AAPG ANNUAL CONFERENCE AND EXHIBITION
Making the Next Giant Leap in Geosciences
April 10-13, 2011, Houston, Texas, USA
A Multi-site Appraisal of Geobody Morphometric Properties Atop Ten Modern Carbonate Platforms
(1) National Coral Reef Institute, Nova Southeastern University, Dania Beach, FL.
(2) ExxonMobil Upstream Research Co., Houston, TX.
The field of morphometrics involves studying variations in the form (size, shape, complexity, orientation, thickness) of objects. The discipline is easily combined with GIS and is relevant to carbonate sedimentology for highlighting similarities or differences between sites, structural motifs, and environments of deposition. It is well established that variations in size and geometry parameters (e.g., length, width, complexity, etc.) of modern shallow-water carbonate geobodies is predictable and can be mathematically captured. Satellite and airborne remote sensing technologies have also been proven capable of mapping facies distributions in variable water depths at platform-scale. This work assembles meter-scale facies maps for ten platforms spread through the Atlantic, Pacific, and Indian Oceans. The portfolio spans examples of the dominant motifs of shallow-marine carbonate deposition, including island- and continental-attached shelves, isolated atolls, banks, and ramps. Exceptional control on the topography and distribution of geobodies for these sites is facilitated through fused analysis of high-resolution satellite imagery and airborne bathymetric LiDAR. To enable comparison both within and between sites, the facies mosaic for each platform is partitioned on the basis of three environments of depositions (EODs) that represent the gradient in energy from the outer margin to the sheltered interior. Our results constrain the diversity in morphometric behavior within different EODs and between platform-types and reaffirm this to be a powerful and appropriate strategy to parameterize geobody distributions in the Modern. By extension, it is also a method to extrapolate modern-data for interpretation of ancient examples in seismic and outcrop.