Impact of Mineralogy and Diagenesis on Reservoir Quality of the Lower Cretaceous Upper Mannville Formation (Alberta, Canada)
Bibliographic record
Abstract
The Lower Cretaceous Upper Mannville Formation in West- Central Alberta has been intensively penetrated by wells targeting deeper reservoirs during the last decades. Production and well log data in this area suggest that significant volumes of gas are still present in both conventional and tight reservoirs of this formation. The Upper Mannville reservoirs in West-Central Alberta consist of fluvial sandstones filling incised valleys. The valley infills are made up of arkosic sandstones with a complex mineralogy. The matrix of these sandstones is made up of various amounts of quartz, feldspars, clay minerals and rock fragments. They were subjected to a complex diagenetic history and the resulting paragenesis influenced the present reservoir properties. Consequently, heterogeneities in the petrophysical properties result in significant exploration risks and production issues. We present in this paper results of a diagenetic study, performed within a well constrained stratigraphic framework, that aims at understanding the impact of mineralogy and diagenesis on reservoir quality evolution. Seventy one core samples from eight wells were collected to perform a petrographic analysis, and to propose a paragenetic sequence. Four main diagenetic events were identified that occurred during burial: – clay coating around the grains; – compaction/dissolution of matrix grains; – quartz and feldspars dissolution that initiated smectite-illite transformation and kaolinisation; – carbonate cementation in the remaining pore space. Clay minerals content and carbonate cementation are the main factors that altered the reservoir quality of these sandstones. The Smectite-Illite transformation was initiated after potassium was released in the formation fluids due to K-feldspars dissolution. This transformation proportionally increased with temperature during burial. Carbonate cementation occured during the uplift phase of the basin, intensively plugging the pore space where the clay content is reduced. Additional SEM and XRD analyses allowed characterizing and quantifying more accurately the different mineralogical phases occluding the porous network. The characterization of both mineralogy and petrophysical properties gives useful keys to locate the diagenetic phases laterally and vertically, and to predict the petrophysical properties distribution.
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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 | 0.000 |
| 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".