Wettability Alteration During Low-Salinity Waterflooding in a Deep Tight Carbonate Reservoirs: A Quantitative and Visual Investigation Through Spontaneous Imbibition and Zeta Potentiometric Studies
Bibliographic record
Abstract
Abstract This study focusses on the investigation of wettability alteration behavior during low salinity waterflood (LSWF) process in a tight carbonate reservoir through Zeta potential studies in conjunction with spontaneous imbibition tests and estimation of the contact angle between the wetting fluid and the rock surface. This will help in understanding the role rock-oil-brine interactions play during an LSWF process. The classical streaming potential technique were used to determine Zeta potential. Measurements were carried out with diluted brines using different rock samples of in two states: oil-saturated and brine-saturated. The experimental results imply that the value of zeta potential becomes more negative with increasing percentage of dilution (25%, 10%, and 1%). This is attributed to electrical double-layer expansion which is caused, primarily, by the reduced ionic strength. We concluded that rock saturated with oil may give an insight on oil rock interactions while the rock saturated with brine may give insight on rock-brine interactions. The dilution of water helps increase the electrostatic repulsive forces between the two interfaces, which in turns, leads to the incremental recovery during LSWF process. This observation was also confirmed by coreflooding and wettability experiments through spontaneous imbibition tests and contact angle measurements conducted using the same oil-brine-rock systems. This is an investigative study of oil-brine-rock interaction behavior during a LSWF process that is difficult to accomplish through and during a conventional coreflooding displacement test. In addition, this study also couples the relationship between the wettability alteration and oil-brine-rock interactions during an LSWF process.
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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 | 0.000 |
| 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 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".