Shallow sea multilayer seabed geoacoustic parameter inversion method based on nonlinear Bayesian theory

A geoacoustic parameter and Bayesian technology, applied in seismology, seismology, multi-objective optimization, etc. in areas covered by water, can solve problems such as the uncertainty of inversion results, improve accuracy and The effect of resolution and small uncertainty

Pending Publication Date: 2021-01-01
ZHEJIANG OCEAN UNIV
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Problems solved by technology

Due to the inevitable existence of various errors in the measured data at sea, these factors will lead to certain uncertainties in the inversion results

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  • Shallow sea multilayer seabed geoacoustic parameter inversion method based on nonlinear Bayesian theory
  • Shallow sea multilayer seabed geoacoustic parameter inversion method based on nonlinear Bayesian theory
  • Shallow sea multilayer seabed geoacoustic parameter inversion method based on nonlinear Bayesian theory

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[0079] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. the embodiment. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0080] Such as figure 1 As shown, the present embodiment provides a shallow sea multi-layer submarine geoacoustic parameter inversion method, including: inverting the submarine geoacoustic parameters according to the nonlinear Bayesian inversion method; applying the sound pressure field as the research object, and then The Bayesian method is used to estimate the density of each laye...

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Abstract

The invention belongs to the technical field of geoacoustic parameter inversion, and particularly relates to a shallow sea multilayer seabed geoacoustic parameter inversion method based on a nonlinearBayesian theory, which comprises the following steps of: inverting seabed geoacoustic parameters according to a nonlinear Bayesian inversion method to accurately judge an actual seabed structure frommeasured data; adopting the correction simulated annealing algorithm, so that the accuracy and the discrimination degree of an inversion result can be improved; compared with two types of sound velocity attenuation and density, determining that the uncertainty of the longitudinal wave sound velocity and the transverse wave sound velocity is smaller; and compared with a semi-infinite substrate, determining that the uncertainty of each parameter in the deposition layer is smaller.

Description

technical field [0001] The invention belongs to the technical field of inversion of geoacoustic parameters, and in particular relates to a method for inversion of geoacoustic parameters in shallow sea and multi-layer seabed based on nonlinear Bayesian theory. Background technique [0002] Seabed geoacoustic parameters are one of the important parameters that make up the ocean's underwater acoustic environment. The acoustic parameters of the seabed, such as sound velocity, density, and sound velocity attenuation, have an important impact on sound propagation in the marine environment, especially in shallow sea environments. The degree of mastery of the above-mentioned submarine geoacoustic parameters will directly affect the prediction and evaluation of the performance of underwater acoustic equipment, the numerical prediction of the ocean acoustic field, and the utilization of the characteristics of the ocean acoustic field. How to obtain seabed geoacoustic parameter informa...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F17/18G01V1/30G01V1/38G06F111/06G06F111/08
CPCG06F30/27G06F17/18G01V1/38G01V1/303G01V1/306G06F2111/06G06F2111/08
Inventor 祝捍皓薛洋洋崔志强陈超王其乐肖瑞
Owner ZHEJIANG OCEAN UNIV
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