Inhibitor Partitioning Efficiency Using Fluorescence Spectroscopy Detection
Bibliographic record
Abstract
Abstract Inhibitors have been used to mitigate corrosion in oil and gas producing assets. The efficiency of inhibitors are affected by several variables with the ability of an inhibitor to transport through the produced fluids onto the metal surface being one of the most important requirements. This can be achieved by formulating inhibitor products with a variety of chemistries that minimize their solubility in oil and are either soluble or dispersible in the brine. The partitioning of inhibitor products between the oil and aqueous phases require a reliable method to evaluate different inhibitor products. An analytical method using fluorescence spectroscopy has been developed as a means to measure inhibitor concentration. This new method offers several advantages over other commonly used techniques, such as dye transfer methods. The method offers a greater degree of accuracy, can be performed in the laboratory or at the well site, and individual analysis can be performed relatively quickly. Further, the performance of such formulations were evaluated under autoclave conditions in order to determine their applicability to existing producing systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".