Air Injection into Condensate Reservoirs in the Middle and Late Stages Increases Recovery with Thermal Miscible Mechanism
Bibliographic record
Abstract
Summary Condensate gas reservoirs in the middle and late stages of development are faced with problems such as formation pressure reduction, serious retrograde condensation, and oil and gas seepage channel plugging, which make it difficult to further improve oil and gas recovery by conventional development methods. For this kind of condensate gas reservoir, in this paper we put forward air injection technology as a development means, taking the K condensate gas reservoir in the Tarim Oilfield as the research object. We explored the thermal oxidation characteristics and displacement efficiency of condensate oil/volatile oil by air injection through the thermal oxidation displacement experiment. In addition, we determined quantitatively the minimum miscibility pressure (MMP) of oil samples at high temperature and the correlation between MMP and temperature through a high-temperature, high-pressure slimtube experiment, and clarified the mechanism of “thermally assisted miscible” through fine full-component numerical simulations under high-temperature and high-pressure conditions, which indoor experiments could not achieve. The results showed that condensate oil/volatile oil can form a stable thermal front by injecting air, and the oil displacement efficiency is more than 90%. The MMP of flue gas produced by condensate oil and oxidation reaction decreases gradually with temperature increase, and the MMP is only 11 MPa at 260°C. The high temperature formed by oxidation heat release forces the oil phase into the gas phase, and the extraction of flue gas makes C2-C4 in the oil phase increase continuously, both of which promote the realization of heat-assisted evaporation miscible phase. This thermal-assisted miscible-phase mechanism makes air injection displacement technology an innovative replacement technology for greatly improving the recovery efficiency of condensate gas reservoirs in the middle and late development stages.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".