Research and Application of Fire-Flooding Technologies in Post-Steam Injected Heavy Oil Reservoir
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Bibliographic record
Abstract
Abstract As fire-flooding has strong adaptability to develop the reservoir, it can be considered as a follow-up EOR technology of the low economic profit and high oil recovery reservoirs flooded by water or steam. Because of the complicated secondary water and steam channels, fire-flooding in post-steam-injected reservoir is far different from that in original reservoir. In this paper, the mechanism and problems associated with development engineering of fire-flooding in post-steam-injected heavy oil reservoir was studied systematically by using1D&3D physical simulation systems and reservoir numerical simulator. The temperature of combustion zone decreased and high-temperature zone enlarged because there existed secondary water formed during steam injection which could absorb and carry heat towards producers out of combustion front during fire flooding, but high saturation of water in layer caused by secondary water had less influence on the quantity of fuel deposit and air consumption. In the process of 3D fire flooding experiments, air override was observed during combustion front moving forward and resulted in a coke zone in the bottom of layer, and the ultimate recovery factor reached 65%~70% on fact that the saturation of oil within the coke zone was no more than 20%. The flooding model, well pattern, well spacing, and air injection rate was optimized according to the specific property and the existed well pattern in post-steam-injected heavy oil reservoir, and the key techniques of ignition, lifting, and anticorrosion was also selected in the same time. The pilot of fire flooding in H1 block in Xinjiang oil field was carried out since Dec. 2009on the base of these research work, and now the pilot begin to show the better performance. The production oil is about 49t/d, and the water cut is stable below 70%, the air oil ratio is about 2000m3/t, the good performance is gained for this kind of abandoned post-steam-injected heavy oil reservoir.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it