Lithostratigraphic compilation of Phanerozoic bedrock units and 3D geological model of southern Ontario
Bibliographic record
Abstract
A 3D geological model of the Paleozoic bedrock geology of Southern Ontario is being developed through a collaborative project involving the Ontario Geological Survey (OGS), Geological Survey of Canada (GSC), Ministry of Natural Resources & Forestry (MNRF), and Oil, Gas, Salt, Resources Library (OGSRL). This multi-year initiative involves a number of parallel objectives, including: 1) update of rock unit nomenclature at formation and group levels; 2) characterize criteria for delineating formational contacts; 3) better constrain the bedrock topography surface by integrating data from regional MOECC (water) and OGSRL (oil and gas) wells; 4) develop a revised bedrock topography for Lake Ontario from legacy shallow reflection data; 5) revise formation boundaries to update the Paleozoic bedrock geology maps; and 6) delineate groundwater types (potable vs non-potable) with a focus on potable groundwater within the shallow, karst-influenced, carbonate-dominated and cuesta-forming bedrock successions. The latter two initiatives will extend beyond the scope of the 3D Paleozoic bedrock model project. This project builds upon the OGS mandate to map the potable groundwater resources of Ontario and the GSC mandate to delineate key aquifers across the country. Preliminary 3D geologic models have been developed using LeapfrogTM Hydro implicit modelling software based on more than 26,700 deep petroleum boreholes and published OGS bedrock geology maps. The model area covers approximately 110,000 km2, extending across south-central and southwestern Ontario and beneath the Great Lakes to the US border, but not Manitoulin Island. The model currently comprises 61 layers and attempts to render the bedrock topography, the Precambrian- Paleozoic contact, and the regional variability of 58 Paleozoic bedrock formations plus sediment cover. It is a product of an ongoing, iterative process of interim modelling, model review, and QA/QC editing of formation picks. LeapfrogTM modelling software is used to produce 3D models based upon Radial Basis Functions primarily using the formation depth picks. LeapfrogTM lends itself well to iterative data QA/QC because data inputs can be readily reloaded without the need to re-construct the formation contact structure and model chronostratigraphy. The formation model will eventually be reclassified to a hydrostratigraphic model. In 2015 and 2016 project geologists reviewed over 50,000 formation picks by examination of geophysical logs, core and drill cuttings, and more than 100,000 digital water well records. Issues resolved include: well location errors, formation assignment, anomalous data points, and wells with missing or incorrect formation picks and bedrock characterization. The study integrates traditional outcrop/field- and lab-based protocols and petroleum industry subsurface mapping techniques, with GIS, database mining and queries, and 2D and 3D mapping and modelling techniques. Over the past 12 months, efforts have focused on refining formational contacts and regional distributions of Paleozoic formations, including: 1) stacked Ordovician-, Silurian- and Devonian-age carbonates that form regional karstic escarpments that are variably blanketed by Quaternary sediments; 2) select Devonian and Cambrian siliciclastics; and 3) key regional clay-rich sedimentary rocks and mixed carbonates-siliciclastics that appear to form regional to sub-regional aquitards.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".