Numerical Simulation Investigation on Foamy Oil Behavior for a System of Heavy Oil-Mixture Solvent in Porous Media
Bibliographic record
Abstract
Abstract Heavy oil resources, as a non-renewable energy resource, often require extra enhanced oil recovery techniques such as solvent-based processes. Many kinds of solvents including pure and mixed solvents have been tested in solvent-based applications. Compared with pure solvent, the solvent mixture has the advantage of relatively higher dew point pressure while maintaining desirable solubility in heavy oil. The characterization of foamy oil behavior in a pure solvent system is different from that of the solvent mixture system despite their similarities. Thus, an additional numerical simulation study is necessary for the solvent mixture system. This work conducted simulation studies to investigate foamy oil behavior in a heavy oil-mixture solvent (C1 + C3) system from pressure depletion tests. A better understanding of foamy oil characterization and mechanism in a heavy oil-mixture solvent system is obtained. A reliable non-equilibrium model is developed to perform simulation studies. Since previous experiments suggest the behavior of foamy oil in the solvent mixture system share similarities with the heavy oil-methane system, this investigation first conducted a simulation study with consideration of two reactions in the model and achieved good agreements between the simulated calculation results and experimentally measurement. Then, four reactions are considered in the model for simulation study and obtained better history match results. The simulation results suggest methane has more impact on the foamy oil behaviors than propane in the heavy oil-mixture solvent system. This work also discussed the effect of model parameters involved in the history matching process and conducted sensitivity analysis.
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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) | 0.000 | 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".