Rock-physics modeling for the elastic properties of organic shale at different maturity stages
Bibliographic record
Abstract
ABSTRACT Modeling the elastic properties of organic shale has been of long-standing interest for source rocks and unconventional reservoir characterization. Organic shales exhibit significant variabilities in rock texture and reservoir properties at different maturity stages, subsequently affecting their elastic responses. We have developed a new rock-physics modeling scheme honoring the maturity levels (immature, mature, and overmature), which are constrained by the evolution of the physical properties of organic shale upon kerogen maturation. In particular, at different maturity stages, the manners in which the compliant organic materials interact with the inorganic mineral matrix are characterized by different effective medium theories. On the basis of the developed rock-physics templates, organic shales have different elastic behaviors at different maturity stages. Ignoring the impact of kerogen maturation is insufficient to adequately characterize the elasticity of the whole organic shale system. Modeling results suggest that the elastic responses of organic shale are sensitive to two dominant factors — organic matter content and mineralogical composition. The elastic anisotropy characteristics are not only affected by the kerogen content and clay alignment but also depend on the morphology of kerogen distribution. Our results compare satisfactorily with data from ultrasonic velocity and log measurements, confirming validity and applicability of our modeling framework.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".