The Development of Sulfur/Corrosion Inhibitor Product for Extremely Sour Environments
Bibliographic record
Abstract
Abstract There are aggressive wells in Canada, Germany, and the Middle East that have high temperature, high H2S and CO2 content, and which produce several tons of elemental sulfur each day. These wells must be produced with co-injection of sulfur solvents to prevent the plugging of the well bore. As one might expect these wells can also be highly corrosive and chemical products must also include corrosion inhibitors to extend the lifespan of the wells. Qualification of sulfur solvents with corrosion resistant properties is the key to mitigating the risk of these assets. The qualification process can be challenging since laboratory testing under so harsh conditions requires addition of liquid H2S and liquid CO2 to the autoclaves at room temperature. This process requires equation-of-state calculations to model the contents of the autoclave at room temperature to achieve at-temperature conditions. This paper addresses one such qualification where the field conditions were predicted to be extremely sour with 35% of H2S, 9.5% of CO2, and a total pressure of 3400 psi at bottom hole. Temperatures were expected to exceed 300°F. The wells are also expected to produce significant amounts of elemental sulfur (>100 lb/MMScf). A combination sulfur solvent with corrosion inhibitor product was developed specifically for this sour gas field. The sulfur uptake, boiling point, emulsion tendency and the corrosion inhibition performance of the new product were evaluated in the laboratory.
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.
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".