Water Mixing During Waterflood Oil Recovery: The Effect of Initial Water Saturation
Bibliographic record
Abstract
Summary This work studies the mixing of injected water and in-situ water during waterfloods and demonstrates that the mixing process is sensitive to the initial water saturation. The results illustrate differences between a waterflooded zone and a preflooded zone during, for example, water-based EOR displacement processes. The mixing of in-situ, or connate, water and injected water during laboratory waterfloods in a strongly water-wet chalk core sample was determined at different initial water saturations. Dynamic 1D fluid-saturation profiles were determined with nuclear-tracer imaging (NTI) during waterfloods, distinguishing between the oil phase, connate water, and injected water. The mixing of connate and injected water during waterfloods, with the presence of an oil phase, resulted in a displacement of all connate water from the core plug. During displacement, connate water banked in front of the injecting water, separating (or partially separating) the injected water from the mobile oil phase. This may impact the ability of chemicals dissolved in the injected water to contact the oil during secondary recovery and EOR processes. The effect of the connate-water-bank separation was sensitive to the initial water saturation (Swi). The time difference between breakthrough of connate water and breakthrough of injected water at the outlet showed a linear correlation to the initial water saturation Swi. The results obtained in chalk confirmed earlier findings in sandpacks (Brown 1957) and thus demonstrated the generality in the results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".