Workshop 2

Description

To meet the carbon dioxide emissions pledges made by governments across the globe, there needs to be a drastic, worldwide shift in energy sources towards a mixed renewables solution that can balance demand, reliability and cost. Offshore renewable energy sources, such as wind, wave and tidal, are seen as key elements in this new energy approach, offering the possibility to generate clean energy on an extremely large scale. But, to meet the global emissions targets, offshore renewables capacity needs to increase rapidly, which in turn means exploring and deploying new approaches to streamline the development timescale, maximizing the information from all available data. To this end, there has been significant interest in recent years around the development of fully integrated, quantitative ground models that seek to integrate information from all available disciplines (geology, geotechnics and geophysics) into a single, spatially continuous model of the ground conditions.

We propose a workshop that will bring together all parties involved in the development and use of quantitative ground models for offshore renewables projects. We want to stimulate an open debate that involves everyone associated with the multi-faceted process, including: geoscientists, who are heavily involved in the model development from an early project phase; geotechnical engineers, who incorporate the results into engineering ground models and subsequent infrastructure design; data scientists and geostatisticians, who link the various parameters and establish the 3D soil property population and assess the uncertainties; and end-clients, who finance and over-see the whole project cycle. In doing so, we aim to address five key questions surrounding the current status and future development of quantitative ground models:

1. What can we achieve using the quantitative ground models as currently available and how do these models provide benefit to site characterization for renewables infrastructure?
2. How do these quantitative ground models best fit into the site development workflow to maximize impact, reducing the time and resource for the required volume of site characterization?
3. How should these quantitative ground models be considered by engineers for the design of offshore renewables foundations?
4. What advances are necessary, in terms of geophysical data acquisition, processing, analysis, validation and/or modelling methods, to make quantitative ground models more robust or useful for engineering applications?
5. What should/could be done to improve geotechnical and borehole geophysical data acquisition tools and methods (including acquisition procedures) to make quantitative ground models more robust or useful for engineering applications?

The impacts of such a workshop will be three-fold. Firstly, to broaden the awareness of current state-of-the-art quantitative ground modelling capabilities for offshore renewables by engaging with the broad range of interested parties. Secondly, to bring experts in the different disciplines (e.g., geophysicists, geologists, geotechnical engineers [including foundations, anchors and cables specialists], ground modelers, data scientists, project managers and decision makers) together for an open and frank discussion on the current state-of-the-art outputs from integrated ground models and how these are best deployed to maximise impact. Thirdly, to identify gaps in our technical ability and/or knowledge-base that can form the focus of research and development activities over the next 5 to 10 years.

Sub-Topics that will be covered in the workshop:

The potential topics covered by the workshop are broad. However, we particularly encourage submissions targeting one of more of the following sub-topics”

• • Geophysical and geotechnical data acquisition, processing, and interpretation;
  • Design considerations, hazards and constraints, data presentation, uncertainty and accessibility;
  • Inversion and/or Machine Learning (applied independently or via an integrated approach);
  • Ground Modelling, GIS, (geo)statistics, regulatory compliance and certification, geological context and case histories.