Using laboratory data to understand how pore aspect ratio influences elastic parameters and amplitude variation with offset
Bibliographic record
Abstract
ABSTRACT Pore geometry is an important parameter in reservoir characterization that affects the permeability of reservoirs and can also be a controlling factor on the impact of pressure and saturation on reservoirs elastic properties. We have used selective laser sintering 3D printing technology to build physical models to experimentally investigate the impacts of pore aspect ratio on compressional (P-) and shear wave (S-wave) velocities and amplitude variation with offset (AVO). We printed six models to study the effects of the pore aspect ratio of prolate and oblate pore structures on elastic properties and AVO signatures. We found that the P-wave velocity is reduced by decreasing the pore aspect ratio (flatter pore structure), whereas the S-wave velocity is less sensitive to the pore aspect ratio. This effect is reduced when the samples are water saturated. We developed new experimental and processing techniques to extract realistic AVO signatures from our experimental data and found that the pore aspect ratio has similar effects on AVO as fluid compressibility. This indicated that not considering the pore aspect ratio in AVO analysis can lead to misleading interpretations. We also found that these effects are reduced in water-saturated samples.
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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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".