Statistical analysis of forward stratigraphic models in complex salt provinces: The central Scotian Basin case study
Bibliographic record
Abstract
ABSTRACT Predicting vertical and lateral facies variations in various depositional environments remains a major challenge in the oil and gas industry because it impacts petroleum system assessments and the associated exploration-risking phase. The use of multidisciplinary constraints (geomorphology, geology, geophysics) in forward stratigraphic models sheds light on the complex interaction of local, regional, and global driving mechanisms that influence sediment transport and deposition along continuously evolving landscapes. In this paper, we develop an integrated statistical approach to examine the sensitivity of forward stratigraphic models in complex salt provinces to several parameters, including water discharge, sedimentary load, grain size and associated diffusion coefficients, and slope. This statistical analysis was applied to the Barremian–Albian sequence of the central Scotian Basin (Canada) and highlights the influence of complex salt kinematics on sediment pathway diversion and accumulation around salt domes and canopies. Forward stratigraphic modeling results point to regions of higher probability of Lower Cretaceous sandy reservoirs. Automating simulation runs significantly reduced the time required to achieve a statistically valid number of simulations and allowed the sensitivity of the model to be evaluated.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.010 | 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".