Abstract
This paper applies Bayesian geoacoustic inversion with a hybrid seabed model parameterization to modal-dispersion data from the New England Mud Patch to attempt to estimate gradient structure in the upper mud layer. The hybrid seabed parameterization is based on an upper layer with a general representation of gradients based on Bernstein-polynomial basis functions, above an unknown number of discrete (uniform) layers formulated trans-dimensionally. The dataset, collected during the 2017 Seabed Characterization Experiment (SBCEX17), involves high-order modes (up to mode 21) extracted via warping time-frequency analysis from recordings of a combustive sound source on a vertical hydrophone array. The inversion results are compared to those from a trans-dimensional inversion of the same data with no gradient layer, and to results from other acoustic data sets collected in the region as well as to nearby core measurements.
Published Version
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