Geoacoustic Model Research Articles

Geoacoustic Model of Erosional Shelf Ridges in the Mid-eastern Yellow Sea

Geoacoustic Model of Erosional Shelf Ridges in the Mid-eastern Yellow Sea

Bottom Multi-Parameter Bayesian Inversion Based on an Acoustic Backscattering Model

The geoacoustic and physical properties of the bottom, as well as spatial distribution, are crucial factors in analyzing the underwater acoustic field structure and establishing a geoacoustic model. Acoustic inversion has been widely used as an economical and effective method to obtain multi-parameters of the bottom. Compared with traditional inversion methods based on acoustic propagation models, acoustic backscattering models are more suitable for multi-parameter inversion, because they contain more bottom information. In this study, a Bayesian inversion method based on an acoustic backscattering model is proposed to obtain bottom multi-parameters, including geoacoustic parameters (the sound speed and loss parameter), partial physical parameters of the sediment, and statistical parameters of the seafloor roughness and sediment heterogeneity. The bottom was viewed as a kind of fluid medium. A high-frequency backscattering model based on fluid theory was adopted as the forward model to fit the scattering strength between the model prediction and the measured data. The Bayesian inversion method was used to obtain the posterior probability density (PPD) of the inversion parameters. Parameter estimation, uncertainty, and correlation were acquired by calculating the maximum a posterior (MAP), the mean values, the one-dimensional marginal distributions of the PPD, and the covariance matrix. Finally, the high-frequency bottom backscattering strength from the Quinault Range site was employed for inversion tests. The estimated values and uncertainties of various bottom parameters are presented and compared with the directly measured bottom parameters. The comparison results demonstrate that the method proposed herein can be used to estimate the sediment/water sound speed ratio, the sediment/water density ratio, and the spectral exponent of the roughness spectrum effectively and reliably.

Inference of geoacoustic model parameters from acoustic field data: Perspectives on Geoacoustic Inversion

Estimation of parameters of geoacoustic models from acoustic field data has been a central research theme in acoustical oceanography and ocean acoustics. During the past several decades, highly efficient numerical inversion techniques have been developed that provide model parameter estimates and their uncertainties based on statistical inference methods. However, the methods are model-based and the inversions are prone to errors related to model mismatch. In any event, the inversions can generate only effective models of the true structure of the ocean bottom, which is generally highly variable over relatively small spatial scales in range and depth. There are also questions about the theory for modelling sound propagation in porous sediment media that raise doubt about the validity of inversion results. In most inversions, a visco-elastic theory is used, but is this the most appropriate propagation model? Another question is about the impact of neglecting shear waves in geoacoustic models. Most inversions assume a fluid model of the ocean bottom. This paper revisits issues that have raised questions about limitations of geoacoustic inversion methods, and discusses the impact of various mitigation measures that have been applied. The paper concludes with musings about new inversion techniques based on machine learning.

Seabed Analysis on the New England shelf break using ambient sound data and trans-dimensional geoacoustic inversion

The New England Shelf Break Acoustics (NESBA) Signals and Noise experiment was conducted in April-May 2021. Ambient sound data were collected over several days in the mud-patch area as well as in deeper water closer to the shelf break. A 16-hydrophone vertical array was used to measure the natural sound of breaking waves on the sea-surface. Using beamforming in the 500–700 Hz band, these data were used to obtain an estimate of the bottom reflection coefficient as well as the seabed layering. The reflection coefficient data were subsequently used with trans-dimensional inversion techniques to produce a geoacoustic model for the seabed (e.g., sound speed, density, and layering). Results show the ambient sound data can be used to produce well resolved geo-acoustic parameters, especially in the upper part of the seabed (e.g., <10 m). These results are compared between several locations on the New England Shelf Break area and are also compared with other published results using different estimation techniques. In addition, some of the issues related to the impacts of data errors and preferred measurement geometries will also be presented. [Work supported by the Office of Naval Research.]

