Finding a realistic velocity distribution based on iterating forward modelling and tomographic inversion

Tomography is like a photograph that was taken by a camera with blurred and defective lenses that deform the shapes and colours of objects. Reporting quantitative parameters derived from tomographic inversion is not always adequate because tomographic results are often strongly biased. To quantify the results of tomographic inversion, we propose a forward modelling and tomographic inversion (FM&TI) approach that aims to find a more realistic solution than conventional tomographic inversion. The FM&TI scheme is based on the assumption that if two tomograms derived from the inversion of observed and synthetic data are identical, the synthetic structure may appear to be closer to the real unknown structure in the ground than the inversion result. However, the manual design of the synthetic velocity distribution is usually time-consuming and ambiguous. In this study, we propose an approach that automatically searches for a probabilistic model. In this approach, a synthetic model is iteratively updated while taking into account the bias of the model in previous stages of the FM&TI performance. Here, we present an example of synthetic modelling and real data processing for an active source refraction data set corresponding to a marine profile across the subduction zone in Chile at about 32°S latitude. A key feature of the model is a low-velocity channel above the subducted oceanic crust, which was defined in the synthetic model and expected in the real case. The conventional first arrival traveltime tomography was barely able to resolve this channel. However, after several iterations of the FM&TI modelling, we succeeded in reconstructing this channel clearly. In the paper, we briefly discuss the nature of this low-velocity subduction channel, and we compare the results with other studies.