Numerical Simulation Study on the Technology of Different Nature Polymer Injection in Thin and Bad ReservoirNumerical Simulation Study on the Technology of Different Nature Polymer Injection in Thin and Bad Reservoir
Bibliographic record
Abstract
The thin and poor reservoir , as an important replacement of production decline in the later stage of oilfield development, is gradually becoming the target of three oil recovery due to the large proportion of its reserves. For Class Ⅲ and Class Ⅳ of thin and poor reservoirs with large contradiction between the layers, if the same molecular weight polymer flooding is used to drive oil, it is easy to affect the development effect because of low producing degree of poorly matched reservoir. On the basis of the fine geological model, the water cut and cumulative oil production of the simulated area were fitted by the simulation software of eclipse, and the development effect of different production schemes is analyzed and forecasted. Research results show that the effect of different layer different nature polymer injection is better than that of general polymer injection, and the effect of different stage different nature polymer injection is better than that of the different layer different nature.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".