Optimization of Well Spacing Ratio of Injection Production Wells in Low Permeability Anisotropic Reservoir
Bibliographic record
Abstract
According to the characteristics of anisotropy existed during the development of low permeability reservoirs, Shengli oilfield in Niu 20 reservoir as an example, by using reservoir numerical simulation method, considering the existing well pattern in low permeability reservoir, the effect of the well pattern, well spacing and array direction, and well pattern array distance ratio on the oilfield production capacity has been researched by numerical simulation. The results of the study show that: For the anisotropy of low permeability reservoirs, permeability ratio fixed, the semi logarithmic curve of well drainage distance ratio and degree of recovery shows a quadratic parabola relationship, the optimal well spacing ratio can be obtained by the curve fitting. And by numerical simulation of the actual reservoir, verify well array spacing ratio optimization to improve the degree of recovery.
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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 | 0.001 |
| 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".