Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

Noise Reduction of Seismic Signal via Empirical Mode Decomposition

Authors
Baotong Liu
Corresponding Author
Baotong Liu
Available Online May 2015.
DOI
https://doi.org/10.2991/asei-15.2015.4How to use a DOI?
Keywords
Seismic signal, Denoising, Predictive filter, Intrinsic mode.
Abstract

This paper developed a denoising method termed f-x empirical-mode decomposition (EMD) predictive filtering. In this new method, we first applied EMD to each frequency slice in the f-x domain and obtained several intrinsic mode functions (IMFs). Then, an autoregressive model was applied to the sum of the first few IMFs to predict the useful steeper events. Finally, the predicted events were added to the sum of the remaining IMFs. This process improved the prediction precision by using an EMD-based dip filter to reduce the dip components before f-x predictive filtering. A synthetic data example is provided to show the performance of presented method.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
10.2991/asei-15.2015.4
ISSN
2352-5401
DOI
https://doi.org/10.2991/asei-15.2015.4How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Baotong Liu
PY  - 2015/05
DA  - 2015/05
TI  - Noise Reduction of Seismic Signal via Empirical Mode Decomposition
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 16
EP  - 19
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.4
DO  - https://doi.org/10.2991/asei-15.2015.4
ID  - Liu2015/05
ER  -