Porosity characterization using medical computed tomography scans of two deeply buried paleokarst aquifers in Silurian carbonates, southern Ontario, Canada
Bibliographic record
Abstract
Abstract Paleokarst and paleokarst aquifers are not as well-documented as shallow karst, and studies of pores and pore networks are rare. Paleokarst lacks the open conduits typical of karst due to compaction, infilling, and diagenetic recrystallization by deep burial, so groundwater movement is through matrix porosity. In this case study, porosity networks in two saline aquifers in carbonate paleokarst of the Silurian Guelph Formation and Salina A-1 Carbonate Unit in southern Ontario (Canada) have been studied in drill cores at microscopic to macroscopic scales, utilizing medical computed tomography (CT) scans, optical petrography, macroscopic core examination, and scanning electron microscopy. The CT scans provided nondestructive three-dimensional visualization and quantification of pore distribution, size and volume, pore connections, and estimates of total porosity, similar to gas porosimetry. In the A-1 Carbonate, 50% of the pore volume comprises layers of macropores associated with algal laminations, with good horizontal connections. In the Guelph Formation, vuggy macropores contribute most of the pore volume. They are connected through subvertical fractures and rubble-filled karst conduits and by abundant small pores and micropores with poor horizontal connections. The Guelph paleokarst represents a longer period of subaerial exposure as evidenced by its greater thickness and geographic extent, former karst conduits, and near-total destruction of primary sedimentary fabrics. The findings provide real-world examples for construction of laboratory scale models of paleokarst aquifers, demonstrate the value of a multi-scale approach to porosity studies, and showcase the value of medical CT scans with its unique ability to visualize pore connections within drill cores.
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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 | 0.001 | 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 | 0.001 |
| 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".