Liquid Permeability Determination from Vacuum Imbibition in Tight/Shale Core Plugs
Bibliographic record
Abstract
Liquid permeability is a key petrophysical parameter that quantifies the ability of a liquid to flow through porous rock/soil and can be used in determining the efficiency of many subsurface processes, including enhanced hydrocarbon recovery, groundwater transport, carbon dioxide geostorage, underground hydrogen storage, etc. However, it is time-consuming (usually >16–240 h) and challenging to measure the liquid permeability for tight/shale rocks, particularly when the permeability is 100 nD or lower. The objective of this study is to develop a rapid and simple approach to determine liquid (brine or oil) permeability in tight siltstones/shales. Specifically, the developed method is based on the combination of one-dimensional (1D) vacuum imbibition experiments in tight/shale core plugs and a modified Lucas–Washburn model. For our proof-of-concept study, the results have demonstrated that (1) only 44–116 h are required to determine the liquid permeability (98–608 nD) for the analyzed samples from the Montney and Yanchang Formations; and (2) the acquired brine permeability was 28.3–28.5% lower than the slip-corrected nitrogen (N 2 ) permeability derived from the pulse-decay permeability tests. This is the first attempt to determine the absolute permeability of a liquid according to a 1D vacuum imbibition experiment and theory. This study provides a promising technique for the fast characterization of ultratight formation permeability of around 100 nD.
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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 | 0.001 | 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 | 0.001 |
| 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".