Experimental and theoretical quantification of phase behaviour for solvents/water/heavy oil systems with the PC-SAFT equation of state
Bibliographic record
Abstract
• Phase behaviour and physical properties of solvents/heavy oil/water systems are quantified. • PC-SAFT EOS, ASP fractions, SCN-type method, and temperature-independent BIPs are integrated to reproduce the measured data. • The predicted two/three-phase boundaries exhibit an overall RMSRE of 2.50%. • Water is found to reduce phase boundaries of N 2 and CO 2 -heavy oil systems but increases them for the DME-heavy oil system. • SF of pure DME is higher than that of pure CO 2 and introducing CO 2 into DME reduces the SF. In this work, a new framework has been proposed to quantify phase behaviour of solvents-water-heavy oil systems based on the perturbed-chain statistical associating fluid theory equation of state (PC-SAFT EOS) and then compared it with the cubic EOSs (e.g., PR EOS). Experimentally, constant composition expansion (CCE) tests were meticulously conducted to measure saturation pressure ( P s a t ), phase volume, and phase compositions for CO 2 /heavy oil, N 2 /heavy oil, and dimethyl ether (DME)/heavy oil systems with and without water at pressures up to 20 MPa and temperatures up to 433.2 K. Theoretically, a PC-SAFT EOS framework incorporated temperature-independent binary interaction parameters (BIPs) is employed to reproduce the measured P s a t and other physical properties of the aforementioned systems. Addition of water into each of the aforementioned systems is found to increase its P s a t compared to the systems without water. By characterizing heavy oil as four pseudocomponents, density of the aforementioned systems can be accurately predicted with the root-mean-squared relative error (RMSRE) of 1.84%. Then, the BIPs for each binary pair of the aforementioned systems are obtained by minimizing the deviation between the experimentally measured P s a t and the corresponding calculated values. Compared with the modified PR EOS, the proposed framework shows its superior performance with an RMSRE of 2.93% for the predicted P s a t of the aforementioned systems.
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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".