Development of a novel water shut‐off test method: Experimental study of polymer gel in porous media with radial flow
Bibliographic record
Abstract
Polymer gel treatment is an economic and effective method to reduce excessive water production in hydrocarbon reservoirs. However, there exist unsuccessful applications of polymer gel due to a mismatch of theoretical and experimental results in field conditions. In this study, a gel treatment experiment was implemented using a novel test method which includes a unique two‐dimensional coreflooding setup and a new procedure of simultaneous oil and water injection. To form the gel in situ, a Cr(III)‐acetate‐hydrolyze polyacrylamide (HPAM) gelant was used. The results showed that polymer gel could be successfully applied to water shut‐off (WSO) treatments in low‐permeable porous media with radial flow. The residual resistance factors for oil and water were 78.50 and 1.96, respectively. Polymer gel also showed disproportionate permeability reduction (DPR) behaviour in coreflooding experiments. The flow resistance to water was 40 times greater than that to oil. In gel treatment, high gel selectivity (DPR scale) of 0.83 was measured by simultaneous oil and water flow to the core, and the determined oil cut was much greater than the water cut, whereas a lower well production rate led to a higher water cut. In addition, a water blockage problem was examined in simultaneous injection at constant pressure. No observation of water in the outlet was reported, though water saturation through the sandpack was increased to 84 %. Finally, this paper suggests a new experimental test to increase the chances of successful WSO treatment under laboratory circumstances close to the field conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".