Full waveform inversion (FWI) is a data-fitting method that exploits the full information from the seismic data to provide high-resolution models of the subsurface. To reconstruct realistic models from field measurements the forward modeling should correctly account for wave propagation phenomena present in the recorded data. This mainly concerns the correct modeling of seismic amplitudes that are sensitive not only to the velocity variations, but also to the density, attenuation, seismic noise. The objective of this study is to investigate the role of density in the reconstruction of P-wave velocity models in the marine environment. We generated a realistic, synthetic data set with the conventional streamer geometry, and the frequency range from 3 to 20 Hz. We performed series of numerical experiments, testing various initial density models and different strategies for the density update. Our results suggest that it is important to include the realistic density information into the inversion scheme to bring improvement in the P-velocity reconstruction. Moreover, we investigated the potential benefits of multi-parameter inversion (P-velocity and density) of the noisy data, by considering random and spatially coherent noise. Density inversion has partly absorbed noise-related artefacts, which yielded better resolved P-wave models than the single-parameter inversion.


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