Natural gas vaporization in a nanoscale throat connected model of shale: multi-scale, multi-component and multi-phase
Bibliographic record
Abstract
Production of hydrocarbons from shale is a complex process that necessitates the extraction of multi-component hydrocarbons trapped in multi-scale nanopores. While advances in nanofluidics have allowed researchers to probe thermodynamics and transport in single, discrete nanochannels, these studies present a highly simplified version of shale reservoirs with homogeneous pore structures and/or single-component fluid compositions. In this study, we develop and apply a 30 000-pore nanomodel that captures the inherent heterogeneity in reservoir pore sizes (100 nm pores gated by 5 nm-pores) to study vaporization of a representative natural gas hydrocarbon mixture. The nanomodel matches major North American formations in the volumetric and number contributions of the pore sizes, porosity (10.5%), and ultra-low permeability (44 nD). Combined experimental and analytical results show 3000× slower vaporization owing to the nanoscale throat bottlenecks. At low temperatures, mixture effects reduce rates further with stochastic vaporization of light components in large pores dominating. Collectively this approach captures the coupled complexity of multicomponent, multiphase fluids in multiscale geometries that is inherent to this resource.
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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 | 0.000 |
| 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".