Method for low frequency sound reflection coefficient measurements in a compact space

2019 ◽  
Vol 145 (3) ◽  
pp. 1882-1882
Author(s):  
Xiuyuan Peng ◽  
Junfei Li ◽  
Chen Shen ◽  
Kiegan Lenihan ◽  
Steven Cummer
Keyword(s):  
Reflection Coefficient ◽  
Compact Space ◽  
Low Frequency ◽  
Frequency Sound ◽  
Sound Reflection

scholarly journals Low-Frequency Expansion Approach for Seismic Data Based on Compressed Sensing in Low SNR

2021 ◽  
Vol 11 (11) ◽  
pp. 5028
Author(s):  
Miaomiao Sun ◽  
Zhenchun Li ◽  
Yanli Liu ◽  
Jiao Wang ◽  
Yufei Su
Keyword(s):  
Reflection Coefficient ◽  
Compressed Sensing ◽  
Objective Function ◽  
Low Frequency ◽  
Original Data ◽  
Seismic Exploration ◽  
High Signal ◽  
Inversion Process ◽  
Frequency Information ◽  
Low Snr

Low-frequency information can reflect the basic trend of a formation, enhance the accuracy of velocity analysis and improve the imaging accuracy of deep structures in seismic exploration. However, the low-frequency information obtained by the conventional seismic acquisition method is seriously polluted by noise, which will be further lost in processing. Compressed sensing (CS) theory is used to exploit the sparsity of the reflection coefficient in the frequency domain to expand the low-frequency components reasonably, thus improving the data quality. However, the conventional CS method is greatly affected by noise, and the effective expansion of low-frequency information can only be realized in the case of a high signal-to-noise ratio (SNR). In this paper, well information is introduced into the objective function to constrain the inversion process of the estimated reflection coefficient, and then, the low-frequency component of the original data is expanded by extracting the low-frequency information of the reflection coefficient. It has been proved by model tests and actual data processing results that the objective function of estimating the reflection coefficient constrained by well logging data based on CS theory can improve the anti-noise interference ability of the inversion process and expand the low-frequency information well in the case of a low SNR.

scholarly journals Study on broadband low-frequency sound insulation of multi-channel resonator acoustic metamaterials

AIP Advances ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 045321
Author(s):  
Chi Xu ◽  
Hui Guo ◽  
Yinghang Chen ◽  
Xiaori Dong ◽  
Hongling Ye ◽  
...  
Keyword(s):  
Low Frequency ◽  
Sound Insulation ◽  
Acoustic Metamaterials ◽  
Frequency Sound

Lightweight Low‐Frequency Sound‐Absorbing Composites of Graphene Network Reinforced by Honeycomb Structure

2021 ◽  
pp. 2100183
Author(s):  
Fan Xu ◽  
Siying Zhang ◽  
Guigen Wang ◽  
Daqiang Zhao ◽  
Junwei Feng ◽  
...  
Keyword(s):  
Low Frequency ◽  
Honeycomb Structure ◽  
Frequency Sound

Effects of low‐frequency sound (ATOC) on marine mammals: An experimental approach

1995 ◽  
Vol 97 (5) ◽  
pp. 3352-3352
Author(s):  
Daniel P. Costa ◽  
Dawn Goley ◽  
Danielle Waples ◽  
Don Croll ◽  
Burney Le Boeuf ◽  
...  
Keyword(s):  
Marine Mammals ◽  
Experimental Approach ◽  
Low Frequency ◽  
Frequency Sound
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