Static and Dynamic Testing of Silicate Scale Inhibitors
Bibliographic record
Abstract
Alkaline surfactant polymer (ASP) floods in sandstone reservoirs are associated with silicate scaling of production wells. Silicate scaling has been a significant problem in ASP-flooded fields in China (e.g., Daqing field) and Canada. This paper describes the results of both static and dynamic testing that reproduced the field conditions in a typical oil production well in a field under ASP flood. The tests were used to screen chemical inhibitors for the prevention of magnesium silicate scaling. Carbonate and silicate were allowed to scale concurrently in both tests. The static test was used to screen inhibitors, and the best performers were tested dynamically. The static and dynamic tests correlated well in terms of individual inhibitor results. In the static test, silicate slowly forms from the beginning of the test and calcium carbonate forms about two hours into the test. In the dynamic test, calcium carbonate forms very slowly while silicate scale forms more quickly and dominates. It is interesting to note that none of the chemicals tested acted as a threshold inhibitor and prevented scaling at low doses. Rather, the inhibitors tended to delay scaling. Significant delay of scaling required doses of 50 to 100 ppm (as active). This effect was observed both in static tests and dynamic tests. Although none of the products tested acted as threshold inhibitors, the best inhibitors could still be effective in the oilfield if silicate scaling can be delayed long enough so that fluids are moved out of the well before significantly depositing on surfaces downhole.
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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".