Quantifying Resources for the Surmont Lease with 2D Mapping and Multivariate Statistics
Bibliographic record
Abstract
Summary The McMurray formation consists of heterogeneous Cretaceous-bitumen-saturated sands. The reservoirs are thick and laterally extensive in the main fairways. Many commercial projects are in the early stages of development. Resources too deep to mine are considering steam assisted gravity drainage (SAGD) (Butler 1991). Detailed high-resolution 3D geostatistical modeling is useful for individual well-pair or pad flow simulation, but is neither practical nor necessary for resource assessment across large areas. A methodology for resource assessment is developed from a geostatistical study on the Surmont lease. The uncertainty in more than 30 correlated variables is calculated on a dense 2D grid using all available information including wells, seismic, and geologic trends. The correlation structure between the variables is modeled under a multivariate Gaussian model. The local distributions of uncertainty have been checked with cross validation and with more than 100 new wells drilled during the last two drilling seasons. Resource uncertainty across the entire lease area and a number of arbitrary development areas is derived from the 2D maps of uncertainty. A combined P -field/LU simulation approach is used; the global uncertainty is consistent with the local uncertainty.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".