The Effects of Accretion-package Geometry On Lithofacies Distribution in Point-bar Deposits
Bibliographic record
Abstract
Abstract Many fluvial point-bar accretion packages show lithological variability, from sand- to mud-dominated. However, the controls on this variability are often poorly constrained. High-quality 3-D seismic data and information from hundreds of wellbores from the Lower Cretaceous McMurray Formation (Alberta, Canada) are employed to characterize the deposits of three point bars and discern the lithological variations amongst and along the length of component accretion packages. Five recurring accretion-package geometries were distinguished: uniform width, wide at apex, narrow at apex, downstream wedge, and upstream wedge. Each of the three point bars was characterized by a breadth of these accretion packages, indicating varied processes during their evolution. The recurrence of accretion packages with consistent geometry and width, however, suggests some consistency and predictability in formative point-bar accretion processes. Each major migration mode (i.e., bar translation, expansion, extension, rotation) produces accretion packages with distinct depositional architecture. Laterally migrating meanders are most commonly associated with “wide at apex” accretion packages formed by sedimentation concentrated at the bar apex. Downstream-translating meanders are composed of “wide at apex” packages alternating with “downstream wedge” packages. If present, distinct lithological changes in point-bar deposits are expected to occur across the discontinuity surfaces that bound accretion packages, particularly if the surface is associated with a change in migration mode. Based on our dataset, point bars with high planform complexity that are the product of multiple migration modes (e.g., point-bar “toggling”) may be more lithologically variable than point bars deposited by a single migration mode. The change from a mudstone-dominated to sandstone-dominated package suggests a shift in the parameters governing grain-size distribution and point-bar sedimentation, such as an increase in sediment supply due to the sudden release of sediment upstream of the meander bend, evolving channel geometry and sinuosity in response to bend curvature, or variability in discharge and sediment concentration related to climatic cycles. Identification of discrete depositional packages in point-bar deposits enables more detailed paleoenvironmental reconstructions, accurate characterization of point-bar sandstone bodies, and a method of predicting point-bar reservoir distribution based on planform images.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| 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".