Estimating geoacoustic parameters using matched-field inversion methods

In this paper, we use matched-field inversion methods to estimate the geoacoustic parameters for three synthetic test cases from the Geoacoustic Inversion Techniques Workshop held in May 2001 in Gulfport, MS. The objective of this work is to use a sparse acoustic data set to obtain estimates of the parameters as well as an indication of their uncertainties. The unknown parameters include the geoacoustic properties of the sea bed (i.e., number of layers, layer thickness, density, compressional speed, and attenuation) and the bathymetry for simplified range-dependent acoustic environments. The acoustic data used to solve the problems are restricted to five frequencies for a single vertical line array of receivers located at one range from the source. Matched-field inversion using simplex simulated annealing optimization is initially used to find a maximum-likelihood (ML) estimate. However, the ML estimate provides no information on the uncertainties or covariance associated with the model parameters. To estimate uncertainties, a Bayesian formulation of matched-field inversion is used to generate posterior probability density distributions for the parameters. The mean, covariance, and marginal distributions are determined using a Gibbs importance sampler based on the cascaded Metropolis algorithm. In most cases, excellent results were obtained for relatively sensitive parameters such as wave speed, layer thickness, and water depth. The variance of the estimates increase for relatively insensitive parameters such as density and wave attenuation, especially when noise is added to the data.     

Matched field inversion for geoacoustic model parameters usingadaptive simulated annealing

A method is described for the estimation of geoacoustic model parameters by the inversion of acoustic field data using a nonlinear optimization procedure based on simulated annealing. The cost function used by the algorithm is the Bartlett matched-field processor (MFP), which related the measured acoustic field with replica fields calculated by the SAFARI fast field program. Model parameters are perturbed randomly, and the algorithm searches the multidimensional parameter space of geoacoustic models to determine the parameter set that optimizes the output of the MFP. Convergence is driven by adaptively guiding the search to regions of the parameter space associated with above-average values of the MFP. The performance of the algorithm is demonstrated for a vertical line array in a shallow water enviornment where the bottom consists of homogeneous elastic solid layers. Simulated data are used to determine the limits on estimation performance due to error in experimental geometry and to noise contamination. The results indicate that reasonable estimates are obtained for moderate conditions of noise and uncertainty in experimental geometry     

Estimation of ocean-bottom properties by matched-field inversion ofacoustic field data

A method for estimating properties of the ocean bottom such as bathymetry and geoacoustic parameters such as sound speed, density and attenuation, using matched-field inversion is considered. The inversion can be formulated as an optimization problem by assuming a discrete model of unknown parameters and a bounded search space for each parameter. The optimization then involves finding the set of parameter values which minimizes the mismatch between the measured acoustic field and modeled replica fields. Since the number of possible models can be extremely large, the method of simulated annealing, which provides an efficient optimization that avoids becoming trapped in suboptimal solutions, has been used. The matching fields are computed using a normal mode model. In inversions for range-dependent parameters, the adiabatic approximation is employed. This allows mode values to be precomputed for a grid of parameter values and stored in look-up tables for fast reference, which greatly improves computational efficiency. Synthetic inversion examples are presented for realistic range-independent and range-dependent environments     

Velocity structure and gas hydrate saturation estimation on active margin off SW Taiwan inferred from seismic tomography

This paper presents results of a seismic tomography experiment carried out on the accretionary margin off southwest Taiwan. In the experiment, a seismic air gun survey was recorded on an array of 30 ocean bottom seismometers (OBS) deployed in the study area. The locations of the OBSs were determined to high accuracy by an inversion based on the shot traveltimes. A three-dimensional tomographic inversion was then carried out to determine the velocity structure for the survey area. The inversion indicates a relatively high P wave velocity (Vp) beneath topographic ridges which represent a series of thrust-cored anticlines develop in the accretionary wedge. The bottom-simulating reflectors (BSR) closely follow the seafloor and lies at 325 ± 25 m within the well-constrained region. Mean velocities range from ~1.55 km/s at the seabed to ~1.95 km/s at the BSR. We model Vp using an equation based on a modification of Wood’s equation to estimate the gas hydrate saturation. The hydrate saturation varies from 5% at the top ~200 m below the seafloor to 25% of pore space close to the BSR in the survey area.     

