Feasibility Study on Steam and Gas Push with Dual Horizontal Wells in a Moderate - Depth Heavy Oil Reservoir
Bibliographic record
Abstract
Non-condensable gas (NCG) with steam co-injection makes steam assisted gravity drainage less energy-intensive as well as reduces greenhouse gas emission and water consumption.Numerous studies have shown that the technology called steam and gas push (SAGP) is feasible for heavy oil and bitumen.However, most of these studies have focused on shallow heavy oil reservoirs and only a few works have investigated moderate-depth heavy oil reservoirs.In this study, laboratory experiments and numerical simulations were conducted to study shape change, steam chamber expansion, and temperature change after co-injecting NCG with steam into an actual moderate-depth heavy oil reservoir.Results showed that after co-injecting NCG with steam, the transverse expansion rate of the steam chamber accelerated, vertical expansion slowed down, thermal utilization increased, and oil-steam ratio improved.In addition, the injection parameters of SAGP were also optimized via numerical simulation, which indicated that SAGP could effectively improve development effect and recovery for moderate-depth heavy oil 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 | 0.000 | 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) | 0.001 | 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".