Development of Probabilistic Geotechnical Ground Models for Offshore Engineering

Abstract

Traditional offshore site investigation (SI) practice focuses on characterising ground conditions around a single asset and its spatially-limited foundations. Applying a conventional approach to both widely distributed and deep water sites often limits the scope of geotechnical data gathering to principally remote geo-physical sensing combined with sparse sampling of questionable representative-ness. SI design can be improved to cope with distributed assets and multiple geo-hazards, while better SI sequencing and recent advances in geophysical techniques have improved the SI process considerably. However, the time and cost implications of applying these advances are potentially unacceptable when dealing with multiple facility footprints distributed over broad areas of seabed with complex, heterogeneous ground conditions, e.g., wind farm developments on the UK continental shelf. A cost-effective alternative that integrates the inter-disciplinary SI functions better and embraces probabilistic ground models is required. Applying techniques developed for seismic hazard assessment with limited data sets, probability distribution functions can be derived allowing rational, fact-based ‘forecasts’. This approach permits limited datasets to be evaluated for both epistemic uncertainty (data paucity) and aleatory (natural) variability, allowing the selection of representative geotechnical parameters. Probabilistic methods and spatial analysis techniques are applied to synthetic models of the seabed for the purpose of testing the effect of sampling, size and pattern, in accurately determining soil parameters, such as the undrained shear strength and friction angle or engineering parameters like pile penetration depth. A number of different sampling patterns are examined. The results suggest that there is a relation between pattern efficiency in describing the uncertainty and the existence of spatial trends in soil parameters or the existence of features like buried channels. These approaches have the potential to increase the efficiency of offshore SI, leading to more cost effective foundation design.