Lithological Controls on Mechanical Anisotropy in Shales to Predict In Situ Stress Magnitudes and Potential for Shearing of Laminations During Fracturing
Bibliographic record
Abstract
Abstract Accurate and repeatable assessments of in situ stress magnitudes and orientation in unconventional reservoirs can be complicated by the heterogeneous, inelastic, and/or anisotropic mechanical properties of these rocks and their complex history of burial and diagenesis. The associated vertical and lateral variation in pore pressure and stress through the target zones and bounding intervals can further complicate this effort. For these reasons, some additional factors need to be considered beyond the typical workflow of determining closure stress from standard mini-frac data and using this data to calibrate log derived stress profiles. We present some case study examples from hydrocarbon-producing shales where a more rigorous analysis of the mechanical properties of the shale has allowed a more accurate and repeatable assessment of in situ stress and potential for lamination shearing. Horizontal fracture growth through shear activation of bedding-parallel fabric can be a preferred fracture propagation mechanism in these shales and this behavior can be diagnosed by this improved workflow. In one case study example, in the tight gas Montney siltstone of Western Canada, shear strength anisotropy is shown to be very significant, with bedding parallel shear cohesion less than 10% of the bulk rock cohesion. For such situations it can be shown that shear fracturing of laminations is likely. It has been demonstrated through pressure transient analysis of minifrac injection and flowback data that this can be diagnosed. Many fracturing related mechanisms are also stress dependent and their understanding requires assessment of all in situ stress magnitudes, not just minimum horizontal stress. An improved method of analyzing these stress magnitudes and fracturing mechanisms is described through anisotropy measurements in core samples and a micro-mechanical understanding of the rock fabric. In this way, a petrophysical relationship can be established between anisotropy parameters and rock properties.
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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 | 0.001 | 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 | 0.000 | 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".