Why this work is in the frame
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Bibliographic record
Abstract
Abstract An investigation is presented on the use of Flow Control Valves (ICVs, FCVs) to control steam placement in the early stages of a Steam Assisted Gravity Drainage (SAGD) process. The two parts of this process that are examined in this paper are the steam circulation preheating period and the early stages up to one year of injection/production in which the steam chamber is beginning to form. Steam injection and production in this and other thermal processes can be difficult to control because steam has a high mobility ratio and tends to establish flow paths that may be difficult to break once established. This is especially pronounced in heterogeneous reservoirs. Two SAGD case studies have been designed that accurately model the initial preheating period in which both wells circulate steam through an inner tubing and outer annulus in order to conductively and, to a lesser extent convectively, heat the region around the well pair in order to establish communication. After this initial circulation period, the wells switch to injection and production. Both cases have the same base configuration but differ in the degree of reservoir heterogeneity. In the injection well, ICV devices are placed to control steam/water flow through the outer screens. In the producer, FCV valves are used to flatten the production profile along the well. Two methods are examined to change valve apertures. One uses proportional-integral-derivative (PID) controllers while the second applies an optimization algorithm directly on each individual connection productivity index. A preliminary investigation is presented here into using feedback controllers and optimization with instantaneous reservoir parameters to improve a SAGD process in the presence of reservoir heterogeneity.
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.
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) | 0.002 | 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 it