Investigation on Swelling Performance of Oil Sands and Its Impact on Oil Production during SAGD Processes
Bibliographic record
Abstract
SAGD (Steam Assisted Gravity Drainage) is used in Canadian fields where there are interlayers that impede steam chamber development and thus impede production. Many experiments have been conducted on the effect of interlayers on oil recovery. However, the swelling characteristics of interlayers under different conditions, as well as the possible clay mineral transformation and particle migration of clay particles at high temperatures, are rarely studied. In this paper, the swelling characteristics of natural oil sands and artificial clay samples were studied by high temperature hydration swelling experiments to obtain a better comparison. The effects of temperature, pressure and solution type on the swelling rate of oil sand were studied. The uniaxial compressive strength of the core in the presence of clay was studied by the scribe test. In addition, before and after the aging test at 220 °C and 2.5 MPa, the clay mineral composition was studied by the X-ray diffraction method, and the mineral transformation was proved. Finally, the impact of clay swelling on oil production is investigated by simulating the particle migration effect while considering the swelling effect. The results show that the swelling rate of oil sand increases with the increment of temperature and the decrement of pressure. The swelling rate of an artificial clay sample in distilled water is the highest, while a 1% KCl + 1% CaCl2 solution has the best swelling inhibition effect. This study aims to provide new insights into reservoir damage research during SAGD development.
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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 | 0.000 | 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) | 0.001 | 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 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".