Seismic imaging across fault systems in the Abitibi greenstone belt – an analysis of pre- and post-stack migration approaches in the Chibougamau area, Quebec, Canada
Bibliographic record
Abstract
Abstract. Two high-resolution seismic reflection profiles acquired north and south of Chibougamau, located in the northeast of the Abitibi subprovince of Canada, help understand historic volcanically hosted massive sulfide (VMS) deposits and hydrothermal Cu–Au mineralization found there. Major faults crossed by the profiles include the Barlow fault in the north and the Doda fault and the Guercheville fault in the south, all targets of this study that seeks to determine spatial relationships with a known metal endowment in the area. Common-offset DMO corrections and common-offset pre-stack time migrations (PSTMs) were considered. Irregularities of the trace midpoint distribution resulting from the crooked geometry of both profiles and their relative contribution to the DMO and PSTM methods and seismic illumination were assessed in the context of the complex subsurface architecture of the area. To scrutinize this contribution, seismic images were generated for offset ranges of 0–9 km using increments of 3 km. Migration of out-of-plane reflections used cross-dip element analysis to accurately estimate the fault dip. The seismic imaging shows the thickening of the upper-crustal rocks near the fault zones along both profiles. In the northern seismic reflection section, the key geological structures identified include the Barlow fault and two diffraction sets imaged within the fault zone that represent potential targets for future exploration. The south seismic reflection section shows rather a complicated geometry of two fault systems. The Guercheville fault observed as a subhorizontal reflector connects to a steeply dipping reflector. The Doda fault dips subvertical in the shallow crust but as a steeply dipping reflection set at depth. Nearby gold showings suggest that these faults may help channel and concentrate mineralizing fluids.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".