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‘Triggering’ = a perturbation in the loading deformation that leads to a change in the probability of failure. Overview of Evidence for Dynamic Triggering.

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Presentation on theme: "‘Triggering’ = a perturbation in the loading deformation that leads to a change in the probability of failure. Overview of Evidence for Dynamic Triggering."— Presentation transcript:

1 ‘Triggering’ = a perturbation in the loading deformation that leads to a change in the probability of failure. Overview of Evidence for Dynamic Triggering

2 ‘Triggering’ = a perturbation in the loading deformation that leads to a change in the probability of failure. How do we know it happens?

3 ‘Triggering’ = a perturbation in the loading deformation that leads to a change in the probability of failure. How do we know it happens? Measure or infer a loading perturbation, & observe a change in seismicity rate (fault population or single fault recurrence), possibly its spatial variation too.

4 The ‘Reference’ State Central California Ambient Seismicity

5 The Perturbation Coyote Lake Mainshock & Ambient Seismicity

6 The Perturbation & Response Coyote Lake Mainshock & Aftershocks

7 Dynamic loads: Seismic waves (oscillatory, transient)

8 Dynamic loads: Seismic waves (oscillatory, transient) Aseismic slip (not oscillatory, may be permanent)

9 Dynamic loads: Seismic waves (oscillatory, transient) Aseismic slip (not oscillatory, permanent) Solid earth tides and ocean loading (oscillatory, ongoing)

10 Dynamic loads: Seismic waves (oscillatory, transient) Aseismic slip (not oscillatory, permanent) Tides (oscillatory, ongoing) Surface/shallow: snow and ice, reservoir filling/draining, mining, ground water, fluid injection or withdrawal (localized) Magma movement (temperature, pressure, and chemical changes too)

11 What’s unique about dynamic loads?

12 They’re transient!

13 shear stress failure threshold time tt Static Load Change

14 shear stress failure threshold time Static Load Change tt tt

15 shear stress failure threshold time Dynamic Triggering

16 shear stress failure threshold time Dynamic Triggering tt

17 shear stress failure threshold time tt What’s unique about dynamic loads? They’re transient; the failure conditions must change!

18 What’s unique about dynamic loads? They’re transient; the failure conditions must change! They’re oscillatory, but they only enhance failure probability (ASSUMPTION); no stress shadows.

19 What’s unique about dynamic loads? They’re transient; the failure conditions must change! They only enhance failure probability (ASSUMPTION); no stress shadows. Slower distance decay than static stress changes.

20 Dynamic Triggering Observations (by load type) Seismic waves (transient, oscillatory) Remote (many source dimensions) Near-field (few source dimensions) Distance-independent Quasi-seismic responses Laboratory Aseismic slip (slow, permanent) Tides (oscillatory, ongoing) Surface/Shallow: snow and ice, reservoir filling/draining, mining, ground water, fluid injection or withdrawal (localized)

21 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Seismicity rate increases following large earthquakes.

22 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Seismicity rate increases following large earthquakes.

23 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Seismicity rate increases following large earthquakes.

24 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Seismicity rate increases following large earthquakes. Missing? rate increases.

25 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Correlation of spatial rate increase with directivity.

26 Pollitz & Johnston, 2007 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Correlation of spatial rate increase with directivity. Correlation of (no) rate change with co-located seismic & aseismic events.

27 Pollitz & Johnston, 2007 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Correlation of spatial rate increase with directivity. Correlation of (no) rate change with co-located seismic & aseismic events.

28 Ma et al., 2005 Chi-Chi earthquake shadows start with 3-month rate increases. Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Correlation of spatial rate increase with directivity. Correlation of (no) rate change with co-located seismic & aseismic events. Early excess of aftershocks. Rate increases in stress shadows

29 “Observed seismicity rate decreases in the Santa Monica Bay and along parts of the San Andreas fault are correlated with the calculated stress decrease.” Stein, 1999

30 Time history of seismicity from Santa Monica Bay (Marsan, 2003).

31 “The [Stein, 1999] interpretation is made difficult by the fact that the transient activity modulation by the 1989 M5 Malibu earthquake was still ongoing….the quiescence observed after 1994 can be tracked back several months before Northridge, the latter main shock actually triggering seismicity in the region at the very short (i.e. days) timescale. Marsan, 2003

32 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Measured Linear Aftershock Densities Felzer & Brodsky, 2006

33 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Modeled Linear Aftershock Densities number of aftershocks at distance r number of potential nucleation sites per unit distance probability of nucleation  constant!

