Challenges in building a 3-D geologic model of the Paleozoic bedrock of southern Ontario
Bibliographic record
Abstract
A regional 3-D geological model of the Paleozoic bedrock of southern Ontario is in its third year of development. The current version is in the early stages of review and is scheduled to be available as a public domain product in autumn 2018. The model encompasses all south-western and south-central Ontario, an area of 110,000 km2 and the complete Paleozoic sedimentary bedrock succession. This project is a collaboration of the Geological Survey of Canada, Ontario Geological Survey (OGS), Ontario Ministry of Natural Resources and Forestry (MNRF) and the Oil, Gas and Salt Resources Library (Library). The model is constructed in Leapfrog© Hydro (Aranz Geo Limited) - an implicit modelling application. Layers representing 58 geological formations were constructed using formation depth data from 26,700 petroleum borehole records in the Ontario Petroleum Data System (OPDS), supplemented by hundreds of deep bedrock boreholes compiled by OGS. OPDS is an Oracle relational database built and maintained by the MNRF and the Library, representing borehole data collected over 150 years of petroleum drilling. Formation depth data in the borehole records comprise the primary data input for the 3-D model. Leapfrog also allows layers to be augmented by 3-D vector objects. For this model an OGS digital bedrock topography surface is combined with a revised 2-D subcrop geology map to assemble a grid of 3-D points that approximate the subcrop surface of each mapped formation. These, along with digitized 3-D surface polyline and point constraints are used to better align the modelled layers with expert knowledge and mapped geology. Model development is an iterative cycle of interim model construction, expert geological appraisal to identify errors/inconsistencies in both the model construction and borehole database, followed by editing of formation depth data using geophysical logs, drill cuttings and drill core and a revised lithostratigraphy. Errors in early models were dominated by incorrect borehole location coordinates, data entry errors, and missing and inconsistent formation contact picks, and were expressed as anomalies on modelled formation surfaces. Database integrity and model construction have improved to the point that the current model is approaching a geologically robust result. Issues that have been corrected or are in the process of being dealt with include: inaccurate thickness extrapolations beneath Lake Huron, to be remedied by addition of Michigan borehole data; gaps in continuity of thin formations caused by widely-spaced boreholes, to be remedied by addition of control points with inferred formation depths; obsolete stratigraphic terminology in the database has been corrected; lack of subdivision of the Lockport Group into its constituent formations has been corrected for 397 wells; extrapolations of modelled Silurian formations beyond their erosional limit at the Niagara Escarpment will likely require manual intervention due to functional limitations in the Leapfrog Hydro application; incorrect pinchout edges, caused by data gaps, remedied by addition of measured sections and OGS stratigraphic boreholes; scattered anomalous outliers for several formations may require manual intervention; inconsistent identification of Devonian sandstones, remedied by a separate project to characterize and map the sandstone units; inconsistent identification, correlation and integration of the Bois Blanc and Onondaga formations + unnamed sandstone units. The model is vetted by geologists with many years of experience working in southern Ontario. The model will provide an unprecedented regional perspective and digital framework to support resource exploration, hydrogeological/environmental investigation, education and informed decision-making related to resource management and land-use planning. The model lacks the level of detail needed for a small-scale site-specific investigation, but provides a regional context and may be adapted with the addition of detailed field mapping, new boreholes and structural data.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".