presentation chapter 3: seismic instrumentation
DESCRIPTION
TRANSCRIPT
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Overview ta3520Introduction to seismics
• Fourier Analysis• Basic principles of the Seismic Method• Interpretation of Raw Seismic Records• Seismic Instrumentation• Processing of Seismic Reflection Data• Vertical Seismic Profiles
Practical:• Processing practical (with MATLAB)
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Convolutional model of seismic data
In time domain, output is convolution of input and impulse responses
X(t) = S(t) * G(t) * R(t) * A(t)
where
X(t) = seismogramS(t) = source signal/waveletG(t) = impulse response of earthR(t) = impulse response of receiverA(t) = impulse response of recording-instrument
![Page 3: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/3.jpg)
Convolutional model of seismic data
In frequency domain, output is multiplication of spectra:
X(ω) = S(ω) G(ω) R(ω) A(ω)
where
X(ω) = seismogramS(ω) = source signal/waveletG(ω) = transfer function of earthR(ω) = transfer function of receiverA(ω) = transfer function of recording-instrument
(transfer function = spectrum of impulse response)
![Page 4: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/4.jpg)
Convolutional model of seismic data
In time domain, output is convolution of input and impulse responses
X(t) = S(t) * G(t) * R(t) * A(t)
where
X(t) = seismogramS(t) = source signal/waveletG(t) = impulse response of earthR(t) = impulse response of receiverA(t) = impulse response of recording-instrument
![Page 5: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/5.jpg)
Seismic Instrumentation
• Seismic sources:• Airguns• VibroSeis• Dynamite
• Seismic detectors:• Geophones• Hydrophones
• Seismic recording systems
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Seismic at sea
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Seismic at sea
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Seismic at sea
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Seismic at sea
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Seismic source at sea: Airgun
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Seismic source at sea: Airgun
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Seismic source at sea: Airgun
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Airgun: mechanical behaviour
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Seismic source on land: VibroSeis
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Seismic source on
land: VibroSeis
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Seismic source on
land: VibroSeis
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Seismic source on land: VibroSeis
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VibroSeis: simple mechanical model
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VibroSeis: mechanical model
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Source signals S(t): Vibrator source
Time domain
frequency domain
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Source signal: -pulse
Time domain Frequency domain
time
-pulse
0
frequency
amplitude
1
0
frequency
phase
00
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Source signal: band-limited -pulse
Time domain Frequency domain
time
band-limited -pulse
0
frequency
phase
0
frequency
amplitude
1
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Source signal: band-limited sweep(=VibroSeis)
Time domain Frequency domain
time
band-limited sweep
0
frequency
phase
0
frequency
amplitude
1
0
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Source signal: shifted -pulse
Time domain Frequency domain: exp(-2i f T)
frequency
amplitude
1
0
frequency
Phase= 2 f T
0
time
-pulse
0 T
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Source signals: Vibrator source
For sweep:Higher frequencies,later in time
So: 2 f Tnon-linear (more quadratic)
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Source signals: Vibrator source
Undoing effect source signal (phase and amplitude):deconvolution
Notice that numerator of stabilized deconvolution is correlation
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Source signals: Vibrator source
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Seismic source on land: dynamite
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Dynamite
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Dynamite
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Dynamite: model
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Source signals S(t): Dynamite
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Source signal: symmetrical signal
Time domain Frequency domain
time
symmetrical pulse
0
frequency
phase
0
frequency
amplitude
1
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symmetrical signal in time=
spectrum is purely real, sozero phase
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Source signal: causal signal(with causal inverse)
Time domain
time
Causal pulse(with causal inverse)
0
Causal signal =
Amplitude zero before zerotime
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Source signal: causal signal(with causal inverse)
Time domain Frequency domain
time
Causal pulse(with causal inverse)
0
frequency
phase
0
frequency
amplitude
1
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causal pulse with causal inverse in time
=phase spectrum is minimally going
through 2π, sominimum-phase
Minimum-phase pulse has most of its energy in the beginning
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Source signals S(t): Dynamite
Dynamite signal seen as minimum-phase signal
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Dynamite: spectrum
Frequency (Hz)
amp
litu
de
- 2
2
0
Frequency (Hz)P
has
e (r
ad)
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Convolutional model of seismic data
In time domain, output is convolution of input and impulse responses
X(t) = S(t) * G(t) * R(t) * A(t)
where
X(t) = seismogramS(t) = source signal/waveletG(t) = impulse response of earthR(t) = impulse response of receiverA(t) = impulse response of recording-instrument
![Page 41: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/41.jpg)
Impulse response of earth G(t)
Desired for processing
Still: undesired events need to be removed
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Convolutional model of seismic data
In time domain, output is convolution of input and impulse responses
X(t) = S(t) * G(t) * R(t) * A(t)
where
X(t) = seismogramS(t) = source signal/waveletG(t) = impulse response of earthR(t) = impulse response of receiverA(t) = impulse response of recording-instrument
![Page 43: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/43.jpg)
Seismic detector on land:geophone (velocity sensor)
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Seismic detector on land:
geophone
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Geophone
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Spectrum of geophone R(ω)
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Spectrum of geophone R(ω)
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Spectrum of geophone R(ω)
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Seismic detector at sea:hydrophone (pressure sensor)
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Hydrophone (pressure sensor)
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Hydrophones (pressure sensors)
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Hydrophone model:piezo-electricity
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Hydrophone: piezo-electric
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Hydrophone: piezo-electric
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Spectrum of hydrophone R(ω)
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Spectrum of hydrophone R(ω)
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Spectrum of hydrophone R(ω)
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Convolutional model of seismic data
In time domain, output is convolution of input and impulse responses
X(t) = S(t) * G(t) * R(t) * A(t)
where
X(t) = seismogramS(t) = source signal/waveletG(t) = impulse response of earthR(t) = impulse response of receiverA(t) = impulse response of recording-instrument
![Page 59: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/59.jpg)
On-board QC
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On-board QC
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Storage: IBM 3592 tapes (right-hand corner above)
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Seismic recording systems
Main tasks:
• Convert Analog signals to Digital signals
• Store data
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Recording Instrument
Sample data correctly:
Nyquist is determined by setting time-sampling interval Δt:
fNyquist = 1 / (2 Δt)
Then:
Cut high frequencies such that above fNyquist analog signal is damped below noise level
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Recording instrument A(ω): high-cut filter
Frequency domain
frequency
phase
0
frequency
amplitude
1
1/(2Δt)-1/(2Δt)
1/(2Δt)-1/(2Δt)
High-cut filter=
Anti-alias filter
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Total response of instrumentation
In frequency domain, output is multiplication of spectra:
X(ω) = S(ω) G(ω) R(ω) A(ω)
where
X(ω) = seismogramS(ω) = source signal/waveletG(ω) = transfer function of earthR(ω) = transfer function of receiverA(ω) = transfer function of recording-instrument
(transfer function = spectrum of impulse response)
![Page 66: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/66.jpg)
Total response of instrumentation
In frequency domain, output is multiplication of spectra:
X(ω) = S(ω) G(ω) R(ω) A(ω)
![Page 67: Presentation Chapter 3: Seismic Instrumentation](https://reader034.vdocument.in/reader034/viewer/2022052522/5537f890550346f53d8b4681/html5/thumbnails/67.jpg)
Total response of instrumentation
amplitude phase