Quantification of Phase Behaviour and Physical Properties of Alkane Solvents/CO2/ Water/Heavy Oil Systems under Equilibrium and Nonequilibrium Conditions
Bibliographic record
Abstract
Abstract The hybrid steam-solvent injection has been considered as a promising technique for enhancing heavy oil/bitumen recovery, while its main mechanisms including the heat transferred and dissolution of solvents (e.g., C3H8, C4H10, CO2, N2, and DME) into heavy oil/bitumen to reduce its viscosity and swell it are closely related to the phase behaviour of the solvents/water/heavy oil systems. To allow the seamless integration with the existing reservoir simulators, the traditional cubic equations of state (i.e., SRK EOS and PR EOS) have been modified and improved to accurately quantify the phase behaviour and physical properties of the aforementioned systems under equilibrium and nonequilibrium conditions. Firstly, a huge database has been built to develop the corresponding alpha functions by minimizing the deviation between the measured and calculated vapour pressures for water as well as nonhydrocarbon and hydrocarbon compounds available from the public domain. Such obtained alpha functions are further validated with enthalpy of vaporization for pure substances, and then the reduced temperature has been optimized and the eccentric factor has been redefined. Finally, a pressure-implicit strategy has been developed to optimize the binary interaction parameters (BIPs) by treating heavy oil as one pseudocomponent (PC) or multiple PCs. Also, the contributions of each solvent to the aforementioned systems have been compared and analyzed within a consistent and unified framework. In addition to new alpha functions for hydrocarbons and water, respectively, the reduced temperature is found to have its optimum value of 0.59 for the two equations of state (EOSs), while 0.60 is recommended for practical use. Such improved EOSs have been further employed to reproduce the experimentally measured multiphase boundaries (or pseudo-bubble-point pressures), density, viscosity, (mutual) solubility, and preferential mass transfer for the aforementioned mixtures under equilibrium and nonequilibrium conditions. The swelling effect for the heavy oil can be enhanced due to the addition of C3H8 and/or C4H10 or their mixtures into the CO2 stream. Due to the existence of water, isenthalpic flash leads to more accurate quantification of multiphase boundaries and physical properties for the hybrid solvent-thermal processes. Each component of a binary or ternary gas mixture is found to diffuse preferentially into heavy oil at high pressures and elevated temperatures in the absence and presence of porous media, while each of them is found to exsolve differently from gas-saturated heavy oil under nonequilibrium conditions.
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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 | 0.001 | 0.001 |
| 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".