Physical and Mathematical Aspects of Tortuosity in Regard to the Fluid Flow and Electric Current Conduction in Porous Media: Example of the Hibernia and Terra Nova Reservoirs, Off the Eastern Coast of Canada
Bibliographic record
Abstract
Tortuosity tau is physically defined as the ratio (or the square of the ratio) of the effective length of pore channels (through which the hydraulic flow and electric current are conducted) to the length parallel to the overall direction of the pore channels in a porous medium. It has a significant influence on hydraulic flow and electric current because of its response to the variations in lithology, pressure and petrophysical properties. Determination of tortuosity enables one to understand the mechanisms of hydraulic flow and electric current, and the channel-network com plexities in porous media. In this study, physical and mathematical aspects of tortuosity are discussed. Also, tortuosity is mathematically derived as the square root of the dimensionless formation resistivity factor times fractional porosity. Tortuosity can be successfully used for interpretation of the physical behavior of unconsolidated and consolidated porous media, similarly, and for formations characterized by high degrees of compaction, heterogeneity and anisotropy, as in the case of the Hibernia and Terra Nova reservoirs, off the eastern coast of Canada.
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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 | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 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 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".