Fluvial reservoirs stacked in thin deltaic successions of the Lower Cretaceous Grand Rapids Formation, east-central Alberta, Canada
Bibliographic record
Abstract
Abstract The Manatokan Field in east-central Alberta offers a unique opportunity to characterize paralic sandstone reservoirs in 3D using a dense network of well data (approximately 3 wells/km2). Within the 400 km2 study area, the 100-m thick Lower Cretaceous Grand Rapids Formation is dominantly composed of sediment deposited in two depositional environments: river-dominated deltas and marine-influenced fluvial rivers. Up to 33 individual fluvial bodies, occurring at five stratigraphic levels and eroding into deltaic parasequences, are identified in the oil-charged upper part of the formation. The width and thickness of fluvial bodies typically range from 50 to 9000 m and from 5 to 50 m, respectively. Examination of cores, wireline logs, and strategically located 3D seismic data indicates that fluvial bodies are dominantly filled by inclined heterolithic deposits emplaced as downflow translation point bars (PBs) separated by mud-filled abandoned channels. Although individual PBs are relatively small (≤10 km2), the dense subsurface data set provides the means to build facies maps that illustrate their internal architecture and the distribution of reservoir heterogeneities. Reservoir-quality sandstone occurs on the upstream portion of PBs and usually forms continuous beds along the base of fluvial bodies that extend underneath abandoned channel deposits. High reservoir connectivity along the base of these heterolithic fluvial bodies constitutes a major advantage for heavy oil reservoir production driven by gravity. Core evidences also indicate potential communication between fluvial bodies and surrounding deltaic sandstones or older underlying fluvial reservoirs, which may lead to unexpected results during field development. The Grand Rapids Formation provides a good subsurface analogue of complex marginal-marine clastic reservoirs, and its study may help to explain unanticipated production results in similar hydrocarbon areas.
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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 | 0.003 |
| 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) | 0.002 | 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".