Characterization of Foamy Oil and Gas/Oil Two-Phase Flow in Porous Media for a Heavy Oil/Methane System
Bibliographic record
Abstract
In our previous study, a series of experiments had been conducted by applying different pressure depletion rates in a 1 m long sand-pack. In this study, numerical simulation models are built to simulate the lab tests, for both gas/oil production data and pressure distribution along the sand-pack in heavy oil/methane system. Two different simulation models are used: (1) equilibrium black oil model with two sets of gas/oil relative permeability curves; (2) a four-component nonequilibrium kinetic model. Good matching results on production data are obtained by applying black oil model. However, this black oil model cannot be used to match pressure distribution along the sand-pack. This result suggests the description of foamy oil behavior by applying equilibrium black oil model is incomplete. For better characterization, a four-component nonequilibrium kinetic model is developed aiming to match production data and pressure distribution simultaneously. Two reactions are applied in the simulation to capture gas bubbles status. Good matching results for production data and pressure distribution are simultaneously obtained by considering low gas relative permeability and kinetic reactions. Simulation studies indicate that higher pressure drop rate would cause stronger foamy oil flow, but the exceed pressure drop rate could shorten lifetime of foamy oil flow. This work is the first study to match production data and pressure distribution and provides a methodology to characterize foamy oil flow behavior in porous media for a heavy oil/methane system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".