Four-Phase Flash Calculation Algorithm Based on the Free-Water Assumption
Bibliographic record
Abstract
An aqueous phase, which exists due to the presence of the original water saturation or appears due to the use of secondary and tertiary recovery methods (such as water flooding and water-alternating-gas process), is inevitable in the pore spaces of an oil reservoir. With the existence of an aqueous phase and multiple hydrocarbon phases, up to a total of four phases can coexist at equilibrium under reservoir conditions. To reduce the computational complexity of the four-phase equilibrium calculation problem, we propose a four-phase flash calculation algorithm based on the free-water assumption (i.e., assuming the aqueous phase contains pure water only). The free-water algorithm uses the successive substitution iteration (SSI) method. It contains an outer loop and an inner loop. The outer loop is used to update the equilibrium ratios based on the fugacity equations, while the inner loop is used to calculate the phase fractions. Special measures are adopted to enhance the robustness of the developed algorithm. Case studies involving two fluid mixtures, i.e., one n -butane/heavy-oil/water mixture under high-temperature conditions and one CO 2 /hydrocarbons/water mixture under low-temperature conditions, are conducted to examine the performance of the four-phase free-water flash calculation algorithm. The algorithm works well for both mixtures, without encountering any convergence issues. It is also shown that the proposed algorithm can help reduce the computational cost (up to 41.51%) of four-phase flash calculations. For the n -butane/heavy-oil/water mixture, the four-phase free-water flash algorithm yields an acceptable deviation from the results given by the conventional full flash calculation algorithm. But it is not applicable to the CO 2 /hydrocarbons/water mixture since CO 2 can have a large solubility in the aqueous phase under high pressures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".