Comparison of Two SEM-EDX Methods for the Analysis of Produced Water Scale Filter Papers
Bibliographic record
Abstract
Abstract Low-vacuum scanning electron microscopy (SEM) / energy dispersive x-ray (EDX) analysis can be used to characterize the nature of inorganic scale from produced water (Method 1); routinely used to visually determine the degree, form and composition of scale particulates. Quantitative data on scale coverage can be extracted through image analysis, and morphology can indicate origins of particulates (transported scale, active scale…). Recent trends demand more detailed quantitative analysis, believed to produce more accurate / reproducible results. Such a method is automated SEM-EDX particle analysis (Method 2). This has the advantage of full automation and delivers quantitative data on scale coverage, composition, shape and size. Neither method is perfect, the first relies on experienced SEM users, is a manual method, susceptible to bias, and is often perceived as producing qualitative data, while the second method although producing large quantitative data sets, depends upon the criteria used to classify particles, and can be time consuming. Both methods were used to examine a number of filtered produced water samples. The traditional manual method provides good representative results on scale coverage, details on particulate morphology and composition, and can be undertaken in about thirty minutes per sample; it is also a simple matter to differentiate between particulate and blanket scale deposits. The second method generates superior levels of quantitative data, but results are dependent on image thresholding (for particle selection), erroneous misleading results are all too easily obtained (unless rigorously tested particle classification schemes are used), and the method can take in excess of an hour per sample. In general Method 1 should be adequate to track scale issues from produced water, which can be supplemented where desired by automated particle analysis (APA). Where APA is to be used it is recommended that an industry standard classification criterion be developed, which will increase the degree of confidence that can be applied to results, and allow direct comparison of results between laboratories.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".