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TitleThree-dimensional magnetotelluric numerical simulation of realistic geologic models
AuthorAnsari, S M; Schetselaar, EORCID logo; Craven, J; Farquharson, C
SourceGeophysics vol. 85, no. 5, 2020 p. 1-20,
Alt SeriesNatural Resources Canada, Contribution Series 20200478
PublisherSociety of Exploration Geophysicists
Mediapaper; on-line; digital
File formatpdf; html
NTS63J/12; 63J/13; 63K/09; 63K/10; 63K/15; 63K/16
AreaSnow Lake
Lat/Long WENS-101.0000 -99.5000 55.0000 54.5000
Subjectseconomic geology; geophysics; Science and Technology; mineral deposits; sulphide deposits; models; computer simulations; magnetotelluric data; bedrock geology; lithostratigraphy; host rocks; wireline logs; resistivity; shear zones; Lalor Deposit; Threehouse Shear Zone; Methodology; geological contacts
Illustrationslocation maps; cross-sections; 3-D models; tables; plots; schematic representations; profiles; models
Released2020 07 28
AbstractWe 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.
Summary(Plain Language Summary, not published)
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.
The study 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.

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