Estimates of geoacoustic model parameters from inversions of horizontal and vertical line array data

This paper describes results from geoacoustic inversion of low-frequency acoustic data recorded at a receiving array divided into two sections, a sparse bottom laid horizontal array (HLA) and a vertical array (VLA) deployed in shallow water. The data are from an experiment conducted by the Norwegian Defence Research Establishment (FFI) in the Barents Sea, using broadband explosives (shot) sources. A two-layer range-independent geoacoustic model, consistent with seismic profiles from the area, described the environment. Inversion for geoacoustic model parameters was carried out using a fast implementation of the hybrid adaptive simplex simulated annealing (ASSA) inversion algorithm, with replica fields computed by the ORCA normal mode code. Low-frequency (40-128 Hz) data from six shot sources at ranges 3-9 km from the array were considered. Estimates of sediment and substrate p-wave velocities and sediment thickness were found to be consistent between independent inversions of data from the two sections of the array.     

浅海聚焦定位中简化地声模型的应用研究

为了提高定位算法的环境宽容性,聚焦法将环境参数纳入了寻优空间。聚焦法虽然降低了对环境测量的要求,但是反演参数的增加也增加了反演的复杂性。基于海底反射特性,用两个参数对海底进行建模。通过标准的反演测试问题对简化地声模型在浅海聚焦定位中的有效性进行了分析。结果表明:基于简化地声模型的聚焦定位是可行的。在获得正确定位结果的同时,随着地声参数个数的减少,匹配场处理的便捷性得到了提高。文中引入的简化地声模型是聚焦问题中参数最少的地声模型,它可以有效减少聚焦定位参数维数以提升反演的便捷性。同时,简化地声模型在参数敏感性和耦合性上有较好的表现,这些优点可以保证定位结果的稳健性。     

Geoacoustic Uncertainties From Viscoelastic Inversion of Seabed Reflection Data

This paper applies nonlinear Bayesian inversion to seabed reflection data to estimate viscoelastic parameters of the upper sediments. The inversion provides maximum a posteriori probability (MAP) parameter estimates with uncertainties quantified in terms of marginal probability distributions, variances, and credibility intervals; interparameter relationships are quantified by correlations and joint marginal distributions. The inversion is applied to high-resolution reflectivity data from two sites in the Strait of Sicily. One site is characterized by low-speed sediments, resulting in data with a well-defined angle of intromission; the second is characterized by high-speed sediments, resulting in a critical angle. Data uncertainties are quantified using several approaches, including maximum-likelihood (ML) estimation, treating uncertainties as nuisance parameters in the inversion, and analysis of experimental errors. Statistical tests are applied to the data residuals to validate the assumed uncertainty distributions. Excellent results (i.e., small uncertainties) are obtained for sediment compressional-wave speed, compressional attenuation, and density; shear parameters are less well determined although low shear-wave speeds are indicated. The Bayesian analysis provides a quantitative comparison of inversion results for the two sites in terms of the resolution of specific geoacoustic parameters, and indicates that the geoacoustic information content is significantly higher for intromission data     

Geoacoustic model parameter estimation using a bottom-moored hydrophone array

This paper describes results from an experiment carried out to investigate geoacoustic inversion with a bottom-moored hydrophone array located in the shallow waters of the Timor Sea off the northern coast of Australia. The array consisted of two arms in a V shape, horizontally moored at a site that was essentially flat over a large area. Hydrophone positions were estimated using an array element localization (AEL) technique that established relative uncertainties of less than 1 m on the seafloor. The data used for geoacoustic inversion were from experiments with continuous wave (CW) tones in the 80- to 195-Hz band transmitted from a towed projector. A hybrid search algorithm determined the set of geoacoustic model parameters that maximized the Bartlett fit (averaged coherently spatially at each tone and incoherently over frequency) between the measured and modeled data at the array. Due to the long range experimental geometry, the inversion was sensitive to attenuation in the sediment. The inverted geoacoustic profile performed well in a simple test for localizing the sound source at other sites in the vicinity of the array. Range-depth localization performance for the horizontal array was comparable to that for an equivalent vertical array.     

