Trans-dimensional joint inversion of seabed scattering and reflection data

This paper examines joint inversion of acoustic scattering and reflection data to resolve seabed interface roughness parameters (spectral strength, exponent, and cutoff) and geoacoustic profiles. Trans-dimensional (trans-D) Bayesian sampling is applied with both the number of sediment layers and the...

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Published in:	The Journal of the Acoustical Society of America Vol. 133; no. 3; pp. 1347 - 1357
Main Authors:	Steininger, Gavin, Dettmer, Jan, Dosso, Stan E, Holland, Charles W
Format:	Journal Article
Language:	English
Published:	United States 01-03-2013
Subjects:	Acoustics Bayes Theorem Geologic Sediments Markov Chains Models, Theoretical Motion Oceans and Seas Scattering, Radiation Signal Processing, Computer-Assisted Signal-To-Noise Ratio Sound Sound Spectrography Time Factors Water
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Abstract	This paper examines joint inversion of acoustic scattering and reflection data to resolve seabed interface roughness parameters (spectral strength, exponent, and cutoff) and geoacoustic profiles. Trans-dimensional (trans-D) Bayesian sampling is applied with both the number of sediment layers and the order (zeroth or first) of auto-regressive parameters in the error model treated as unknowns. A prior distribution that allows fluid sediment layers over an elastic basement in a trans-D inversion is derived and implemented. Three cases are considered: Scattering-only inversion, joint scattering and reflection inversion, and joint inversion with the trans-D auto-regressive error model. Including reflection data improves the resolution of scattering and geoacoustic parameters. The trans-D auto-regressive model further improves scattering resolution and correctly differentiates between strongly and weakly correlated residual errors.
AbstractList	This paper examines joint inversion of acoustic scattering and reflection data to resolve seabed interface roughness parameters (spectral strength, exponent, and cutoff) and geoacoustic profiles. Trans-dimensional (trans-D) Bayesian sampling is applied with both the number of sediment layers and the order (zeroth or first) of auto-regressive parameters in the error model treated as unknowns. A prior distribution that allows fluid sediment layers over an elastic basement in a trans-D inversion is derived and implemented. Three cases are considered: Scattering-only inversion, joint scattering and reflection inversion, and joint inversion with the trans-D auto-regressive error model. Including reflection data improves the resolution of scattering and geoacoustic parameters. The trans-D auto-regressive model further improves scattering resolution and correctly differentiates between strongly and weakly correlated residual errors.
Author	Dosso, Stan E Holland, Charles W Dettmer, Jan Steininger, Gavin
Author_xml	– sequence: 1 givenname: Gavin surname: Steininger fullname: Steininger, Gavin email: gsteinin@uvic.ca organization: School of Earth and Ocean Sciences, University of Victoria, Victoria, BC V8W 3P6, Canada. gsteinin@uvic.ca – sequence: 2 givenname: Jan surname: Dettmer fullname: Dettmer, Jan – sequence: 3 givenname: Stan E surname: Dosso fullname: Dosso, Stan E – sequence: 4 givenname: Charles W surname: Holland fullname: Holland, Charles W
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Title	Trans-dimensional joint inversion of seabed scattering and reflection data
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