Quantifying Centimeter- to Microscale Heterogeneities in Sedimentary, Compositional, and Geomechanical Properties of Siltstone Deposits in the Lower Triassic Montney Formation, Northeastern British Columbia, Canada
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Bibliographic record
Abstract
Abstract Geological and geomechanical heterogeneities exist at multiple scales in fine-grained rocks; however, the complexity of characteristics at the centimeter- to microscale heterogeneities remains poorly understood. In this study, 10 representative samples composed of three centimeter-scale sedimentary fabrics (massive siltstone (F1), stratified siltstone (F2), and bioturbated siltstone (F3)) were analyzed from the Lower Triassic Montney Formation in the Western Canada Sedimentary Basin to describe sedimentological heterogeneity based on sedimentary fabric, compositional, and geomechanical properties. Sedimentary fabric was determined based on grainsize and the distribution of bedforms, which subdivide the facies into four μm- to mm-scale microfacies (massive siltstone (MF1), pinstriped laminated siltstone (MF2), planar- to cross-stratified siltstone (MF3), and bioturbated siltstone (MF4)). Microscale analysis using a scanning electron microscope was used to characterize microfacies and their respective mineralogical makeup (matrix, cement, and framework grains). To quantify heterogeneity, sedimentary fabric was assessed using a CT scan complemented by elemental composition (using X-ray fluorescence), and geomechanical hardness (using Equotip Piccolo Bambino handheld microhardness tool) was collected within a 1 cm by 1 cm grid within each sample. Datasets were compared using a discriminant analysis (DA) to recognize trends between multiple properties and suggest that sedimentary fabric with the highest centimeter-scale aluminum content from XRF (avg. 11%) comprises microfacies that are comparatively matrix-rich consisting of micas, negligible calcite cement, and exhibit the lowest handheld hardness values (<770). Alternatively, sedimentary fabric with a higher elemental calcium component (avg. 18%) comprises microfacies that are matrix-poor, cemented by carbonate (calcite and dolomite) and quartz, and overall exhibit a positive trend with hardness measurement (770–850). Furthermore, to relate the elemental and geomechanical proxies to controls on rock mechanics, natural calcite-filled fractures within the studied core intervals were characterized. Fractures were subdivided into three types—brecciated, bed-parallel, and vertical to subvertical fractures with each type being constrained to a specific sedimentary fabric. Based on centimeter gridding, microscale analysis and the degree of fabric interbedding play a primary role on the variability in mechanical hardness and the geometry and termination of natural fractures. Collectively, this dataset provides insight into the influence that sedimentary fabric and the distribution of elemental composition has on mechanical properties and natural fractures below well log resolution. These findings can be used to better model and predict fine-grained deposit characteristics before undergoing hydraulic stimulation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it