Parallel tempering in trans-dimensional Bayesian inversion for seabed geoacoustic models with many parameters per layer

Trans-dimensional (trans-D) Bayesian inversion is a powerful tool for estimating seabed geoacoustic models from ocean-acoustic data, combining quantitative model selection with parameter/uncertainty estimation. The approach applies reversible-jump Markov-chain Monte Carlo methods to sample probabilistically over the number of seabed layers and the corresponding geoacoustic parameters for each layer. Layers are added and removed during sampling, referred to as birth and death moves, respectively, changing the dimension of the model. However, the probability of accepting birth and death moves can approach zero for formulations that include many parameters per layer. This paper considers the use of parallel tempering to mitigate this degradation in efficiency. Parallel tempering employs a series of interacting Markov chains with successfully-relaxed acceptance criteria, achieved by raising the likelihood to powers of 1/T, with T greater than or equal to 1 referred to as the sampling temperature. While only the T = 1 chain provides unbiased sampling, probabilistic interchange between chains provides a robust ensemble sampler that mixes more readily over the trans-D model space. The approach is illustrated for wide-angle reflection-coefficient inversion including compressional and shear parameters in the seabed model, resulting in a total of 5 unknown parameters per layer.

Low frequency inversion method based on multi-layer holizontal variation shallow seafloor model

Sound propagation in shallow water is significantly influenced by geoacoustic properties. Estimating these geoacoustic parameters is essential for sound field analysis and sonar performance assessment. As a common practice, the seafloor is often treated as a single-layer or two-layer range-independent geoacoustic model to reduce the number of involved parameters. However, acoustic parameters inverted through these two geoacoustic models are typically limited in their applicability to a specific frequency range, thus posing challenges when applied across a broader frequency range. A range-dependent multi-layer geoacoustic model based on experimental measurements obtained with a sub-bottom profiler is proposed in this study. The inversion scheme combines three inversion methods to estimate geoacoustic parameters, considering the different sensitivities of geoacoustic parameters to different physical parameters within the acoustic field. Firstly, modal dispersion is used to invert the geoacoustic parameters of each layer, with the dispersion curve obtained through warping transform and the Wigner-Ville distribution. After that, both the localization using matched field processing and the dispersion curve fitting demonstrate the effectiveness of the inversion results for each layer, although the peak of the probability distribution of sound speed in the first layer is broader than in others. Secondly, matched field processing is employed to invert the geoacoustic parameters of the first layer. This method is based on the theory that as frequency increases, the depth of sound rays penetrating the seabed decreases, revealing changes in the first layer's sound speed with the seabed depth. Lastly, bottom attenuation coefficients at different frequencies are inverted by the transmission loss (TL), and a fitting relationship between the attenuation coefficient and the frequency is derived. The inversion results obtained by using the range-dependent multi-layer geoacoustic model are compared with results estimated by the single-layer geoacoustic model. The findings indicate that the transmission loss (TL) error from the range-dependent multi-layer geoacoustic model in this study is smaller than that from the single-layer geoacoustic model, especially in the lower frequency band. The range-dependent multi-layer geoacoustic model proves to be suitable for a broader frequency range, providing better precision in explaining various acoustic phenomena.

Prediction Model of the Sound Speed of Seafloor Sediments on the Continental Shelf of the East China Sea Based on Empirical Equations

Based on the data of the acoustic and physical properties of seafloor sediments obtained on the continental shelf area of the East China Sea (ECS), prediction equations of the sediment sound speed based on single and dual parameters were established, and the correlation of the sound speed with physical parameters was discussed. The results show that the sediment sound speed (c) is strongly correlated with water content (w), density (ρ), void ratio (e), mean grain size (Mz) and median grain size (Md), and the coefficient of determination R2 of the empirical regression equation is generally greater than 0.80, while the empirical regression equation coefficient of determination R2 of the compression coefficient (a) and compression modulus (E) are slightly lower, with 0.79 and 0.73, respectively. The coefficients of determination of the dual parameter regression equations between sediment sound speed with physical property parameters are generally higher than those of the single parameter equations, which are all higher than 0.90 indicating better prediction performance. The sensitivity of the physical parameters to the sound speed was analyzed, and the result shows that the sequence of sensitivity from high to low influence on sediment sound speed is void ratio, density, compressibility coefficient, median grain size and mean grain size. The prediction equations established in this study are a good extension and supplement to marine geoacoustic models and is of great significance for obtaining the acoustic properties of the seafloor sediments on the shelf of the East China Sea.

Geoacoustic model based on physical property characterization of the southeastern shelf sediments (Korea Strait) of Korea

Deep-core samples collected from the southeastern shelf (Korea Strait) of Korea were used to characterize physical properties of the area with respect to burial depth. Laboratory analyses of the acoustic and physical properties of the samples were conducted and shear-wave velocity, velocity ratio, and Poisson’s ratio were calculated. Geoacoustic and physical property data at the two sites were in correlation with the lithological units alternating between sandy mud and muddy sand at sedimentary depth. Geoacoustic units (GAUs) identified from sites 19ESDP-104 and 21ESDP-203 were divided into 6 and 15 units with sedimentary depth, respectively, and geoacoustic models were developed for the sedimentary layers around these sites. This suggests that the physical properties are not only controlled by lithology and compaction caused by dewatering with burial depth but also by different sedimentary environments after deposition. Based on the velocity ratio and velocity anisotropy (particularly at site 21ESDP-203), clay particles within the sediment layers had a greater effect on compaction owing to the overburden pressure with burial depth.

