The Application of Performed Particle Gel for Water Shutoff and Flooding in Severe Heterogeneous Reservoir
Bibliographic record
Abstract
The success of in-depth fluid diversion and enhancement of the pay zones production are hot issues in long term water flooded oilfields. However, the effect of most chemical-based water cut technologies and conformance-control treatments on fluid profile conformance are normally useful surround near wellbore zones. In addition, chemical particles can probably result in formation damage on low permeable parts of pay zone and the other potential drawbacks. Comparing to general chemical agents such as cross linker, polymer gel, foam fluid and so forth. A water shutoff plugging agent called PPG (Performed Particle Gel) show its advantage in strength-control, size-control and environment-friendly. PPG is a type of gel and synthesized with aqueous, acrylamide, cross linker and the other additives, which can be prepared at surface rather than in the wellbore, thus it is not so sensitive to high temperature and high salinity. A series of studies and field experiments through core flooding were investigated in this paper. The results indicate PPG can significantly achieve in-depth conformance in sever heterogeneous formation and can be widely applied in mature water flooded oil fields. Key words: Heterogeneous; Performed particle gel; Water shutoff; Recovery
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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".