Society faces two critical challenges: 1) increasing energy demand and 2) effects of climate change. These challenges require decarbonisation of the energy system by increasing the use of renewable and clean resources, and implementation of CO2 mitigation strategies. In this context, the offshore environment and the geosciences both play a pivotal role in the sustainable production of green energy offshore and reduction of CO2 emissions [1]. Then, we require accessible, transparent and cost‐efficient seabed characterization technologies. For the green and digital transition, these technology components should satisfy the demands of the emerging renewable energy market, such as offshore wind, which focuses on the shallow sub-seafloor and cover large seafloor areas. Currently, it is time consuming and costly to collect, integrate, and process all the data required for the design and construction of green energy developments offshore. The aim of this project is to develop a physics-constrained, data-driven approach to estimate geotechnical parameters from seismic data. This approach encourages in-situ and non-intrusive geotechnical parameter estimation and reduces the number of samples to be tested in the laboratory. Ultimately, it promotes the use of green geo-resources offshore by reducing uncertainty, costs and time in the design of offshore foundations.
Seismic data can provide a cost-efficient, non-intrusive approach to estimate geotechnical parameters such as sediment strength, bulk and shear moduli, porosity, permeability, and their spatial variation. Seismic data-derived geotechnical properties can be used e.g. in the scoping phase of offshore developments for optimising the required in-situ sampling strategy [2]. There is, however, uncertainty on how seismic wave velocities and attenuations relate quantitatively to the geotechnical parameters required for the design of offshore foundations. This uncertainty is associated to the different loading frequencies and magnitudes, and deformation mechanisms experienced during geophysical and geotechnical tests (both in-situ and in laboratory tests). These differences partly justify the use of empirical correlations as common practice at present. The principal aim of this project is to increase confidence in the use of seismic data for geotechnical parameter estimation by linking seismic and geotechnical properties at a more fundamental-mechanistic level [e.g. 3]. This will be achieved by developing an open access and generic physics-constrained data driven approach. For training and testing the model the candidate will use open-access geotechnical and geophysical data from the Dutch sector of the North Sea and other relevant data from the project partners NGI and SAND Geophysics.
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. Specific training will include: offshore geotechnical data interpretation and analysis, shallow sub-seafloor seismic data processing and 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. They will have opportunities to participate in geophysical data acquisition in near-shore and/or deep ocean environments. In addition, the student may participate in a commercial marine geotechnical/geophysical investigation with one of the external project partners NGI and/or SAND Geophysics.
Please see https://inspire-dtp.ac.uk/how-apply for details.
[1] Velenturf et al. (2021). Geoscience solutions for sustainable offshore wind development, Earth Science, Systems and Society Review, doi: 10.3389/esss.2021.10042.
[2] Vardy M. E., Clare M. A., Vanneste M., Forsberg C. F., and Dix J. K. (2018). Seismic Inversion for Site Characterization: when, where and Why Should We Use it? Proc. Annu. Offshore Technol. Conf. 3,2089–2097, doi:10.4043/28730-ms
[3] Marín-Moreno, H, S K Sahoo, and A I Best. 2017. “Theoretical Modeling Insights into Elastic Wave Attenuation Mechanisms in Marine Sediments with Pore-Filling Methane Hydrate.” Journal of Geophysical Research: Solid Earth 122 (3): 1835–47, doi: 10.1002/2016JB013577.
