Theoretical Interpretation of pH and Salinity Effect on Oil-in-Water Emulsion Stability Based on Interfacial Chemistry and Implications for Produced Water Demulsification
Bibliographic record
Abstract
The petroleum industry produces thousands of barrels of oilfield waters from the initial stage driven by primary production mechanisms to the tertiary stage. These produced waters contain measurable amounts of oil-in-water emulsions, the exact amounts being determined by the chemistry of the crude oil. To meet strict environmental regulations governing the disposal of such produced waters, demulsification to regulatory permissible levels is required. Within the electric double layer theory, coupled with the analytical solutions to the Poisson–Boltzmann Equation, continuum electrostatics approaches can be used to describe the stability and electrokinetic properties of emulsions. In the literature, much of the surface charge density and zeta potential relationship to emulsion stability has been confined to systems with less salinity. In this paper, we have exploited the theoretical foundations of the electric double layer theory to carry out theoretical evaluations of emulsion salinity based on zeta potential and surface charge density calculations. Most importantly, our approaches have enabled us to extend such theoretical calculations to systems of the higher salinity characteristic of oil-in-water emulsions found in oilfield-produced waters, based on crude oil samples from the literature with varying surface chemistry. Moreover, based on the definition of acid crude oils, our choice of samples represents two distinct classes of crude oils. This approach enabled us to evaluate the stability of emulsions associated with these produced oilfield waters in addition to predicting the potential of demulsification using demulsifiers. Given that the salinity range of this study is that encountered with the vast majority of produced oilfield waters, the findings from our theoretical predictions are perfect guides as far as emulsion stability is concerned.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".