Identification of SSC (Sulfide Stress Cracking)-Susceptible Wells and Risk Prediction
Bibliographic record
Abstract
Abstract Hydrogen sulfide (H2S) generated by aquathermolysis—a high-temperature reaction of condensed steam (water) with sulfur-bearing bitumen in the reservoir rock—may increase the risk of sulfide stress cracking (SSC) in cyclically steam stimulated (CSS) wells. In a given field, H2S levels and wellbore conditions vary significantly among wells and so do their SSC-susceptibility. Identifying the SSC-susceptible wells is important in terms of reducing SSC risk by allocating resources and implementing pro-active intervention measures to the SSC-susceptible wells. A comprehensive research program, with a dedicated instrumented CSS well as the centerpiece, has been undertaken by Imperial Oil Resources with the objectives of characterizing H2S evolution in the wellbore and developing a tool for identifying the SSC-susceptible wells. The research includes laboratory and field tests, and statistical, phase behaviour and kinetic modelling. The SSC-susceptible zone for Cold Lake CSS has been established from Cyclic Slow Strain Rate (CSSR) laboratory tests incorporating CSS fluid chemistry, stress-strain environments, casing metallurgy, and variable temperature and H2S partial pressure. A statistical logistic model matches the experimental CSSR data well. The instrumented well data validate the phase behavior model, which in turn explains the measured H2S profile in the wellbore. An aquathermolysis kinetic model has been developed for the instrumented well and validated with data from nine other CSS wells. The research has led to the development of an engineering tool for identifying the wells at the risk of falling into the SSC-susceptible zone.
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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 | 0.000 | 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) | 0.000 | 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".