Post on 12-Jan-2016
Analysis of complex seismicity pattern generated by fluid diffusion and aftershock triggering
Sebastian Hainzl Toni Kraft
System
Statsei4
Introduction
A Closed System = “plate boundary scenario”
Assumption: tectonic loading + earthquake induced effects
Statistical Earthquake Models:
- long-term mainshock occurrence: Stress-Release model (Vere-Jones, 1978)
- short-term clustering: ETAS model (Ogata, 1988) Epidemic Type Aftershock Sequences
talk: Bebbington poster: Kuehn & Hainzl
Introduction
B Open System
= “intraplate scenario”
Assumption: tectonic loading + earthquake induced effects + external forcing
Examples: - volcano related seismicity
- postglacial rebound
- fluid intrusion
Introduction
In the latter case, statistical modeling has to take care of the spatiotemporally varying external forcing.
Two examples are shown:
1) Unknown external force: (Hainzl & Ogata, JGR 2005)
“Vogtland Swarm Activity”
2) Known hypothetical source:
“Seismicity at Mt. Hochstaufen”
1) Vogtland swarm activity
1896/97, 1903, 1908/09, 1985/86, 2000
episodic occurrence of earthquake swarms:
Possible mechanism:
“...fluid overpressure in the brittle crust”
(Braeuer et al., JGR 2003)
swarm 2000
mag
nitu
de
time / date
(Hainzl & Ogata 2005)
Statistical modeling by means of the ETAS model
Each earthquake has a magnitude-dependent ability to trigger aftershocks:
f(M) = K exp( a M )The aftershock rate decays according to
the modified Omori law:
h(t) = (c+t)-p
1) Vogtland swarm activity
external triggering tectonic loading +pore pressure increase
aftershock triggering induced stress + pressure changes
(Hainzl & Ogata 2005)
Method to extract the forcing signal:
fit of the ETAS model by maximum likelihood method
estimation of the ETAS parameter in a moving time window
Results:
external triggering accounts only for a few percent of all events
1.
method is successfully tested for model simulations:Fluid signal can be reconstructed!
3.
temporal variation of the forcingsignal is correlated with phases of (i) diffusion-like spatiotemporal migration (Parotidis et al. 2003) (ii) enhanced tensile components (Roessler et al. 2005)
2.time [days]
forc
ing
rate
[#/
day]
1) Vogtland swarm activity (Hainzl & Ogata 2005)
1) Vogtland swarm activity
Unknown driving force:
reconstruction of the spatiotemporal pattern of the external force is possible
revealed pattern can be compared with competing source models
Indirect test of seismicity models
2) Seismicity at Mt. Hochstaufen
- spatially isolated activity- earthquakes are felt since more than 700 years- seasonally variations
hypothesis: rainfall induced (Kraft et al., 2006)
2) Seismicity at Mt. Hochstaufen
Analysis of the high-quality data from year 2002
INPUT: daily measured rainfall
OUTPUT: earthquake catalog > 1100 events > 500 locations
2) Seismicity at Mt. Hochstaufen
2) Seismicity at Mt. Hochstaufen
lambda=0.3, c=4600 day/bar, D= 0.32 m2/s 80% rain-triggered & 20% background events
2) Seismicity at Mt. Hochstaufen: RESULTS
rain
pressure
comparison:
pressure increase
& earthquake rate
2) Seismicity at Mt. Hochstaufen: RESULTS
Coefficient of Correlation as a function of the delay time between
daily seismic rate & daily rain
2) Seismicity at Mt. Hochstaufen: RESULTS
high correlation with the pore pressure diffusion model
Coefficient of Correlation as a function of the delay time between
daily seismic rate & daily rain
daily seismic rate & pore pressure increase
Summary:
- direct test of the hypothesis of rain-triggered activity
- model yields high correlation with observation
- this suggests that very tiny stress changes are able to trigger earthquakes
2) Seismicity at Mt. Hochstaufen: