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Abstract:

Geologically constrained inversion of gravity and magnetic field data of the Victoria property (located in Sudbury, Canada) was undertaken in order to update the present three dimensional (3D) geological model. The initial and reference model (used to constrain the inversion) was constructed based on geological information from approximately 965 drillholes. As well, down-hole density and magnetic susceptibility measurements of seven holes were statistically analyzed to derive lower and upper bounds on the physical properties of the lithological units in the reference model. A neural network was trained to predict lithological units from the physical properties measured in seven holes. Then, the trained network was applied on the 3D distribution of physical properties derived from the inversion models to produce a 3D litho-prediction model. Some of the features evident in the lithological model are remnants of the constraints, where the data did not demand a significant change in the model from the initial constraining model. However other changes from the initial model are evident, for example: a larger body was predicted for quartz diorite which may be related to the prospective offset dykes; a new zone was predicted as sulfide which may represent potential mineralization; and a geophysical subcategory of metabasalt was identified with high magnetic susceptibility and high density. The litho-prediction model agrees with the geological expectation for the 3D structure at Victoria, and is consistent with the geophysical data, which results in a more holistic understanding of the subsurface lithology. 2016 SEG.

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Compilation and indexing terms, Copyright 2018 Elsevier Inc.<br/>20172003662434