BOPfailure1 {bnRep} | R Documentation |
BOPfailure Bayesian Networks
Description
Providing a comprehensive approach to oil well blowout risk assessment.
Format
A discrete Bayesian network for risk assessment of oil well blowout (Fig. 5 of the referenced paper). Probabilities were given within the referenced paper. The vertices are:
- BOP_System_Failure
(F, S);
- X1
BOP stack failure (F, S);
- X2
Valve failure (F, S);
- X3
BOP control system failure (F, S);
- X4
Line failure (F, S);
- X5
Choke manifold failure (F, S);
- X6
Annular preventer (F, S);
- X7
Ram preventer (F, S);
- X8
Kill valve fail (F, S);
- X9
Choke valve fail (F, S);
- X10
Choke line fail (F, S);
- X11
Kill line fail (F, S);
- X12
Upper annular preventer fails (F, S);
- X13
Lower annular preventer fails (F, S);
- X14
Upper pipe ram fail (F, S);
- X15
Middle pipe ram fail (F, S);
- X16
Lower pipe ram failure (F, S);
- X17
Blind shear ram failure (F, S);
- X18
Power system failure (F, S);
- X19
4Way valve failure (F, S);
- X20
Remote panel valve failure (F, S);
- X21
Signal line failure (F, S);
- X22
Accumulator line failure (F, S);
- X23
Air-driven pump failure (F, S);
- X24
Electric pump failure (F, S);
- X25
Choke valve failure (F, S);
- X26
Hydraulic choke valve failure (F, S);
- X27
Gate valve failure (F, S);
- X28
Choke remote panel failure (F, S);
- X29
Hydraulic choke valve failure (F, S);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Satiarvand, M., Orak, N., Varshosaz, K., Hassan, E. M., & Cheraghi, M. (2023). Providing a comprehensive approach to oil well blowout risk assessment. Plos One, 18(12), e0296086.