GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 355-6
Presentation Time: 9:00 AM-6:30 PM

BACK TO THE FUTURE: USING A GIS TO POPULATE 3D GEOCELLULAR GEOLOGIC MODELS


SWEETKIND, D.S., U.S Geological Survey, Denver Federal Center, Mail Stop 980, Denver, CO 80225, LANGENHEIM, V.E., U.S. Geological Survey, 345 Middlefield Road, Menlo Park, CA 94025 and HANSON, R.T., U.S. Geological Survey, 4165 Spruance Road, Suite 200, San Diego, CA 92101, dsweetkind@usgs.gov

Three-dimensional (3D) volumetric geologic models are digital representations of a conceptual geologic model, serve as a digital repository for geologic datasets, and are digital input to many applications. However, 3D geologic models are labor intensive to build, requiring expensive software and skilled personnel, and can be difficult to distribute to cooperators and stakeholders. Using the 2.5D nature of a GIS (x and y dimension plus multiple z attribute values) can make creation of a volumetric geologic model more accessible to project geologists and stakeholders alike. The geometry of the geologic system is defined by three framework elements: faults, the elevation of the top of each geo-unit, and boundary lines depicting the subsurface extent of geo-unit. Gridded surfaces representing the geo-unit tops are created from a geologic map, a DEM, and other user-defined data derived from boreholes or geophysical methods. Deterministic 3D geological models are created from geologic and geophysical datasets using a GIS to populate XY cells that form the basis for a geocellular model, a 3D array of orthogonal, vertically stacked cells. Model cells are populated manually in the GIS by mapping geo-unit surfaces to an x,y array of nodes representing the centroids of cells in the geocellular model. XYZ data are exported to 3D visualization and modeling software to compute a cell-based solid model where the 3D volume is populated by regular rectangular volume elements that completely define each geo-unit at all points in space. Three examples of the approach are given from different geologic environments. In the Petaluma basin (northern CA), strike-slip faulting has juxtaposed regions of different stratigraphic stacking order, which can be defined within the GIS. In the lower Rio Grande (New Mexico), offset on numerous rift-related normal faults was challenging to model in the 3D environment, whereas manually editing grids in a GIS was a workable solution. In Salinas Valley (central CA coast), onshore and offshore geologic data were managed and merged in a GIS prior to model construction. The GIS-based approach to geocellular modeling allows for easy export to other users using spatial data platforms and also allows for direct comparison with other data sets, such as aeromagnetic data, that do not lend themselves to 3D portrayal.