3d tem-ip inversion workflow for galvanic source tem data · a1 a2 a3 a4 a1 a2 a3 a4 measure...
TRANSCRIPT
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1/332016 IP workshop
The University of British Columbia
Geophysical Inversion Facility
gif.eos.ubc.ca
Seogi Kang and Douglas W. Oldenburg
3D TEM-IP inversion workflow for
galvanic source TEM data
IP workshop 2016
6th June 2016
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2/332016 IP workshop
Conceptual model for IP response
Air
Earth
v
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3/332016 IP workshop
Air
Earth
v
EM coupling?
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4/332016 IP workshop
• Measured voltage includes both EM and IP
effects
– How are we recovering conductivity and
chargeability?
– Are we okay with EM-contamination when
recovering chargeability?
Questions?
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5/332016 IP workshop
• Maxwell’s equations:
Simulation of TEM data
Ohm’s law in frequency domain Ohm’s law in time domain
Frequency domain Time domain
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6/332016 IP workshop
• Cole-Cole model (Pelton et al., 1978)
Complex conductivity
Inverse Fourier
transform
Frequency domain Time domain
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7/332016 IP workshop
• Maxwell’s equations:
Simulation of TEM data with IP
Ohm’s law in frequency domain Ohm’s law in time domain
Frequency domain Time domain
EMTDIP code
(Marchant et al., 2015)
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Observed response?
• Voltage
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9/332016 IP workshop
Observed response?
• Voltage
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10/332016 IP workshop
Define IP datum
Observation
FundamentalIP = Observation - Fundamental
• IP datum:
• Voltage
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11/332016 IP workshop
Define IP datum
Observation
FundamentalIP = Observation - Fundamental
• IP datum:
• Voltage
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12/332016 IP workshop
• Oldenburg and Li (1994)
Two stage IP inversion workflow
Invert DC data,
to recover
Linearized equations
Invert data,
recover pseudo-chargeability Seigel (1959)
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13/332016 IP workshop
• Kang and Oldenburg (2015)
Invert TEM data,
to recover
Invert data,
recover pseudo-chargeability
Linearized equations
Compute IP datum
Remove EM responses
Estimate intrinsic
IP parameters
IP = Observation - Fundamental
3D TEM-IP inversion workflow
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14/332016 IP workshop
• Decouple EM induction effects in the
observed data
– What conductivity?
• Half-space
• Recovered by inverting DC data,
• Recovered by inverting TEM data
• Invert IP datum, recover 3D chargeability
An objective
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15/332016 IP workshop
Forward modelling set up
A1 A2
A3 A4
A1 A2
A3 A4
Measure potential difference (Easting direction)
- 200 m bi-pole (625 mid points)
Time range: 1 – 600 ms
Chargeable objects: A2 and A3
- Cole-Cole parameters:
3D mesh:- Core cells:
100mx100mx50m
100mx100mx100m
- # of cells:
52x52x55
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16/332016 IP workshop
Forward modelling set up
A1 A2
A3 A4
Conductivity at
Infinite frequency:
A1 A2
A3 A4
Measure potential difference (Easting direction)
- 200 m bi-pole (625 mid points)
Time range: 1 – 600 ms
Chargeable objects: A2 and A3
- Cole-Cole parameters:
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17/332016 IP workshop
Observed DC data
Voltage Apparent conductivity
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18/332016 IP workshop
Observed data (off-time)
Off-time at 5 ms
• Decaying curves at A1-A4
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19/332016 IP workshop
Observed data (off-time)
Off-time at 80 ms
• Decaying curves at A1-A4
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20/332016 IP workshop
Observed data (off-time)
Off-time at 130 ms
• Decaying curves at A1-A4
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21/332016 IP workshop
Observed data (off-time)
Off-time at 650 ms
• Decaying curves at A1-A4
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22/332016 IP workshop
• Time decaying curves (off-time)
EM decoupling
IP = Observation - Fundamental
No hope Can make a
difference
No need to
do anything
EM
Induction
Intermediate
IP
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23/332016 IP workshop
• Off-time at 80 ms
EM decoupling: true
Observation Fundamental IP
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24/332016 IP workshop
• Off-time at 80 ms
EM decoupling: true
Observation Fundamental IP
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25/332016 IP workshop
What data we have?
Late on-time data (DC) Early off-time data (TEM)
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26/332016 IP workshop
• Data misfit:
• Tikhanov style regularization:
• Statement of the inversion:
• Depth weight:
3D inversion methodology
DC-IP inversion: SimPEG-DCIP
TEM inversion: UBC-H3DTD code
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27/332016 IP workshop
• Recover 3D conductivity
3D DC inversion
A1 A2
A3 A4
A1
A3 A4
True Estimated
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28/332016 IP workshop
• Off-time at 130 ms
EM decoupling:
Observation Predicted
True IP
Raw IP
Half-space
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29/332016 IP workshop
• Recover 3D conductivity
3D TEM inversion
EM
Induction
Intermediate
IP
Use uncontaminated EM data
Observed vs. Predicted
Time range: 1-6 ms
(6 channels) A1 A2
A3 A4
A1
A3 A4
Estimated
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30/332016 IP workshop
• Off-time at 80 ms
EM decoupling:
Observation Predicted
True IP
Raw IP
Half-spaceDC
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31/332016 IP workshop
• Recovered 3D conductivity
Comparison of 3D conductivities
True
A1 A2
A3 A4
A1
A3 A4
Estimated
A1 A2
A3 A4
A1
A3 A4
Estimated
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32/332016 IP workshop
• Fundamental data at 80 ms
Comparisons of Fundamental
Fundamental Half-space DC TEM
A3
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33/332016 IP workshop
• IP data at 80 ms
Comparisons of IP
True IP Half-space DC TEM
False chargeable target
Wrong amplitude
A3
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34/332016 IP workshop
• Chargeability: recovered by inverting:
3D IP inversion
A1 A2
A3 A4
A1
A3 A4
A1 A2
A3 A4
A1
A3 A4
A1 A2
A3 A4
A1
A3 A4
SimPEG-DCIP code
True Half-space
A1 A2
A3 A4
A1
A3 A4
DC TEM
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35/332016 IP workshop
• Pseudo-chargeability > 0.015
3D cut-off volume
A1 A2
A3
A1 A2
A3
A1 A2
A3
True Half-space
TEMDC
A1 A2
A3
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36/332016 IP workshop
Summary
Invert TEM data,
to recover
Invert data,
recover pseudo-chargeability
Linearized equations
Compute IP datum
Remove EM responses
Estimate intrinsic
IP parameters
3D-TEM IP inversion workflow
Observation Predicted Raw IP
dI Pr aw (t) = F [σ(t)] − F [σE M
est ] + noise(t)
A1 A2
A3
TEMDC
A1 A2
A3
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37/332016 IP workshop
“Traditionally, early time TEM data has been discarded”
“By using these discarded TEM signals we can better
estimate both 3D conductivity and chargeability”
Take home
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38/332016 IP workshop
Thank you
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39/332016 IP workshop
• Special thanks to
– SimPEG developers for utility codes to make
this study, and constructive discussions
– SimPEG-DCIP package for DC-IP inversions
– UBC-GIF for allowing us to use H3DTD codes
– Patrick Belliveau and Eldad Haber for
developing time domain IP code
Acknowledgements