Pressure Maintenance at post-CHOPS Cyclic Solvent Injection (CSI) Well Using Gas Injection at Offset Well
Bibliographic record
Abstract
Abstract In the $40 million Joint Implementation of Vapor Extraction Program (JIVE), an experiment was performed to investigate CSI behaviour in the Lloydminster region under pressure support from CH4 injection at an offset well. The oil sand pack had high permeability (500 Darcy) and low permeability (3 Darcy) zones that represented regions with and without wormholes. Primary production was followed by two CSI cycles in which the solvent (60% CH4–40% C3H8) was injected at the high permeability end. CH4 offset gas was injected at the low permeability end during CSI production periods. Solvent recovery strategies were evaluated. The primary production drawdown strategy (designed using numerical simulation) resulted in 10.0% oil recovery. Production was only obtained after 6 hours due to a delay in gas exsolution and foamy oil drive. During CSI, a delay in oil recovery also occurred as the pressure-supporting offset gas required time to drive foamy oil generated in that region into the high permeability region. Cycle 1 oil recovery was 6.2%. Cycle 2 had low oil recovery. Post-run gas saturations indicated gravity override occurred. Asphaltene precipitation/deposition occurred as seen from microscopic observation. The asphaltene content was reduced in the produced oil and increased in the post-run oil sand. A rapid pressure drawdown after a third solvent injection period caused 1.7% oil recovery and foamy oil in the production line (Figure 1c). Additional oil recovery (4.5%) was obtained from offset CH4 injection, heating of the sand pack to ~60 °C, and 22 °C nitrogen offset gas injection. Numerical simulations of primary production and CSI cycles showed: the best strategy is rapid well depressurization during productionhigh offset gas rate enhances gravity override and reduces oil production
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".