Meshfree modelling of magnetotelluric and controlled-source electromagnetic data for conductive earth models with complex geometries
Bibliographic record
Abstract
Geophysical electromagnetic survey methods are particularly effective in locating conductive mineral deposits or mineralization zones in a mineral resource exploration. The forward modelling of the electromagnetic responses over such targets is a fundamental task in quantitatively interpreting the geophysical data into a geological model. Due to the ubiquitous irregular and complex geometries associated with the mineral rock units, it is critical that the numerical modelling approach being used is able to adequately and efficiently incorporate any necessary geometries of the Earth model. To circumvent the difficulties in representing complex but necessary geometry features in an Earth model for the existing mesh-based numerical modelling approaches (e.g., finite element and finite difference methods), I present a meshfree modelling approach that does not require a mesh to solve the Maxwell’s equations. The meshfree approach utilizes a set of unconnected points to represent any geometries in the Earth model, allowing for the maximal flexibility to account for irregular surface geometries and topography. In each meshfree subdomain, radial basis functions are used to construct meshfree function approximation in transforming the differential equations in the modelling problem into linear systems of equations. The method solves the potential function equations of the Maxwell’s equations in the modelling. The modelling accuracy using the meshfree method is examined and verified using one magnetotelluric model and two frequency-domain controlled-source models. The magnetotelluric model is the well-known Dublin Test Model 2 in which the spherical geometry of the conductor in the shallow subsurface may pose as a challenge for many numerical modelling methods. The first controlled-source model is a simple half-space model with the electric dipole source for which analytical solutions exist for the modelling responses. The second controlled-source model is the volcanic massive sulphide mineral deposit from Voisey’s Bay, Labrador, Canada in which the deposit’s surface is highly irregular. For all modellings, the calculated electromagnetic responses are found to agree with other independent numerical solutions and the analytical solutions. The advantages of the meshfree method in discretizing the Earth models with complex geometries in the forward modelling of geophysical electromagnetic data is clearly demonstrated.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".