Simultaneous source separation by shot collocation and strength variation
Bibliographic record
Abstract
ABSTRACT Simultaneous shooting offers opportunities for significant cost savings in seismic data acquisitions. The most common strategy uses random delay shots where source separation is achieved during the processing stage, thereby doubling source densities. We have determined that the creation of a collocated source survey, where shots are repeated simultaneously at multiple positions, is a viable alternative strategy, with the additional benefit that it may increase source density even further while keeping the acquisition duration unchanged. Source separation is achieved using overcomplete independent component analysis by first by applying a directional wavelet transform to separate source signals with different slowness, then estimating the mixing matrix, followed by solving an optimization problem with an energy constraint combined with a sparseness inducing prior and obtaining the required waveforms. Synthetic tests find average reconstruction quality on the order of 22.1, 15.4, and 8.4 dB if, respectively, three, four, or five shots are acquired in two mixtures. Examination of the true versus obtained zero-offset sections also demonstrates the robustness of our signal recovery strategy. The advantage of shot collocation over conventional acquisitions is that it may triple or even quadruple the source density for unchanged acquisition durations with superior reconstruction results compared with dithered acquisitions using similar blending factors.
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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".