Application of Electrochemical Noise Monitoring to Inhibitor Evaluation and Optimization in the Field: Results from the Kaybob South Sour Gas Field
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Electrochemical noise monitoring produces real time corrosion data, which provides information both on the level of corrosion activity in a system and the dominant corrosion mechanism. This data can be used to efficiently evaluate corrosion inhibitor effectiveness and to optimize injection rates. This paper will present data obtained in Canada's Kaybob South Sour Gas field during inhibitor evaluation and optimization testing. Details of the field equipment setup and the data analysis process will be presented along with conclusions regarding inhibitor effectiveness and the field use of electrochemical noise monitoring for inhibitor evaluation. The inhibitor testing completed in the Kaybob South field was successful in significantly reducing inhibitor costs in the field as well as in increasing confidence in inhibitor performance and better understanding of how the inhibitors work in the system. It was also successful in proving electrochemical noise is a viable option for field inhibition testing and that by using electrochemical noise it is possible to obtain complete inhibitor testing in the field in a very short period of time compared to traditional testing methods
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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 it