Jack up rigs are used widely in offshore drilling and for offshore wind turbine installation. Such rigs can be often times supported by spudcan footings such as the ones shown below. However, there are multiple challenges in evaluating the capacity of such footings.

Punch-through of spudcan legs for offshore barges is defined as rapid uncontrolled barge leg penetration into the seabed. Such an event could result in catastrophic damage and even loss of lives such as the one shown in the figure below.

Spudcan legs jacked against seabed that is made of interbedded soil layers creates a recipe for potential punch-through. In addition, the presence of a strong soil layer on top of a weak layer can contribute to sometimes unaccounted for punch-through. These risks can be quantified using a probabilistic approach as a decision-making tool.

Barges are typically proof-loaded by vertical preloading through water ballasting prior to being operational, in order to obtain a safety margin against extreme storm design events. It is a common practice to assess the potential for barge leg penetration into the seabed using both lower and upper bound soil parameters. This analysis requires engineering judgment to choose the right soil parameters based on the available soil information using a deterministic approach. A more informative methodology is to perform a quantitative probabilistic study taking into account all possible variable soil data as well as other uncertainties. Insurance companies may be more willing to insure a project once the risks of failure are properly quantified.

A probabilistic analysis can be performed easily when the variability of soil properties or other input parameters is known. The most common approach is to assume that a normal distribution with a specified mean value and a standard deviation of a parameter, based on the available geotechnical information, can accurately represent the “randomness” of such input parameters. The parameters can be soil properties such as undrained shear strength and friction angle, or geometry parameters (e.g., soil layer thickness).

Such analyses can be commonly performed with simple random number generator tools, two way data tables (What-if Analysis) in tools like Excel. A common way to incorporate probabilistic data from multiple variables is a Monte Carlo simulation. Via this simulation, a cumulative probability distribution function of the spudcan footing’s factor of safety can be determined. An example of such a cumulative probability curve is shown in the figure below. An engineer, a project owner, or an insurance agent can then be able to better represent the uncertainty in the factor of safety calculation. For example, in the schematic below, there is only a 20% probability for the factor of safety to be less than 2, and a 90% probability that the factor of safety is less than 3.

This simple probabilistic approach can be applied to any engineering equation to quantify the associated results in a simple risk language.

*Assem Elsayed is the Vice President and Practice Area Leader of GeoStructural Engineering at Geocomp. Assem has extensive experience with waterfront and marine structures, design of monopiles for wind farms, and support of deep excavation.*