Modelling Pore Occupancies in Three-phase Displacements from Micro-CT Images Using a Physics-Based Theory of Wettability and Miscibility Conditions
Bibliographic record
Abstract
Abstract Advanced digital rock technology using X-ray microtomography (micro-CT) has been applied to investigate three-phase pore occupancies in rock samples. These three-phase experiments involved different injection sequences in water-wet, oil-wet and mixed-wet rocks under immiscible and near miscible conditions using carbon dioxide or nitrogen as injected gases. In this work, the process-based theory of van Dijke et al ., which has been previously used in both capillary bundle (CB) and 3D-lattice pore network models (PNM), is applied to simulate all the available published three-phase pore occupancy data. The predicted three-phase pore occupancies from the CB model are compared to the experimental results. The three-phase theory first uses the physical parameters as reported by the original authors; namely, the three values of interfacial tension (σ ow , σ go , and σ gw ), wetting conditions and the distribution of oil–water contact angle where a single contact angle is assigned to each pore. However, there are some uncertainties in these quantities, and to achieve a good match some reasonable adjustment of the input data is usually required. For water-wet systems, the best agreement with the measured pore occupancy is achieved with only minor parameter adjustments: for example, a change of 2 mN/m in gas-oil interfacial tension and a decrease in gas–water interfacial tensions to represent true three-phase equilibrium conditions. For oil-wet and mixed-wet systems, adjusted contact angle distributions, within the experimental uncertainty, are also required to match the data. Both the experimental results and modelling predictions show that three-phase displacements are the same at immiscible (gas-oil interfacial tensions of around 10 mN/m or more) and near-miscible (gas-oil interfacial tensions of approximately 1 mN/m) conditions for water-wet cases, while in oil-wet systems, miscibility affects the wetting order of gas and water. Water becomes the most non-wetting phase at near-miscible conditions and gas is intermediate-wet. The model developed in this work also helps (i) to interpret the physical processes in the experiment and (ii) to determine the likely equilibrium values of interfacial tension and contact angles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".