Statistical Inference of Sound Speed and Attenuation Dispersion of a Fine-Grained Marine Sediment
Acoustic recordings of signals in the 1.5-4.0-kHz band were analyzed for information about the sound speed and attenuation frequency dispersion of a fine-grained sediment found in the New England Mudpatch. Analysis of piston cores established prior bounds for a geophysical parameterization of a seab...
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| Veröffentlicht in: | IEEE journal of oceanic engineering 2022-07, Vol.47 (3), p.553-564 |
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| creator | Knobles, David Paul Escobar-Amado, Christian D. Buckingham, Michael J. Hodgkiss, William S. Wilson, Preston S. Neilsen, Tracianne B. Yang, Jie Badiey, Mohsen |
| description | Acoustic recordings of signals in the 1.5-4.0-kHz band were analyzed for information about the sound speed and attenuation frequency dispersion of a fine-grained sediment found in the New England Mudpatch. Analysis of piston cores established prior bounds for a geophysical parameterization of a seabed model that predicts Kramers-Kronig dispersion relations. Sediment layers are described by the Buckingham viscous grain shearing (VGS) model that accounts for the effects of overburden pressure of compressional and shear speeds and attenuations. A statistical inverse problem was solved by using multiple samples of received levels recorded on two vertical line arrays as a function time and hydrophone depth for six frequencies in the 1.5-4.0-kHz band. A statistical inference model that assumed both model parameters and data samples are random variables quantified information content from marginalization of a conditional posterior probability distribution for the geophysical parameters that characterize the mud layer. From the inferred geophysical parameter point estimates the sediment sound speed and attenuation frequency dispersion are predicted and compared to previously reported direct measurements. Also, the predicted sound-speed gradient in the mud sediment from the VGS model is compared to a previous inference that utilized explosive sources. |
| doi_str_mv | 10.1109/JOE.2021.3091846 |
| format | Article |
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Analysis of piston cores established prior bounds for a geophysical parameterization of a seabed model that predicts Kramers-Kronig dispersion relations. Sediment layers are described by the Buckingham viscous grain shearing (VGS) model that accounts for the effects of overburden pressure of compressional and shear speeds and attenuations. A statistical inverse problem was solved by using multiple samples of received levels recorded on two vertical line arrays as a function time and hydrophone depth for six frequencies in the 1.5-4.0-kHz band. A statistical inference model that assumed both model parameters and data samples are random variables quantified information content from marginalization of a conditional posterior probability distribution for the geophysical parameters that characterize the mud layer. From the inferred geophysical parameter point estimates the sediment sound speed and attenuation frequency dispersion are predicted and compared to previously reported direct measurements. Also, the predicted sound-speed gradient in the mud sediment from the VGS model is compared to a previous inference that utilized explosive sources.</description><identifier>ISSN: 0364-9059</identifier><identifier>EISSN: 1558-1691</identifier><identifier>DOI: 10.1109/JOE.2021.3091846</identifier><identifier>CODEN: IJOEDY</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Acoustics ; Attenuation ; Conditional probability ; Data ensemble maximum entropy (DEME) ; Dispersion ; frequency dispersion ; Frequency measurement ; Geophysics ; Hydrophones ; Inverse problems ; Marine sediments ; Mathematical model ; Mathematical models ; Mud ; Ocean floor ; Parameter estimation ; Parameterization ; Parameters ; Pressure effects ; Probability distribution ; Probability theory ; Random variables ; Samples ; Sea measurements ; seabed geophysical parameters ; Sediment ; Sediments ; Shearing ; Sound ; Sound velocity ; Statistical analysis ; Statistical inference</subject><ispartof>IEEE journal of oceanic engineering, 2022-07, Vol.47 (3), p.553-564</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-cd946f5ca89e802a16919a0d9e4d0685c6f63943307c9607e4ffdbe6786fb3483</citedby><cites>FETCH-LOGICAL-c291t-cd946f5ca89e802a16919a0d9e4d0685c6f63943307c9607e4ffdbe6786fb3483</cites><orcidid>0000-0001-8555-742X ; 0000-0002-7699-0202 ; 0000-0002-9729-373X ; 0000-0001-9481-1362 ; 0000-0002-4420-7180 ; 0000-0003-2907-7311</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9515024$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9515024$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Knobles, David Paul</creatorcontrib><creatorcontrib>Escobar-Amado, Christian D.</creatorcontrib><creatorcontrib>Buckingham, Michael J.</creatorcontrib><creatorcontrib>Hodgkiss, William S.</creatorcontrib><creatorcontrib>Wilson, Preston S.</creatorcontrib><creatorcontrib>Neilsen, Tracianne B.