Fault segmentation user perspective
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Fault Segmentation: User Perspective. Norm Abrahamson PG&E March 16, 2006. Segmentation Approaches in Seismic Hazard Practice. Pre ~1985 Used 1/3 to 1/2 fault length for the characteristic (max) earthquake Implies segmentation but unknown segmentation points 1985-1995

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Fault Segmentation: User Perspective

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Fault segmentation user perspective

Fault Segmentation:User Perspective

Norm Abrahamson

PG&E

March 16, 2006


Segmentation approaches in seismic hazard practice

Segmentation Approaches in Seismic Hazard Practice

  • Pre ~1985

    • Used 1/3 to 1/2 fault length for the characteristic (max) earthquake

    • Implies segmentation but unknown segmentation points

  • 1985-1995

    • Geologist identified segmentation points

    • Used full length of segments for characteristic earthquake

    • Typically considered segmented or unsegmented cases through logic tree (e.g. epistemic uncertainty), but not aleatory variability in segmentation

  • 1995 - Current

    • Begin to include aleatory variability in segmentation (sometimes individual segment rupture, sometimes multi-segment ruptures


Unknown segmentation

Unknown Segmentation

  • Truncated exponential model for mag pdf is sometimes used as proxy for segmentation


Example effects of segmentation slip rate 10 mm yr

Example: Effects of SegmentationSlip-rate=10 mm/yr


Deterministic approach median sa

Deterministic Approach(Median Sa)


Example effects of segmentation pga site 1 at segmentation point

Example: Effects of SegmentationPGA: Site 1 (at segmentation point)


Example effects of segmentation t 3 site 1 at segmentation point

Example: Effects of SegmentationT=3: Site 1 (at segmentation point)


Example effects of segmentation pga site 2 middle of a segment

Example: Effects of SegmentationPGA: Site 2 (middle of a segment)


Example effects of segmentation t 3 site 2 middle of a segment

Example: Effects of SegmentationT=3: Site 2 (middle of a segment)


User needs for segmentation

User Needs for Segmentation

  • Fault Models

    • Need rates of ruptures on faults

    • Develop credible models of the fault behavior in terms of segmentation that are consistent with observations

  • Avoid Bias

    • Should not include intentional conservatism

      • Not clear what is conservative

  • Uncertainty

    • Uncertainty in segmentation is handled using alternative models of fault behavior

      • Should not just be single segments ruptures and all segment ruptures


Truncated exponential model for faults

Truncated Exponential Modelfor faults

  • Hecker evaluated variability of surface slip at a point

  • Found that the truncated exponential model will produce much larger variability than observed

  • Concluded that truncated exponential model is not applicable to individual faults


User needs

User Needs

  • Earthquake probabilities for ruptures are useful, but they need to be converted to PSHA inputs

  • More useable information is the equivalent slip-rate that for each rupture (single segment or multi-segment)

    • Allows direct input into standard PSHA codes


Example from wg03 94 moment in char eqk

Example from WG0394% Moment in Char Eqk


Coefficient of variation of surface slip at at point from hecker

Coefficient of Variation of Surface Slip at at Point (from Hecker)


Testing of magnitude recurrence models using c v

Testing of Magnitude Recurrence Models Using C.V.

  • Forward Modeling of expected observations of slip at a point

    • Prob (M) (from mag recurrence model)

    • Prob (rupture to surface given M)

    • Prob (rupture past site given Rup Length(M))

    • Prob (amount of surface slip given M)

    • Prob (detection) including effect of adding slip from non-detected events to the detected events

  • Magnitude recurrence models

    • Truncated exponential

    • Youngs & Coppersmith Characteristic

    • Max Mag = 7.5, MinMag = 6.0


Amount of surface slip

Amount of Surface Slip

  • Average Displacement

    • Use Wells and Coppersmith for all fault types

    • log(AD) = -4.8 + 0.69M ± 0.36 (±0.82 ln units)

  • Variation in Displacement along Strike

    • Use results from (ref?)

    • Sigma along strike approx 0.7 natural log units

  • Total standard deviation of slip-at-a-point

    • Sqrt(0.822+0.702)=1.07


C v from modeling results case1 using full slip variability for given m

C. V. from Modeling ResultsCase1:Using full Slip Variability for given M


Fault segmentation user perspective

C. V. from Modeling ResultsCase1:Using reduced Variability for given M (reduced to 0.3 natural log units)


Conclusions from forward modeling of surface slip

Conclusions from Forward Modeling of Surface Slip

  • Variability of slip at a point must be much smaller than expected using global models

  • The Y&C mag recurrence model can give C.V. values similar to observed values if small variability in slip for given mag is used.

  • The truncated exponential mag recurrence model gives much larger C.V. values than observed even with reduced variability in slip given mag.

    • The truncated exponential model is not consistent with the observed C.V. values.


Effect of small number of events per site

Effect of Small Number of Events per Site

  • Use Monte Carlo

    • Population C.V.=0.4

    • Same sampling as in data set

  • Result:

    • Average C.V.=0.41 (small bias toward larger CV)


Event position of smallest slip

Event Position of Smallest Slip

  • Smallest slip is more often the most recent event

  • Accommodate effect by overprinting

  • Calibrate levels for overprinting (e.g. 40% of amplitude) using observed frequencies


Fault segmentation user perspective

Effect of Probability of Detection and OverprintingExample: mean slip is close to detection thresholdresult: Increase in C.V.


Fault segmentation user perspective

Effect of Probability of DetectionExample: mean slip is 2.5 times detection thresholdResult: Similar C.V.


Probability of surface rupture modified from igns 2003

Probability of Surface Rupture (modified from IGNS, 2003)


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