The Research and Application of Low Density Cement Slurry System at Low Temperature in Daqing Oilfield
Bibliographic record
Abstract
During long sealing cementing of low temperature shallow gas well in Daqing oilfield, for the low density cement slurry at low temperature, the setting time is longer, gelling strength development is slower, filter loss is greater and the anti-channeling ability is weak. It would make the happening of annular gas channeling and fluid emitting, affect the cement job quality. Low density low temperature anti-channeling cement slurry system was studied with compound early strength agent, polyacrylate polymer latex drop loss of water, dispersed polymer powder anti-channeling agent, improve the comprehensive performance low density cement slurry. Laboratory experiments showed that setting time shortened by 50%, early strength increased by 46%, permeability decreased by 50%, interfacial bond strength increased by 47%, compared with the low density cement and the class G well cement. The application tests in the field were carried out in 18 wells. High-quality rate of well cementing increased by 11.1 percentage points. The incidence rate of fluid emitting is decreased by 1.6%. This cement slurry system can satisfy the requirements of cementing operation. It will improve the cementing quality of long sealing section in a shallow layer in Daqing Oilfield.
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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 | 0.000 | 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) | 0.001 | 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 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".