Advances in Understanding Relative Permeability Shifts by Imbibition of Surfactant Solutions into Tight Plugs
Bibliographic record
Abstract
Abstract Various chemical additives have been recently proposed to enhance imbibition oil recovery from tight formations during the shut-in periods after hydraulic fracturing operations. Although, soaking experiments under laboratory conditions usually confirm the performance of such additives, their effects on oil regained permeability during the flowback process are poorly understood. This is mainly because measuring effective permeability of such low-permeability rocks is extremely challenging. We develop and apply a laboratory protocol mimicking leak-off, shut-in, and flowback processes to evaluate the effects of fracturing fluid additives on oil regained permeability. We modify the conventional coreflooding apparatus to measure oil effective permeability (koeff) before and after the surfactant-imbibition experiments. Adjusting the system total compressibility allows quickly achieving steady-state conditions at multiple ultra-low flowrates. We apply the proposed technique on two tight plugs with and without initial water saturation (Swi), and observe pressure humps during the flowback process that can be explained mathematically using the fractional-flow theory. Spontaneous imbibition of the surfactant solution into the two oil-saturated plugs results in recovery of around 20% of the initial oil. For the plug with Swi = 0, koeff is reduced from around 3 µD to 1 µD, indicating the adverse effect of water trapping over the favorable effects of interfacial tension reduction and wettability alteration by the surfactant. For the plug with Swi = 0.21, koeff increases from 0.85 µD to 1.08 µD that can be explained by the combined effects of Swi reduction and wettability alteration, favorably shifting the oil relative permeability curve.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".