Effective utilization of seismic reflection technique with moderate cost in uranium exploration
Bibliographic record
Abstract
ABSTRACT In participation with numerous industrial partners, the Seismic Laboratory of the University of Saskatchewan has conducted a variety of active seismic reflection experiments; both on the west and east sides of the Athabasca Basin. Results of the investigations at Shea Creek, McArthur River and Keefe Lake illustrate that the seismic investigations deliver effective, highly relevant primary structural images of the subsurface, with resolution that no other geophysical technique can match. Correlation of similar seismic signatures, on several distant but inter‐related seismic sections, allowed spatial extension of promising exploration target zones previously unrecognized. Within the three‐dimensional seismic volume, comparable reflectivity patterns defined the complex areal distribution of mineralization‐related fault systems. Beyond these novel contributions, extended analysis of seismic signal attributes (amplitude and frequency), optical televiewer, and full‐wave sonic data offer detailed lithological characterization, including alteration zones, clay content, as well as porosity and fracture density information. Although these structural and geologically relevant anomalies are primary indicators of mineralization, presenting novel exploration advantages, the seismic method is still not a standard component of the Athabasca Basin exploration approach, due to the negative perception that ‘it is very expensive’. Comparing the costs of all geophysical techniques to the cost of a single logged drill hole illustrates that the results of a properly designed seismic data acquisition program not only leads to more effective planning of a drilling program, but also would lead to a much quicker recognition of the major mineralized zone(s), and a reduction in the number of required exploration boreholes. This integrated approach to exploration would then translate into a significant reduction of the total exploration expenditures. Unquestionably, the drilling of boreholes provides the most explicit, reliable information to a certain depth, but only within a very small area. Directly connecting the borehole information to seismic results extends the local reliable data; permitting reduction of the number of boreholes to create accurate two‐dimensional or three‐dimensional subsurface images and reduction of the expenditures of the total exploration program.
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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".