Three-Dimensional Physical Simulation of Heavy Oil Exploitation by Hot Solvent Injection
Bibliographic record
Abstract
To improve the thermal effects of solvents on heavy oil reservoirs and realize the combined action of multiple flooding mechanisms, such as solvent heating and extraction, without steam mixing, based on the M Block heavy oil reservoir in Canada, three sets of comparative hot solvent-assisted gravity drainage experiments under different temperatures and pressures were carried out through an indoor three-dimensional (3D) physical simulation device. The development characteristics of the solvent chamber in the hot solvent-assisted gravity drainage technology were studied under different pressures and temperatures, and the recovery factor, cumulative oil exchange rate, and solvent retention rate were analyzed. The results showed that due to the effect of gravity differentiation, the development morphology of the solvent chamber could be divided into three stages: rapid ascent, lateral expansion, and slow descent. When the temperature was constant, the reservoir pressure decreased, the recovery rate increased, the cumulative oil exchange rate increased, and the solvent retention rate decreased; when the pressure was constant, the temperature increased, the viscosity of heavy oil decreased, the recovery rate increased, the cumulative oil exchange rate increased, and the solvent retention rate was low. Additionally, the study also showed that for hot solvents in different phases, the use of hot solvent vapor not only required less injected solvent but also exhibited a high oil production rate, which shortened production time and reduced energy consumption. Moreover, the oil recovery rate was higher than 60%, the solvent retention rate was lower than 10%, and the cumulative oil exchange rate was higher than 3 t / t , which constituted better economic benefits and provided a reliable theoretical basis for onsite oilfield applications.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".