Effect of small scale flow barriers heterogeneities and connate water on displacement efficiency of polymer floods to heavy oil reservoirs
Bibliographic record
Abstract
Abstract This work concerns a fundamental understanding of how heterogeneities induced by flow barriers and connate water affect the displacement efficiency of polymer floods, which has rarely been studied in the available literature. Here, a series of water/polymer injection experiments to heavy oil performed on five‐spot glass micromodels containing randomly distributed shale structures is presented. It has been found that macroscopic efficiency of polymer flooding majorly depends on flow barriers distribution/configuration; shale content and geometrical characteristics; presence of connate water and wettability of medium. Microscopic pictures revealed that the main parts of connate water were trapped in some pores/throats near and especially behind the shale streaks; also, presence of connate water causes a reduction of sweep efficiency due to premature breakthrough of displacing fluid in an oil‐wet media. In absence of connate water, polymer solution could linger and stick to the pore walls to delay the time for a polymer to channel to the production site. Results of this work disclose requirements for a detailed geologic study of barrier size and distribution for successful design of EOR processes in heterogeneous reservoirs.
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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".