3D reflection seismic imaging of the Zinkgruvan mineral‐bearing structures in the south‐eastern Bergslagen mineral district (Sweden)
Bibliographic record
Abstract
Abstract Mineral exploration is facing greater challenges nowadays because of the increasing demand for raw materials and the lesser chance of finding large deposits at shallow depths. To be efficient and address new exploration challenges, high‐resolution and sensitive methods that are cost‐effective and environmentally friendly are required. In this work, we present the results of a sparse 3D seismic survey that was conducted in the Zinkgruvan mining area, in the Bergslagen mineral district of central Sweden. The survey covers an area of 10.5 km 2 for deep targeting of massive sulphides in a polyphasic tectonic setting. A total of 1311 receivers and 950 shot points in a fixed 3D geometry setup were employed for the survey. Nine 2D profiles and a smaller 3D mesh were used. Shots were generated at every 10 m, and receivers were placed at every 10–20 m, along the 2D profiles, and 40–80 m in the mesh area. An analysis of the seismic fold coverage at depth was used to determine the potential resolving power of this sparse 3D setup. The data processing had to account for cultural noise from the operating mine and strong source‐generated surface waves, which were attenuated during both pre‐ and post‐stack processing steps. The processing workflow employed a combination of 2D and 3D refraction static corrections, and post‐stack FK filters along inlines and crosslines. The resulting 3D seismic volume is correlated with downhole data (density and P‐wave, acoustic impedance, reflection coefficient), synthetic seismograms, surface geology and a 3D model of mineral‐bearing horizons in order to suggest new exploration targets at depth. The overall geological architecture at Zinkgruvan is interpreted as two EW overturn folds, an antiform and a synform, affected by later NS‐trending folding. Two strong sets of shallow reflections, associated with the Zn–Pb mineralization, are located at the hinge of an EW‐trending antiform, while a strong set of reflections, associated with the main mineralization, is located at the overturned apex of the EW synform. The NS Knalla fault that crosses the study area terminates the continuation of the mineral‐bearing deposits at depth towards the west, a conclusion solely based on the reflectivity character of the seismic volume. This study illustrates that sparse 3D data acquisition, while it has its own challenges, can be a suitable replacement for 2D profiles while line cutting, and environmental footprints can totally be avoided.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".