Distribution of diagenetic minerals in Lower Cretaceous sandstones and their relationship to lithofacies from a proximal to distal transect: Como P-21, Panuke B-90, Cohasset A-52, Balmoral M-32 and Lawrence D-14 wells, Scotian Basin
Bibliographic record
Abstract
Diagenetic cements are of decisive importance in determining the reservoir quality. It is therefore important to understand how such cements form. Only a few recent studies of diagenetic alteration have been published for the Scotian basin. The spatial and temporal distribution of diagenetic cements has been interpreted in relationship to lithofacies of the Lower Cretaceous sandstones from a proximal to distal transect from 5 wells (Como P-21, Panuke B-90, Cohasset A-52, Balmoral M-32, and Lawrence D-14). Polished thin sections were studied by optical microscopy and electron microprobe to characterize grain size, texture, and chemical composition of diagenetic minerals. Kaolinite, pyrite, illite, quartz overgrowths, early and late carbonates are the diagenetic minerals cementing the Lower Cretaceous sandstones. Kaolinite, early calcite I, Fe-calcite I, siderite A and B occur in fluvial and river-mouth to prodeltaic sandstones; lithofacies strongly influenced by meteoric water and with not much organic carbon. Siderite hemispheres are restricted to estuary sandstones and intertidal to subtidal sandstones. Pyrite is abundant in tidalestuary to fluvial sandstones, transgressive, shoreface sandstones, and in river-mouth to prodeltaic turbidites. The highest amounts of pyrite were found in samples lacking early calcite I and Fe-calcite I cements. Quartz overgrowths occur in all lithofacies, and better developed in coarse sandstones. Late carbonate cements including Fe-calcite II and ankerite occur in most of the lithofacies including tidal-estuary to fluvial sandstones, prodeltaic turbidites, sand flat-intertidal to subtidal sandstones, and in shoreface sandstones. Abundance of late carbonate cements are partly related to limestones and bioclastic sandstones in the section; samples with high amounts of late carbonate cements were found either below or above intervals rich in bioclasts or limestones. In summary, in the Como-Panuke-Cohasset-Balmoral-Lawrence transect, the succession seems to be more marine from Como to Lawrence. Kaolinite is abundant in Como, Panuke and Cohasset and it is rare in Balmoral and absent in Lawrence, whereas carbonate cements are rare in Como and more abundant in Panuke, Cohasset, Balmoral and Lawrence. Limestones and bioclasts are the source of some of the calcium for the late carbonate cements. This study demonstrates that the distribution of diagenetic minerals and their impact on reservoir-quality evolution can be better elucidated when linked to lithofacies.
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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 | 0.001 |
| 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) | 0.001 | 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".