Hydrocarbon flow modeling in complex structures (Mackenzie Basin, Canada)
Bibliographic record
Abstract
Abstract The Mackenzie Basin in northwest arctic Canada has many characteristics of a typical terrestrial, gas-rich sedimentary basin, but the origins of this important hydrocarbon province are still not well known. The three-dimensional basin modeling approach employed here illustrates not only improved capabilities but also potential pitfalls in reproducing flow in complex stratal and structural basin architectures of present-day models. Listric fault structures especially are still inadequately reproduced in most migration models. By integrating individual styles of deformation and introducing a sequence-stratigraphic approach to reproduce the stratal architecture, we are able to identify temporal and spatial relationships between sources and reservoirs. Based on these considerations, three genetic groups of oils in the basin are proposed: a first group mainly related to a Paleocene source rock, a second group related almost exclusively to an early mature source in the Eocene Taglu formation, and a third group related to the Upper Cretaceous Smoking Hills and Boundary Creek formations. In contrast to oil accumulations, gas accumulations resulted mainly from a filling event in the late Miocene, which is interpreted to be related to a decrease in pressure during a late Miocene uplift and erosional event. The Mackenzie Basin is therefore an excellent example to show that the gas proneness of a mature petroleum system, especially if the organic matter is predominantly of terrestrial origin, is mainly a function of expulsion efficiency and timing and thus is directly linked to the structural history of the basin.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".