Determining the likelihood of incidents caused by human error during dynamic positioning drilling operations

Sanchez-Varela, Zaloa; Boullosa-Falces, David; Larrabe-Barrena, Juan-Luis; Gomez-Solaeche, Miguel A.

doi:10.1017/s0373463321000291

Cited by 4 publications

(3 citation statements)

References 41 publications

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“…The configuration of the DP system is different on each occasion, and it is not the same as the need for a drilling platform, which needs to stay stationary in a position, as the configuration is required for ROV operations and the vessel needs to follow up a predefined route. According to this explanation, the results differ from those of Sanchez-Varela et al [27] for drilling operations. Although the same independent variable, the percentage of thrusters, is considered in the model, the equation defined for DP drilling operations is more robust than the one presented in this paper.…”

Section: Limitations Of This Studycontrasting

confidence: 82%

“…Sanchez-Varela et al [27] proposed a method to determine the odds of incidents caused by humans during dynamic positioning drilling operations. The authors collected data on incidents and associated human causes during drilling operations and used statistical techniques to identify the factors contributing to incidents caused by humans.…”

Section: The Human Elementmentioning

confidence: 99%

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Analysis of Human-Related Incidents during Dynamic Positioning Operations

Sanchez-Varela,

Boullosa-Falces,

Skoko

et al. 2024

JMSE

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Dynamic positioning systems ensure additional position accuracy in different operations in the maritime industry, such as shuttling, drilling, diving, pipe laying, and others. Although they are known to be robust systems, they are not exempt from failures leading to incidents, among which we can find human-related incidents. This research analyzes 62 human-related dynamic-positioning incidents and aims to determine which segment in the dynamic positioning system influences these occurrences by applying binary logistic regression modeling techniques in the test sample and validating the results using a control sample. The results indicate that thrusters have the most significant influence on human-related incidents; however, not all DP operations are affected in the same measure. By stratifying the database and considering the different operations in progress, it is noted that human-related incidents while drilling operations are in progress are effectively influenced using a higher percentage of thrusters online.

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Section: Limitations Of This Studycontrasting

confidence: 82%

Section: The Human Elementmentioning

confidence: 99%

Analysis of Human-Related Incidents during Dynamic Positioning Operations

Sanchez-Varela,

Boullosa-Falces,

Skoko

et al. 2024

JMSE

Self Cite

View full text Add to dashboard Cite

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“…Several studies have covered the importance of human errors in the maritime industry in general (13-15) and during DP operations in particular (16)(17)(18). Human errors are very interesting from the training point of view because they can be studied and somewhat corrected through different training.…”

Section: Dp Training and Certification Schemementioning

confidence: 99%

Human error analysis in dynamic positioning incidents according to the nature of the operations in progress

Varela¹,

Boko²,

Skoko³

et al. 2022

Maritime Transport Conference

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Human errors are known to contribute to incidents in the maritime industry. Although the dynamic positioning operator has to undergo a standard training schedule before becoming a full operator, human errors contribute to 20% of the incidents in dynamic positioning operations. This research aims to investigate which dynamic positioning operations have a more considerable percentage of human errors. With a 266 dynamic positioning incidents database, different offshore operations are classified and then cross-tabulated with the human causes, classified as either primary or secondary cause as described in the incident report. The results and discussion present that drilling and diving operations are significantly correlated with human causes. This study's results could help provide better directions for the training schedule, proposing simulator exercises based on these scenarios.

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Learning-based framework for industrial accident prevention: fuzzy cognitive mapping approach

Boulagouas,

Guelfen,

Karoune

2024

IJQRM

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PurposeDespite efforts to improve safety management practices in industrial companies, major accidents seem to be inevitable. Many accidents still occur because companies are unable to learn from past occurrences due to ineffective incident and accident learning processes. This study proposes a learning-based framework for industrial accidents investigation and contributes to accident prevention research.Design/methodology/approachThe proposed learning process includes the analysis of the industrial accident using the Event Tree Analysis (ETA) method, capitalisation of causative factors using the Swiss Cheese Model (SCM), and finally modelling the relationships among the accident causative factors and analysing their causality using the Fuzzy Cognitive Mapping (FCM) technique and running learning scenarios.FindingsThe proposed learning process was applied to an industrial accident, and the results showed that human unsafe behaviours and unsafe supervision were the principal causative factors of the blowout accident.Practical implicationsThe proposed learning-based framework provides a structured approach for oil and gas companies to systematically analyse and learn from past accidents, enhancing their prevention strategies. Theoretically, the framework bridges the gap between theory and practice by demonstrating how established accident analysis methods can be combined and applied in a real-world industrial context.Originality/valueThe proposed learning process combines accident analysis and investigation techniques with simulations for an in-depth and robust learning-based framework for accident prevention.

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Determining the likelihood of incidents caused by human error during dynamic positioning drilling operations

Cited by 4 publications

References 41 publications

Analysis of Human-Related Incidents during Dynamic Positioning Operations

Analysis of Human-Related Incidents during Dynamic Positioning Operations

Human error analysis in dynamic positioning incidents according to the nature of the operations in progress

Learning-based framework for industrial accident prevention: fuzzy cognitive mapping approach

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