Risk Assessment of Gas Condensates Export Pipelines by Indexing Method (Case Study: Special Economic Energy Zone of South Pars-Assaluyeh)
Bibliographic record
Abstract
Due to the sensitivity and vital and undeniable role of gas energy in the energy basket of the country, especially in economy, evaluation of risk assessment studies on the designing and exploiting of this massive and extensive industry including oil and gas pipelines seems to be very necessary. Generally, risk assessment is process of the determining the risk quantity and quality by analyzing potential risks in the project which will be done by taking into account the sensitivity or vulnerability of the surrounding environment. kent Muhlbauer’s method based on relative scoring of parameters that are involved in risks creation deals with the risk assessment. In order to establishment this system for risk assessment of statistical data collection, due to the failure of Iranian oil and gas pipelines, experts and scholars’ experiences as a field project (South Pars gas condensate export pipeline) were collected. According to the existing conditions and availability of information sources in the Iranian oil and gas industry, finally, these data as safety risk assessment criteria of pipelines were processed in a graph and scoring was conducted based on the relative weighting of risk starter elements in the pipeline. according to the obtained scores and the relative risk of different areas of pipeline by considering km scale of areas, it was identified that 16% of the total pipeline had very high risk level, 34% of the total pipeline had high risk level, 34% of the total pipeline had medium risk level and 16% of the pipeline had low risk level.
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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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".