Investigating gradients in mud based on Bayesian modal-dispersion inversion and a hybrid geoacoustic model parameterization

Abstract

An important issue in understanding seabed geoacoustic properties at the site of the 2017 Seabed Characterization Experiment (SBCEX) on the New England Mud Patch is the extent to which gradients exist in geoacoustic properties (sound speed and density) over the upper mud layer. This paper applies Bayesian inversion and uncertainty quantification to modal dispersion data, resolved by warping analysis, to consider whether mud-layer gradients are required to fit the data. The inversion is based on a hybrid seabed-model parameterized in terms of an upper sediment layer with a general representation of smooth, continuous gradients in geoacoustic properties based on Bernstein-polynomial basis functions, above an unknown number of discrete layers formulated trans-dimensionally. The inversion results are compared to those from other acoustic data sets collected in the region as well as to nearby core measurements.