Geoacoustic inversion for sediments in the South China Sea based on a hybrid inversion scheme

Li, Zhenglin; Li, Fenghua

doi:10.1007/s00343-010-9117-z

Cited by 23 publications

(6 citation statements)

References 20 publications

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“…It is based on the quantification of the influence of the bottom parameters on the sound propagation and makes possible the estimation of sediment parameters such as sound speed, density, and porosity. A variety of geoacoustic inversion methods have been developed in recent years using both active and passive sound sources [3,[24][25][26]. Active geoacoustic inversion methods are based on data acquisition using powerful, controlled sound sources [27], whereas passive geoacoustic inversion methods are based on using the ubiquitous ambient noise as a replacement for the active sound sources [28].…”

Section: Methods For Estimating the Sound Speed In The Seafloormentioning

confidence: 99%

Geoacoustic Estimation of the Seafloor Sound Speed Profile in Deep Passive Margin Setting Using Standard Multichannel Seismic Data

Uzhansky

Gadol

Lang

et al. 2021

JMSE

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Seafloor geoacoustic properties are important in determining sound propagation in the marine environment, which broadly affects sub-sea activities. However, geoacoustic investigation of the deep seafloor, which is required by the recent expansion of deep-water operations, is challenging. This paper presents a methodology for estimating the seafloor sound speed, c0, and a sub-bottom velocity gradient, K, in a relatively deep-water-compacting (~1000 m) passive-margin setting, based on standard commercial 2D seismic data. Here we study the seafloor of the southeastern Mediterranean margin based on data from three commercial seismic profiles, which were acquired using a 7.2 km-long horizontal receiver array. The estimation applies a geoacoustic inversion of the wide-angle reflections and the travel times of the head waves of bending rays. Under the assumption of a constant positive K, the geoacoustic inversion converges to a unique set of parameters that best satisfy the data. The analysis of 24 measurement locations revealed an increase in the average estimates of c0 from 1537 ± 13 m s−1 to 1613 ± 12 m s−1 for seafloor depths between ~1150 m and ~1350 m. K ranged between 0.75 and 0.85 m s−1 with an average of 0.80 ± 0.035 s−1. The parameters were consistent across the different locations and seismic lines and they match the values that were obtained through depth-migration-velocity analysis and empiric relations, thereby validating our estimation methodology.

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Section: Methods For Estimating the Sound Speed In The Seafloormentioning

confidence: 99%

Geoacoustic Estimation of the Seafloor Sound Speed Profile in Deep Passive Margin Setting Using Standard Multichannel Seismic Data

Uzhansky

Gadol

Lang

et al. 2021

JMSE

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“…Wu et al proposed a multiple-step TL inversion method to invert sound speed, density and attenuation in deep water environment [14]. Li et al inversed bottom parameters in a thermocline environment in the northern area of the South China Sea using the experiment data [15]. Zhang et al conducted the transverse horizontal spatial coherence of explosive signals in the northern area of South China Sea [16].…”

Section: Introductionmentioning

confidence: 99%

Deep-sea explosion sound signal propagation loss measurement and model verification

Tian

Chen

2023

J. Phys.: Conf. Ser.

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This paper researched the low-frequency sound field propagation characteristics in the continental slope sea area, the sound field propagation loss is calculated by using the radiated sound field data of the deep-fixed explosive sound sources with 50 m and 200 m depth in the continental slope sea area, and the experimental results are verified by combining with the Kraken normal wave model. The model verification results are in good agreement with the experimental measurement data.

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“…and they are not included in the state vector (this hybrid estimation method was presented in Ref. [17]).…”

mentioning

confidence: 99%

Sequential Parameter Estimation Using Modal Dispersion Curves in Shallow Water

Xue-dong¹,

Wu²,

Niu³

et al. 2018

Chinese Phys. Lett.

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Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile (SSP) and geoacoustic parameters based on the ensemble Kalman filter. The warping transform is implemented to the signals received by a single hydrophone to obtain the dispersion curves. The experimental data are collected at a range-independent shallow water site in the South China Sea. The results indicate that the SSPs are well estimated and the geoacoustic parameters are also well determined. Comparisons of the observed and estimated modal dispersion curves show good agreement.

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Geoacoustic inversion for sediments in the South China Sea based on a hybrid inversion scheme

Cited by 23 publications

References 20 publications

Geoacoustic Estimation of the Seafloor Sound Speed Profile in Deep Passive Margin Setting Using Standard Multichannel Seismic Data

Geoacoustic Estimation of the Seafloor Sound Speed Profile in Deep Passive Margin Setting Using Standard Multichannel Seismic Data

Deep-sea explosion sound signal propagation loss measurement and model verification

Sequential Parameter Estimation Using Modal Dispersion Curves in Shallow Water

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