- 1State Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao, China (lfu@upc.edu.cn; haidi.yang@upc.edu.cn)
- 2EOST/ITES, Université de Strasbourg, France (qingyu.wang@unistra.fr)
- 3Institut des Sciences de la Terre, Saint Martin d’Hères, France (michel.campillo@univ-grenoble-alpes.fr)
- 4Laboratory for Marine Mineral Resources, Qingdao Marine Science and Technology Center, Qingdao, China (lfu@upc.edu.cn)
Postseismic healing generally involves nonlinear mechanical deformations characterized by the strain-dependent changes of seismic velocities. Brenguier et al. (2008) documented postseismic seismic-velocity changes after the 2004 Parkfield earthquake and primarily compared dv/v with along-fault displacement; GPS-derived strain was discussed mainly at an order-of-magnitude level, suggesting a potential link between dv/v and strain without providing a detailed quantitative analysis. Here ambient noise studies using seismic interferometry reveal the stress-dependent change of seismic velocities during the fault healing. To quantify this coupling, we develop acoustoelastic seismic interferometry that couples ambient-noise Green’s-function reconstruction with an acoustoelastic stress–velocity mapping to convert interferometric dv/v into the spatiotemporal evolution of stress changes during healing. The mapping is evaluated using second- and third-order elastic constants taken from experimental studies with Snake River Plain Basalt (Wang and Schmitt, 2024). We validate the approach independently using coseismic stress-drop and postseismic stress-recovery constraints with active-source benchmarks reported by Niu et al. (2008). Applied to the Parkfield sequence, we analyze the dv/v recovery trend with the corresponding stress-recovery pattern. This provides a physics-based route from phenomenological dv/v monitoring to quantitative inference of fault-zone stress evolution. The theoretical framework can be extended to other fault systems to continuously image stress transfer and healing from ambient noise and to inform earthquake-cycle models.
References
Niu, F., Silver, P. G., Daley, T. M., Cheng, X., & Majer, E. L. (2008). Preseismic velocity changes observed from active source monitoring at the Parkfield SAFOD drill site. Nature, 454(7201), 204-208.
Wang, W., & Schmitt, D. R. (2024). Measurement of the static nonlinear third-order elastic moduli of rocks: Problems and applicability. Journal of Geophysical Research: Solid Earth, 129(10), e2024JB028784.
Brenguier, F., Campillo, M., Hadziioannou, C., Shapiro, N. M., Nadeau, R. M., & Larose, É. (2008). Postseismic relaxation along the San Andreas fault at Parkfield from continuous seismological observations. science, 321(5895), 1478-1481.
How to cite: Yang, H., Fu, L.-Y., Wang, Q.-Y., and Campillo, M.: Nonlinear stress dependence from seismic interferometry for postseismic healing of the 2004 Parkfield earthquake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19450, https://doi.org/10.5194/egusphere-egu26-19450, 2026.