Managing Process Safety in a Decommissioning Project
Bibliographic record
Abstract
Abstract Michael Green, Conor Crowley and John Spiteri (Atkins Limited – SNC Lavalin). Lee Allford (Energy Institute) It is estimated that more than 120 platforms with a combined weight of more than 1 million tonnes will be decommissioned over the next 10 years in the North Sea alone. This will involve a significant number of personnel engaged offshore in potentially hazardous operations during the removal of these facilities, underlining the need for ensuring high standards of process safety within the associated decommissioning projects. The need for effective management of process safety during decommissioning was highlighted in the major structural collapse incident at the Didcot power station in the UK in 2016 that resulted in 4 fatalities. This together with the fact that the police and HSE are conducting a joint investigation to consider corporate manslaughter, gross negligence manslaughter and health and safety offences, highlights the gravity of getting it wrong. With support from the Energy Institute and cross-industry involvement from oil companies, contracting companies and the UK Safety Regulator, new guidance has been developed that will support those engaged in decommissioning offshore facilities to plan, design and execute their projects so as to manage risk from major accident hazards (Energy Institute, 2019). This paper presents the key elements of this guidance which provides a roadmap to managing process safety across the lifecycle of a decommissioning project, from initiation through execution. The guidance is set-out according to typical phases of a decommissioning project, providing useful insights into key process safety considerations, objectives, tasks and outputs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".