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Abstract

Most 3D geological modelling tools were designed for the needs of the oil industry or detailed mine planning and are not suited to the variety of situations encountered in other application domains. Moreover, the usual modelling tools are not able to quantify the uncertainty of the geometric models generated. The potential field method was designed to build 3D geological models from data available in geology and mineral exploration, namely the geological map and a digital terrain model (DTM), structural data, borehole data, and interpretations of the geologist. This method considers a geological interface as a particular isosurface of a scalar field defined in the 3D space, called a potential field. The interpolation of that field, based on cokriging, provides surfaces that honour all the data. The 3D model and its parts are always consistent with the observations. New developments allow the covariance of the potential field to be identified from the structural data. This makes it possible to associate sensible cokriging standard deviations to the potential field estimates and to express the uncertainty of the geometric model. It also, for the first time, gives a statistically optimal, geologically sound way of interpolating geology, other than directly joining the dots as you do with CAD. Practical implementation issues for producing 3D geological models are presented: how to handle faults, how to honour borehole ends, how to take relationships between several interfaces into account, how to model thin beds over many kilometres, how to optimise lithological properties and how to integrate gravimetric and magnetic data. We describe all geology surfaces and volumes using implicit functions. These are then rendered onto the required sections, plans etc. The estimation of ore-body grades and tonnes, using an unbiased and optimal geostatistical technique, makes use of the stratigraphically bound 3D geology model. An application to the geological modelling of the Hamersley Iron Ore district, Australia, is briefly presented.

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/content/papers/10.3997/2214-4609-pdb.241.fitzgerald_paper1
2009-09-16
2024-04-26
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609-pdb.241.fitzgerald_paper1
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