Wettability Alteration of Heavy-Oil-Bitumen-Containing Carbonates by Use of Solvents, High-pH Solutions, and Nano/Ionic Liquids
Bibliographic record
Abstract
Summary Capillary imbibition tests are commonly applied to measure wettability-alteration potential of chemicals. However, these tests are exhaustive, time-consuming, and expensive, and the underlying physics of the alteration process from a surface-chemistry point of view is often limited and/or unexplained. Contact-angle measurement is a quicker and more-feasible screening tool to assess the emerging wettability modifiers. It also provides visual data on the mechanics of the wettability-alteration process. This paper focuses on contact-angle measurements as a means to evaluate the wettability alteration on mineral plates and porous-rock samples. Imidazolium ionic liquids were tested at different concentrations. To study the effect of pH on the wettability, sodium chloride and sodium borate were used at different concentrations. The composition of divalent ions was varied because of their possible use with low-/high-salinity water as wettability-alteration agents. Unmodified and surface-modified silica, zirconium, and alumina nanoparticles were also tested. Contact-angle measurements were performed initially on mica, marble, and calcite plates. Experiments were repeated on polished surfaces of Berea sandstone, Indiana limestone, and cleaned Grosmont carbonate cores. Oils (pure and solvent-mixed crude oils) with different viscosities and densities were used to test the effect of oil type on the process. The images were obtained by an single-lens reflex (SLR) camera at different temperatures ranging from 25 to 80°C. By testing with different concentrations, the optimum chemicals were found for different mineral-plate/porous-rock systems. Then, the results were cross checked with the imbibition tests performed on the same samples to validate the contact-angle-measurement observations. Thermal-stability tests were also performed in case of their use during or after a thermal method. For the thermal-stability tests, contact-angle experiments were conducted in a high-pressure and high-temperature (up to 200°C) cell. It was shown that certain ionic liquids and nanofluids are stable at high temperatures and can be efficiently used at low concentrations.
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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) | 0.001 | 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".