Geoacoustic inversion via genetic algorithm using a broadband signal and two hydrophones

An inversion method using a wide-band signal and two near field receivers is proposed. The inversion problem can be formulated into a probabilistic model composed of signals, a forward model and additive noise. A forward model to simulate wide-band signals, such as chirp signals, is chosen to be the source-wavelet-convolution plane wave modeling method. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the ranges for a priori uniform distribution is based. The genetic algorithm can be applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L₂ norm of the difference between measured and modeled signals. Not only the marginal pdf but also its statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm. The examples applied show that for synthetic data with noise, it is possible to carry out geoacoustic parameter inversion for the sedimentary layers using the proposed inversion method