CONSTRUCTING A 3D GEOLOGIC MAP

3D geologic mapping requires a shift in approach, from geologic field mapping to an integration of geophysical and geostatistical techniques with geologic mapping. Because almost all of the map volume is physically inaccessible, geologic features must be defined by indirect means. Regional mapping in 3D is especially difficult in areas with complex structure. From work on several 3D maps in CA and NV, we are developing a new toolset for geologic mapping in 3D that includes geophysical surveys, and mapping and geostatistical algorithms.

The surface geologic map is the primary data source, informing on rock units and sub-surface structure. In 3D, the surface geologic map must be simplified to accommodate the lack of locational and stratigraphic detail with depth. We use existing and new algorithms for automated down-dip projection, generalizing projected surface information with depth.

Geophysical modeling is particularly well-suited to defining regional structural features. We use gravity inversion methods to map the depth and extent of sedimentary basins, magnetic inversion methods to map vertical edges and folded rock units, and tomography to define geologic bodies in 3D. When the identified features are not accessible through surface outcrops, these units may be defined solely from their inversion-derived properties.

We use geostatistical methods to simulate sedimentary bodies in the subsurface, matching all available surface and well information and generating shapes whose spatial inter-relations are consistent with those observed in the surface geologic map. Such modeling produces a non-unique set of possible subsurface unit shapes.

The integrated approach to 3D mapping requires that geologists, geophysicists and modelers work closely together, with project members authoring particular map elements. Thus many map elements are models unto themselves, (e.g. an inversion model), generated using methods and algorithms either independently or weakly related to other map elements. The challenge is one of integrating these models, taking into account their respective scale, resolution, and accuracy. The result is a quantitative, visually intuitive 3D map, as in the 3D geologic map of the Hayward Fault zone (http://pubs.usgs.gov/sim/3045/).