Analysis of factors influencing the interpretation of a digitally examined fluvial meanderbelt system: Joggins Formation, Nova Scotia
Bibliographic record
Abstract
Clastic reservoir exploration, development, and exploitation are inherently complex with recovery depending largely on the understanding of sand body architecture and interlayered clayey/silty baffles and barriers. Numerous data collection techniques and methods are now widely available for helping to enrich reservoir outcrop analogue data extraction from the well scale to the larger seismic scale. This integrated study uses the inherited, combined data from a localized light detection and ranging survey, measurements taken from a portable handheld spectrometer and air permeameter, in addition to total (or absolute) porosity measurements from thin sections to assist with the analysis of components influencing the interpretation of a digitally analyzed fluvial meanderbelt system outcrop. The purpose is not to perform a detailed reservoir characterization or to model a potential reservoir, but rather to study a section of a reservoir analogue and apply reservoir geology with integrated data collection techniques to highlight potential benefits and shortcomings of this type of approach. A point cloud survey generated from light detection and ranging, coupled with other tools including a portable handheld spectrometer and permeameter, supplements data from the light detection and ranging scan and increases the confidence of interpretations. Spectrometer measurements recorded at the outcrop are used to generate a pseudo-gamma log. Handheld air permeameter measurements give a sense of the permeability of corresponding lithologies, as well as the variability in permeability of the reservoir both laterally and vertically. Light detection and ranging also provides important information regarding rock properties. The high detail of the outcrop images is used for the assessment of reservoir characteristics. The reservoir data leads to an increased understanding of subsurface reservoirs, particularly of the fluvial meanderbelt type. This study shows the importance and drawbacks of a combined digital data collection approach for the analysis of a sedimentary outcrop.
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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 | 0.001 |
| 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 | 0.000 | 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".