Evaluation of Inherent Safety Potential in Offshore Oil and Gas Activities
Bibliographic record
Abstract
The inherent safety approach is the best option for hazard/risk management in offshore oil and gas activities. Some of the main drivers for inherent safety in the offshore industry are to reduce manning levels and provide minimum facilities installations, encourage the use of compact and simple technology, and reduce the need for operators to be present. Though this approach is comparatively mature and has been widely accepted in onshore process industries, its applications in offshore industries are still limited. A recent pilot study to assess the extent to which the concept and principles of inherent safety are being applied in the development and design of offshore oil and gas installations revealed that the term inherent safety is only just beginning to be recognized in the industry, mainly as a result of its inclusion in the Design Safety Case Guidance, and the UKOOA Fire and Explosion Hazard Management Guide. There appears to be a number of subtle but significant differences of opinion as to what inherent safety is, including ‘hazard avoidance’, ‘hazard prevention’, ‘risk minimization’, and ‘good engineering’. While all of these may form part of an inherently safer strategy, they do not encompass a full understanding of the role of inherent safety. This paper discusses inherent safety in offshore oil and gas activities and presents methods to evaluate inherent safety potential. It also highlights areas for further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".