evelyn roelo s u. s. geological survey earthquake science center … · 2017. 2. 25. ·...
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Analyzing Borehole Strainmeter Data
Evelyn RoeloffsU. S. Geological Survey
Earthquake Science Center
March 28, 2016
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 1 / 26
1 Analyzing gauge elongation dataLong-term trendsAtmospheric pressureSeasonal signals
2 Non-ideal strainmetersVertical couplingNon-identical gauges
3 Calibrating BSMsCalibration matrices from coupling coefficientsOrientation corrections
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 2 / 26
Long-term gauge elongations: Examples
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 3 / 26
What causes long-term trends?
Drilling the borehole and installing the strainmeter creates a stressfield that varies around the borehole
BSM gauges measure localized formation creep caused by thesestresses
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 4 / 26
Long-term gauge elongations: Examples
During first weeks-months, trends are complex and non-monotonicas curing grout expands and gives off heatElongation time series typically approach non-zero steady ratesSeasonal signals are superimposed on long-term trends
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 5 / 26
Long-term gauge elongations: Removal
A function that can be fit to thegauge extension time series e(t)for many PBO BSMs is:e(t) = a+ bt+ c(t− t0)
p
where:t is time, t0 is a reference timea is an arbitrary reference valueb is a constant elongation ratep is an exponent with 0 < p < 1and usually 0.1 < p < 0.4
Seasonal signals remain afterremoving this function...
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 6 / 26
Atmospheric pressure response
Atmospheric pressure is a load on the earth’s surface
PBO BSMs all have some response to atmospheric pressure
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 7 / 26
PBO BSMs: Atmospheric pressure response coefficients
940 950 960 970 980 990
10/08/11 10/22/11 11/05/11 11/19/11 12/03/11 12/17/11 12/31/11
hPa
B003_PhPa_eo
0 2 4 6 8
10
milli
met
ers B003_RFmm
-0.15
0
0.15
mic
rost
rain
B003 CH3 cB003 CH3 c.tb
-0.15
0
0.2
mic
rost
rain
B003 CH2 cB003 CH2 c.tb
-0.3
0
0.5
mic
rost
rain
B003 CH1 cB003 CH1 c.tb
-0.1
0
0.1
mic
rost
rain
B003 CH0 cB003 CH0 c.tb
BSM gauges contract whenatmospheric pressure increases
Atmospheric pressure responsecoefficients differ among thefour gauges
Atmospheric pressure responsecoefficients are generally largerin the Pacific Northwest thanin California.
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 8 / 26
Atmospheric pressure time series: Examples
Check for and correct artificial offsets and/or drift
Atmospheric pressure contributes a seasonal variation
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 9 / 26
Seasonal variations in gauge data
Seasonal variations aretypically not the same onthe different gauges of aBSM
Measured parameters maycorrelate with seasonalvariations:
downhole temperatureatmospheric pressurepore pressuredepth of surface-waterbodies
Groundwater pumping thataffects strainmeters mayalso occur seasonally
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 10 / 26
Seasonal variations compared with slip-event signals
B012
B004
M6.4 Sept. 9 2011
B927
B009B010B011
B003B005B006B007
B018
B926
B928
B013B943
B017
B014?
?B001
Seasonal variations dwarf slip-event signals
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 11 / 26
Seasonal variations after removing atmospheric pressure
No pressure correction After pressure correction
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 12 / 26
Loading from individual rainfall events
940 950 960 970 980 990
10/08/11 10/22/11 11/05/11 11/19/11 12/03/11 12/17/11 12/31/11
hPa
B003_PhPa_eo
0 2 4 6 8
10
milli
met
ers B003_RFmm
-0.15
0
0.15
mic
rost
rain
B003 CH3 cB003 CH3 c.tb
-0.15
0
0.2
mic
rost
rain
B003 CH2 cB003 CH2 c.tb
-0.3
0
0.5
mic
rost
rain
B003 CH1 cB003 CH1 c.tb
-0.1
0
0.1
mic
rost
rain
B003 CH0 cB003 CH0 c.tb
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 13 / 26
Seasonal gauge elongations and GPS-derived seasonaldisplacements
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 14 / 26
Seasonal gauge elongations and downhole temperature
Peak extension on B003 CH3lags peak downholetemperature by about twomonths
Coefficient about 2.5microstrain/◦C
For comparison, coefficients ofthermal expansion:
Steel 9.9-17 microstrain/◦CConcrete 12 microstrain/◦C
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 15 / 26
Removing repeatable seasonal signals
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
10/1/10 10/1/11 10/1/12 10/1/13 10/1/14 10/1/15 10/1/16Date m/d/y
rela
tive
gaug
e ex
tens
ion
X10-6
B024 Daily averages, trend fit and subtracted
CH0 (N142E)
CH1(N82E) CH2
(N22E)
CH3(N172E)
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
10/1/10 10/1/11 10/1/12 10/1/13 10/1/14 10/1/15 10/1/16Date m/d/y
B024 Daily averages, trend fit and subtracted
