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This paper describes geoacoustic inversion of low frequency air gun data acquired during an experiment on the New Jersey shelf. Hybrid optimization and Bayesian inversion techniques based on matched field processing were applied to multiple shots from three air gun data sets recorded by a vertical line array in a long-range shallow water geometry. For the Bayesian inversions, full data error covariance matrix was estimated from a set of consecutive shots that had high temporal coherence and small spatial variation in source position. The effect of different data error information on the geoacoustic parameter uncertainty estimates was investigated by using the full data error covariance matrix, a diagonalized version of the full error covariance, and a diagonal matrix with identical variances. The comparison demonstrated that inversion using the full data error information provided the most reliable parameter uncertainty estimates. The inversions were highly sensitive to the near sea floor geoacoustic parameters, including sediment attenuation, of a simple single-layer geoacoustic model. The estimated parameter values of the model were consistent with depth averaged values (over wavelength scales) of a high resolution geoacoustic model developed from extensive ground truth information. The interpretation of the frequency dependence of the estimated attenuation is also discussed.

In situ porosity and permeability were measured on Great Bahama Bank sediments using electrical conductivity and permeability probes. Core samples were recovered at the probe measurement sites for laboratory determinations of porosity and permeability. Penetration depths of cores and probes were approximately 2.5 m subbottom.In situ porosities of the oölitic sands for depths of 0-2.5 m subbottom ranged between 36% and 50%, and at sites in the somewhat muddier oölitic sediments the porosities ranged from 42% to 61%. The in situ permeabilities ranged from 0.0032 cm/s (3.3 darcys) to 0.068 cm/s (71 darcys) at the sites where porosities were determined. Laboratory values of porosity are comparable to values obtained by in situ measurements; however, laboratory permeability values are approximately an order of magnitude lower than in situ values. The reduced permeability measured in the laboratory is attributed to disturbance of the microfabric during coring, Mohsen Badiey's present affiliation is the University of Delaware. 1 Downloaded by [University of Florida] at 09:19 01 June 2016 2 R. H. Bennett et al. . transport, and laboratory sampling. A detailed examination of the microfabric can be found in a companion articleThe high in situ porosities and permeabilities of these carbonate sediments are predominantly the result of the combined effects of both the sediment grain size distribution and the microfabric. The classification scheme of Dunham (1962) for carbonate rocks (wackestone, packstone, etc.) does not always provide a clear picture of some of the crucial properties of carbonate sediments (porosity, permeability, etc.), nor does this scheme provide a realistic functional description of the behavior of these sediments when subjected to static and dynamic stresses.

Sea surface roughness is one of several factors that significantly influences high-frequency (1–50-kHz) acoustic wave propagation in shallow water. The evolving sea surface introduces several variability effects including Doppler shift. Data analyses from high-frequency acoustic experiments show high-correlation between time, angle, and intensity fluctuations of received signals and varying sea surface conditions. In order to assess detailed acoustic signal interactions with the sea surface, a realistic wave model is developed and combined with an acoustic ray-based model. Model validity is evaluated by comparing the results with data from multiple experiments. [Work supported by ONR 321OA.]

SUMMARYWater wave over a porous sea bottom drives a seepage #ux into and out of the sediment. The volume of #uid exchange per wave cycle and per wave length may be tied to the mass transfer rate of contaminant in sediment.In the "rst part of the paper, the analytical solution of seepage #ux is presented based on the Biot theory of poroelasticity. Parameter e!ect on the seepage #ux as well as on the pore pressure is examined. In the second part, empirical relationships are introduced to reduce the data requirement of the model to two parameters: the porosity and the degree of saturation. With the existence of a multi-sensor piezometer known as &MPAS', the pore pressure data in the sediment can be collected. Utilizing the empirical relations, parameter inversion can be achieved based on pore pressure data alone.

The Airy phase is identified in the received signals from explosive charges deployed in a shallow water acoustic experiment conducted in the New England Mudpatch region during the spring of 2017. Measured and modeled time-frequency dispersion curves are compared and a geoacoustic sensitivity study utilizing marginal probability distributions for the sound speed in five sediment layers is performed. The analysis suggests that inclusion of the Airy phase frequency and arrival time in a geoacoustic-inversion method could lower the uncertainty of sound speed parameter estimation in a multi-layer sediment as compared to methods that do not include the Airy phase structure.

A procedure for estimating acoustic wave velocity and attenuation in ocean sediment using a minimum amount of geological and geotechnical data is demonstrated. First, the Biot–Stoll theory is presented. Next, various asymptotic formulae for the attenuation coefficient are derived for high, low, and intermediate frequencies. These expressions clearly isolate the effects of intergranular Coulomb friction and fluid viscous dissipation on the attenuation of shear and compressional waves. Under the constraint of a minimum amount of geological and geotechnical information, a sequence of empirical equations is compiled to convert basic data, such as blow count number from a Standard Penetration Test or shipboard density, into sediment geoacoustic properties. As a demonstration, two well-known field cases, the Atlantic Generating Station (AGS) site and the Atlantic Margin Coring (AMCOR 6010) site, are examined. By incorporating the uncertainty involved in the data collection, the estimated geoacoustical parameters are provided with a standard deviation.

Abstract. An empirical fetch-limited ocean wave spectrum has been combined with an acoustic ray-based model to predict the acoustic signal time-angle fluctuations induced by sea surface roughness. Rough sea surface realizations are generated and used as sea surface boundaries with the acoustic model. To validate this model, results are compared against experimental data collected in a fetch limited region. These data includes simultaneous wind speed and acoustic propagation (1-18 kHz) measurements in a fetch limited coastal region. Modeled time-angle fluctuations compare well with field data at lower wind speeds (< 10 m/s).