Characterization of Mixed Wettability using Surface Energy Distribution
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Bibliographic record
Abstract
Abstract A systematic approach to characterize the mixed wet configurations of various reservoir rocks (sandstone and carbonates) by evaluating their surface energy distributions has been presented in this paper. This approach was tested against the macroscopic spatial distribution of oil-wet and water-wet sites and at different temperatures for validation. The new approach used to characterize the mixed wettability of a reservoir rock pertains to establishing a relation between the volume fraction of the mixed-wet reservoir rocks and surface energy of the mixture. This approach is based on an accurate description of the various physico-chemical interfacial forces present at the reservoir rock surface using Inverse Gas Chromatography (IGC). Mixed-wet configurations of various reservoir rocks are created by combining water-wet and oil-wet samples of the rock in different volume fractions and shaken together to establish uniform distribution. These samples are then subjected to the IGC analysis at different temperatures to deduce their surface energy distribution. The relation developed herein is tested against spatial heterogeneity by combining the oil-wet and water-wet rock samples in a layered fashion to validate the approach. The complete method to deduce the surface energy distribution of a rock surface using IGC has also been explained in detail. A definite and conclusive relationship between the surface energy and mixed wettability of silica glass beads, calcite, and dolomite samples was established in this study. The mixed-wet configurations of the rock samples ranged from 0% oil-wet (meaning water-wet samples) to 100% oil-wet samples. The findings indicated that the Lifshitz-van der Waals component of the rock mixture did not undergo any change with change in the wetting state of the system under study. However the acid base components showed a marked decrease with increasing oil wetness before plateauing. Temperature was found to have a profound impact on the surface energy of a rock surface. Spatial heterogeneity by way of layered and segregated distribution of oil-wet and water-wet sites did not affect the eventual surface energy distribution thereby validating the new approach.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 it