Shear Wave Anisotropy Measurement from Azimuthally Focused LWD Sonic Tool
Bibliographic record
Abstract
Abstract A new logging-while-drilling (LWD) logging tool has been developed to measure shear wave anisotropy and provide a wellbore acoustic image. The tool consists of a focused transmitter and six focused receivers. The transmitter fires rapidly and waveforms are acquired in the six receivers as the tool rotates in the borehole. Sixteen azimuthal waveforms are acquired for each receiver and processed to produce compressional and shear velocities of the formation as a function of azimuth. Anisotropy ratio and maximum/minimum stress directions are determined from the velocity images. Borehole images of the compressional and shear velocities of the formation are also obtained from the azimuthal velocities. This paper shows modeling data of the tool response in different anisotropic formations to assess the accuracy and viability of the measurement. The ability of the measurement to determine formation anisotropy at different borehole inclinations and the sensitivity of the borehole image to the formation acoustic properties are also discussed. Field examples of the anisotropy measurement and the borehole images obtained in vertical, deviated, and horizontal wells are presented.
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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 | 0.001 |
| 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) | 0.001 | 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".