An overview of laboratory apparatuses to measure seismic attenuation in reservoir rocks
Bibliographic record
Abstract
ABSTRACT Intrinsic wave attenuation at seismic frequencies is strongly dependent on rock permeability, fluid properties, and saturation. However, in order to use attenuation as an attribute to extract information on rock/fluid properties from seismic data, experimental studies on attenuation are necessary for a better understanding of physical mechanisms that are dominant at those frequencies. An appropriate laboratory methodology to measure attenuation at seismic frequencies is the forced oscillation method, but technical challenges kept this technique from being widely used. There is a need for the standardization of devices employing this method, and a comparison of existing setups is a step towards it. Here we summarize the apparatuses based on the forced oscillation method that were built in the last 30 years and were used to measure frequency‐dependent attenuation in fluid‐saturated and/or dry reservoir rocks under small strains (10−8–10−5). We list and discuss important technical aspects to be taken into account when working with these devices or in the course of designing a new one. We also present a summary of the attenuation measurements in reservoir rock samples performed with these apparatuses so far.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".