Anisotropy estimate for the Horn River Basin from sonic logs in vertical and deviated wells
Bibliographic record
Abstract
Abstract Shale anisotropy must be quantified to obtain reliable information about reservoir fluids, lithology, and pore pressure from seismic data. Failure to account for anisotropy in seismic processing can lead to errors in normal moveout (NMO), dip moveout (DMO), migration, time-to-depth conversion, and amplitude variation with offset (AVO) analysis. Kriged estimates of density, vertical compressional-wave, and shear-wave velocities were derived from vertical wells in an area of interest in the Horn River resource play in northeastern British Columbia. The kriged predictions were compared with measured logs along the trajectory of a deviated well. Whereas the density comparison provided a blind test of kriging accuracy because density is scalar and independent of well deviation, the same comparison for sonic velocities revealed that they are systematically higher than the kriged vertical velocities. This difference was used to estimate anisotropy parameters at the location of the deviated well. The fact that the higher velocities observed are caused by anisotropy was confirmed subsequently by using the derived anisotropy parameters to apply a nonhyperbolic moveout correction η to flatten gathers from a seismic survey 10 km north of the area of interest, within which the anisotropy parameters were estimated.
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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".