Multistep matched-field inversion for broad-band data from ASIAEX2001

This paper discusses the results of geoacoustic inversion carried out using explosive charge data from the Asian Seas International Acoustic Experiment (ASIAEX) East China Sea (ECS) Experiment. A multifrequency incoherent matched-field inversion processor and a genetic algorithm (GA) are used for the inversion. A multistep matched field inversion approach is presented, which makes use of the varying sensitivities of wave fields at various frequencies to reduce the inversion problem into a sequence of smaller inversions with fewer unknowns to estimate at each stage. Different parameters are estimated using data at different frequencies according to their sensitivities. Inversion results for different areas in the ECS region are summarized and compared with core data.     

A New Multistep Algorithm for Geoacoustic Inversion via Subspace Extraction

This communication presents a new multistep matched-field algorithm for geoacoustic inversion by subspace extraction with a threshold. In this algorithm, according to the varying sensitivities of geoacoustic parameters, parameters are separated into several subsets (or subspaces). Then, inversions are carried out in each sensitive subspace using an optimization algorithm, and for each inversion, a sub-subspace is extracted where values of objective functions are lower than a given threshold. Finally, in all the extracted sub-subspaces combined with the subspace of insensitive parameters, an inversion is performed for all parameters to find the optimal solution. After the extracting process, the search space is greatly reduced, and generally, the true parameter values will not be excluded from the sub-subspace if a reasonable threshold is designed. Thus, higher efficiency and accuracy can be obtained when compared with other algorithms. Simulation is carried out on synthetic data and results indicate that the new algorithm's performance is significantly superior to those of other algorithms.      

Phenomenological and global optimization inversion

This paper discusses geoacoustic inversion results based on benchmark range-dependent data using SAGA, a global inversion package, and using phenomenological inversions. In phenomenological inversions, physical and signal-processing approaches are used to enhance the data to extract specific features. The global optimization approach is carried out on complex-valued vertical array data, transmission loss data, and reverberation data. The importance of checking the solution is emphasized by inspecting the match with the data and the error estimates and by checking the solution using data that has not been used in constructing the solution. The results show that we are able to estimate the geoacoustic parameters and that these parameters could be used to predict the field for different frequencies and/or source-receiver geometry than used in the inversion.     

Generating interface waves using a freely falling, instrumentedsource

In recent years, interface waves such as the Scholte wave have become important tools in the study of the geoacoustic properties of near-bottom seafloor sediments. Traditionally, these waves have been generated by explosive or pneumatic sources deployed at or near the seafloor and monitored by ocean-bottom seismographs or geophone arrays. While these sources generate the requisite interface waves, they also produce higher frequency compressional waves in the water and sediment that tend to contaminate the surface wave and make inversion of the data difficult in the near field. In this paper, a new source consisting of a freely falling projectile instrumented with an accelerometer is described. When the projectile impacts the bottom, the exact time history of the vertical force applied to the sediment is known and therefore may be convolved with the transfer function of a sediment geoacoustic model to produce accurate synthetic seismograms. Moreover, the vertical force applied to the seafloor is very efficient in generating surface wave motion while producing very little compressional wave energy so that the near-field signals are much more easily analyzed. An example of the use of the new source is presented including inversion of the received signals to obtain shear-wave velocity and attenuation as a function of depth in the near bottom sediments at a shallow-water site     

Geoacoustic Information Content of Horizontal Line Array Data

This paper examines the effectiveness of horizontal line arrays (HLAs) for matched-field inversion (MFI) by quantifying geoacoustic information content for a variety of experiment and array factors, including array length and number of sensors, source range and bearing, source-frequency content, and signal-to-noise ratio (SNR). Emphasis is on bottom-moored arrays, while towed arrays are also considered, and a comparison with vertical line array (VLA) performance is made. The geoacoustic information content is quantified in terms of marginal posterior probability distributions (PPDs) for model parameters estimated using a fast Gibbs sampler approach to Bayesian inversion. This produces an absolute, quantitative estimate of the geoacoustic parameter uncertainties which can be directly compared for various experiment and array factors.     