Comparative Review and Outlook of Research Progress in Backscatter-based Seafloor Substrate Classification Methods

Background: The seafloor is an essential ocean boundary, and the detection of seafloor information is necessary basis for seafloor scientific research. The classification and identification of seafloor geological types is necessary for researchers to conduct seafloor research, military activities, and marine platform construction. Objective: The purpose of this paper is to summarize the progress of seafloor substrate classification research based on backscattering and to seek a new development direction for seafloor substrate classification research. Method: The literature on various types of submarine sediment attenuation geoacoustic models, backscatter intensity calculations, and submarine substrate classification is summarized, and the progress of theoretical research required for the positive and negative problems of submarine substrate classification is described that include the geoacoustic parameter models based on fluid theory, elastomer theory and poroelastic theory and submarine acoustic scattering models, including the small roughness perturbation approximation model, the Kirchhoff approximation model, the Kirchhoff approximation model and the Kirchhoff approximation model. Result: The development of the Kirchhoff approximation model, the slight slope approximation model, the volume scattering model, and the inversion methods for seafloor substrate classification are summarized, and breakthroughs in seafloor substrate classification are sought by summarizing previous studies. Conclusion: The classification of seafloor substrate based on backscattering intensity needs the support of a perfect geoacoustic model and scattering model, and the current research of low and medium-frequency scattering models and multi-layer seafloor scattering models are the further development direction in the future. Currently, the better performance of the prediction model, geo-acoustic parameter inversion results are more than 90% accuracy, sound velocity ratio and other parameters in the high-frequency band inversion accuracy of 98%, are able to better meet the measured data. Finally, some patented technologies are also reported.

Application of trans-dimensional particle filtering for geoacustic inversion

The acquiring geoacoustic model and associated geoacoustic parameters is vital for sound propagation modelling in a range-dependent environment. Conventional sequential methods, e.g., particle filtering and Kalman filtering have been widely used for geoacoustic inversion in range-dependent environment, which encounter challenges when confronted with unknown geoacoustic models that intrinsically varying with range. As an attempt to estimate geoacoustic model and associated geoacoustic parameters as well, a trans-dimensional particle filtering method is presented here. This method integrates birth-death rules into the filtering process, enabling automatic selection of appropriate geoacoustic models and estimating geoacoustic parameters in the same time. Numerical simulations were conducted based on an environment model of the South China Sea, where a sea trial was conducted in 2022. Numerical results demonstrate the efficiency in accurately estimating the geoacoustic model variations and associated parameters. Preliminary results of sea trial data processing are also presented here.

Propagation of ship noise in shallow water over a high shear-speed seabed

Assessing the acoustic impact of shipping close to the coast and within ports and harbours requires an understanding of the propagation of underwater sound in these environments. In the Australian context, this often means propagation over seabeds with shear speeds approaching the in-water sound speed, a situation that results in very different propagation conditions to the low shear speed sediments more commonly encountered in other parts of the world. Acoustic propagation modelling approaches were explored using a dataset of continuous underwater recordings featuring a mix of shipping, industrial, and recreational activities, acquired from 23 Jul to 16 Sep 2022 in Cockburn Sound, off the west coast of Australia. Cockburn Sound is a sheltered marine embayment with a relatively uniform water depth of 17–20 m in the 5 km × 11 km central portion of the basin, with a thin, variable thickness (0.5 m–5 m) layer of silty sediments overlying a calcarenite basement. The results of modelling the calcarenite basement as an equivalent fluid were compared to those obtained by modelling it as an elastic solid, and with measurements. Subsequent implications of the choice of geoacoustic model will be discussed

Active intensity vortex and stagnation point singularities in a shallow underwater waveguide.