34 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Modeled Linear Aftershock Densities number of aftershocks at distance r number of potential nucleation sites per unit distance probability of nucleation  constant!

35 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view ‘Linear density’ = number of aftershocks within a volume defined by surface S everywhere at distance r and width  r D triggering fault

36 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Modeled Linear Aftershock Densities

37 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Modeled Linear Aftershock Densities number of aftershocks at distance r number of potential nucleation sites per unit distance probability of nucleation  constant!

38 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Modeled Linear Aftershock Densities

39 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Modeled Linear Aftershock Densities

40 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Are dynamic deformations consistent with these probabilities?

41 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Peak Velocities vs r, M Are dynamic deformations consistent with these probabilities?

42 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Peak Velocities vs r, M Peak Velocities vs r/D, M perhaps! Are dynamic deformations consistent with these probabilities?

43 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses ‘Low-frequency’ events Sumatra surface waves in Japan High-passed Sumatra surface waves in Japan Correlation with Rayleigh waves - Dilatation & Fluids Miyazawa & Mori, 2006

44 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses ‘Low-frequency’ events Sumatra surface waves in Japan High-passed Sumatra surface waves in Japan Correlation with Rayleigh waves - Dilatation & Fluids Denali surface waves in Japan, Correlation with Love waves - Shear Load! Miyazawa & Mori, 2006Rubinstein et al., 2007

45 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses ‘Low-frequency’ events Creep and tilt Response to Hector Mine waves on Imperial Fault (260 km) Glowacka et al., 2002 H H

46 Dynamic Triggering Observations (by loading type) Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses Laboratory “Our results predict that a transient dynamic normal load during creep can strengthen a fault…gouge particles become compacted into a lower energy configuration.” Richardson and Marone, 1999 Granular surface quasi-static experiments.

47 Sobolev et al., 1996 Granite surface stick-slip experiments. Dynamic Triggering Observations Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses Laboratory delayed failure

48 Sobolev et al., 1996 Granite surface, shear vibration, stick-slip experiments. Dynamic Triggering Observations Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses Laboratory delayed failure Vibration Clock-advances Failure

49 Dynamic Triggering Observations Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses Laboratory Granular surface, acoustic vibration, stick-slip experiments.

50 Dynamic Triggering Observations Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses Laboratory Granular surface, acoustic vibration, stick-slip experiments. acoustic transient triggered ‘new’ seismic events clock-delayed failure

51 Dynamic Triggering Observations Seismic waves Remote (many source dimensions) Near-field (few source dimensions) Distance-independent view Quasi-seismic responses Laboratory Granular surface, acoustic vibration, stick-slip experiments. acoustic transient triggered ‘new’ seismic events clock-delayed failure memory

52 Dynamic Triggering Observations (by loading type) Seismic waves Aseismic slip Earthquakes Hawaii Slow Slip & Earthquakes Number of earthquakes & displacement

53 Dynamic Triggering Observations (by loading type) Seismic waves Aseismic slip Earthquakes Tremor Dragert et al., 2002 Cascadia Slow Slip & Tremor Geodetic Displacement (mm east) Tremor Activity (hrs in 10 days)

54 General features: apparent more commonly in areas of geothermal & Quaternary to recent volcanism, extensional regimes, high strain rates, seismic strains required ~  strains, sometimes instantaneous but also delayed.

55 Models Coulomb-Navier failure: no delays Frictional: traditional clock-advance models can’t explain long delays, require high (near lithostatic) pressures or critical conditions, changing frictional properties or stability regime. Subcritical crack growth: same behavior as rate-state friction. Dynamic nonlinear softening. Fluid and pore pressure mechanisms: decrease effective normal stress, local, fluid-driven deformation disruption of clogged fractures and hydraulic fracturing bubbles rectified diffusion (volatiles selectively pumped into bubbles during the dilatation) advective overpressure (rising of loosened bubbles within magma body )