rela
tive
gaug
e ex
tens
ion
X10-6
CH0 (N142E)
CH1(N82E)
CH2(N22E)
CH3(N172E)
-0.4
-0.2
0
0.2
0.4
0.6
10/1/10 10/1/11 10/1/12 10/1/13 10/1/14 10/1/15 10/1/16Date m/d/y
CH0 (N142E)
CH1(N82E)
CH2(N22E)
CH3(N172E)
rela
tive
gaug
e ex
tens
ion
X10-6
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 16 / 26
Evidence for vertical coupling: Large atmosphericpressure response
970 975 980 985 990 995
1000
02/06/16 02/13/16 02/20/16 02/27/16 03/05/16 03/12/16 03/19/16
hPa
B084_160205_160321_PhPa 0
0.5 1
1.5 2
2.5
mm B084_160205_160321_RFmm
-0.03-0.02-0.01
0 0.01 0.02 0.03 0.04 0.05
mic
rost
rain
B084 CH3 N 47.0E-0.02-0.01
0 0.01 0.02 0.03 0.04
mic
rost
rain
B084 CH2 N 77.0E-0.04-0.03-0.02-0.01
0 0.01 0.02 0.03 0.04 0.05 0.06
mic
rost
rain
B084 CH1 N137.0E-0.03-0.02-0.01
0 0.01 0.02 0.03 0.04
mic
rost
rain
B084 pinyon084bcs2006 33.6116 -116.45637B084 CH0 N 17.0E
990 995
1000 1005 1010 1015 1020
02/06/16 02/13/16 02/20/16 02/27/16 03/05/16 03/12/16 03/19/16
hPa
-1-0.5
0 0.5
1m
m B073_160205_160321_RFmm-0.06-0.04-0.02
0 0.02 0.04 0.06 0.08 0.1
0.12
mic
rost
rain
B073 CH3 N120.0E-0.06-0.04-0.02
0 0.02 0.04 0.06 0.08 0.1
0.12
mic
rost
rain
B073 CH2 N150.0E-0.1
-0.05 0
0.05 0.1
0.15
mic
rost
rain
B073 CH1 N 30.0E-0.1
-0.05 0
0.05 0.1
0.15 0.2
mic
rost
rain
B073 varian073bcs2006 35.9467 -120.4717B073 CH0 N 90.0E
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 17 / 26
More general coupling formulation
ei = Ci(εxixi + εyiyi) +Di(εxixi − εyiyi) + Fiεzz
Each gauge has its own coupling coefficientsCoupling to vertical strain is includedCoupling to 2εxiyi is probably unnecessary
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 18 / 26
Effect of the free surface
Strainmeter responds differently to a surface load than to a sourcefrom within the earth
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 19 / 26
Effect of vertical coupling on areal strain response
εzz = −ν1−ν (εxx+εyy) = −ν
1−ν (εxixi +εyiyi)
ei = [Ci − ν1−νFi](εxixi + εyiyi) +Di(εxixi − εyiyi)
Define an apparent areal strain coupling coefficient C̃i = [Ci − ν1−νFi]
ei = C̃i(εxixi + εyiyi) +Di(εxixi − εyiyi)
For sources much deeper than strainmeter:
Vertical coupling reduces apparent areal strain responseApparent areal strain response can even be negative
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 20 / 26
Coupling and calibration matrices
Coupling coefficients Ci, Di, and Fi (or C̃i) are estimated fromgauge response to ”known” strainsThe equations expressing the responses of all the gauges to strainin common (x, y) coordinates are assembled as rows of a ”couplingmatrix”, C, in which θi is angle of ei CCW from x:e0e1e2e3
=
C0 D0 cos 2θ0 D0 sin 2θ0C1 D1 cos 2θ1 D1 sin 2θ1C2 D2 cos 2θ2 D2 sin 2θ2C3 D3 cos 2θ3 D3 sin 2θ3
εxx + εyyεxx − εyy
2εxy
= C
εxx + εyyεxx − εyy
2εxy
The ”calibration matrix”, S, ”inverts” the coupling matrix toexpress the strains in terms of the gauge elongationsεxx + εyy
εxx − εyy2εxy
= S
e0e1e2e3
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 21 / 26
Calibration matrices
εxx + εyyεxx − εyy
2εxy
= S
e0e1e2e3
The ”calibration matrix”, S, depends on
Coordinate system (x, y)Gauge subset used (all 4, or any subset of 3)
For identical gauges, the coupling matrices for subsets of 3 gaugescan be inverted analytically to obtain calibration matrices
In general, the coupling matrices must be inverted numerically
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 22 / 26
Need for orientation corrections
-100
-50
0
50
4/13/09 5/3/09 5/23/09 6/12/09 7/2/09-150
-100
-50
0
50
100
nano
stra
in (D
=1.5
) nanostrain(D=1.14)
CH1=N118ºE
CH1=N108ºE(measured)
CH1=N98ºE
εxx−εyyDifferentialExtension
100
150
4/13/09 5/3/09 5/23/09 6/12/09 7/2/09-100
0
100
150
200
-50
0
50
nano
stra
in (D
=1.5
)
nanostrain(D=1.14)
CH1=N118ºE
CH1=N108ºE(measured)
CH1=N98ºE
2εxyEngineering
Shear
B004 shear strains for 2009Cascadia aseismic slip event
The strain tensor is afunction of π (not 2π)
Orientation error istwice as important as fordisplacement
PBO BSM measuredorientations may requirecorrection
Some orientations werenot measured atinstallation
see Hodgkinson et al.,JGR, 2012
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 23 / 26
Calibration Choices
Assume gauges are ideal and identical, but keep in mind:
areal strain may not be reliableshear strain coupling coefficient may not be knownstated orientation may not be corrected
Use tidal calibration and orientation correction that has alreadybeen done
Roeloffs JGR, 2010; Hodgkinson et al. JGR 2012not all BSMs attempted and not all of those attempted could becalibrated successfully
Use seismic calibration for Anza BSMs (Grant and Langston)
based on strains estimated from broadband seismic array
Try your own tidal or seismic calibration
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 24 / 26
Any questions?
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 25 / 26
Evelyn Roeloffs, USGS ESC Analyzing BSM Data March 28, 2016 26 / 26