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Lecture

Data-driven geo-solutions for efficient offshore wind foundations, London

Event organised by Offshore Engineering Society

Date
02 October 2019
Time
19:00 - 21:00 BST (GMT+1)
Location
Institution of Civil Engineers
One Great George Street
Westminster
London
London, SW1P 3AA
United Kingdom

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Overview

For offshore wind farm developments, there is potential for significant cost savings by utilising all collected data in improved integrated and streamlined quantitative geo-models.

Reduced costs result from better planning of geophysical and geotechnical site investigations, better prediction of soil parameters and associated uncertainties and early-phase semi-automated foundation design at specific unsampled locations as well as across the entire site.

Hence, these data-driven geo-solutions provide robust tools for improved site characterisation, and hazard and risk assessments associated with the foundation design in different phases of a project, ultimately leading to efficient foundation designs.

The keystone in the data-driven solution is the quantitative ground model which provides a tool to estimate various soil parameters as well as their associated uncertainties, through the full integration of geological, geophysical and geotechnical data, across the development site. This presentation by Rasmus T. Klinkvort will provide a summary of the latest work on quantitative ground models done in cooperation with Maarten Vanneste, Guillaume Sauvin, Carl Fredrik Forsberg from NGI and Mark Vardy from SAND Geophysics.

A workflow has been developed to build quantitative ground models and to evaluate the associated uncertainties. The presentation will first discuss why the in-depth integration of geology, geophysics and geotechnics is important and what the challenges are.

The workflow will then be illustrated using publicly available data from the Holland Kust Zuid wind farm site in the Dutch sector of the North Sea. Keywords in this workflow are Quantitative Interpretation, Seismic Inversion, Machine Learning and Geostatistics. The focus is to understand the associated uncertainties when using data-driven models to evaluate geotechnical parameters.

The next step is to demonstrate how the quantitative ground model is efficiently used in foundation design, for example, how we can obtain optimal monopile foundation geometry for the entire wind farm area, also for non-borehole locations. Finally, the presentation will provide some challenges, ideas and recommendations on the way forward to implement these models in practice.

For more information please contact:

Elira Alushi