Noise Based Detection Method for the ANSS

by Dan McNamara

With Collaborators: Ray Buland, Harley Benz, Rob WessonArt Frankel and Dirk Erickson

Topics• ANSS Probabilistic Noise Analysis• Noise Based Detection Technique• Detection System Applications• ANSS Network Design Recommendations

ANSS Seismic Noise Monitoring• Establish ANSS station noise baselines• ANSS backbone instrumentation• ANSS backbone site criteria• Network detection thresholds• Station maintenance issues

– System transients– Prioritize repairs– Automate problem notification

• Cultural noise source modeling• Microseism modeling

MotivationHailey, ID 08/2001-05/2002

All data is included, no pre-screening for quakes, data gaps, glitches, high noise data.

2370 individual PSDs, binned in 1/8 octave intervals, are used to construct a Seismic Noise Probability Density Function for HLID BHZ.

McNamara and Buland (2004) in press BSSA

Cars Local QuakesTeleseismsApproach

ResultsRealistic view of noise conditions at a station. Not simply lowest levels experienced.

Seismic Noise PDFsnoise as a function of location and site type

Idaho Springs, CO Bozeman, MTContinental Interior: Mine Site Continental Interior: Borehole

Western US rocks sites tend to have low noise although the minimumis generally higher than the NLNM.

Seismic Noise PDFsnoise as a function of location and site type

Eastern US: Surface vaultBinghamton, NY

Island Site: BoreholeBig Island Hawaii

Very high noise in microseism bandBut quiet at long periods due to borehole.

Higher noise across all bands in Highly populous Eastern US.

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique

– Brune source modeling method– Comparison of Brune source modeling results with

NEIC autopicker

• Detection System Applications• ANSS Network Design Recommendations

Method to Compute Theoretical ANSS Detection Threshold based on Brune Source Modeling.

fc=10Hz Mw=3.1 fc=1Hz Mw=5.1

For each 1 degree cell we model Brune sources over a range of frequenciesBrune (1970, 1971).

A detection is declared if the Brune source P-wave amplitude exceeds our noise threshold at 5 ANSS stations.

€

Mo = 2.29σr 3

σ =108

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r =2.21β

2πcf

Mw = 0.667 log(Mo) – 10.7 (Kanimori, 1977)

Compute shear-wave amplitude from Mw(Brune 1970, 1971).

Apply Q(f) models to shear-wave amplitude.

Convert to P-wave amplitude. Convert velocity amplitude to dB for noise comparison.

Shear-wave moment (dyne-cm) Brune (1970, 1971).

Fault Dimension in cm

CalculationsFor each frequency (1/period) per cell.

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique

– Brune source modeling method– Comparison of Brune source modeling results with

NEIC autopicker

• Detection System Applications• ANSS Network Design Recommendations

Brune minimum Mw, 80% noise threshold

NEIC Autopicker Minimum mb.

ANSS Detection Threshold Modeling Results

Mw/mbUsed 63 existing ANSS backbone stations with well established noise baselines. Detection declared if at least 5 stations in solution.

Model shows minimum Mw at regions where network is dense in western and eastern US.

Mw max occur in regions of low station density.

Model minimums ~0.2 units higher than catalog.

Model maximums ~0.2 units lower than catalog.

General pattern close match.

Brune minimum Mw, PDF mode noise threshold

NEIC Autopicker Minimum mb.

ANSS Detection Threshold Modeling Results

Mw/mb PDF mode noise threshold pattern similar to 80th with minimum Mw regions expanded.

PDF mode noise threshold demonstrates how lowering noise can extend minimum detection threshold.

Model minimums ~0.1 units higher than catalog.

Model maximums 1.0-1.2 units lower than catalog.

General pattern close match but overall pattern better matched by 80th noise threshold.

Brune source modeling not an exact match to NEIC autopicker?

• Mb:Mw bias?• Simplistic application of Q models • Noise baselines affected by system transients• Incomplete and complicated autopicker catalog

mb:Mw Bias

Sipkin (2003)Mw=1.46mb-2.42UC Berkeley

Northern CA Moment Tensor Catalog

1988-2004

For mb 5.5-7.3

No Magnitude bias at small mb

Brune source modeling not an exact match to NEIC autopicker?

• Mb:Mw bias?• Simplistic application of Q models • Noise baselines affected by system transients• Incomplete and complicated autopicker catalog

New frequency Dependent Q Models3Hz

6Hz

Q

Considerable time spent modeling Lg amplitudes for frequency dependent US Q.Erickson et al, 2004;McNamara et al 2004;Wesson and McNamara 2003.

At this point Q(f) chosen by source region.

More realistic approach is to project each path through Q model to more accurately predict amplitudes.

Should lead to better modeling of Mw regional variations.

Brune source modeling not an exact match to NEIC autopicker?

