Mobility Control by Polymers Under Bottom-Water Conditions, Experimental Approach
Bibliographic record
Abstract
Abstract In many light or moderately viscous oil reservoirs in Saskatchewan and Alberta, a high water saturation zone ovarying thickness and extent ("bottom-water zone") occurs in communication with the oil zone above. As a result, the primary production period is short, and water coning occurs very early in the life of the reservoir. Later, during the secondary recovery stage, such a zone can have an adverse effect on the waterflood efficiency. This research addresses the problem of waterflooding such reservoirs. This study was directed towards reducing water mobility in the bottom-water zone for more efficient oil displacement. Polymer in various concentrations was used as a blocking agent in the bottom-water zone and as a mobility control agent in the oil zone. Different strategies were investigated to reduce the water mobility in the bottom-water zone and improve the vertical sweep efficiency. The variables examined were: relative water-oil layer thickness, oil viscosity, polymer concentration, injection rate and injection point, as well as the effect of vertical and horizontal injection and production wells. The results showed that oil recovery could be increased by minimizing crossflow between layers by blocking the bottom- water zone completely. It was also found that for an unfavourable mobility ratio, as the injection rate increases the ultimate oil recovery increases. The injection of a polymer solution had a favourable impact on waterflood performance. Moreover, the worse the conventional waterflood performance was, the more effective the polymer was as a mobility and blocking control agent. The use of horizontal wells showed slightly better oil recovery over vertical wells in a conventional waterflood of reservoirs under bottom-water conditions. In addition, some certain well combinations (horizontal production and vertical injection) gave better oil recovery due to the increase in the swept area.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".