Bibliographic record
Abstract
The activity of sulfate reducing bacteria (SRB) can cause many industrial problems in oil and gas production. SRB activity can account for the reduction of quality of product due to the souring of wells through hydrogen sulfide production and the corrosion of tubulars, which leads to a reduction in wellbore radius and an increase in total suspended solids (TSS). Historically, SRB problems have not been handled with preventative measures. The oil industry has a “wait and see” attitude to this problem. Since SRB causes corrosion, this attitude can cause permanent damage to production wells. Current prevention practices include injecting harmful and expensive chemicals into the formation. Depending on the situation, production may have to be shut down to achieve limited and temporary results. Microwave and ultrasonic irradiation have been proposed to prevent corrosion by eliminating SRB. The effects of microwave and ultrasound on SRB have been studied and experimental results are presented. By utilizing microwave or ultrasound irradiation, one can continuously eliminate SRB in the injection and production wells, thus removing the persistent problems associated with it.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".