Frequency-dependent Streaming Potential of Reservoir Rocks
Bibliographic record
Abstract
Summary The scientific literature is almost devoid of frequency-dependent electro-kinetic measurements on geological materials. We have designed, constructed and tested an apparatus that allows the measurement of the streaming potential coupling coefficient and zeta potential of unconsolidated reservoir materials. The apparatus uses an electro-magnetic drive and operates in the range 1 Hz to 1 kHz. The sample diameter is 25.4 mm and samples can be up to 150 mm long. We have made streaming potential coupling coefficient measurements on samples of Ottawa sand as a function of frequency. The results have been analyzed using critically and variably damped second order vibrational mechanics models as well as the theoretical models of Packard (1953) for capillary tubes and Pride (1994) for porous media. Such modelling allows a transition frequency to be calculated, which can in turn be used to calculate the pore radius of the samples. The permeability of the samples can then be obtained using the work of Walker and Glover (2010). In all cases the transition frequencies were in good agreement with those expected from independent measurements of effective pore radius that were derived from laser diffraction and MICP measurements. This indicates that the transition frequency measurements can be used to calculate the effective pore radius of the reservoir material. Fluid permeability predicted from the transition frequency were also in good agreement with those measured on the sand samples.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".