What are the Dominant Flow Regimes During Carbon Dioxide Propagation in Shale Reservoirs’ Matrix, Natural Fractures and Hydraulic Fractures?
Bibliographic record
Abstract
Abstract Carbon dioxide (CO2) injection in low permeability shale reservoirs has recently gained much attention due to the claims that it has a large recovery factor and can also be used in CO2 storage operations. This research investigates the different flow regimes that the CO2 will exhibit during its propagation through the fractures, micropores, and the nanopores in unconventional shale reservoirs to accurately evaluate the mechanism by which CO2 recovers oil from these reservoirs. One of the most widely used tools to distinguish between different flow regimes is the Knudsen Number. Initially, a mathematical analysis of the different flow regimes that can be observed in pore sizes ranging between 0.2 nanometer and more than 2 micrometers was undergone at different pressure and temperature conditions to distinguish between the different flow regimes that the CO2 will exhibit in the different pore sizes. Based on the results, several flow regime maps were conducted for different pore sizes. The pore sizes were grouped together in separate maps based on the flow regimes exhibited at different thermodynamic conditions. Based on the results, it was found that Knudsen diffusion dominated the flow regime in nanopores ranging between 0.2 nanometers, up to 1 nanometer. Pore sizes between 2 and 10 nanometers were dominated by both a transition flow, and slip flow. At 25 nanometer, and up to 100 nanometers, three flow regimes can be observed, including gas slippage flow, transition flow, and viscous flow. When the pore size reached 150 nanometers, Knudsen diffusion and transition flow disappeared, and the slippage and viscous flow regimes were dominant. At pore sizes above one micrometer, the flow was viscous for all thermodynamic conditions. This indicated that in the larger pore sizes the flow will be mainly viscous flow, which is usually modeled using Darcy's law, while in the extremely small pore sizes the dominating flow regime is Knudsen diffusion, which can be modeled using Knudsen's Diffusion law or in cases where surface diffusion is dominant, Fick's law of diffusion can be applied. The mechanism by which the CO2 improves recovery in unconventional shale reservoirs is not fully understood to this date, which is the main reason why this process has proven successful in some shale plays, and failed in others. This research studies the flow behavior of the CO2 in the different features that could be present in the shale reservoir to illustrate the mechanism by which oil recovery can be increased.
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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 | 0.001 |
| 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".