Water Ion Interactions at Crude Oil-Water Interface: A New Fundamental Understanding on SmartWater Flood
Bibliographic record
Abstract
Abstract SmartWater flooding through tailoring of injection water salinity and ionic composition is getting good attention in the industry for improved oil recovery in carbonate reservoirs. Surface/intermolecular forces, thin-film dynamics and capillary/adhesion forces at rock-fluids interfaces govern crude oil liberation from pores. On the other hand, stability and rigidity of oil-water interfaces control the destabilization of interfacial film to promote coalescence between released oil droplets and contribute to recovery. As a resultant, the oil recovery in SmartWater flood is due to the combined effect of favorable interactions occurring at both oil-brine and oil/brine-rock interfaces across the thin-film. Most of the laboratory studies reported so far have been focused on only studying the interactions at rock-fluids interfaces. The other important aspect of characterizing water ion interactions at crude oil-water interface has not been well recognized and still remains largely unexplored. In this study, a detailed experimental investigation was carried out to understand the effects of different water ions at crude oil-water interface, using several novel instruments such as Langmuir trough, interfacial shear rheometer, attension tensiometer and coalescence time measurement apparatus. The crude oil from a typical Saudi Arabian reservoir and four different water recipes with varying salinities and individual ion concentrations were used. Interface pressures, compression energy, interfacial viscous and elastic moduli, oil droplet crumpling ratio and coalescence time between crude oil droplets are the major experimental data measured. Interfacial pressures gradually increased with compressing surface area for all the brines and deionized (DI) water. The compression energy (integration of interfacial pressure over the surface area change) is the highest for DI water, followed by the lower salinity brine containing sulfate ions indicating rigid interfaces. The transition times of interfacial layer to become elastic-dominant from viscous-dominant structures is found to be much shorter for brines enriched with sulfates, once again confirming the rigidity of interface. The crumpling ratios (oil drop wrinkles when contracted) are also higher with the two recipes of DI water and sulfates-only brine to indicate the same trend and confirm elastic rigid skin at the interface. The coalescence time between oil droplets were the least in brines containing sufficient amount of calcium, magnesium and sodium ions, while the highest in DI water and sulfate rich brine respectively. These results therefore showed good correlation of coalescence times with the rigidity of oil-water interface, as interpreted from different measurement techniques. This study for the first-time provided a comprehensive characterization of crude oil-water interface to understand microscopic scale water ion interactions and mechanisms responsible for coalescence between crude oil droplets in SmartWater flood. The results also indicated the importance of both salinity and certain ions, such as calcium, and magnesium in the SmartWater, to enhance the coalescence between released crude oil droplets and quickly form oil bank in the reservoir for faster oil 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 | 0.001 |
| Scholarly communication | 0.000 | 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".