Bibliographic record
Abstract
Abstract In SAGD process a pair of horizontal wells is drilled at the base of a heavy oil and bitumen reservoir, vertically one above the other. Steam is injected into the upper well and the heated and mobilized bitumen drains to the bottom producer and is withdrawn either by natural lift or artificial lift. Uniform distribution of steam along the entire length of the well bore is very important for the uniform growth of the steam chamber. This is very important to make the entire length of the well productive. Pressure drop along the length of the injector and producer may cause steam break through in one segment and build up of liquid level between the wells. Generally steam is injected at the heel and the toe of the well and is distributed along the entire length primarily through slotted liner. It is expected that this will provide a higher quality steam at the toe end of the well. However, with out proper design the counter current heat transfer between the two streams may result in delivering a poor quality to the toe. In the producer it is necessary to withdraw fluid from the toe and heel. In a concentric design this may cause serious lifting problem if the tubulars are not designed properly and the split between the streams is not right. This paper presents the issues related to SAGD well bore design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".