Pore Scale Modeling of Gravity Drainage Dominated Flow under Isothermal and Non-Isothermal Conditions
Bibliographic record
Abstract
Abstract Immiscible or miscible gas injection and steam assisted gravity drainage are well known examples of gravity dominated recovery processes under isothermal and non-isothermal conditions, respectively. It is commonly observed in these processes that field scale applications yield less recovery than estimated. In order to clarify the reasons associated with the amount of the remaining oil in these processes, especially for the non-isothermal ones such as steam assisted gravity drainage (SAGD), pore scale experimental analysis of the mechanics is needed. In this paper, as complementary to our previous work (Argüelles and Babadagli, 2011) that used horizontally positioned circular capillaries, we studied the gravity drainage dominated flow of heavy-oil at pore scale using vertically positioned square and circular capillary tubes. Heavy crude oil samples were used and an elementary volume in the swept zone of SAGD was simulated using a single capillary tube. Detailed experiments were carried out to analyze: (1) the effects of oil viscosity on non-isothermal gravity drainage (including free fall), (2) behavior of co-current gravity driven displacement, (3) interplay among capillary, gravity and viscous (injection rates) forces and wettability, and (4) residual oil saturation and phase distribution in the capillaries. Also, we compared the residual oil saturation development results obtained for square capillaries with those for the circular ones having a diameter approximately equal to the side of the square capillary tube.
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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 | 0.001 | 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".