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Integration of Radar-Derived Dems with Engineering and Borehole Data Sets to Detect Subtle Structural Features

Dacre, Cynthia 1; Berry, John 2; Wolhart, Steve 3; Brunke, Suzanne 4; Way, Doug 1
1 MDA Federal. Inc., Rockville, MD.
2 John Berry Associates, Austin, TX.
3 Pinnacle Technologies, Inc., Houston, TX.
4 MDA Geospatial Services, Richmond, BC, Canada.

Geologists have traditionally used terrain indicators (e.g. valleys, stream segment alignments) to decide the location of faults and fractures inferred during surface geologic mapping using fieldwork or stereo aerial photographs. Similarly, geologists mapping subsurface structures from borehole data have generally had to interpolate between sparse data points (boreholes). In more recent decades, synthetic aperture radar (SAR) derived or Light Detection and Ranging (LIDAR) based Digital Elevation Models (DEMs) have become available on a variety of scales. The application of a variety of image-processing techniques, such as filters (e.g. edge enhancement) or statistical packages allow the recognition of much more subtle negative topographic features in these 'dense' (or continuous) topographic data sets than was previously possible. In addition, the use of GIS software allows the fitting of surfaces to geological data sets such as formation tops or tiltmeter data, as well as to SAR-derived DEMs. This allows the measurement of offsets and the rapid iteration of interpretative hypotheses. Results of these surface techniques can be both verified and extended into the subsurface by the integration of borehole engineering data. Exploration and development applications range from regional (using SRTM or NED data) to local (using Interferometry SAR - InSAR) to extremely local (using LIDAR). We demonstrate the power of this approach using examples of structures investigated in central Texas and elsewhere.


AAPG Search and Discovery Article #90090©2009 AAPG Annual Convention and Exhibition, Denver, Colorado, June 7-10, 2009