Vector acoustic properties of a narrowband acoustic field are observed as a function of range from a source towed in waters of depth 77 m on the New England Mud Patch. At the source frequency (43 Hz), the waveguide supported three trapped modes, with mode 2 weakly excited owing to the towed source depth. The receiving sensor was positioned 1.45 m above the seafloor with a sampling range aperture of 2500 m. The vector acoustics observations enabled study of vortex regions that encompass two singular points for active acoustic intensity: the vortex point, which is co-located with a dislocation, and stagnation point. Interpretative modeling, based on the normal modes and using a geoacoustic model consistent with those emerging from studies conducted at this location, is in agreement with these measurements. Model-data comparisons were based on the first-order variables of acoustic pressure and velocity along with inverse Hankel transforms, which yield normalized horizontal wavenumber spectra, and second-order variables in the form of horizontal and vertical intensity as well as non-dimensional intensity-based ratios. These measures provide a degree of observational confirmation of some vortex region properties. Both observations and modeling point to a gradual deepening of such regions with increasing range owing to sediment attenuation.

Bayesian optimization with Gaussian process surrogate model for source localization.

Source localization with a geoacoustic model requires optimizing the model over a parameter space of range and depth with the objective of matching a predicted sound field to a field measured on an array. We propose a sample-efficient sequential Bayesian optimization strategy that models the objective function as a Gaussian process (GP) surrogate model conditioned on observed data. Using the mean and covariance functions of the GP, a heuristic acquisition function proposes a candidate in parameter space to sample, balancing exploitation (sampling around the best observed objective function value) and exploration (sampling in regions of high variance in the GP). The candidate sample is evaluated, and the GP conditioned on the updated data. Optimization proceeds sequentially until a fixed budget of evaluations is expended. We demonstrate source localization for a shallow-water waveguide using Monte Carlo simulations and experimental data from an acoustic source tow. Compared to grid search and quasi-random sampling strategies, simulations and experimental results indicate the Bayesian optimization strategy converges on optimal solutions rapidly.

Joint trans-dimensional inversion for water-column sound speed and seabed geoacoustic models.

This letter considers joint estimation of the water-column sound-speed profile (SSP) and seabed geoacoustic model through Bayesian inversion of ocean-acoustic data. The inversion is formulated in terms of separate trans-dimensional models for the water column (as an unknown number of nodes of a piecewise-continuous SSP) and seabed (as an unknown number of uniform layers) to intrinsically parameterize each according to the information content of the data. The inversion estimates marginal posterior probability profiles, quantifying the resolution of water-column and seabed structure. To validate the proposed method, modal-dispersion data from the New England Mud Patch, collected using hand-deployable systems, are considered.

Experimental demonstration of low signal-to-noise ratio matched field processing with a geoacoustic model extracted from noise.

Passive localization of a low signal-to-noise ratio (SNR) source in a shallow water waveguide without prior geoacoustic information is accomplished by combining the mode-extraction method modal-MUSIC (multiple signal classification) with range-coherent matched field processing (MFP). Range-coherent MFP coherently combines snapshots from different resolution cells to obtain gain over noise. Modal-MUSIC uses knowledge of the water column sound speed profile (no bottom information) to extract noisy estimates of modal wavenumbers from ship noise recorded on a partially spanning vertical line array (VLA). A geoacoustic model is then fit to the wavenumber estimates extracted from noise with modal-MUSIC and used to compute replicas for range-coherent MFP. The combination of these two methods applied to a 21-element VLA achieves successful source localization at SNR levels as low as -20 dB using ten tonals transmitted during the SWellEx96 experiment.

Detailed composition and physical properties analyses of surficial and sub-surface fined-grained sediments from the Continental Shelf and Upper Slope Sediments Offshore Southern New England, USA

In recent years, detailed geological characterization of the seafloor and shallow sub-surface on the northern U.S. Atlantic margin have been an important component of multi-disciplinary ocean acoustics and environmental sensing projects to support experiment planning and inform geoacoustic models of sound propagation. Comprehensive surficial sediment and core sampling across shallow continental shelf, shelf-edge, and upper continental slope sites offshore southern New England provide the opportunity to evaluate the importance of many sediment characteristics that impact sound propagation through the seabed. Beginning in the mid-shelf New England Mud Patch and continuing into deeper water, we have begun to develop a detailed understanding of the composition and physical properties of the shallow sediment column record using a combination of surficial and sub-surface sediment sampling tools, coupled with an extensive suite of discrete laboratory analyses. Quantitative data on sediment density, porosity, mineral and biogenic composition, and grain size distribution provides both valuable input parameters for geoacoustic models and helps establish a framework for interpreting independently derived measurements and modeling results. The physical, biological, and other environmental sediment characteristics can be integrated with existing geological assessments of the region and used to investigate ocean and sub-surface acoustic propagation. [Work supported by the Office of Naval Research.]

