Phase behavior of single and multi-component liquid hydrocarbons in real reservoir rocks
Bibliographic record
Abstract
Phase-alteration phenomenon has a considerable influence on the dynamics and distribution of fluids in porous media. One of the major factors affecting the phase behaviour of fluids in reservoirs is the capillarity effect, which becomes unavoidably significant as the media becomes tighter (confinement effect) and contains more pores at nano sizes. Comprehending the nature of vaporization and condensation of hydrocarbon in such confined media is important for accurate modelling of two-phase envelopes and thereby the performance of energy production from hydrocarbon reservoirs. This paper studies the vaporization of single- and multicomponent hydrocarbons in different types of rocks (namely sandstones, limestones, tight sandstones, and shales). The vaporization temperatures were measured experimentally in each rock type and compared with boiling points measured at bulk conditions to investigate the deviation between the phase-change temperatures in capillary media and bulk values. The deviation between the measured vaporization temperatures and the bulk measurements ranged from 4.4% (1.6% in Kelvin unit) to 19.7% (5.2% in Kelvin unit) with single-component solvents and 1.4% (0.4% in Kelvin unit) to 27.6% (5.3% in Kelvin unit) with the hydrocarbon mixtures. The vaporization temperatures, obtained from the experiments, were also compared with the computed two-phase envelopes, calculated by the classical Peng-Robinson Equation of State. The deviation percentages of measured vaporization temperatures from the computed values were at least 4.4% (1.6% in Kelvin unit) with single-component solvents and 2.1% (0.7% in Kelvin unit) with the hydrocarbon mixtures.
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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 | 0.000 |
| 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) | 0.001 | 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".