Risk Analysis of Oilfield Gathering Station
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it