Effect of Rate and Viscosity on Gas Mobility during Solution-Gas Drive in Heavy Oils
Bibliographic record
Abstract
Abstract Some heavy oil reservoirs under primary production have shown higher recovery and production rates than expected. Many studies have shown that gas mobility in these reservoirs is low contributing to improved oil displacement and also that gas mobility may depend not only on gas saturation but also on depletion rate and oil viscosity. Despite the observed effect of oil viscosity and depletion rate on gas mobility, it is not yet clear to what extent these factors affect relative permeability and critical gas saturation. In this study, we have conducted depletion experiments in a linear unconsolidated sand-pack. Three oils were used, with oil viscosities that varied by a factor of 30. The experiments were conducted at two different depletion rates for each of the oils. Experimental results show that as oil viscosity or depletion rate increases, critical gas saturation increases, gas mobility decreases and oil displacement becomes more effective. Critical gas saturation for all the runs was in the range of 0.2 – 5±1%. Furthermore, it was found that relative permeability to gas decreased as withdrawal rate or oil viscosity increased. The effects of oil viscosity and withdrawal rate were combined in the form of a depletion index, such that oil recovery increased as the depletion index increased.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".