|Titre||Three-dimensional magnetotelluric numerical simulation of realistic geologic models|
|Auteur||Ansari, S M; Schetselaar, E; Craven, J; Farquharson, C|
|Source||Geophysics vol. 85, no. 5, 2020 p. 1-20, https://doi.org/10.1190/geo2019-0214.1|
|Séries alt.||Ressources naturelles Canada, Contribution externe 20200478|
|Éditeur||Society of Exploration Geophysicists|
|Document||publication en série|
|Media||papier; en ligne; numérique|
|SNRC||63J/12; 63J/13; 63K/09; 63K/10; 63K/15; 63K/16|
|Lat/Long OENS||-101.0000 -99.5000 55.0000 54.5000|
|Sujets||gisements minéraux; gîtes sulfureux; modèles; simulations par ordinateur; données magnétotelluriques; géologie du substratum rocheux; lithostratigraphie; roches hôtes; diagraphies par câble électrique;
résistivité; zones de cisaillement; Méthodologie; contacts géologiques; géologie économique; géophysique; Sciences et technologie|
|Illustrations||cartes de localisation; coupes transversales; modèles 3D; tableaux; graphiques; représentations schématiques; profils; modèles|
|Diffusé||2020 07 28|
|Résumé||(disponible en anglais seulement)|
We have developed a workflow for constructing realistic mesh-based magnetotelluric (MT) models from 3D geologic models. The routine is developed for
unstructured meshes that adapt to the complex shapes of geologic bodies including 3D surfaces and volumes in realistic modeling scenarios. The methodology is applied to the complexly altered Lalor volcanogenic massive sulfide deposit in Manitoba,
Canada. The host rock envelope of the Lalor deposit is compartmentalized into lithostratigraphic units leading to a watertight model. This model then is meshed into unstructured tetrahedral meshes suitable for synthetic geophysical modeling of the MT
method. Subsequently, two 3D resistivity models are generated from wireline logs: (1) a host rock background model in which each tetrahedral cell is attributed with the average resistivity of each lithostratigraphic unit and (2) a heterogeneous
background-ore model in which the resistivity values of the cells are resampled from a 3D curvilinear grid model, generated by computing sequential Gaussian simulations from the resistivity data for each unit of a 3D lithofacies model produced by
categorical kriging. To calculate the synthetic response of this model for MT, a numerical-modeling code is developed based on solving the vector-scalar potential formulation of the electromagnetic diffusion equation using the finite-element method
on unstructured meshes. After validating the numerical method for the Commemi test model, the MT response of the Lalor model is investigated. A reasonable agreement is observed between the survey field data and the data synthesized from our
constructed heterogeneous model. Using an investigation of the inductive and galvanic parts, we conclude with the ideal frequency range for detecting the ore deposit. We also conclude with and visualize the importance of regional-scale alteration
zones around the ore deposits and model inhomogeneities in boosting the detectability of the ore formations through feeding electrical currents as a result of galvanic field dominance at depth.
|Sommaire||(Résumé en langage clair et simple, non publié et disponible en anglais seulement)|
The publication introduces a method for creating detailed 3D models of the Earth's subsurface to study
mineral deposits. The researchers focus on the Lalor volcanogenic massive sulfide deposit in Manitoba, Canada, known for its complex geological features.
The objective is to build highly realistic models of the Earth's underground structures and
their electrical properties, which are crucial for mineral exploration. To do this, the researchers use advanced computational techniques, such as unstructured tetrahedral meshes, to adapt to the complex shapes of geological formations.
creates two key 3D resistivity models: one for the background host rock and another for the ore deposit. These models help simulate the Earth's electrical properties for magnetotelluric (MT) surveys, a geophysical method used in mineral exploration.
The publication shows that the synthetic MT responses generated from their complex models match well with actual field data, validating the approach.
The scientific impact is significant because this method can enhance mineral exploration by
providing more accurate 3D models of ore deposits. It allows geologists and exploration companies to better understand the subsurface and locate valuable mineral resources efficiently.