Accurate Prediction of the Saturation Pressures of Hydrocarbons in Unconventional Reservoirs: A Modified Alpha-Function for the Peng-Robinson Equation of State
Bibliographic record
Abstract
Abstract Due to the confinement and strong adsorption to the pore wall in meso- and nano- pores, fluid phase behavior in the confined media, such as the tight and shale reservoirs, can be significantly different from that in the bulk phase. A large amount of work has been done on the theoretical modeling of the phase behavior of hydrocarbons in the confined media. However, there are still inconsistencies in the theoretical models developed and validations of those models against experimental data are inadequate. In this study, we conducted a comprehensive review of experimental work on the phase behavior of hydrocarbons under confinement and analyzed various theoretical phase-behavior models. Emphasis was given to the modifications to the Peng-Robinson equation of state (PR EoS). Through the comparative analysis, we developed a modified alpha-function in PR EoS for accurate prediction of the saturation pressures of hydrocarbons in porous media. This modified alpha-function accounts for the pore size and was derived based on the regression results through minimizing the deviation between the experimentally measured and numerically calculated saturation pressure data. Meanwhile, the thermodynamic properties of propane were calculated in the bulk phase and in the nanopores. Finally, we validated the newly developed model using the experimental data generated within our research group. By applying the modified PR EoS, a more accurate representation of the experimentally measured saturation pressure data in confined nanopores was achieved. This newly developed model not only enhanced the accuracy of the predictions but also provided valuable insights into the confinement effects on the phase behavior of hydrocarbons in nanopores. Notably, we observed significant changes in the properties of propane within confined nanopores, including suppressed saturation pressure and fugacity, indicating a greater tendency for the gas to remain in the liquid phase. Additionally, the gas compressibility factor and enthalpy of vaporization were found to increase highlighting increased difficulty in transitioning from liquid to gas phase under confinement. To validate its applicability, the newly developed model was applied to the experimental data obtained in real rock samples. Interestingly, it was observed that the phase change in these samples predominantly occurred in the smallest pores. This finding highlights the importance of considering the pore size distribution when studying the phase behavior of hydrocarbons in a capillary medium even if the rock has high permeability. This study provided a simple and easy-to-implement modification to the PR EoS for accurate prediction of the phase behavior of petroleum fluids under confinement. The modification to PR EoS was more straightforward and simplified compared to the modifications available in the literature.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".