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Postgraduate research project

Reconciling geotechnical and seismic data to accelerate green energy developments offshore

Competition funded View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree View full entry requirements
Faculty graduate school
Faculty of Environmental and Life Sciences
Closing date

About the project

The offshore environment and the geosciences play a pivotal role in the sustainable production of green energy offshore [1] and the geotechnical characterization of the seabed requires technologies that are reliable and can cover large seafloor areas. This project aims at improving knowledge in the use of seismic data for estimating geotechnical parameters. 

The green and digital transition requires technology that can meet the demands of the growing renewable energy market, such as offshore wind, which focuses on the shallow seabed and covers large seafloor areas. Seismic data can provide a non-invasive approach to estimate geotechnical parameters for design of renewable energy infrastructure such as sediment strength, bulk and shear moduli, porosity, permeability, and their spatial variation. 

Geotechnical parameters derived from seismic data can also be used e.g. in the scoping phase of offshore developments for optimising the required in-situ sampling strategy. There is, however, uncertainty on how seismic wave velocities and attenuations relate quantitatively to the geotechnical parameters required for the design of offshore foundations of say wind farms. This uncertainty is due to the different loading frequencies and magnitudes, and deformation mechanisms experienced during geophysical and geotechnical tests. 

The main aim is to improve knowledge of and confidence in the use of seismic data for estimating geotechnical parameters by linking seismic and geotechnical properties. This will be achieved by developing a machine learning approach that uses (i) geotechnical and geophysical data and (ii) theoretical models that provide physical constraints to the relations between such data [e.g. 3]. The student will use open-access data mainly from the Dutch sector of the North Sea and data from the project partners NGI  and SAND Geophysics.  

The proposed research contributes to addressing the key challenge of rapidly increasing deployment of renewable energy infrastructure to meet the UK’s net zero carbon emission target by 2050. 

Supervisory team

The supervisory team includes supervisors from several organisations, including our INSPIRE Partners. Please contact the Lead Supervisor for more information about the team.


The INSPIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. 

The student will be registered at the University of Southampton and hosted at the School of Ocean and Earth Science. The student will gain specific training in: 

  • offshore geotechnical data interpretation and analysis
  • shallow sub-seafloor seismic data processing 
  • interpretation, geophysical and machine learning inversion, seismic wave propagation modelling, and rock physics modelling

The student will join the UK’s most active marine geophysics group in Southampton. They will have opportunities to participate in geophysical data acquisition in near-shore and/or deep ocean environments. In addition, the student may be able to participate in a commercial marine geotechnical/geophysical investigation with one of the external project partners (NGI and/or SAND Geophysics). 

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