Research on Enhancing Heavy Oil Recovery Mechanism of Flue Gas Assisted Steam Flooding
Bibliographic record
Abstract
Abstract Flue gas is industrial waste gas produced by the burning of fossil fuels. Its main compositions are 10% - 15% of carbon dioxide and 80% - 85% of the nitrogen, two key components needed for gas flooding. Adding a certain amount of flue gas into steam in displacement could decrease steam partial pressure, improve the steam quality and reduce heat loss, resulting in reduction of steam injection amount and improvement of development performance. The objective of the research is to investigate the mechanism of enhanced oil recovery (EOR) of flue gas assisted steam flooding which has a dual significance of reducing greenhouse gas emissions and improving oil displacement efficiency. In this paper, PVT measurements at high temperature and high pressure (HTHP) were firstly conducted to analyze the effect of flue gas on property of heavy oil. Then sandpack displacement experiments containing 5 sub-experiments: steam flooding, flue gas assisted steam flooding, first steam flooding then flue gas assisted steam flooding, water flooding, flue gas assisted water flooding, were operated to compare the contribution of heat and gas on recovery. In the experiment of flue gas assisted steam flooding, the production rate and composition of gas were measured and analyzed, and the form of the produced oil was also compared with steam flooding. The PVT measurements results show that with flue gas dissolved, viscosity of heavy oil declines and volume expands. The solubility of flue gas in heavy oil decreases with temperature and increases with pressure. The greater the solubility of flue gas, the lower viscosity of heavy oil, the larger volume. At the same solubility, as the temperature increases, the viscosity reduction effect of flue gas weakens and the volume expansion effect enhances. The displacement experiments results indicate that the addition of flue gas to steam can significantly improve oil displacement efficiency compared with steam injected alone. In the test of flue gas assisted steam flooding, the heavy oil was produced in the form of foamy oil because of dissolution of flue gas, especially CO2, which could expand oil volume and reduce the flow resistance of heavy oil to a certain extent. Besides, the cumulative volume of the produced gas was smaller than the injected gas, and in the produced gas the proportion of CO2 was less than the injected proportion. Furthermore, the contribution of flue gas to recovery when injected with steam is greater than with water because of the synergistic effect of heat and gas.
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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".