Atomic-Force Microscopy: A New Tool for Gas-Shale Characterization
Why this work is in the frame
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Bibliographic record
Abstract
Summary An atomic-force microscope (AFM), a relatively new tool for studying surface characterization, can generate image features down to atomic resolution. Not only can the AFM obtain topographic images of surfaces, but it also can simultaneously identify different materials on a surface at high resolution. Since its invention in the 1980s, AFM has been used in material science and medical research, although it has not received the attention that it probably deserves in reservoir engineering. The emergence of unconventional shale-gas reservoirs, however, has opened new research frontiers for the AFM in the field of reservoir engineering. The unique capabilities of the AFM make it ideal for studying nanopores, organic materials (kerogen), minerals, and diagenetic fractures in shales. It also can be used to measure localized bulk modulus of elasticity on a surface for further implications in geophysical exploration and designing hydraulic fracturing. We introduce different AFM techniques for all these applications, along with example results.
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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 | 0.001 | 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