Optimized passive seismic interferometry for bedrock detection: A Singapore case study
Yunhuo Zhang1,2, Yunyue Elita Li1, Heng Zhang3 and Taeseo Ku1
1 National University of Singapore, 2 Land Transport Authority,
3Chinese Academy of Sciences, Institute of Tibetan Plateau Research16 Oct 2018
1
Objective – bedrock detection
http://adeptconstruction.solutions/kvc-pile-geotechnical-parameters/
Bedrock detection is a common and criticalobjective in various Civil Engineeringdevelopments, despite onshore oroffshore.
Source: Straits Times2
Geology map of Singapore
Source: Defence Science and Technology Authority Singapore, (2009)
• Presence of igneous andsedimentary formations
• Top of bedrock variesfrom a few meters to50m below groundsurface.
3
Current Challenges
https://www.kwangsing.com.sg/images/services/big/11438935175.jpg
Conventional site investigation --drilling boreholes
• Require an area allowable to drill. • Take times (2 weeks or longer).
Early developed geophysical survey
• Sometimes not accurate• Constrains due to active source• Large footprint and long
duration (passive) 4
Specific Aim:
1. Seek a passive alternative to detect the bedrock as accurate asdrilling a borehole.
2. Optimize acquisition to ease implementation (smaller footprint,shorter acquisition duration).
5
Seismic Interferometry – turning a receiver to a virtual source
6
Geophone A Geophone BImpulsive Source
Geophone A Geophone BImpulsive Source Virtual Source A’
Testing Site
Site Location
Array Configuration
Acquisition parameters:• 4.5 Hz geophone• 30m/40m array length• 30 mins duration• 3 L-shape arrays acquired at different time
7
Raw signal
8
Normalized the average power spectraAmbient noise recorded from Blue Array
Direction of arrival of ambient noise –Beam forming
Coherent semblance: • Plane wave direction (0 - 360)• Plane wave speed (100 – 1200 m/s)
Synthetic data
10
#1#6
#11
C=500 m/s
Θ=0 ⁰
Coherent semblance
Synthetic data
11
#1#6
#11
C=800 m/s
Θ=60 ⁰
Coherent semblance
Field data
12
Blue Array
Red Array
Yellow Array
5 Hz 6 Hz 7 Hz 10 Hz
-1 0 1
Time lag (s)
0
2
4
6
Rec
eive
r num
ber
13
Greens’ function
0 10 20 30
Time (s)
0
2
4
6
Rece
iver n
umbe
r
-1 0 1
Time lag (s)
0
2
4
6
Rec
eive
r num
ber
𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴 = 𝑢𝑢 𝑟𝑟𝐴𝐴, 𝑠𝑠 𝑢𝑢′(𝑟𝑟𝐴𝐴,𝑠𝑠) 𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴 = 𝑢𝑢 𝑟𝑟𝐴𝐴,𝑠𝑠 𝑢𝑢′(𝑟𝑟𝐵𝐵,𝑠𝑠)
|𝑢𝑢 𝑟𝑟𝐴𝐴,𝑠𝑠 |^2
14
Phase velocity maps
5 10 15 20
Frequency (Hz)
200
400
600
800
1000
1200
Phas
e Ve
loci
ty(m
/s)
5 10 15 20
Frequency (Hz)
200
400
600
800
1000
1200
Phas
e Ve
loci
ty(m
/s)
by crosscorrelation by crosscoherence
1D shear wave velocity profile bedrock prediction
15
Inferred Bedrock
Actual Bedrock
Backfill (Very soft to soft soil)Residual Soil (Firm soil)Completely weathered granite (Firm to stiff soil)Highly weathered granite (stiff soil)Moderately weathered granite (moderate strong rock)Moderately weathered granite (strong to very strong rock)
Specific Aim:
1. Seek a passive alternative to detect the bedrock as accurate asdrilling a borehole.
2. Optimize acquisition to ease implementation (smaller footprint,shorter acquisition duration).
16
30 80 150 300 600 900 1200 1500
Duration (s)
2
4
6
8
10
12
14
MA
PE
(%)
Optimal acquisition duration
17
Mean Absolute Percentage Error(MAPE)
𝐶𝐶0: reference dispersion curve𝐶𝐶𝑖𝑖: ith dispersion curve
Various length of data
Entire recorded data
𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 =100𝑛𝑛
�1
𝑛𝑛
|𝐶𝐶0 − 𝐶𝐶𝑖𝑖𝐶𝐶0
|
15minutes are optimal and sufficient to derive a accurate and stable dispersion curve.
Optimal acquisition array length
18
0 5 10 15 20 25 30
Frequency (Hz)
0
0.5
1
1.5
Am
plitu
de (d
B)
Blue Array
Red Array
Yellow Array
Synthetic signal by wave equation:
Optimal acquisition array length
12m
19
30m 60m
20
30m Array
Optimal acquisition array length
30m long array is optimal and sufficient to derive a accurate and stable dispersion curve.
Specific Aim:
1. Seek a passive alternative to detect the bedrock as accurate asdrilling a borehole.
2. Optimize acquisition to ease implementation (smaller footprint,shorter acquisition duration).
21
Thank you
22