QUANTIFYING AND LINKING DEPOSITIONAL TEXTURES OF PERMIAN BRUSHY CANYON FORMATION SANDSTONES WITH PETROGRAPHIC STATISTICS AND FLUME EXPERIMENTS

This study will relate changes in sorting, grain size, and matrix composition to velocity structure and the role of carbonate matrix on turbulence suppression. Changes in matrix concentration within experimental flows will be compared with the mapped outcrop distribution of these textural attributes.

This investigation is part of an integrated outcrop and subsurface study encompassing the 255 km² deep-water outcrop within the 33,500 km² Permian Delaware Basin. The 50 km² study area occupies a basinal position up to 40 km from the shelf feeder. Feldspar, silt and carbonate content nearly double within strata containing few channels, and dominated by sheet and lobeform sedimentary bodies.

Framework mineralogy, matrix content, grain size, sorting, and porosity quantified from analysis of 80 thin sections correlates silty sand to a silt content >9% and coarse-skewed grain size distribution. Carbonate matrix >15% corresponds to this increased silt content. Cathodoluminescence fails to distinguish detrital from authigenic carbonate. Therefore, flume experiments have been designed to establish whether enhanced silt content is related to suppression of turbulence by micrite. Experimentation will consist of a series of flows with variable carbonate proportions, measuring flow turbulence with sonic velocity probes. Spatial evolution of flows with transitional turbulent properties over the critical range of carbonate proportions will be measured. Sampling the resultant deposits will document textural attributes to be compared with petrographic and outcrop datasets.

Comparison of experimental, petrographic and outcrop data links hydrodynamic processes to the deposits they construct. Petrographic analysis provides quantitative textural data linked to mapped outcrop distributions providing local spatial context. Integration with regional data provides a basinal context. This approach links fundamental physical processes to their temporal and spatial distribution with the goal to produce a global predictive model that describes and reproduces these subaqueous flow behaviors.