Microscopic regulation and displacement mechanism of polymer–microsphere plug combination for enhanced oil recovery in sandstone reservoirs
Bibliographic record
Abstract
Abstract To investigate the mechanisms of deep regulation and displacement technologies for enhancing oil recovery in sandstone reservoirs, a proprietary profile control experimental system integrated with real‐time computed tomography scanning was utilized to achieve, for the first time, full‐cycle three‐dimensional visualization of the microscopic residual oil displacement process. Despite the promising results, pore blockage and long‐term stability of the injected plugs require further investigation. By conducting comparative analyses of the evolution characteristics of microscopic residual oil saturation before and after regulation and displacement under varying plug conditions, the changes in the spatial distribution and occurrence state of microscopic residual oil were quantitatively examined. Results indicate that: (a) Microscopic residual oil primarily exists in network‐like, porous, and isolated forms, with network‐like and porous forms accounting for 82.93%–91.41%, the reduction of which indicates the improved displacement effectiveness and better recovery subsequently; (b) Regulation and displacement effectively block high‐permeability channels and increase displacement pressure in medium‐to‐small pores, network‐like and porous residual oil gradually transitions into isolated residual oil after the deep regulation and displacement, with its proportion increasing from 0.8% to 39.6%; (c) The polymer–microsphere plug combination exhibits superior performance compared to a single plug, the recovery of the combination plug reaches 1.11 times that of the single plug method, presenting a great potential field applications by taking care of some scale‐up considerations, like formation heterogeneity, chemical stability, and so on. The research provides theoretical support for designing regulation and displacement strategies for water‐flooding sandstone 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) | 0.000 | 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 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".