Double-weave 3D seismic acquisition — Part 1: Sampling and sparse Fourier reconstruction
Bibliographic record
Abstract
ABSTRACT A stochastic simulation technique analyzes the effectiveness of sparse Fourier reconstruction methods for multidimensional sampling functions. A regular 2D sampling pattern, called a weave pattern, is a suitable sampling scenario for sparse Fourier recovery. The simplicity of a weave sampling pattern provides a good alternative to replace random sampling patterns in compressive sensing applications. A double-weave 3D seismic acquisition design has been developed by using the weave sampling pattern for the shot and receiver distributions. Besides its homogeneous spatial coverage in the shot-receiver and offset-azimuth coordinates, double-weave 3D acquisition is a compatible survey design for alias-free 5D sparse Fourier interpolation in the shot and receiver domains. Zigzag and orthogonal double-weave acquisition layouts were proposed for land seismic surveys considering the economic and environmental parameters. The effectiveness of 5D interpolation for double-weave 3D acquisition were tested using synthetic planar 5D seismic events.
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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".