Improved workflow for Single-Channel Seismic surveys in offshore wind farm site assessments: a case study from Fangchenggang, Guangxi.

Abstract

A critical factor in the transition towards renewable energies is offshore wind, and therefore efficient site investigation to assure the safety and stability of the wind turbines' foundations is needed. Conventionally, borehole drilling and in-situ testing are used. Although these techniques can provide accurate geological data, their costs are prohibitive and their scope of survey is restricted. This drives the need for complementary geophysical survey methods. The Single-Channel Seismic (SCS) method is a cost-effective and rapid technique that can be employed for regional seabed survey. However, low signal-to-noise ratio (SNR) and poor stratigraphic continuity result when applying conventional processing workflow on seismic data obtained from complex settings, such as thick sand layers, shallow water environment with the presence of strong multiples, and sea surface swell conditions. To overcome these problems, an optimized SCS processing workflow which introduces three new techniques is proposed: (i) eigenvalue based swell correction with adaptive sliding window smoothing, (ii) shearlet transform based sparse representation of seismic data to remove random noise, and (iii) combined predictive deconvolution (for short period multiples) and SRME with Bayesian separation (for long period multiples). This algorithm has been applied to a field data survey at Fangchenggang, Guangxi (water depths: 0-25 m, total area is 99 km 2 ), and a substantial increase is observed: SNR enhancement from about 8-12 dB (from comparison with F-K spectrum analysis), the stratigraphic continuity improvement by factor of about 2.5 (estimated by reflection event tracing), and elimination of over 70% multiple energy within targeted range. The final result successfully delineates bedrock topography and structural settings required for wind farm installation site investigation. This new approach makes it possible to enhance shallow-marine seismic data quality even with difficult geological conditions and extract information indispensable for offshore wind farm development.