Experimental Study on Enhanced Condensate Recovery by Gas Injection in Yaha Condensate Gas Reservoir
Bibliographic record
Abstract
A condensate gas reservoir is an important special oil and gas reservoir between oil reservoir and natural gas reservoir. Gas injection production is the most commonly used development method for this type of gas reservoir, but serious retrograde condensation usually occurs in the later stages of development. To improve the recovery efficiency of condensate oil in the middle and late stages of production of a condensate gas reservoir, a gas injection parameter optimization test study was carried out, taking the Yaha gas condensate reservoir in China as an example. On the premise that the physical experimental model and key parameters met the actual conditions of the formation, the injection method, injection medium, injection-production ratio, and other parameters of the condensate gas reservoir were studied. Research on the injection method showed that the top injection method had a lower gas-oil ratio and higher condensate oil recovery. The study of injection medium showed that the production effect of carbon dioxide (CO2) injection was the best injection medium, and the maximum recovery rate of condensate oil was 95.11%. The injection-production ratio study showed that the injection-production ratio was approximately inversely proportional to the recovery factor of condensate gas and approximately proportional to the recovery factor of condensate oil. When the injection-production ratio was 1 : 1, the maximum recovery rate of condensate oil was 83.31%. In summary, in the later stage of gas injection development of the Yaha condensate gas reservoir, it was recommended to choose the development plan of CO2 injection at the top position with an injection-production ratio of 1 : 1. This research can not only provide guidance for the later formulation of gas injection plans for Yaha condensate gas reservoirs but also lay a foundation for the research of gas injection migration characteristics of other condensate gas reservoirs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".