Case Study

In the interviews conducted with the RNNP (2014) study, one of the persons described a sce- nario that could be experienced, and that causes challenges for the control room operators. The scenario was as follows (Vinnem, 2014a): During normal operations, only one crew mem- ber is present in the control room and the other crew member is “somewhere” doing “some- thing else”. Even though the guidelines to the Activity Regulations, section 31, indicates that there should be at least two persons in the control room (PSA, 2014b), this is seldom the case. The one crew member that is present in the control room is then responsible for the ballast- ing operations. The scenario starts out with a counter ballasting operation to compensate for some heavy lifting, for example lifting of casing pipes onto the platform from a supply vessel. During this operation a ballast valve breaks down and no immediate redundancy is available, causing the ballasting operation to stop. It was indicated that this causes a lot of stress for the control room operator. The question now is, how does these events affect the risk of loosing stability?

To analyze this scenario, the states are given to the affected RIFs is shown in table 6.8. With no additional information about the remaining RIFs, these are not instantiated. The analy- sis results in a probability of being in state bad of 42%, compared to 32% without evidence.

RIF State Description

Stress f It was indicated that this was one of the most stressing scenarios encountered, and hence estimated to be state

f .

Simultaneous Activities d A situation where two operations that affects stability are conducted simultaneously.

Work Practice d The practice of not following the guidelines to the activi- ties regulations, by only employing one control room op- erator

Valves f A breakdown in a component with no redundancy caus- ing the ballasting operation to stop is considered to be state f

Table 6.8: Evidence provided to the model to analyze the case study

Figure 6.9 shows how the probability of being in the three states changes when evidence is pro- vided.

(a) No evidence (b) Evidence provided

Figure 6.9: Probability distribution of center node with no evidence and evidence according to case study

Figure 6.10 shows the BBN and the specified RIFs that are instantiated. All the RIFs that are not given any evidence have a probability distribution equal to the communication RIF as il- lustrated in figure 6.10. The resulting probability distributions for the three barrier functions in the middle circle can be used to estimate the probability of loosing stability according to equa- tion 4.4 given on page 40. Again, the result here is as compared to the world average.

Ploss of stability= Pbasi s n X i =1 wi f X k=a Pi kQi k = 2.85 · Pbasi s = 2.85 · 27 · 10−4 (6.4)

From equation 6.4 we can see that the probability of loosing stability is almost three times higher when the situation explained above occurs. This result is very high, and this is due to the evidence that is used. Since only four nodes were instantiated, and these were all in a condition worse than average, this will cause the result to be far worse than what it realistically is. If all the other RIFs also were instantiated the result would be better, but since the condition of the other RIFs are unknown in this case, they are not taken into consideration in this analysis. However, it may be reasonable to assume that the other RIFs are in an average state, c. An analysis was performed to find the probability of loss of stability with the RIFs as specified in table 6.8, and all other RIFs in state c. The result was Ploss of stability= 2.12 · Pbasi s = 5.73 · 10−3per platform

year. This is a more valid result, because all RIFs are instantiated, hence reducing the uncer- tainties involved. The assumption here is that all other RIFs are in state c, which is unknown in our case. This does however show the strengths of how BBNs are capable of handling uncer- tainties, but the result must also be treated thereafter. When some RIFs are uninstantiated, it is clear that the result from the model will be conservative, this is shown as a higher probability of loosing stability.

A similar analysis has been done for the cases studied in the MTO analyses in chapter 5.2.1. The PLoss of stabilityis given in table 6.9, and screenshots from the GeNIe analysis can be found

in appendix E. These analyses are based on the information provided by the accident reports, and the author has used subjective interpretation to assign RIF states based on the available information. The column of “only affected RIFs instantiated” shows the probability of loos- ing stability when only the RIFs that were not in an average state are given evidence, whereas the “all RIFs instantiated” shows the probability when RIFs without a specified state are given evidence of being in state c.

Probabilty for loss of stability

Unit Only affected RIFs instantiated All RIFs instantiated Ocean Ranger 3.48 · Pbasi s= 9.40 · 10−3 2.84 · Pbasi s= 7.68 · 10−3

Thunder Horse 3.55 · Pbasi s= 9.57 · 10−3 3.13 · Pbasi s= 8.45 · 10−3

Scarabeo 8 3.33 · Pbasi s= 8.98 · 10−3 2.85 · Pbasi s= 7.70 · 10−3

(...) 2.83 · Pbasi s= 7.66 · 10−3 2.26 · Pbasi s= 6.10 · 10−3

Table 6.9: Results from BBN analysis of MTO cases

As for the case study analysis, the probabilities in the MTO cases are also quite high, and a similar argumentation must be considered for these cases. By providing evidence for the re- maining RIFs, assuming that they are in an average condition, c, the probabilities of stability loss are reduced. It is interesting to notice that the Thunder Horse accident results in a higher probability than the Ocean Ranger, even though the Ocean Ranger was more severe in terms of loss of lives and assets. In a way we can say that the Ocean Ranger (and Alexander Kielland) accidents saved the Thunder Horse, due to new design regulations.