An evaluation of enhanced oil recovery strategies for a heavy oil reservoir after cold production with sand
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Bibliographic record
Abstract
Cold heavy oil production with sand (CHOPS) is the process of choice for unconsolidated heavy oil reservoirs with relatively high gas content. The key challenge of CHOPS is that the recovery factor tends to be between 5% and 15%, implying that the majority of the oil remains in the ground after the process is rendered uneconomic. Continued cold production (without sands) is not productive for a post-CHOPS reservoir because of the low oil saturation and depleted reservoir pressure in the wormhole regions. There is a need to develop viable recovery processes for post-CHOPS reservoirs. Here, different follow-up processes are examined for a post-CHOPS heavy oil reservoir. In post-CHOPS cold water flooding, severe water channeling is ineffective at displacing high viscosity heavy oil. Hot water flooding improves the sweep efficiency and produces more oil compared with cold water flooding. However, the swept region is limited to the domain between the neighboring wormhole networks, and the energy efficiency of the process is relatively poor. Compared with the hot water flooding case, steam flooding achieves higher oil production rates and lower water use. A cyclic steam stimulation strategy achieves the best performance regarding oil production rates and water usage. Based on our results, it is observed that thermally based techniques alone are not capable to recover the oil economically for post-CHOPS reservoirs. However, it is suggested that techniques with combined use of thermal energy and solvent could potentially yield efficient oil recovery methods for these reservoirs. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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