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Exploring Observed Cognitive Error Types in Teams Working in Simulated Drilling Environments

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Advances in Human Factors in Energy: Oil, Gas, Nuclear and Electric Power Industries

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 495))

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Abstract

Errors made by drilling teams were observed during simulator-based exercises that formed part of a well control training course. Each course lasted four days and comprises both non-technical and technical theory with five simulator-based exercises. The exercises are observed for key team non-technical skills (NTS). In feedback sessions, the observers debriefed the team members about their areas of effective NTS performance and also where improvements could be made. This paper will specifically focus on the errors (i.e. performance that was classified as either ‘marginally below’ or ‘well below’ expectations) made by the teams during 105 observed exercises. An understanding of such errors will allow future training programs to focus on areas for improvement and designing training that transfers into the real rig-site.

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Appendix: Full Typology of Observed Cognitive Errors by Category and Rating

Appendix: Full Typology of Observed Cognitive Errors by Category and Rating

Team behavioural marker

Type of error

Marginally below expectations

Well below expectations

Count

%

Count

%

Team situation awareness

Information not shared with relevant other team members

25

17

6

11

Distractions during operations (no sterile cockpit)

19

13

12

21

Too much information available but not being paid attention too

15

10

0

0

Losing track of the current situation

11

8

6

11

Information present but missed

11

8

3

5

Accept only one assessment of situation (Tunnel vision)

10

7

7

12

Data misinterpreted

10

7

2

4

Fixated on non-existing problems

9

6

2

4

Failing to challenge the assumptions made by other team members

9

6

2

4

Poor structure to tool box talk

8

6

0

0

Important information disregarded

5

3

10

18

Initial parameters not recorded

5

3

1

2

Confirmation bias (looking for what they expected to see)

3

2

0

0

Actions carried out without other team members being advised

3

2

6

11

Total number of errors

143 

57 

Team decision Making

Team members not contributing to decision making process

30

21

19

29

Choosing first option discussed and no contingencies considered

22

15

26

39

No-one taking responsibility for making decisions

21

15

3

5

Options discussed but selected option not articulated

17

12

3

5

Team dividing into separate groups and making different decisions

14

10

4

6

Team members not assertively presenting their opinions or option(s)

12

8

3

5

Individual team members making decisions without involving other team members

10

7

2

3

Lots of discussion but no actual decision made

9

6

6

9

Inexperienced team members not being invited to contribute during decision making process

7

5

0

0

Total number of errors

142 

66 

 

Not verifying information being exchanged

44

22

28

25

Incorrect use of open or closed questioning

34

17

14

13

Unclear/non-specific instructions given or comments made

24

12

18

16

Use of leading questions

19

9

0

0

Multiple conversations taking place simultaneously

16

8

6

5

Roles not confirmed or allocated

14

7

19

17

Team members not listening or paying attention

13

6

5

4

Team members not participating in team discussions

13

6

13

12

Missing or poor handover

7

3

0

0

Interruptions while others speaking

7

3

7

6

Interference when other team members are performing tasks

3

1

0

0

Team members ignoring input from others during discussions

7

3

2

2

Total number of errors

201

112

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Crichton, M.T., Moffat, S., Crichton, L.M. (2017). Exploring Observed Cognitive Error Types in Teams Working in Simulated Drilling Environments. In: Cetiner, S., Fechtelkotter, P., Legatt, M. (eds) Advances in Human Factors in Energy: Oil, Gas, Nuclear and Electric Power Industries. Advances in Intelligent Systems and Computing, vol 495. Springer, Cham. https://doi.org/10.1007/978-3-319-41950-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-41950-3_9

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