Study on the Fine Optimization of Water Injection in SZ Oilfield of Bohai Bay
Bibliographic record
Abstract
Bohai SZ Oilfield has entered into high water cut stage, how to realize the goal of fine optimization of water injection to enhance oil recovery is an important problem for reservoir engineers. Fine optimization of water injection needs ‘inject enough’, ‘inject well’ and ‘inject effectively’. The paper gets relationship between annual oil production rate and annual water production rate of different water cut stages of SZ Oilfield with the life cycle theory and draws the annual water injection rate and annual oil production rate chart to ensure ‘inject enough’, optimizes injection allocation method according to new reservoir research and gets a very good precipitation effect of increasing oil production. The paper also puts forward the method to recognize low effective and ineffective injection circulation to guide the oilfield ‘inject effectively’. Key words : Fine optimization of water injection; Logistic theory; Prediction of water injection; Injection allocation; Low effective and ineffective injection circulation
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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 | 0.000 |
| 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".