Diagenetic imprints in the reservoirs of Agbada Formation, Niger Delta Basin: Implication for reservoir quality and appraisal of calcite cement
Bibliographic record
Abstract
The main exploration targets for hydrocarbons in the Niger Delta Basin are within the Agbada sandstone reservoirs. The current study utilizes a multitechnical approach (SEM-MLA, SEM-EDS, XRD and LA-ICP-MS) to evaluate the roles of framework composition and diagenetic processes, particularly calcite cementation on reservoir quality in Miocene intervals of the Agbada Formation sandstone, Niger Delta Basin. Petrographic analysis reveals that the sandstones are feldspatho-quartzose to quartzose sandstones, with a preponderance of quartzose sandstones. The overall diagenetic imprints suggest minimal compaction and lack of pervasive cement, which have contributed significantly to the high porosity. Although the degree of mechanical compaction is generally low, it has comparatively exercised a better control on porosity than the growth of cement, excluding some intervals with considerable cementation (siderite and ferroan calcite) where compactional porosity-loss was minimal. The occurrence of ferroan calcite cement (CaCO3 = 95.9 ± 0.4, MgCO3 = 0.8 ± 0.1, FeCO3 = 2.9 ± 0.2 mol%) is generally small, probably discontinuous and unlikely to represent significant barriers to fluid flow with their localized influence, but understanding their locally significant influence may still contribute to building good reservoir models. Petrographic observations suggest that the precipitation of "poikilitic" calcite was early, but the shale normalized REY patterns do not mimic seawater patterns (Y/Ho ratios; 36.3 ± 1.6) due to possible contributions from clastic or detrital grains and/or incorporation of particulate matter that can preferentially scavenge LREEs from the overlying water column. A possible concern during reservoir production is the occurrence of clay mineral matrix (mostly kaolinitic) anticipated to cause the production of fines and formation damage, but this can be mitigated with proper reservoir management.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".