Quantitative Risk Assessment: Underground Natural Gas Storage Facilities
Bibliographic record
Abstract
TransGas undertook a risk-ranking project for storage facilities as the first step in the process of evaluating the financial and life-safety risk associated with the eight storage facilities that they operate in Saskatchewan, Canada. Based on this analysis, two salt cavern storage facilities were selected for a quantitative risk assessment. The most cost-effective maintenance actions for each cavern were determined as follows: Fault trees were prepared for all of the identified failure scenarios. Several unique computer models were developed to predict the failure rates of the events identified in the fault trees and the consequences associated with both sub-surface and atmospheric releases from the storage facilities. Both life-safety and financial risk were considered in the analysis. For each of the caverns, a number of potential maintenance scenarios were selected that address the dominant failure causes. Life-safety risk was assessed first and compared to the TransGas tolerance. A cost optimization analysis was then carried out in which the total expected future cost associated with each maintenance option was amortized over the benefit period and compared to the total expected future cost associated with the current maintenance practice. The paper describes the risk analysis and cost optimization approach and provides case study examples of the caverns analyzed and the recommendations reached in each case.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".