An Investigation of Multicomponent Gas Flow in Porous Media
Bibliographic record
Abstract
Abstract The complex gas dynamics in tight and shale reservoirs have become an important research topic in the oil and gas industry. This study proposes a steady-state flow test using adsorbing and non-adsorbing gases of single and binary gas components through tight adsorbing and non-adsorbing cores to investigate the true permeability value of its diffusion and slip counterparts. A steady-state flow permeability test was chosen to capture the complex gas dynamics in nanopore throats and the presence of organic matter. 1-D experiments in adsorbing (shale) and non-adsorbing (sandstone) cores are conducted under high overburden pressure at room temperature. The pressure difference and gas flow rates across the cores are measured. Helium (base case) is flowed, followed by adsorbing gases (N2 and CH4). This is followed by flowing gas mixtures to verify whether the single component values can be used in multicomponent systems. The results are compared to existing theoretical and analytical models. The apparent gas permeability for shale and sandstone decreases as the gas changes from non-adsorbing to adsorbing. This observation is not in line with the proposed hypothesis of the current models, where the flow mechanisms in tight and shale formations are treated like parallel resistors, where the total permeability is the addition of each component. The adsorbing gas significantly influences gas permeability when comparing the Klinkenberg plots for single and binary gas. The binary gas permeabilities skewed heavily to the gas with higher adsorbing capacity. Besides that, the adsorbing gas permanently changes the shale pore throat morphology by decreasing the pore radius, which significantly affects the flow mechanisms in shale. The study centered on the dissection of the flow mechanisms (viscous flow, surface diffusion, and Knudsen diffusion) contributing to the permeability calculations. Viscous flow dominates the more permeable porous media, while Knudsen diffusion is in the shale. Besides that, the binary gas mixture in a standard steady-state flow test in permeability estimation is introduced. The binary gas mixture in permeability measurement introduces the effect of gas flooding on the measured permeability. The more adsorbing gas actively displaces the less adsorbing gas and contributes to the surface diffusion permeability.
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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 | 0.001 | 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) | 0.000 | 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 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".