Joint and constrained inversion of magnetic and gravity data: A case history from the McArthur River area, Canada
Bibliographic record
Abstract
ABSTRACT Magnetic and gravity data are used in the early stages of exploration for uranium deposits in the Athabasca Basin of Canada, just as for many other mineral exploration scenarios. Uranium mineralization in the Athabasca Basin is located where faults in the basement intersect the unconformity between the basement and the overlying sandstones. The gravity and magnetic data are dominated by signatures from the basement and an overburden of glacial sediments. The gravity and magnetic data are effective at mapping the basement geology. Any subtle gravity signal from the mineralization related to the formation of the uranium deposits is masked by the signal from the variable-thickness overburden. Three-dimensional joint inversion of gravity and magnetic data, first without and then with constraints, is evaluated as a means of better determining the structure of the three main lithologies (overburden, sandstones, and basement) in the Athabasca Basin. A significant amount of physical property information is available for the main rock units (and overburden), which makes the use of the compositional approach to joint inversion appropriate. For the joint inversion, the fuzzy c-means clustering method is used. Results from representative synthetic examples indicate that the joint inversions can construct the overburden and basement structures better than the independent inversions of gravity and magnetic data. Furthermore, constrained joint inversion allows delineation of all three major layers in the area. The same inversion strategies then are applied to real airborne gravity and magnetic data from the McArthur River area in the eastern Athabasca Basin. The results we obtain demonstrate the capabilities of joint inversion for real-life situations.
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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".