Broad-band geoacoustic inversion in shallow water from waveguideimpulse response measurements on a single hydrophone: theory andexperimental results

The paper discusses an inversion method that allows the rapid determination of in situ geoacoustic properties of the ocean bottom without resorting to large acoustic receiving apertures, synthetic or real. The method is based on broad-band waterborne measurements and modeling of the waveguide impulse response between a controlled source and a single hydrophone. Results from Yellow Shark '94 experiments in Mediterranean shallow waters using single elements of a vertical array are reviewed, inversion of the bottom parameters is performed with an objective function that includes the processing gain of a model-based matched filter (MBMF) receiver relative to the conventional matched filter. The MBMF reference signals incorporate waveguide Green's functions for known geometry and water column acoustic model and hypothesized bottom geoacoustic models. The experimental inversion results demonstrated that, even for complex environmental conditions, a single transmission of a broad-band (200-800 Hz) coded signal received at a single depth and a few hundred forward modeling runs were sufficient to correctly resolve the bottom features. These included the sound speed profile, attenuation, density, and thickness of the top clay sediment layer, and sound speed and attenuation of the silty clay bottom. Exhaustive parameter search proved unequivocally the low-ambiguity and high-resolution properties of the MBMF-derived objective. The single-hydrophone results compare well with those obtained under identical conditions from matched-field processing of multitone pressure fields sampled on the vertical array. Both of these results agree with expectations from geophysical ground truth. The MBMF has been applied successfully to a field of advanced drifting acoustic buoys on the Western Sicilian shelf, demonstrating the general applicability of the inversion method presented     

An adaptive-hybrid algorithm for geoacoustic inversion

This paper presents an adaptive hybrid algorithm to invert ocean acoustic field measurements for seabed geoacoustic parameters. The inversion combines a global search (simulated annealing) and a local method (downhill simplex), employing an adaptive approach to control the trade off between random variation and gradient-based information in the inversion. The result is an efficient and effective algorithm that successfully navigates challenging parameter spaces including large numbers of local minima, strongly correlated parameters, and a wide range of parameter sensitivities. The algorithm is applied to a set of benchmark test cases, which includes inversion of simulated measurements with and without noise, and cases where the model parameterization is known and where the parameterization most be determined as part of the inversion. For accurate data, the adaptive inversion often produces a model with a Bartlett mismatch lower than the numerical error of the propagation model used to compute the replica fields. For noisy synthetic data, the inversion produces a model with a mismatch that is lower than that for the true parameters. Comparison with previous inversions indicates that the adaptive hybrid method provides the best results to date for the benchmark cases     

A Sound Approach to Soft Sediment Resolution

The last few years has seen a surge in research activities directed towards investigating properties and dynamics of young marine, limnic and fluvial sediments. It is by now a well established fact that the sequence of sediments ranging from concentrated benthic suspension over fluid mud to un-consolidated material summarized as liquid sediments (LS), act as carriers for a wide range of pollutants discharged or migrated into waterways. Knowledge of the transport and fate of LS allows determining the transport and fate of adsorbed constituents (e.g., heavy metals, pesticides, PCBs, PAHs). To assess the environmental impact of LS, efforts have to be made to better understand the processes in relation to hydrodynamics and the chemical and physical properties of the layers. Since physical laws limit the resolution and detection power of conventional seismo-acoustic systems in respect of LS, alternative measurement, data analysis and processing approaches have to be found. Adapted acoustic procedures initially developed for shallow water marine environments to extreme shallow water regimes using matched field inversion techniques can reveal geoacoustic parameters including density, compressional wave speed and attenuation as a function of depth and time. The paper outlines the effects of sediment mobility upon the environment followed by a short overview of techniques commonly used to investigate sediments and other freshwater/marine events. The problems faced and limitations of existing systems are briefly outlined. Results obtained with recently developed and refined geoacoustic inversion methods are presented highlighting their potential for long-term study of physical properties and dynamics of LS.     

