decades. Tung, Fielding, et al, 2019;Tung, Katzenstein, et al, 2019;, 2018b2018c;Tung, Masterlark, & Lo, 2018;Williams & Wallace, 2015). In addition to modeling the fault kinematics, the nearfault elastic variabilities should also be considered for accurately calculating the geodetic slip moment (and moment magnitude) and Coulomb stress changes (Das et al, 2019;King et al, 1994;Langenbruch & Shapiro, 2014;Tung, Fielding, et al, 2019;Tung, Katzenstein, et al, 2019).…”

Rapid Geodetic Analysis of Subduction Zone Earthquakes Leveraging a 3‐D Elastic Green's Function Library

“…Yet, the lengthy processes of building FEMs and the corresponding Green's function (GF) matrix are the bottlenecks of realtime analyses (c.f. Kyriakopoulos et al, 2013;Masterlark & Hughes, 2008;Tung, Masterlark, and Lo, 2018). Analogous to seismological and tsunamic analyses, a GF matrix of earthquake deformation renders the impulse-response relation between inaccessible fault-slip sources at depth and displacements of the surface and is an essential component of early warning systems (Hsieh et al, 2016;Newman et al, 2011;Ross & Ben-Zion, 2016).…”