Study and application of technical policy limits for layer system recombination in water drive sandstone reservoirs
Bibliographic record
Abstract
Abstract Layer system recombination is the combination of main layers and non-main layers into a new injection-production well pattern respectively, in order to reduce interlayer contradictions. The main factors restricting layer system recombination are reservoir physical properties, residual material basis, and economic benefits. In this study, according to the actual reservoir characteristics, a conceptual model is established to study the technical policy limits of layer system recombination. Through numerical simulation and mathematical statistics methods, the variation rules of permeability rank difference, recovery degree rank difference, pressure rank difference, viscosity rank difference, and effective thickness upper limit are studied. And the inflection point of the curve is identified as the technical policy limit of layer system recombination. At the same time, the lower limit of reserve abundance under different oil prices is calculated as the economic limit of layer system recombination. Through remaining oil research and well pattern adaptability evaluation, the well pattern reconstruction study is carried out to effectively expand the water drive sweep range and reconstruct efficient displacement flow field. On the basis of layer system recombination and well pattern reconstruction optimization study, the numerical simulation method is used to carry out the research of injection-production technology policy such as reasonable pressure maintenance level, reasonable injection-production ratio, and reasonable oil production rate, which effectively guides the reservoir injection and production control and consolidates the effect of layer system well pattern reconstruction.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".