</creatorcontrib><creatorcontrib>Yang, Jie</creatorcontrib><creatorcontrib>Badiey, Mohsen</creatorcontrib><title>Statistical Inference of Sound Speed and Attenuation Dispersion of a Fine-Grained Marine Sediment</title><title>IEEE journal of oceanic engineering</title><addtitle>JOE</addtitle><description>Acoustic recordings of signals in the 1.5-4.0-kHz band were analyzed for information about the sound speed and attenuation frequency dispersion of a fine-grained sediment found in the New England Mudpatch. Analysis of piston cores established prior bounds for a geophysical parameterization of a seabed model that predicts Kramers-Kronig dispersion relations. Sediment layers are described by the Buckingham viscous grain shearing (VGS) model that accounts for the effects of overburden pressure of compressional and shear speeds and attenuations. A statistical inverse problem was solved by using multiple samples of received levels recorded on two vertical line arrays as a function time and hydrophone depth for six frequencies in the 1.5-4.0-kHz band. A statistical inference model that assumed both model parameters and data samples are random variables quantified information content from marginalization of a conditional posterior probability distribution for the geophysical parameters that characterize the mud layer. From the inferred geophysical parameter point estimates the sediment sound speed and attenuation frequency dispersion are predicted and compared to previously reported direct measurements. Also, the predicted sound-speed gradient in the mud sediment from the VGS model is compared to a previous inference that utilized explosive sources.</description><subject>Acoustics</subject><subject>Attenuation</subject><subject>Conditional probability</subject><subject>Data ensemble maximum entropy (DEME)</subject><subject>Dispersion</subject><subject>frequency dispersion</subject><subject>Frequency measurement</subject><subject>Geophysics</subject><subject>Hydrophones</subject><subject>Inverse problems</subject><subject>Marine sediments</subject><subject>Mathematical model</subject><subject>Mathematical models</subject><subject>Mud</subject><subject>Ocean floor</subject><subject>Parameter estimation</subject><subject>Parameterization</subject><subject>Parameters</subject><subject>Pressure effects</subject><subject>Probability distribution</subject><subject>Probability theory</subject><subject>Random variables</subject><subject>Samples</subject><subject>Sea measurements</subject><subject>seabed geophysical parameters</subject><subject>Sediment</subject><subject>Sediments</subject><subject>Shearing</subject><subject>Sound</subject><subject>Sound velocity</subject><subject>Statistical analysis</subject><subject>Statistical inference</subject><issn>0364-9059</issn><issn>1558-1691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kDFPwzAQRi0EEqWwI7FYYk45x45rj1WhpaioQ2COXOcspWqdYDsD_55ErZi-G953d3qEPDKYMQb65WP3NsshZzMOmikhr8iEFYXKmNTsmkyAS5FpKPQtuYvxAMCEmOsJMWUyqYmpseZIN95hQG-Rto6Wbe9rWnaINTXDtEgJfT_AraevTewwxHEcSENXjcdsHcwQNf00YUhaYt2c0Kd7cuPMMeLDJafke_X2tXzPtrv1ZrnYZjbXLGW21kK6whqlUUFuxr-1gVqjqEGqwkonuRacw9xqCXMUztV7lHMl3Z4Lxafk-by3C-1PjzFVh7YPfjhZ5VIpqfMCRgrOlA1tjAFd1YXmZMJvxaAaRVaDyGoUWV1EDpWnc6VBxH9cF6yAXPA_ERxuSA</recordid><startdate>202207</startdate><enddate>202207</enddate><creator>Knobles, David Paul</creator><creator>Escobar-Amado, Christian D.</creator><creator>Buckingham, Michael J.</creator><creator>Hodgkiss, William S.</creator><creator>Wilson, Preston S.</creator><creator>Neilsen, Tracianne B.</creator><creator>Yang, Jie</creator><creator>Badiey, Mohsen</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Analysis of piston cores established prior bounds for a geophysical parameterization of a seabed model that predicts Kramers-Kronig dispersion relations. Sediment layers are described by the Buckingham viscous grain shearing (VGS) model that accounts for the effects of overburden pressure of compressional and shear speeds and attenuations. A statistical inverse problem was solved by using multiple samples of received levels recorded on two vertical line arrays as a function time and hydrophone depth for six frequencies in the 1.5-4.0-kHz band. A statistical inference model that assumed both model parameters and data samples are random variables quantified information content from marginalization of a conditional posterior probability distribution for the geophysical parameters that characterize the mud layer. 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| subjects | Acoustics Attenuation Conditional probability Data ensemble maximum entropy (DEME) Dispersion frequency dispersion Frequency measurement Geophysics Hydrophones Inverse problems Marine sediments Mathematical model Mathematical models Mud Ocean floor Parameter estimation Parameterization Parameters Pressure effects Probability distribution Probability theory Random variables Samples Sea measurements seabed geophysical parameters Sediment Sediments Shearing Sound Sound velocity Statistical analysis Statistical inference |
| title | Statistical Inference of Sound Speed and Attenuation Dispersion of a Fine-Grained Marine Sediment |
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