Shales: From the Atomic Scale to the Rock-Mass Scale
Bibliographic record
Abstract
ABSTRACT Fine-grained sediments, mudrocks and shales have unique fabric and pore topology that reflect their mineral composition and formation history. Atomic-scale clay-clay electrical interactions coexist with the micron-scale mechanical interactions between silicate and carbonate grains, clay tactoids and organic matter; layering adds cm-scale vertical heterogeneity. The resulting strata define the performance of km-scale natural and engineering systems including oil and gas reservoirs and the long-term geological storage of CO2 and nuclear waste. This study presents the building blocks and physical evidence that support a new multi-scale numerical simulation approach for fine-grained sediments, mudrocks and shales. Atomic-scale studies show the effect of isomorphic substitution and adsorbed water molecules on clay tactoid stiffness. Pore-scale analyses based on SEM images reveal spherical pores in organic matter and elongated/aligned pores bound by clay tactoids. Particle-scale simulations capture fabric evolution including tactoid alignment facilitated by organic matter deformation to accommodate to the evolving mineral fabric. The resulting tactoid and organic matter alignment gives rise to shale fissility. INTRODUCTION Fine-grained sediments develop unique fabrics related to sedimentation environment and mineralogical composition. Eventually, porosity decreases with depth while diagenetic processes overprint new characteristics as fine-grained sediments become mudrocks and shales. Their ensuing hydro-thermo-chemo-mechanical properties affect the performance of near-surface infrastructures (e.g., foundations, pavements, tunnels), hydraulic fracturing and shale gas recovery (Speight, 2013), and the seal capacity for CO2 geological storage (Kang et al., 2011; Heller and Zoback, 2014; Espinoza and Santamarina, 2017). Despite the economic and social importance of these formations, the structure of mudrocks and shales remains poorly understood in part due to their complex topology, associated heterogeneity, anisotropy and wide range of scales (Arif et al., 2021). Previous analytical and numerical studies focused on atomic-scale interactions (molecular dynamics – Liu et al., 2015; Han et al., 2019; Faisal et al., 2021, density functional theory – Zartman et al., 2010), particle-level analyses (discrete elements – Anandarajah, 2000; Yao and Anandarajah, 2003; Pagano et al., 2020; de Bono and McDowell, 2022) and macro-scale constitutive models (Schofield and Wroth, 1968; Sanchez et al., 2005) to account for the effect of scale in fine-grained sediments.
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How this classification was reachedexpand
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) | 0.022 | 0.045 |
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; both teacher heads agree on what is shown here.
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".