A generalization of algebraic surface drawing
SIGGRAPH '82 Proceedings of the 9th annual conference on Computer graphics and interactive techniques
ESCIENCE '11 Proceedings of the 2011 IEEE Seventh International Conference on eScience
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Geoscience modelling plays a vital role in mapping and tracking the earth's resources. Magnetotellurics, which maps the electrical resistivity of the subsurface, is a useful and cost-effective sounding-technique for sensing over a broad scale at depth. However, due to the inherent difficulty in sensing at depth, models produced using MT have a degree of uncertainty. Geoscientists can reduce this uncertainty by producing multiple alternative models, and using multiple modelling techniques and settings, to correlate robust model features with field data responses. Population-based evolutionary search techniques are of interest to MT modelling because they offer an alternative to deterministic techniques, and are able to produce multiple models for analysis. Unfortunately, evolutionary techniques have not been successfully applied to 3D MT modelling. In this work we describe a new, more compact, representation of MT models using volumetric functions. Using this representation we successfully apply evolutionary search techniques to 3D MT modelling for both artificial and real models and show how the development of large scale features during modelling can be correlated with the model's fit to field data.