Matched-field geoacoustic inversion of low-frequency source tow data from the ASIAEX East China Sea experiment

Geoacoustic inversion results based on data obtained during the Asian Seas International Acoustics Experiment (ASIAEX) 2001 East China Sea experiment are reported. The inversion process uses a genetic-algorithm-based matched-field-processing approach to optimize the search procedure for the unknown parameters. Inversion results include both geometric and geoacoustic variables. To gauge the quality of the inversion, two different analyses are employed. First, the inversion results based upon discrete source-receiver ranges are confirmed by continuous source localization over an interval of time. Second, separate inversions at many different ranges are carried out and the uncertainties of the parameter estimation are analyzed. The analysis shows that both methods yield consistent results, ensuring the reliability of inversion in this study.     

A hybrid simplex genetic algorithm for estimating geoacousticparameters using matched-field inversion

Matched-fieId inversion (MFI) undertakes to estimate the geometric and geoacoustic parameters in an ocean acoustic scenario by matching acoustic field data recorded at hydrophone array with numerical calculations of the field. The model which provides the best fit to the data is the estimate of the actual experimental scenario. MFI provides a comparatively inexpensive method for estimating ocean bottom parameters over an extensive area. The basic components of the inversion process are a sound propagation model and matching (minimization) algorithm. Since a typical MFI problem requires a large number of computationally intensive sound propagation calculations, both of these components have to be efficient. In this study, a hybrid inversion algorithm which uses a parabolic equation propagation model and combines the downhill simplex algorithm with genetic algorithms is introduced. The algorithm is demonstrated on synthetic range-dependent shallow-water data generated using the parabolic equation propagation model. The performance for estimating the model parameters is compared for realistic signal-to-noise ratios in the synthetic data     

Rapid geoacoustic characterization using a surface ship of opportunity

The problem of rapid classification of the sea-floor sediment is addressed using horizontal line array (HLA) acoustic data from a passing surface ship. The data are beamformed to improve signal-to-noise ratio. The rapid geoacoustic characterization (RGC) algorithm involves extracting acoustic observables from the data (normalized striation slope, time spread, and transmission-loss slope). A simple single homogenous sediment layer over an acoustic half-space model is used to compute forward estimates of the acoustic observables. An exhaustive search over the two-parameter model is performed. The two parameters searched over are the sediment compressional speed (Cp), which is a polynomial function of the mean grain size (/spl phi/), and sediment thickness (H). This approach provides a real-time technique for classifying the sediment in a way that successfully reproduces the basic physics of propagation.     

Rapid geoacoustic characterization: applied to range-dependent environments

The problem of rapid environmental assessment in a range-dependent environment is addressed. For rapid assessment, the exact geoacoustic parameters are not required, nor is it a requirement that the exact structure of the acoustic field (location of peaks and s) be matched by an acoustic prediction model. The parameters that are relevant are the overall transmission loss (incoherent TL), the time spread (/spl tau/), and the slopes of the range/frequency interference patterns (/spl beta/, the waveguide invariant). The rapid geoacoustic characterization algorithm uses a homogeneous single-sediment layer overlying a hard acoustic basement model to optimally match the predicted acoustic observables with those estimated from data. The approach is presented here and is applied to the range-dependent benchmark cases TC1 and TC2 from the Inversion Techniques Workshop held in Gulfport, MS, in May 2001. The technique successfully reproduces the acoustic observables and estimates the sediment sound-speed, density, and attenuation profiles, as well as the sediment thickness.