Characterization Of Karst Features Using Electromagnetics And Microgravity: A Strategic Approach

The flat-lying limestones of western Texas are naturally jointed with preferential<br>dissolution occurring along joints and bedding planes. This area has some of the<br>largest air-filled open caves in West Texas and large paleokarst collapse features<br>have been identified throughout a wide region. Aerial photos indicate the<br>presence of extensive joints, lineaments and paleokarst. Site characterization to<br>detect and map such subsurface features using borings alone is inadequate to<br>produce a reasonable level of spatial sampling. This paper addresses the<br>application of surface geophysical techniques, and an assessment of the spatial<br>sampling and instrument sensitivities necessary to define the karst features of<br>interest in this geologic setting.<br>Electromagnetic measurements using a Geonics EM34 were selected because<br>the measurements provide an excellent means of locating dissolution-enlarged<br>joints. Microgravity was selected because it is the only surface geophysical<br>method that will provide the location of karst feature regardless of their shape or<br>fill material as long as there is a sufficient density contrast. While both methods<br>have limitations, as do all methods of site characterization, the combination of<br>gravity and EM measurements are complementary in this application.<br>A known cave system was used to establish the spatial sampling criteria for the<br>detection and characterization of such features. Field tests were then run over<br>two known karst sites; a paleokarst collapse; and a localized doline to provide<br>anomaly signatures in this geologic setting.<br>It is clear that the EM and the gravity techniques are appropriate for detecting and<br>characterizing karst features in this geologic setting. However, one of the key<br>issues in planning and carrying out a geophysical survey, is developing a spatial<br>sampling criteria. This criteria should be based upon an understanding of project<br>objectives, a conceptual geologic model of site conditions and, if possible,<br>existing data from the area of interest.