Theoretical Modeling of Gas Exsolution and Liberation during Foamy-Oil Flow in Porous Media
Bibliographic record
Abstract
Summary In the past, many coreflooding laboratory tests have been conducted to study foamy-oil flow in primary heavy oil production and solvent-based enhanced oil recovery processes (e.g., cyclic solvent injection). However, limited important technical data can be obtained from these experimental tests due to the complex nonequilibrium phase behaviors. In general, mathematical or numerical modeling is often performed to history match the experimental data and understand foamy-oil flow trends under different experimental conditions. Many important parameters need to be tuned and determined in the history matching processes, which could be time-consuming and possibly cause large errors. In this paper, we propose a novel and effective theoretical model to quantify the gas exsolution and liberation during foamy-oil flow in porous media. Experimentally, we conducted two laboratory tests in a 2D sandpack model to study the primary production of a heavy oil–methane (CH4) system by using a differential fluid production (DFP) method with two different pressure depletion step sizes. Theoretically, we developed a material-balance-based tank model to describe the foamy-oil productions in these two tests. In this model, the amounts of dissolved and evolved gases were determined directly from material-balance equations by using the measured production data. The subsequent gas-liberation process was modeled through a pressure-dependent relation with two adjustable parameters, which were determined using the measured free-gas–oil ratio (GOR) from the sandpack tests. The model was further used to generate the foamy-oil and free-gas relative permeabilities for the tests. Subsequently, numerical validation was performed against CMG-STARS simulations conducted under different depletion scenarios, which showed similar production trends. This comparison shows that the proposed theoretical model captures the essential features of foamy-oil flow and indicates its potential as a practical and efficient alternative for screening cold heavy oil production (CHOP) reservoirs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".