An investigation of algorithm-induced variability in geoacoustic inversion

This paper investigates the inherent variability in the results of matched-field geoacoustic inversion algorithms. This algorithm-induced variability must be considered when interpreting inversion results in terms of environmental changes as a function of time or space. Fast simulated annealing (FSA), genetic algorithms (GA), and a hybrid algorithm (adaptive simplex simulated annealing; ASSA) are compared by performing multiple inversions of benchmark synthetic data (noise free and noisy) and acoustic data measured over both low- and high-speed sea-bed sediments in the MAPEX 2000 experiment. ASSA produced the lowest variability in inversion results for all cases, followed by GA and FSA. For the high-speed MAPEX 2000 case, the variability is essentially negligible, while for the low-speed case the variability is significant as compared with environmental variations reported in the literature.