Post-Yield Thermal Design Basis for Slotted Liner
Bibliographic record
Abstract
Abstract Slotted liners used for primary heavy oil recovery support relatively minor operational loads at the depths and pressures common in Western Canada. In such applications, installation loading is the primary concern, and load limits can be defined using an elastic design basis to support running operations. In thermal operations, the installation limits need to be more stringent, because of the impact of residual stresses and deformation on the operating response. Furthermore, the high axial loads induced by confined thermal expansion can place the liner into large-scale yield, where localization resistance is virtually eliminated and a variety of deformation failure mechanisms can become manifest. A prudent design takes the deformation mechanisms into consideration, balancing the mechanical requirements for supporting thermally-induced loads against the inflow requirements to generate the final design. Commercial Steam Assisted Gravity Drainage (SAGD) projects currently under development in Northern Alberta typically use slotted liner for both injectors and producers. Reservoir sand grain size distributions and inflow requirements require slot densities as high as possible without compromising the structural integrity of the wells. Therefore, a design assessment was required to determine the relationship between slot geometry and density, thermal and production loading, and post-yield material properties. A variety of possible failure mechanisms were considered, and failure limits in terms of these controlling parameters were evaluated. The outcome was an allowable slot density, slot geometry and post-yield material description required for the liner to operate reliably, and corresponding quality assurance programs to ensure the slots and material satisfy the requirements for reliable operation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".