BOPfailure3 {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. 4 of the referenced paper). Probabilities were given within the referenced paper. The vertices are:
- Kick_Detection_Failure
(F, S);
- X1
Mud volume/ flow change (F, S);
- X2
Circulation pressure change (F, S);
- X3
Gas-cut (F, S);
- X4
Mud property change (F, S);
- X5
Rate of Penetration (ROP) change Failure (F, S);
- X6
Mud tank (F, S);
- X7
Flow Failure (F, S);
- X8
Pump Failure (F, S);
- X9
Pump Rate (Stroke Per Minute: SPM) (F, S);
- X10
Mud density (F, S);
- X11
Mud conductivity (F, S);
- X12
Failure of tank level indicator (float system) (F, S);
- X13
Failure of an operator to notice the tank level change (F, S);
- X14
Failure of flow meter (F, S);
- X15
Failure of an operator to notice the flow meter (F, S);
- X16
Failure of pressure gage (F, S);
- X17
Failure of an operator to notice a change in SPM (F, S);
- X18
Failure of stroke meter (F, S);
- X19
Failure of an operator to notice a change in P.R (F, S);
- X20
Failure of gas detector (F, S);
- X21
Failure of an operator to notice the gauge (F, S);
- X22
Failure of the density meter (F, S);
- X23
Failure of an operator to the density meter (F, S);
- X24
Failure of resistivity (F, S);
- X25
Failure of an operator to notice the conductivity change (F, S);
- X26
Failure of the ROP indicator (F, S);
- X27
Failure of the ROP change (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.