Quantification of the Viscoelastic Effects During Polymer Flooding: A Critical Review
Bibliographic record
Abstract
Summary Since the late 1960s, several enhanced–oil–recovery (EOR) researchers have developed various continuum and pore–scale viscoelastic models for quantifying the altered injectivity and incremental oil recovery because of the polymer's viscoelastic effects. In this paper, limitations in each of the continuum and pore–scale models are discussed. The critiques are made on the basis of the contradicting literature. Most of the earlier models rely on the exclusive use of the Deborah number to quantify the viscoelastic effects. The Deborah number overlooks mechanical–degradation effects. There exists a large difference in the magnitudes of the reported Deborah number in the literature because of the inconsistency in using different relaxation time and residential time. Oscillatory relaxation time used by most of the EOR researchers to calculate the Deborah number failed to distinguish the different porous–media behavior of the viscous and viscoelastic polymer. Therefore, the accuracy of relaxation time obtained from the weak oscillatory field for EOR applications in porous media is questionable. The main limitation with all the existing continuum viscoelastic models is the empirical reliance on coreflood data to predict the shear–thickening effects in porous media. The strain hardening index, needed for quantifying the thickening regime, cannot be obtained by the conventional shear rheological techniques. The conventional capillary number (Nc) failed to explain the reduction in residual oil saturation (Sor) during viscoelastic polymer flooding. Pore–scale viscoelastic models use the conventional oscillatory Deborah number for quantifying the polymer's viscoelastic effects on Sor reduction. However, this approach has many drawbacks. Discussions on the shortcomings of the existing viscoelastic models caution the current chemical EOR (cEOR) researchers about their applications and potential consequences. Also, this research provides a path forward for future research to address the limitations associated with the quantification of viscoelastic flow through porous media.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".