The Research Progress of Oil Sand Separation Technology in China
Bibliographic record
Abstract
From 2007 to 2008, Research Institute of Petroleum Exploration & Development, Langfang Branch launched oil sand resource exploration and the study of hot water separation technology in Fengcheng area, Northwest of Junggar Basin, and the recoverable oil-sand oil resource is 54.98 million tons with the oil content in 7.1-10%, which is distributed in Cretaceous and Jurassic with the thickness of 80-140 meters, the cover depth of oil sand is 50-90 meters. Combining with the characteristics of the oil sand in this area and based on the research of hot water separation mechanism in oil sand, the hot water separation reagent for the oil sand in this area has been successfully developed, and its separation rate reaches 90%, provided that the concentrations of the agent is 4% and the separation temperature is 85 °C. Based on series of study, the construction of testing site, which is capable of processing 10,000 tons oil sand in this area, is completed, and the on-site separation tests of oil sand are launched with the recovery rate of 90% in normal operation, and the hot water separation technology and equipment research & development are successful. Key words : Oil sand; Hot water separation technology; Separation reagent; Tests
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".