Protocols for Slotted Liner Design for Optimum SAGD Operation
Bibliographic record
Abstract
Abstract Slotted liners are used extensively in the majority of steam assisted gravity drainage (SAGD) operations conducted in Western Canada due to their superior mechanical strength and integrity in contrast to other mechanical sand-control devices. These liners are required because of the generally poorly or unconsolidated nature of the majority of formations in which SAGD applications are conducted. These liners can have a variety of configurations with varying slot density, slotting patterns, slot apertures and slot internal geometries. The overall objective of a successful slotted liner design is to ensure that the liner allows the maximum production of bitumen and other fluids with a minimum pressure drop, while retaining the majority of the formation sand and preventing infill of the horizontal section of the well with solids and erosion and failure of downhole pumps and surface equipment. This paper describes a detailed lab test protocol which was successfully developed over a number years for the design and evaluation of slot geometry for SAGD applications, describes test procedures used and quantifies some of the major mechanisms discovered that lead to the plugging of slots. It has been found that in addition to grain size of the sand under consideration and slot geometry, that clay content of the formation, flow velocity, wetting phase type and pH play crucial roles in the plugging mechanism of slotted liners. Clay plugging at the top portion of the slots has been found to be the dominant damage mechanism. Introduction SAGD is being used extensively in Western Canada and other areas in the world as an effective and economic means for the recovery of heavy oil and bitumen reserves and represents the current primary technology for the exploitation of this large hydrocarbon resource(1-5).
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".