Risk Analysis of Oilfield Gathering Station
Bibliographic record
Abstract
Risk analysis and evaluation of oilfield gathering station (OGS) is a challenging task, given that much of the available data are highly uncertain and vague, and many of the mechanisms are complex and difficult to understand. A combinational method of analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) is proposed in this study to assess hazards in OGS associated with multiple subsystems’ failures. The evaluation index system of safety performance in OGS was established, which included tank unit index, pipe unit index, digital monitoring unit index, and other systems. The weight of each index was confirmed through AHP method. Then the AHP and FCE methods were combined to validate the risk levels of representative enterprise S (S‐OGS). The evaluation results show that the evaluation grade of S‐OGS was low risk. This study provides a basis to improve the risk levels of OGS. It is expected that this work may serve as an assistance tool for managers of enterprise in improving the risk levels of oilfield operations. © 2018 American Institute of Chemical Engineers Process Process Saf Prog 38: 71–77, 2019
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".