The Pore Scale Description of Carbon Dioxide Storage into High Asphaltene Content Reservoirs
Bibliographic record
Abstract
Abstract The knowledge of how CO2 interacts with reservoir fluids and rock is essential for effective and reliable CO2 storage. This work investigates CO2 storage in unconventional oil reservoirs with high asphaltene content and explains the CO2 storage mechanism in pore-scale. Considering that asphaltenes are insoluble in CO2, asphaltene precipitation is induced during CO2 injection, controlling CO2 solubility and capillary trapping mechanisms. In this study, CO2-oil interaction is examined through core flooding experiments in a high asphaltene content (34.3 wt%) Canadian bitumen sample with 8.8º API. To study how irreversible clay-asphaltene interaction affects CO2 capillary trapping, the reservoir rock is prepared with and without clay addition. The role of CO2 injection rate on solubility trapping with experiments at varying injection flow rates. Displaced fluids and postmortem samples are subjected to several analyses to observe the CO2 storage mechanisms in pore scale due to CO2-asphaltene and CO2-clay-asphaltene interactions. It was found that CO2-clay-asphaltene interaction may favor CO2 capillary trapping into high asphaltene content reservoirs. Reservoir clays play important roles in porosity and permeability reduction due to clay interactions with asphaltenes. The low CO2 flow rate was found to favor solubility trapping. Therefore, our results suggest that the presence of clays and the CO2 injection rate are critical parameters controlling the effectiveness of CO2 storage in high asphaltene content reservoirs. Introduction Underground carbon dioxide (CO2) storage projects usually target the depleted light oil and natural gas fields due to operational expertise, favorable geological features, and existence of infrastructure [1; 2]. However, as CO2 emissions are projected to increase in the next 35 years [3], other storage alternatives are required to mitigate environmental impacts. In this context, CO2 storage in unconventional oil reservoirs with low API gravity may be an attractive candidate on the short to medium term [4; 5]. These low API gravity oils usually have high asphaltene content, which can represent up to 45.3 wt% of the crude oil [6]. CO2 injection can cause asphaltenes precipitate in the pore space as CO2 is insoluble in asphaltenes [7; 8]. Therefore, the effectiveness of CO2 microscopic storage mechanisms will be affected, particularly for capillary (or residual) and solubility trapping.
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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 | 0.001 |
| 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 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".