• Mb:Mw bias?• Simplistic application of Q models • Noise baselines affected by system transients• Incomplete and complicated autopicker catalog

System Transients can have an effect on noise PDF levels.

90th percentile and mode often track data dropouts when frequent.

Causing localized detection anomalies.

Data Dropouts

Brune source modeling not an exact match to NEIC autopicker?

• Mb:Mw bias?• Simplistic application of Q models • Noise baselines affected by system transients• Incomplete and complicated autopicker catalog

mb

NEIC Minimum Auto Detection Catalog Issues

Catalog possibly incomplete (only 20 months in 2002-2003)Possible false triggers at mb minimums.Mine blasts that do not behave like earthquakes at mb minimums.Multiple magnitude types (mb, ml, mbLg)

Therefore, difficult to achieve exact match.

Brune source modeling not an exact match to NEIC autopicker?

• Mb:Mw bias?• Simplistic application of Q models • Noise baselines affected by system transients• Incomplete and complicated autopicker catalog

Match good enough to play games with detections and learn some things about the network!

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique• Detection System Applications

– Regional Network Evaluation– Maintenance Prioritization– ANSS Network Design

• ANSS Network Design Recommendations

Regional Network Simulation6 stations from NM regional network with well established noise baselines.

Detection threshold lowered in New Madrid region by 0.1-0.3 unitswith addition of NM network.

Regional Station Limitations:- high noise in Cultural noise band (1-10Hz)- PVMO instrumented with Guralp CMG-3esp seismometer (50Hz) and Quanterra Q-380 digitizer at 20sps. Power rolloff at Nyquist~10Hz.

PVMO

Mw

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique• Detection System Applications

– Regional Network Evaluation– Maintenance Prioritization– ANSS Network Design

• ANSS Network Design Recommendations

Satellite GR4

Satellite SM5

Detection Maps Used for Prioritization of Maintenance Issues

Mw

ANSS backbone distributed over 2 satellites to protect against total network outage.

Maintenance decisions could be made based on real-time changes in detection thresholds.

GR4 expected to die within 3 years.

Hughes states.“There will be a seamless transition to a new satellite…”

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique• Detection System Applications

– Regional Network Evaluation– Maintenance Prioritization– ANSS Network Design

• ANSS Network Design Recommendations

SNSD

SNSD

ANSS Site Location Planning

PDF noise baselines used to estimate noise characteristics in regions without existing ANSS stations.

Interpolate from nearby stations with known noise baselines.

With noise baseline estimates we can calculate detection thresholds for new network configurations.

ANSS Site Location Planning

Mw

22 planned ANSS backbone stations added to simulate future detection capabilities.

Mw threshold lowered in regions with sparse station coverage such as the northern midwest and Texas.

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique• Detection System Applications

– Regional Network Evaluation– Maintenance Prioritization– ANSS Network Design

• ANSS Network Design Recommendations– Lower station noise thresholds– Supplement backbone with regional stations– Install Planned ANSS stations– Recording system limitations

Supplement with Regional Broadbands

Decrease Station Noise Levels

Install Planned ANSS Stations

Mw

ANSS Network Design Recommendations

Based on detection work, we can lower detection thresholds across US.

Minimum saturation occurs at Mw~2.2-2.5 despite network improvements.

80th Percentile Noise Level, Brune Mw

Topics• ANSS Backbone Probabilistic Noise Analysis• Noise Based Detection Technique• Detection System Applications

– Regional Network Evaluation– Maintenance Prioritization– ANSS Network Design

• ANSS Network Design Recommendations– Lower station noise thresholds– Supplement backbone with regional stations– Install Planned ANSS stations– Recording system limitations

NEIC AutopickerShort-period Filter(0.75-12Hz) Brune Model

Source SpectrumMw=3.0 fc=11Hz

Brune Model Source SpectrumMw=2.5 fc=20Hz

Brune Model Source SpectrumMw=2.0 fc=35Hz

NEIC Short Period Filter Limitations

Higher frequencies required to record full amplitudes of smaller earthquakes.

Recommendations:

1. Get rid of SP filter.

2. Increase sampling rate.

Detection Simulation with NEIC Filters RemovedMw

Mw Thresholds lowered significantly across US with the removal of NEIC Short period filter and sampling rateincreased to 200 sps.

Noise levels projected to higher frequencies.

At 200sps fny~100HzMw=2.0 fc=35HzMw=1.5 fc=62HzMw=1.0 fc=111Hz

Difficulties:

Short period filters reduce false triggers.

New picker would need filters to deal with false triggerswhile allowing high frequencies through for small events.

Conclusions

• Detection System Useful for Several Applications– Regional Network Evaluation– Maintenance Prioritization– ANSS Network Design

• ANSS Network Design Recommendations– Lower station noise thresholds– Supplement backbone with regional stations– Install Planned ANSS stations– Record higher frequencies