Airborne electromagnetic methods: applications to minerals, water and hydrocarbon exploration
Bibliographic record
Abstract
Electromagnetic methods have a transmitter that carries a current that varies in magnitude as a function of time.This current has an associated (primary) magnetic field that has a similar time dependence.According to Faraday's law of induction, this time varying field induces currents in conductive features in the ground.These currents have an associated (secondary) magnetic field that can be detected by an electromagnetic receiver.There is no need for the transmitter or the receiver to touch the ground, so electromagnetic systems can be mounted on aircraft and used to cover large areas quickly and efficiently.In time domain EM systems, the time variation of the current is a switch on, followed by a rapid switch off.In general, good conductors have secondary field responses which decay slowly after the switch off.One example from the Shea Creek area of the Athabasca Basin (northern Saskatchewan) shows that these good conductors can be detected at depths as great as 700m when the conductor is large and the intervening material is highly resistive.Poor conductors have responses that decay away rapidly.The alteration above the Millennium deposit (also in the Athabasca Basin) is an example of a response that decays away in about 300 microseconds.Historically, airborne electromagnetic methods have been most successful for massive sulphide exploration.Electromagnetic methods are being utilized in the search for fresh water.In an example from Denmark, the method has been used to successfully map the thickness of a freshwater aquifer.Using airborne methods, an area of more than 100 km2 was covered in a few days surveying, where it would have taken months to cover the same area using ground methods.In sedimentary basins, the decay of the electromagnetic response can be used to infer the conductivity as a function of depth.The shallower part of the section is inferred from the early time data and the late time data is used to estimate the deeper parts of the section.When the ground is about 10 Ohm•m, airborne electromagnetic systems can only see about 300 m deep.Hence they cannot see most hydrocarbon deposits.However, electromagnetic methods have been a useful compliment to high resolution seismic in the search for shallow gas in some of the paleochannels in Alberta.They have also been used to better understand the oil sands environment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".