Klinkenberg gas slippage measurements as a means for shale pore structure characterization
Bibliographic record
Abstract
Abstract Established techniques that have been successfully used to characterize pore systems in conventional reservoir rocks lack the resolution and scalability required to adequately characterize the nano‐ to micrometer scale pore systems found in shale and cannot be applied on stressed samples. We have therefore investigated the utility ofKlinkenberg gas slippage measurements for shale pore structure characterization. In contrast to other approaches, slippage measurements characterize the effective porosity of core samples and can be applied at stress conditions experienced in the reservoir during production. Slippage measurements on horizontally and vertically oriented samples from theEagleFordShaleFormation,Texas,USA, at a range of stress states revealed two orders of magnitude in slippage variation over five orders of magnitude permeability range. Slippage measurements are negatively correlated with permeability and follow similar trends to those found in other studies on higher permeability rocks. The samples had varying degrees of slippage anisotropy, which allowed interpretation of the relative contribution of tortuosity and pore size to permeability anisotropy. Slippage and therefore average effective pore size was found to vary up to one order of magnitude at a given permeability, warranting investigation of the significance this might have on flow properties and ultimately hydrocarbon production from shale.
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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 | 0.001 |
| 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) | 0.001 | 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".