Offshore wind energy is rapidly becoming a significant source of renewable energy, with numerous projects underway globally. In Norway, the Norwegian Petroleum Directorate (NPD) has started the process for near subsurface mapping for offshore wind installations for the Sørlige Nordsjø II and Utsira Nord area.
One of the key challenges in developing offshore wind farms is the geospatial variability and complexity of the geology of the seabed (seafloor and sub-seafloor), which can impact the foundation concepts, their dimensions, stability and performance of the wind turbines (geo365.no: Krevende bunnforhold for norsk havvind).
A high volume of multi-disciplinary data is needed to unlock the full potential for offshore wind installations. Norwegian Geotechnical Institute (NGI) and SAND Geophysics (SAND) have integrated seismic, geotechnical data and machine learning (geostatistical) in a holistic ground model, to improve site characterisation and risk assessment in a quantitative way.
Data that conventionally has been used for geotechnical purposes only, Cone Penetration Testing (CPT), now becomes integrated with very-high-resolution seismic data, as the building blocks for a data-driven site characterization and engineering design.
CPT is a geotechnical in situ testing tool which measures a number of parameters while the rod is being pushed into the seabed with a constant velocity, which can then be used to obtain critical information about the soil units.
The model was built based on a generic quantitative workflow that includes soil properties relevant for geotechnical applications (foundation design, geohazard assessment, layout design etc.). At the Netherlands Enterprise Agency’s webpage (TNW General Information) you will find more information published about TNW, including reports, raw data and the final ground model.
NGI and SAND Geophysics acknowledge RVO for awarding the work and allowing publication.