Effects of Wetting Behaviour on Residual Trapping in CO2-Brine Systems
Bibliographic record
Abstract
Abstract After injecting CO2 into the formations containing brine, it starts to penetrate to upper sections and will be trapped under a geological barrier, during this period the formation brine will imbibe the CO2 and some portion of it will be trapped in the pore spaces. Capillary forces prevent complete drainage of CO2 and residual saturation remains trapped in the pores. Wetting behaviour of the CO2-brine system and relative permeability to each of the phases are important modeling parameters in this phenomenon. In such a system with cycling behaviour, hysteresis in relative permeability has strong effect on trapping. There are debates on wetting behaviour of candidate formations for CO2 storage. Different wettability conditions of the formations, affect the residual trapping mechanism. In this study, theoretical concept of residual trapping is defined through flow equations, and the effect of wettability is discussed by conceptual models. To verify the theoretical concept, different wettability conditions are modeled based on the Utsira formation of Sleipner reservoir and also the Viking formation (Canadian brine formation). Hysteresis in relative permeability and capillary pressure is considered in the modeling of both cases. Results indicate that different wettability cases including strongly water wet to intermediate and slightly water wet condition, gives variation in the predicted trapped volume of CO2. This variation is from about 2 to 13% in different scenarios of this case study. Results of the simulations verify that wettability behaviour has both short and long term consequences in CO2 trapping. In low permeability simulation case, residual CO2 volume is more sensitive to the wettability condition. Results are dependent on the choice of hysteresis models but wetting behaviour of the system is the main subject that is targeted in this study.
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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 | 0.001 |
| 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 | 0.001 | 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".