56 Models Coulomb-Navier failure: no delays Frictional: traditional clock-advance models can’t explain long delays, require high (near lithostatic) pressures or critical conditions, changing frictional properties or stability regime. Subcritical crack growth: same behavior as rate-state friction. Dynamic nonlinear softening. Fluid and pore pressure mechanisms: decrease effective normal stress, local, fluid-driven deformation disruption of clogged fractures and hydraulic fracturing bubbles rectified diffusion (volatiles selectively pumped into bubbles during the dilatation) advective overpressure (rising of loosened bubbles within magma body )

57 Parsons, 2005 Power-law distribution of contact areas. Dynamically reduced contact area (i.e. critical slip distance)

58 Parsons, 2005 Power-law distribution of contact areas. Number of ‘events’ vs clock-advance for 10% reduction in critical slip distance. Dynamically reduced contact area (i.e. critical slip distance)

59 Parsons, 2005 Power-law distribution of contact areas. Number of ‘events’ vs clock-advance for 10% reduction in critical slip distance. Perturbed failure rate. Dynamically reduced contact area (i.e. critical slip distance)

60 Models Coulomb-Navier failure: no delays Frictional: traditional clock-advance models can’t explain long delays, require high (near lithostatic) pressures or critical conditions, changing frictional properties or stability regime. Subcritical crack growth: same behavior as rate-state friction. Dynamic nonlinear softening. Fluid and pore pressure mechanisms: decrease effective normal stress, local, fluid-driven deformation disruption of clogged fractures and hydraulic fracturing bubbles rectified diffusion (volatiles selectively pumped into bubbles during the dilatation) advective overpressure (rising of loosened bubbles within magma body )

61 Models Coulomb-Navier failure: no delays Frictional: traditional clock-advance models can’t explain long delays, require high (near lithostatic) pressures or critical conditions, changing frictional properties or stability regime. Subcritical crack growth: same behavior as rate-state friction. Dynamic nonlinear softening. Fluid and pore pressure mechanisms: decrease effective normal stress, local, fluid-driven deformation, disruption of clogged fractures and hydraulic fracturing, bubbles rectified diffusion (volatiles selectively pumped into bubbles during the dilatation) advective overpressure (rising of loosened bubbles within magma body).

62 Elastic moduli decrease (soften) with increasing dynamic load amplitude -> weakening mechanism? Relative Change in Modulus Pulse Experiments, Glass Beads

63 Elastic moduli decrease (soften) with increasing dynamic load amplitude -> weakening mechanism? Relative Change in Modulus % Relative Change in Resonant Frequency % Relative Change in Modulus sinusoid amplitude (strain) Pulse Experiments, Glass Beads Sinusoid Experiments, Rocks

64 Models Coulomb-Navier failure: no delays Frictional: traditional clock-advance models can’t explain long delays, require high (near lithostatic) pressures or critical conditions, changing frictional properties or stability regime. Subcritical crack growth: same behavior as rate-state friction. Dynamic nonlinear softening. Fluid and pore pressure mechanisms: decrease effective normal stress, local, fluid-driven deformation, disruption of clogged fractures and hydraulic fracturing, bubbles rectified diffusion (volatiles pumped into bubbles during the dilatation), advective overpressure (rising of loosened bubbles within magma body), liquefaction.

65 -Outstanding Questions- Is our sampling biased (e.g., best monitoring in high strain rate and/or geothermal areas)?

66 -Outstanding Questions- Is our sampling biased (e.g., best monitoring in high strain rate and/or geothermal areas)? How important are local conditions; are multiple mechanisms at work?

67 -Outstanding Questions- Is our sampling biased (e.g., best monitoring in high strain rate and/or geothermal areas)? How important are local conditions; are multiple mechanisms at work? What are the important characteristics of the dynamic field (frequency/rate, duration, max. value)?

68 Strain Rate (acceleration) Strain (velocity) Displacement

69 Theoretical Frequency Sensitivity Dynamically Induced Pore Pressure Change Velocity Strengthening, Slip Weakening Friction Non-Linear, Slip Weakening Friction

70 -Outstanding Questions- Is our sampling biased (e.g., best monitoring in high strain rate and/or geothermal areas)? How important are local conditions; are multiple mechanisms at work? What are the important characteristics of the dynamic field (frequency/rate, duration, max. value)? How does delayed failure happen?

71 Thanks! Comments?


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