Automatic detection and Automatic detection and location of microseismic location of microseismic events events Tomas Fischer

OutlineOutlineWhy automaticHow automaticErrors West Bohemia swarm 2000Hydraulic stimulation in gas field

in Texas

Why automatic Why automatic processing?processing?Huge datasetsImprove productivityImprove data homogeneityReal time processing – alarms

Utilization of automatic Utilization of automatic processingprocessingMeasurement of arrival times Measurement of amplitudesPhase-waveform extraction

Hypocentre locationSource parameters, focal mechanismsSeismic tomographyAttenuation studies…

ApproachesApproachesClassical - stepwise:

(single station / network)1. Phase detection & picking2. Hypocentre location

Simultaneous (seismic network)– source scanning / back-propagation(Kao & Shan, 2003; Drew 2005)

Classical approach – stepsClassical approach – stepsPhase detection – increased

signal energy, single station

Phase association – consistency betw. stations

Phase picking – identify phase onset

Location of hypocenters

Phase detectionPhase detectionTransform 3C seismogram to a

scalar > 0, characteristic function CF (Allen, 1978)

Find maxima of CF S-wave energy detector

ENZ

–maximum eigenvalue of signal

covariance matrix

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Σnini Σniei

Σniei Σeiei

⎛ ⎝ ⎜

⎞ ⎠ ⎟

in a running window

Distinguishing P and S-Distinguishing P and S-waveswavesHierarchic approach First find S-waves (higher amplitude, horiz.

polarization) Then find P-waves (perpendicular

polarization)

Distinguishing P and S-Distinguishing P and S-waveswavesEqual approach

evaluate horiz. & vert. polarization find consecutive intervals of perpendicular

polarization (ampl. ratio or hor/vert gives hint to which one is P and S)

Phase associationPhase associationSimple kinematic (geometric) criteria

e.g. t2 < t1+t12

A-priori information on source position- plane wave consistency

Preliminary location- test the phase consistency by location residual

1 2

Source

Phase pickingPhase pickingFind onset – abrupt

amplitude increaseSTA/LTA

(non-overlapping)

Higher statistic momentsKurtosis

Waveform cross-correlationSTA/LTA

Kurtosis

Horiz. Polarization

€

S4 =x i − X ( )

4

i=1

N

∑Nσ 4

Automatic locationAutomatic locationNo special needs (each location

algorithm is automatic)Hydrocarbon reservoir stimulations

– linear array of receivers – besides arrival times also backazimuth (polarization) needed => modify the location algorithm to include also the fit to the polarization data

Event locationEvent location2D array (Earth surface)

– P-waves sufficient (S-waves beneficial)

1

2

3

4 t1-t2

t3-t4

t2-t3

Event locationEvent location

depth1

2

3

4

5

t1>t2>t3=t4<t5

1

Map viewDepth

view

1D array (borehole)both P and S-waves needed

GoodnessGoodnessPicking success

◦Amplitude ratio @ pick◦Location residual

Location success◦Location residual◦Sharpness of foci image ?! Location residual – results from

◦ Unknown structure◦ Timing errors◦ Picking errors (Gaussian & gross)=> Residual is not a unique measure of

picking success

Location residual calibration Location residual calibration (remove gross errors)(remove gross errors)Training dataset – if manual

processing availableLoc. error:

difference between manual and automaticlocations

6 samples

Location residual calibration Location residual calibration (remove gross errors)(remove gross errors)Dataset to be processed

Limit for choice of good locations

Swarm 2000 in West Swarm 2000 in West BohemiaBohemia

4 SP stations

0-20 km epicentral distance

synchronous triggered recording

Swarm 2000 Automatic Swarm 2000 Automatic processingprocessingCharacteristic functionS: maximum eigenvalue of the covariance matrix in

horizontal plane (Magotra et al., 1987)

P: sum of the Z-comp. and its derivative (Allen, 1978)

Method1. S-waves, minimum interval>maximum expected tS-tP2. P-waves in a fixed time window prior to S3. Only complete P and S pairs processed

=> homogeneous dataset

)()( tzKtzCFP

2

4 22neeenneenn

neSCF

Swarm 2000 in West Swarm 2000 in West BohemiaBohemiaResulting automatic picks

Swarm 2000 in West Swarm 2000 in West BohemiaBohemia>7000 detected events, 4500 well located

Homogeneous catalog downto ML=0.4Location error: ±100 m horiz. and ±200 m vert. 24.4 .2001

psonset9.pas - N KC m aster(psons22.txt)

- 1 0 1 2 3M l

1

10

100

1000

10000

NAll events

R M S<8 sm pl

0 10 20 30 40 50residuum lokace, sm pl.

0

1000

2000

3000

4000

5000

6000

7000

N

-600 -400 -200 0 200 400 600m eters

0

40

80

120

160ev

ents

-600 -400 -200 0 200 400 600m eters

Difference between manually and automately

obtained hypocentre locations

E-W coo., stdev 77 m

N-S coo., stdev 127 m

depth, stdev 127 m

-0.10 0.00 0.10 0.20 0.30 0.40secs

origin tim e, stdev 38 m s

Swarm Nový Kostel 2000

Automatic locations with RMS<8 smpl.Automatic locations with RMS<8 smpl.compared with 405 manually located eventscompared with 405 manually located events

P1 a P2

1 2 3 4 5 6+7 8 9

Automatic locations of the 2000 swarm

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas field

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas field

8 3C geophonescontinuous recording

Hydraulic stimulation in gas Hydraulic stimulation in gas fieldfieldS-wave picker Get the maximum eigenvalue tof the signal

covariance matrix

Find maxima of polarized energy

arriving at consistent delays j to vertical array (derived from expected slowness)

• Identify the S-wave onsets tS by STA/LTA detector in a short time window preceding the maxima of L(t)

• Measure S-wave backazimuth

• Array compatibility check by fitting hodochrone tS(z) by parabola, outliers repicked or removed

j

jj ttL

Hydraulic stimulation in gas Hydraulic stimulation in gas fieldfieldP-wave picker• Search for signal s polarized in S-ray direction p.

We use the characteristic function

• Find maxima of P-wave polarized energy Cp(t) arriving at consistent slowness (similar as in S-wave detection)

• Identify the P-wave onsets tP by STA/LTA detector in a short time window preceding the maxima of Cp(t)

• Measure the P-wave backazimuth

• Use Wadati’s relation to remove tP outliers

ssps ...Pc

€

tS − tP = tS α − β( ) /β

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas field

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas field

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas field

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas field

Hydraulic stimulation in Hydraulic stimulation in gas fieldgas fieldComparison of manual and auto picks

for 296 manually picked events

Fig. 3. Distribution of time differences between automatically and manualy obtained arrival times of test dataset.

PS

Comparison of manual and auto Comparison of manual and auto locationslocations

ConclusionsConclusionsautomatic processing useful in case of

huge datasets & provides homogeneous results

two approaches◦classic – mimics human interpreter◦modern – direct search for the hypocentre

classic – network consistency beneficial

two case studies show successful implementation of polarization based picker

OutlinesOutlinesuse waveform cross-correlation

for picking