Abstract
We present an algorithm which allows us to model wavefields with frequency-domain methods using a much smaller number of frequencies than that typically required by the classical sampling theory in order to obtain an alias-free result. The foundation of the algorithm is the recent results on the compressed sensing, which state that data can be successfully recovered from an incomplete measurement if the data is sufficiently sparse. Results from numerical experiment show that only 30%; of the total frequency spectrum is need to capture the full wavefield information when working in the hard 2D synthetic Marmousi model.
| Original language | English |
|---|---|
| Pages (from-to) | 2122-2126 |
| Number of pages | 5 |
| Journal | SEG Technical Program Expanded Abstracts |
| Volume | 27 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2008 |
| Externally published | Yes |
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Keywords
- Inversion
- Modeling
- Nonlinear
- Wave equation
- Wave propagation
ASJC Scopus subject areas
- Geophysics
- Geotechnical Engineering and Engineering Geology
Cite this
Interpolating solutions of the helmholtz equation with compressed sensing. / Lin, Tim T Y; Lebed, Evgeniy; Erlangga, Yogi A.; Herrmann, Felix J.
In: SEG Technical Program Expanded Abstracts, Vol. 27, No. 1, 01.2008, p. 2122-2126.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Interpolating solutions of the helmholtz equation with compressed sensing
AU - Lin, Tim T Y
AU - Lebed, Evgeniy
AU - Erlangga, Yogi A.
AU - Herrmann, Felix J.
PY - 2008/1
Y1 - 2008/1
N2 - We present an algorithm which allows us to model wavefields with frequency-domain methods using a much smaller number of frequencies than that typically required by the classical sampling theory in order to obtain an alias-free result. The foundation of the algorithm is the recent results on the compressed sensing, which state that data can be successfully recovered from an incomplete measurement if the data is sufficiently sparse. Results from numerical experiment show that only 30%; of the total frequency spectrum is need to capture the full wavefield information when working in the hard 2D synthetic Marmousi model.
AB - We present an algorithm which allows us to model wavefields with frequency-domain methods using a much smaller number of frequencies than that typically required by the classical sampling theory in order to obtain an alias-free result. The foundation of the algorithm is the recent results on the compressed sensing, which state that data can be successfully recovered from an incomplete measurement if the data is sufficiently sparse. Results from numerical experiment show that only 30%; of the total frequency spectrum is need to capture the full wavefield information when working in the hard 2D synthetic Marmousi model.
KW - Inversion
KW - Modeling
KW - Nonlinear
KW - Wave equation
KW - Wave propagation
UR - http://www.scopus.com/inward/record.url?scp=58049150444&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=58049150444&partnerID=8YFLogxK
U2 - 10.1190/1.3059307
DO - 10.1190/1.3059307
M3 - Article
AN - SCOPUS:58049150444
VL - 27
SP - 2122
EP - 2126
JO - SEG Technical Program Expanded Abstracts
JF - SEG Technical Program Expanded Abstracts
SN - 1052-3812
IS - 1
ER -