In this thesis, we focus on two areas relevant to improving near-surface offshore seismic surveys : inversion-based estimation of subsurface properties and the monitoring of the acquisition-geometry. These issues remain challenging in ultra-high-resolution (UHR) marine geophysics, where imaging the first tens of meters below the seafloor can be limited by both data quality and instrument uncertainties. Through a combination of modelling- and field-data studies and experimental hardware development, we investigate the possibilities for enhancing the characterization of this shallow region which is of interest for the development and monitoring of offshore infrastructure and subsurface resources extraction....

Poor knowledge of source and receiver positions in ultra-high-resolution marine seismic data is the cause of severe damage which requires novel processing techniques to mitigate. This type of seismic data is highly relevant for ultra-shallow subsurface imaging in geo-engineering projects both offshore and in harbours. Current positioning technologies are limited partly by their accuracy but also the fact that they are only placed on head and tail buoys of the towed arrays. This leaves receiver locations on the length of the streamer cable to be interpolated. Rather than developing additional processing methods, we propose to improve the quality of the data by introducing a complimentary receiver positioning system to reconstruct the shape of the streamer cable in 4D using Fiber Optic Shape Sensing (FOSS) technology. In this abstract, we outline the key features of FOSS technology and provide a conceptual overview of our efforts to bring this technology to the field.

Full waveform inversion (FWI) is a popular high-resolution velocity estimation technique which is distinctively hindered when applied to the shallow-subsurface due to the high level of noise, complex structures,\elastic effects as well as the often lacking low frequencies in the dataset. In this abstract we propose a to use a data-driven, reflection based inversion technique (Joint-Migration Inversion (JMI)) to create a starting model for FWI which pushes the inversion out of a local minimum to recover previously hidden structures. The research is applied to a 2D acoustic model and compares the results of using three different types of starting model, including one generated using JMI.