UBC Theses and Dissertations
3D inversion of natural source electromagnetic data Holtham, Elliot Mark
Z-Axis Tipper Electromagnetic (ZTEM) data are airborne electromagnetic data which relate the vertical magnetic field measured by a helicopter to the orthogonal horizontal magnetic field measured at a ground-based reference station. The 30-720 Hz frequency range makes it possible to image structures at a kilometer depth for many geologic settings. This depth of penetration, coupled with rapid spatial acquisition of an airborne system, means that ZTEM data can be used to map large-scale structures that are difficult to survey with ground-based surveys. I present some fundamentals of the ZTEM signatures and then develop a Gauss-Newton inversion algorithm which I test on a synthetic and a field example from the Mt. Milligan porphyry deposit. For large airborne surveys, the high number of cells required to discretize the area at a reasonable resolution can make the computational cost of inverting the dataset prohibitively expensive. I present an iterative methodology that can be used to invert large natural source surveys by using a combination of coarse and fine meshes and a domain decomposition that splits the full model into smaller subproblems which can be run in parallel. After each round of tiled inversions, the tiles are merged together to form an updated model. I demonstrate this procedure first by inverting the data computed from a large synthetic model, before working with a survey over the Pebble porphyry deposit. The inverted ZTEM results are consistent with other electromagnetic datasets. Since a 1D conductivity structure produces no vertical magnetic fields, the technique cannot recover information about a purely 1D model. In order to increase sensitivity to the background structure, and greatly improve the depth of investigation over just ZTEM data, magnetotelluric (MT) and ZTEM data can both be collected. The combination of sparse MT data, with the economical and rapid spatial acquisition of airborne ZTEM data, creates a cost effective exploration technique that can map structures at depths. I develop an algorithm to jointly invert ZTEM and MT data, and apply this technique to a synthetic model and a field example from the Reese River geothermal property.
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Attribution-NonCommercial-NoDerivatives 4.0 International