Solution of Problems of Water-Gas Influence (WGI) on the Layer Using Jet and Electrical Centrifugal Pumping Technology
Bibliographic record
Abstract
Abstract Waterflooding – is currently the most popular method of oilfield development, but very often it does not guarantee high development effectiveness. This fact is the significant problem taking into account that the amount of hard to recover reserves is being increased constantly. The combined water and gas injection to the layer enables us to essentially increase the oil recovery ratio. Use of associated gas for water-gas influence also enables us to solve a problem of its utilization. About 100 field applications of WGI are known since this technology was used in North Pembina (Canada 1957 year) for the first time, and only single cases failed. Today, different technologies of WGI are applied that can be classified in two ways: alternate or simultaneous injection of water and gas (WAG or SWAG Injection). However, traditional ways of applying WGI were not widespread in Russian oil fields, but instead significant amounts of associated gas were flared. WAG compressor technology requires the purchasing of import equipment, essential investments in the initial stage, and high operating costs. Besides compressor stations, the construction of gas treatment plants is required. The separation of rich fraction from associated gas is required for the proper work functioning of compressors. These fractions are not always utilized and than the usage of dry gas for WGI it is less effective in terms of increasing oil 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 | 0.000 |
| 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".