Impact of Porous Media on Saturation Pressures of Gas and Oil in Tight Reservoirs
Bibliographic record
Abstract
Abstract The tremendous efforts have been made by the industry in tapping the recoverable resources from the unconventional reservoirs in the past ten years. Shale (tight) gas and shale (tight) oil are the two typical ones. Some research studies focused on the effect of porous media on the dew point of gas condensates in terms of experimental and theoretical work. The contradictory conclusions were reached. On the other hand, some conclusions were made for crude oil as well on the basis of the measurements of the bubble point pressure of crude oil in porous media. Therefore, it is of great importance to develop an effective method to predict the phase behavior of shale gas and shale oil in porous media and investigate the effects of some factors on the saturation pressures of gas condensate and crude oil in tight reservoirs. In this paper, a general framework of theoretical models has been developed to predict the saturation pressures of shale gas and shale oil in tight reservoirs. The Laplace equation is used to relate to the pressures in vapor and liquid phases from the curved interface. The Parachor model is applied to determine the interfacial tensions of crude oil and gas condensate. By taking into account of porous media in the proposed models, the calculations have been performed in some case studies. The effect tendency of some properties of porous media such as permeability and porosity on the dew or bubble point of reservoir fluid is discussed in this paper.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".