Depositional Processes and Characterization of Multi-scale Heterogeneity of an Organic-rich Mudstone, Second White Specks Formation, SW Alberta
Bibliographic record
Abstract
Research over the past decade has shown that mud aggregates can form and be transported as bedload at current velocities required for the transport and deposition of sand-sized grains. This challenges the assumption that organic-rich source rocks are deposited out of suspension in low energy environments, and that mudrocks are homogeneous, ‘layer-cake’ deposits. Instead, marine mudrocks demonstrate facies heterogeneity at multiple-scales having implications for organic-carbon distribution, sealing and source potential, mechanical properties, nomenclature schemes as well as methodology for capturing important rock properties. Microfacies and facies descriptions from well-preserved core and thin sections are integrated with multiple datasets to address multi-scale heterogeneity of the mixed siliciclastic-organic-rich calcareous mudstones of the Cenomanian to early Turonian Belle Fourche and Second White Specks formations. High-resolution descriptions of microfacies and facies reveal subtle sedimentary structures and compositional elements that demonstrate that organic-carbon accumulation does not always occur in homogeneous suspension settling deposits. Instead, marine organic matter can accumulate in heterogeneous sediments with silt to sand grain sizes that are subject to traction transport processes. Additionally, organic-carbon preservation can be controlled by periodic burial by thin (~1 mm) storm event deposits rather than being dependent on pervasive bottom-water anoxia. Methodologies for capturing important rock properties of a mudstone succession at various scales are explored in this study. Quantification of facies heterogeneity and anisotropy revealed that high-resolution characterization of shorter, representative intervals of core resulted in comparable results to the entire succession, providing a cost and time effective approach for detailed characterization of mudstone successions that can be upscaled. Regional facies trends rotate from following a N-S orientation, to being roughly E-W oriented in southern Alberta during the Cenomanian-Turonian transgression. This has implications for regional scale facies heterogeneity regarding reservoir sweet spot distributions as the facies do not always parallel the thermal maturity trend 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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".