3D reflection seismic imaging for open-pit mine planning and deep exploration in the Kevitsa Ni-Cu-PGE deposit, northern Finland
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT A 3D reflection seismic survey was conducted over an area of about 9 km2 at the Kevitsa Ni-Cu-PGE (platinum group elements) orebody, northern Finland, where open-pit mining started in mid-2012. The principal objective of the survey was to image major fault and fracture zones at depth that may have an impact on the mine stability and safety. Mine planning would then take into account the geometry of these zones at Kevitsa. Processing results, using conventional prestack DMO and poststack migration methods, show gently dipping and steeply dipping reflections from depths of approximately 2 km to as shallow as 150–200 m. Many of the reflections are interpreted to originate from either fault systems or internal magmatic layering within the Kevitsa main intrusion. Further correlation between the surface seismic data and VSP data suggests that numerous faults are present in the imaged volume based upon time shifts or phase changes along horizontal to gently dipping reflections. Some of these faults cross the planned open-pit mine at depths of about 300–500 m, and are therefore critical for geotechnical planning. In terms of in-pit and near-mine exploration, the magmatic layering internal to the intrusion controls the distribution of the bulk of economic mineralization. The ability to image this magmatic layering could therefore guide future drilling, particularly by constraining the presumed lateral extents of the resource area. Exploration also will target discrete reflectors that potentially represent higher-grade sulfide mineralization.
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.
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 | 0.001 |
| 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 it