2006
DOI: 10.1016/j.tecto.2006.03.039
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A way to synchronize models with seismic faults for earthquake forecasting: Insights from a simple stochastic model

Abstract: Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobse… Show more

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Cited by 12 publications
(2 citation statements)
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“…However, as pointed out by Isliker, Anastasiadis, and Vlahos (2000), it is still possible to compute derivatives and thus operators. To the best of our knowledge, at the present time the only other area in which data assimilation techniques are being developed in conjunction with a cellular automaton is in seismic data assimilation of a stochastic random fault model (Rundle et al, 2003;González et al, 2006). We are also using a time series of a global, model-produced variable to define the error, as opposed to the spatial state of the system measured at some time interval beyond the initial condition in which data is being assimilated.…”
Section: Beyond Classical 4d-varmentioning
confidence: 99%
“…However, as pointed out by Isliker, Anastasiadis, and Vlahos (2000), it is still possible to compute derivatives and thus operators. To the best of our knowledge, at the present time the only other area in which data assimilation techniques are being developed in conjunction with a cellular automaton is in seismic data assimilation of a stochastic random fault model (Rundle et al, 2003;González et al, 2006). We are also using a time series of a global, model-produced variable to define the error, as opposed to the spatial state of the system measured at some time interval beyond the initial condition in which data is being assimilated.…”
Section: Beyond Classical 4d-varmentioning
confidence: 99%
“…(1) Based on seismological observations, statistical physics, experiments and mechanical theory, the mechanism of instability evolution is analyzed which allows event prediction to be made. However, due to strong nonlinearity of the seismogenic process, the kinetic equations [11] describing such a process cannot be accurately established. Even if these equations were written out, it would be still rather difficult to determine many geometrical and mechanical parameters.…”
Section: Introductionmentioning
confidence: 99%