Enhanced Heavy Oil Recovery on Depleted Long Core System by CH4 and CO2
Bibliographic record
Abstract
Abstract This paper describes a laboratory study of potential post-cold production strategies for heavy oil reservoirs. The tests were conducted on two primarily depleted long core systems (glassbeads core and sandpack core). The glassbeads core is 18.2 m in length with higher permeability (11.8 Darcy) and the sandpack core is 18.5 m long with lower permeability (1.9 Darcy). Both core systems were recharged by CH4 injection followed by a depletion step similar to the cold production experiment. Both cores were then exposed to a single cycle of CO2 injection, soaking and production. This work aims at further understanding the heavy oil solution gas drive mechanism. Furthermore, the study aims at assessing methane and carbon dioxide recharging as a potential recovery method for heavy oil reservoirs, and at establishing a base line for comparison against each other. Results of this study indicate that CH4 and CO2 recharge processes give an additional 8% and 9% OOIP recovery for the glassbeads core and the sandpack core, respectively. Since the cold production for the glassbeads core (22.2% OOIP) was high, the low recharge recoveries may be pessimistic. However, for the sandpack core, the recharge recovery appears more optimistic with almost similar recovery to that of cold production (about 10.2% OOIP).
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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 | 0.000 |
| 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".