--> Mapping and Distribution of Karst Features on San Salvador Island, Bahamas Using a Morphometric Pattern Recognition Technique to Identify Depressions

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Mapping and Distribution of Karst Features on San Salvador Island, Bahamas Using a Morphometric Pattern Recognition Technique to Identify Depressions

Abstract

Karstification on isolated carbonate platforms often results in surface features that include collapsed water-table caves and pit caves, both of which can be classified as sinkholes. Such features typically exhibit a similar surface expression that fails to capture the processes responsible for their development. Water-table caves form as meter-scale touching vugs along the top of freshwater lenses, whereas pit caves develop as subvertical shafts within the vadose zone. Although recognizing these different styles of surface karst features can be challenging, understanding the type, size distribution, and geographic density can provide key insight into characterizing carbonate reservoirs whose pore system has been modified by karst processes. In order to evaluate how these surface karst features may impact our understanding of the non-matrix component of the carbonate pore system, we utilized a digital elevation model of San Salvador Island, Bahamas that was derived from a high resolution, multi-spectral LiDAR dataset. Surface depressions were discriminated following a pattern recognition technique that characterizes landforms by calculating changes in the relative height around a point of interest. This geomorphic technique, applied to surface depressions, yields computationally-derived results that were statistically compared to ground measurements on San Salvador Island, as well as other geospatial techniques that have been applied to other karst dominated terrains. Our results suggest that, when used in conjunction with hydrologic and elevation data to discriminate between terrains that host pit caves and water-table caves, our approach can be used to quantify surface depressions based on the processes responsible for their development and provide statistics on the size and geographic distribution of individual features. These results provide insight how the non-matrix component of the carbonate pore system may be distributed in carbonate reservoirs, which can have a profound impact on field development and predictions of reservoir performance.