Management, visualisation, and interpretation of large geotechnical and geophysical datasets for ground modelling of offshore wind farms has become a significant challenge.
With this in mind, at Cathie, we deal with increasingly large windfarm areas, greater quantities of exploratory holes and expanding volumes of laboratory tests. Despite this, many areas within the industry continue to utilise historic methods of presenting the data; this includes the likes of extensive PDF reports, heavy figures and often complex and complicated ArcGIS outputs.
However, there is now a clear, definitive move towards the use of ‘machine learning’ in the preparation of ground modelling outputs to aid engineering design. There is a perception within the market that this will primarily help organisations to work smarter and with increased efficiency. Although this is true, for Cathie, unless the initial data management, quality control measures and visualisation of factual data is adequately planned, then this trend will realise less value than predicted.
Cathie has worked alongside key developers in the industry, to advance these technologies and consequently improve the way we’re able to organise, present, and analyse our data in a dynamic and interactive way. We have paid particular attention to the reporting of geotechnical investigation data and its readiness of use in design; specially related to the following:
• Ground investigation field progress
• Laboratory testing progress and reporting
• Ground investigation interpretative reporting
Don’t take our word for it. Here’s a testimonial from leading developer, Atlantic Shores Offshore Wind, USA:
“The ability to quickly and reliably visualise tabular data allows for a real-time understanding of the data that’s being acquired. ASOW have benefitted greatly from the convenient visualisation of detailed soil parameters which allows for key project decisions to be made with ease.
“Our experience with the outputs has given us an insight into real optimisations that can be made at a glance, which may otherwise have gone unidentified – or been part of a more labour intensive approach.”
For more information, contact us today.