HR: 12:05h
AN: T12C-08    [Abstracts]
TI: Detecting Aseismic Fault Slip and Magmatic Intrusion From Seismicity Data
AU: * Llenos, A L
EM: allenos@mit.edu
AF: MIT/WHOI Joint Program, 77 Massachusetts Ave., Cambridge, MA 02139, United States
AU: McGuire, J J
EM: jmcguire@whoi.edu
AF: Woods Hole Oceanographic Institution, MS 24, Woods Hole, MA 02543, United States
AB: Seismicity triggered by aseismic deformation, such as magmatic intrusions or afterslip, can be used to detect the occurrence of these otherwise difficult to observe processes. Recent studies suggest that aseismic deformation can trigger large amounts of seismicity in a variety of plate tectonic settings. We have developed a new technique that takes advantage of this triggered seismicity to estimate the time-history of aseismic stressing rate on a fault- zone by combining the rate and state dependent friction and the Epidemic Type Aftershock Sequence (ETAS) models of seismicity-rate [ Dieterich, 1994; Ogata, 1988]. In the rate-state model, the integration of an observed seismicity rate results in an estimate of the stress rate acting in a given space-time window. However, the seismicity rate observed in any catalog comes from 3 primary sources: coseismically-triggered seismicity (aftershocks), tectonically-triggered seismicity (i.e., from long-term tectonic loading), and aseismically-triggered seismicity (e.g., from dike intrusion, aseismic slip transients, or fluid migration). In catalogs dominated by directly triggered aftershocks (i.e., ETAS branching ratios >~0.7), the coseismically-triggered seismicity rate will be much larger than the aseismically-triggered rate and will dominate the estimate of stressing-rate, obscuring the aseismic transient of interest if the rate-state method is applied directly. The challenge therefore lies in isolating the aseismically-triggered seismicity rate from the coseismically-triggered seismicity rate. The ETAS model [ Ogata, 1988] provides a natural way to separate the aseismic and coseismic seismicity rates, as the ETAS parameter μ essentially reflects the aseismically-triggered rate (as well as the background tectonically-triggered rate). To develop a method that can resolve the magnitude and time history of aseismic stress transients even in high branching ratio regions, we combine the rate-state and ETAS models into a single data assimilation algorithm. For a given earthquake catalog, we produce maximum likelihood estimates of the ETAS parameters and use an extended Kalman filter to estimate the temporal evolution of the underlying state variables (stress, stress rate and γ in the Dieterich formulation). We have tested the algorithm with a number of synthetic catalogs and can successfully detect order-of-magnitude changes in stressing rate. Additionally, we can detect large fault creep events detected independently from geodetic data. Ultimately, we aim to map spatial as well as temporal variations in aseismic stressing rates from seismicity data. With this tool we can then identify the space-time evolution of such processes as afterslip, fluid migration, or magmatic intrusion. Moreover, algorithms that can detect when aseismic transients are occurring should have direct applications in real-time seismicity and hazard forecasts.
DE: 1207 Transient deformation (6924, 7230, 7240)
DE: 3265 Stochastic processes (3235, 4468, 4475, 7857)
DE: 7223 Earthquake interaction, forecasting, and prediction (1217, 1242)
DE: 7230 Seismicity and tectonics (1207, 1217, 1240, 1242)
DE: 8123 Dynamics: seismotectonics
SC: Tectonophysics [T]
MN: 2007 Fall Meeting