Duvernay shale lithofacies distribution analysis in the West Canadian Sedimentary Basin
Bibliographic record
Abstract
In the West Canadian Sedimentary Basin (WCSB), Duvernay shale is considered to contribute most of the Canadian shale gas reserve and production. According to global shale gas exploration and development practice, reservoir property and well completion quality are the two key factors determining the shale gas economics. The two key factors are strongly depending on shale lithofacies. On the basis of inorganic mineralogy theory, all available thin section, X-ray diffraction, scanning electron microscope (SEM), energy dispersive spectrometer (EDS) data were used to assist lithofacies analysis. Gamma ray (GR), acoustic (AC), bulk density (RHOB), neutron porosity (NPHI) and photoelectric absorption cross-section index (PE) were selected for log response analysis of various minerals. Reservoir representative equation was created constrained by quantitative core analysis results, and matrix mineral percentage of quartz, carbonate, feldspar and pyrite were calculated to classify shale lithofacies. Considering the horizontal continuity of seismic data, rock physics model was built, and acoustic impedance integrated with core data and log data was used to predict the horizontal distribution of different lithofacies. The results indicate that: (1) nine lithofacies can be categorized in Duvernay shale, (2) the horizontal distribution of different lithofacies is quite diversified, siliceous shale mainly occurs in Simonette area, calcareous shale is prone to develop in the vicinity of reef, while calcareous-siliceous shale dominates in Willesdon Green area.
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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 | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 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".