Inflow Analysis and Optimization of Slotted Liners
Why this work is in the frame
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Bibliographic record
Abstract
Summary Slotted liners have been used for many years to provide sand control in many oil industry applications. They are commonly applied in western Canadian reservoirs that produce high-viscosity oil from horizontal wells with unconsolidated, high-permeability sands. Both primary and thermal applications are common, and the steam-assisted gravity drainage (SAGD) process1 is beginning to see widespread application in this area of the world. They are relatively inexpensive to manufacture and tolerant of installation loads, but historically they have not been able to offer the very small opening sizes of wire-wrap screens for controlling production of fine sands. However, recent advances in slot manufacturing methods provide slot openings that match and surpass the size and tolerance of wire-wrap screens. Furthermore, slotted liners offer an advantage in providing a variable slot density that can be used to optimize inflow or outflow distributions. In the development of its south Bolney reservoir, Marathon Oil Canada and Noetic Engineering Inc. performed an analytical evaluation of inflow characteristics for a new generation of commercially available slots. Several interesting conclusions were reached, the most significant of which was that inflow resistance depends much more strongly on slot density than on open area. The inflow characterization was also used to optimize the slot-density distribution and to promote more uniform production throughout the well. The slotting was incorporated with a deformation-management system that controlled thermally induced loads, preventing compromise of sand-control characteristics.
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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 | 0.001 |
| 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 it