A Simple Relation between Solubility Parameters and Densities for Live Reservoir Fluids
Bibliographic record
Abstract
A simple equation has been developed for estimating the solubility parameters of live reservoir fluids at elevated pressure and reservoir temperature. The solubility parameters of live reservoir fluids have been simply related to their measured densities by a linear function. The equation has been validated using 45 reservoir fluids covering heavy oil, black oil, volatile oil, and gas condensate with a total of 760 data points. The gas to oil ratio (GOR) range is from (25 to 9369) m 3 ·m −3, and the American Petroleum Institute (API) gravity varies from (16.6 to 50.2). The pressure ranges from (0.1 to 150.7) MPa, and the reservoir temperature is over a range of (323.9 to 422.0) K. The average absolute deviation of solubility parameters is 0.19 MPa 0.5 between the new equation and the method proposed by Wang et al. Furthermore, the new equation and the Peng−Robinson equation of state (PR EoS) have been used to calculate solubility parameters, and the results have been compared with the experimental data at pressures up to 30 MPa and 303.15 K for four pure hydrocarbons as well as dead and live oils. The predictions by the new equation and the PR EoS with an average deviation of < 0.5 MPa 0.5 are within the experimental uncertainty of < 0.8 MPa 0.5 . The results show that the developed equation in this work can be successfully used to approximate the solubility parameters of live reservoir fluids in terms of their measured densities with good accuracy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".