As we’ve moved through this analysis process and applied Mermaid to the consideration of how we can baseline and improve our performance two main objectives have repeatedly arisen:
- Work entirely in the spring and summer to reduce winter downtime.
- Maximise the time spent performing offshore operations when favourable conditions occur by reducing the number of transits required.
Here we are going to perform two simulations which it is hope will improve our performance.
There are two scenarios under consideration here:
- Two vessels operating, both vessels can carry a set of foundations at a time, one vessel is from the base case, the other is a different, slightly less capable vessel (i.e. its station keeping and access/depart operations are more limited).
- As for the previous scenario, but this time we’ve been able to add additional grillage to the base case vessel to allow 3 foundation units to be carried, the less capable vessel can only carry one unit. The division of work is that the more capable vessel will attempt to install 54 foundations, the less capable 18.
There are a number of ways to model these operations in Mermaid, but the simplest this time was to make copies of the base case files, set the number of repetitions to the appropriate number and modified the vessel accordingly. We’ve then concatenated the results in post processing.
The simulation was run for all the start dates used previously, however we’re only really interested in operations starting in March and accessing the whole summer season (as we’ve discussed previously) so let’s only consider these.
The chart below is an updated version of the one introduced in Part 4 and shows all the runs we’ve performed so far, including the particularly poor offshore loading and the discarded (due to the forced pause) split installation.
Using two vessels works particularly well and it’s possible to substantially reduce the duration of the installation to something around 100 days. As it currently stands two vessels both installing half a farm is slightly quicker (more on this later).
We must, however, consider the cost associate with this approach as whilst we have reduced the time we have vessels on hire for we have increased the number of assets we have taken and therefore the cost incurred each day is up.
Shown below are the vessel day rates associated with all the scenarios studied so far. Note that the less capable vessel use in this analysis has a slightly lower day rate than the other, more capable, vessel.
Using two vessels to install the farm in two halves is slightly more expensive than using one larger load vessel. Enabling the more capable vessel with a larger carrying capacity results in a cheaper installation. Both cases are significantly cheaper than our base case.
Looking at the green line, which shows this two vessel increased carry scenario, we can see a change in the gradient. This indicates a change in our daily expenditure, i.e. we off hire one of the vessels. We can also see the effect of this in the durations chart above. The progress made early in the installation is quicker than any other option, but we then off hire a vessel and the rate of progress slows. In the end, the installation completes slower than it might have otherwise done. Let’s scroll down and look at which vessel installs which foundations.
Each row in the image below represents one simulation (i.e. a different March start date across the whole metocean data set per row). Foundations installed by our more capable vessel are shown in green and the foundations installed by our less capable vessel are shown in blue. We can clearly see the point at which this latter vessel off hires.
The Next Steps
It looks, from the data presented, like we’re starting to reach a strategy which is cheap enough and quick enough to interest us. We’ve worked within some realistic constraints, i.e. we can only obtain one of our more capable vessel so have to settle for a less capable second vessel and that we can only fit additional grillage on to one of these vessels (for one reason or another).
Our strategy, however, is not quite finalised yet. It looks like out division of labour is incorrect in our simulations as we off hire the second vessel quite early. Realistically we’d keep both vessels going until all foundations are installed; we’d expect this to be quicker and probably cheaper. The question is, what division of labour produces the best result for us? We’ll take a look at this in the next post.