Using Machine Learning Property Modeling with Assisted Forward Stratigraphic Modeling for Offshore Wind Farm Site Characterization

The integrated workflow discussed in this abstract is a combination of two-2 step approaches for creating predictive models for understanding the shallow sediment distribution effectively and to reduce the related uncertainty when it comes to designing and feasibility of piling foundations for Offshore Wind Farms. It is important to mention here that this workflow is essential and driven by the generation of answer products for reducing uncertainty on the foundation installation of Offshore Wind Farms, by creating predictive sediment models and use of these in estimating capacity for foundational installations by deploying machine learning property modeling workflow.