Abstract

The Database of Aeolian Sedimentary Architecture (DASA) records the architecture and spatio-temporal evolution of a broad range of modern and recently active aeolian systems, and of their preserved deposits in ancient successions. DASA currently stores data on >14,000 geologic and geomorphic entities (including bounding surfaces and transition relationships) extracted from >60 case-study examples documented in the published literature. DASA stores data on a variety of aeolian and associated non-aeolian entities of multiple scales, including attributes that characterize their type, geometry, spatial relations, hierarchical relations, temporal significance, and textural and petrophysical properties; associated metadata are also stored.Database output describes (1) stratigraphic relationships between aeolian and associated fluvial, lacustrine and paralic depositional systems; (2) the geometry of aeolian architectural elements, and hierarchical and spatial relationships between them; (3) the probabilities of vertical and lateral transition from one type of deposit or landform to another; (4) the presence and nature of aeolian bounding surfaces at different scales, and their nested, hierarchical relationships; (5) aeolian lithofacies types, proportions and distributions, and (6) grain-scale textural parameters.DASA is applied to quantitatively characterize and compare modern and ancient aeolian sedimentary systems. Examples of database outputs demonstrate how DASA outputs can be tailored for numerous applications, including: (1) the development of bespoke quantitative facies models, specifically tailored for particular sets of boundary conditions; (2) the empirical assessment of how aeolian systems, and associated preserved sedimentary architectures, represent a response to allogenic and autogenic forcings; and (3) the instruction of forward stratigraphic models and 3D geocellular subsurface models. DASA is a valuable tool for the characterization of subsurface aeolian successions, such that output can help to (1) predict three-dimensional lithological heterogeneity in subsurface successions that are resource targets, (2) constrain geocellular stochastic models, and (3) facilitate borehole correlations of aeolian dune sets or associated non-aeolian elements.

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