Joint trans-dimensional inversion for seabed and water-column properties in the seabed characterization experiments

This paper considers the information content to resolve both a geoacoustic model of the seabed and a model of the water-column sound-speed profile (SSP) in the inversion of modal-dispersion data. A Bayesian formulation of the inverse problem allows prior information representing varying levels of independent knowledge to be applied separately to the seabed and water-column models. Issues of interest include the extent to which knowledge (or lack thereof) of the SSP affects geoacoustic inversion, and the ability to remotely estimate the SSP from acoustic data in cases where the seabed is either well known or poorly known. The joint inversion for seabed and water-column properties is formulated in terms of a separate trans-dimensional model for each, providing an automated approach to quantitative model selection. The seabed model is formulated in terms of an unknown number of uniform sediment layers, while the SSP is formulated as an unknown number of depth/sound-speed nodes, with the reciprocal of sound speed squared varying linearly between nodes, as per normal-mode propagation models. The approach is applied to modal-dispersion data measured during the seabed characterization experiments at the New England Mud Patch. [Work supported by the Office of Naval Research]

Potential and kinetic energy of underwater noise measured at steep grazing angles over contrasting seafloors

Observed near the seabed, broadband noise emissions from a source or vessel passing directly above the sensor exhibit frequency bands where potential acoustic energy is greater than kinetic energy while the opposite occurs in neighboring frequency bands. The condition where the dynamic and kinematic energy forms differ in this manner is characteristic to interference involving steep angles or near-normal incidence reflection from the seafloor. Recent experiments conducted on the New England Mud Patch (NEMP) and the neighboring (towards offshore) shelf break waters demonstrate the sensitivity to seabed structure, which evolves from the soft mud layers at the NEMP into the harder sediments that are exposed on the continental slope. Results are expressed as a ratio of kinetic to potential energy as a function of frequency, with resulting data series yielding information on seabed properties. Variance components as function of frequency are also isolated based on a singular value decomposition of a matrix constructed from the data series (known as singular spectrum analysis). The components are associated with different sub- bottom layering features. A model for kinetic and potential energy combined with candidate geoacoustic models is used to interpret both the data series and components.

Broadband sound speed and attenuation of a mud layer from acoustic propagation experiments in the New England Mud Patch

A series of Seabed Characterization Experiments (SBCEX) have been conducted in the New England Mud Patch area, where a top mud layer overlays a sand sediment. Using broadband acoustic signals from the SBCEX, the sound speed and attenuation of the mud layer as a function of frequency (from a few tens of Hz up to around 1 kHz) have been estimated by various inversion algorithms based on (1) modal dispersion curves and transmission loss [reported at the ASA Spring meeting, 2016], (2) Airy phase [Spring, 2017], (3) modal amplitude [Fall, 2017], (4) spatial coherence measurements [Spring, 2018], (5) mid-frequency modal dispersion analysis [Fall, 2019], and (6) ground waves [Fall, 2022]. This paper summarizes these inverted sound speed and attenuation, which are obtained at various frequencies independently (without using the frequency dependent constraints from any geo-acoustic models), therefore the inverted results could be used to verify the validity of geo-acoustic models. The performances of these inversion methods are evaluated. The performance assessment is helpful for one to select appropriate inversion algorithms and to choose optimal acoustic data for geo-acoustic inversion. [Work supported by ONR Ocean Acoustics.]

Inversion of ocean acoustic modal-dispersion and amplitude data for seabed geoacoustic models including attenuation

The long-range acoustic field due to an initial sound source in a shallow-water waveguide can be expressed as the sum of a number of dispersive, propagating modes. Modal-dispersion data (arrival time as a function of frequency), as extracted with warping time-frequency analysis, have been inverted to estimate seabed sediment sound-speed and density profiles. In this work, measurements of modal amplitudes as a function of frequency are combined with modal-dispersion data in a joint (simultaneous) inversion which also provides sensitivity to frequency-dependent sound attenuation coefficients in the sediment layers. Since the source signature (spectrum) is often unknown in practice, the relative amplitudes between modes can be considered as data, or the source spectrum can itself be included as additional unknowns in the inversion. Here, trans-dimensional Bayesian inversion is applied to modal-dispersion and amplitude data to estimate marginal probability profiles for sediment geoacoustic properties, including attenuation. The signal processing and inversion methods are demonstrated using modal-dispersion and amplitude data extracted from acoustic measurements made by a hydrophone-equipped underwater glider during the 2017 Seabed Characterization Experiment (Work supported by the Office of Naval Research).