Bibliographic record
Abstract
Abstract Relative permeability plays a significant role in predicting oil rate and estimating the ultimate oil recovery factor. Although it is known that the relative permeability can change with temperature, the same set of relative permeability is often used to predict the reservoir performance regardless of the temperature range involved in the process. This can lead to significant errors when the relative permeability changes appreciably with temperature. Athabasca reservoir oil and sand were used to obtain the experimental data using the unsteady state method for relative permeability measurements. First the SAGD residual oil saturations were measured at 180, 200, and 220 °C. Then the oil displacement data collected during hot water and steam injection experiments were utilized to construct the relative permeability curves at different operating temperatures. Finally, a series of reservoir simulations were performed to history match the lab experiments and examine the accuracy of inferred relative permeability curves. The objective of this study is to develop a series of realistic relative permeability curves that are representative of various downhole operating conditions that are encountered in Western Canadian oil-sand operations. The experimental results indicate that oil residual saturation decreases as temperature is increased. A noticeable change in oil residual saturation was also observed when phase change occurred from liquid water to steam phase at a given temperature. Finally, 3 sets of relative permeability curves were developed covering a wide range of SAGD operating conditions.
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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 | 0.001 |
| 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) | 0.001 | 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".