Seismic imaging of a thin unconventional reservoir in highly attenuating media: The case of the Macasty Formation, Anticosti Island, Canada
Bibliographic record
Abstract
Seismic wave propagation through the subsurface is characterized by a loss of high frequency energy desired for high-resolution imaging at depth. This means that the size of geological features that can be resolved increases with depth. In this context, exploration of thin-layered unconventional reservoirs represents a significant challenge for seismic imaging. Here the case of the Macasty Formation, a thin-layered shale reservoir included in a highly attenuating limestone-dominated Silurian-Ordovician succession, is discussed. To retrieve high frequency energy, Q-phase compensation, zero-phase deconvolution and a 90°-phase rotation followed by the application of a Butterworth filter are used. Results provide an amplitude spectrum that is flatter and broader compared to the original data. New imaging resolves internal high amplitude reflections within the reservoir that are correlative to higher TOC values of the pay-zone. Presentation Date: Monday, October 17, 2016 Start Time: 1:25:00 PM Location: 156 Presentation Type: ORAL
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".