--> --> Quantitative Characterization of Shale Drapes within the Tidally-Influenced Fluvial Valley-Fill Deposits of the Ferron Sandstone, Utah—Implications for Subsurface Exploration

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Quantitative Characterization of Shale Drapes within the Tidally-Influenced Fluvial Valley-Fill Deposits of the Ferron Sandstone, Utah—Implications for Subsurface Exploration

Abstract

The study of outcrops is a viable tool in facies architecture and reservoir characterization studies. Combination of high resolution digital outcrop data and traditional field data creates a single visualization, integration and interpretation environment platform where critical information can be extracted. When combined with conventional field geology, the digital outcrop models offer realistic 3D geological realizations with sufficient quantities of numerical data, facilitating a robust, reproducible, and quantitative analysis. The data on the distribution and occurrence and dimensions of mudstone drapes within the fluvial deposits of Turonian Ferron Sandstone in south-central Utah were collected. The study outcrop was composed of a series of laterally and vertically accreting tidally-influenced point-bar deposits and their associated channel forms that are exposed in a series of strike- and dip-aligned exposures. Tide-influenced river deposits have been an interest for the oil industry, but not much published data are available that aims to understand the heterogeneity within the architectural element scale. Approximately, 600 m of both cliff faces have been modeled and interpreted in a 3D sequence stratigraphic framework. Shale lengths, widths, thicknesses, and frequencies were measured from 3D photorealistic digital outcrop models. Preliminary results show that the sand:shale proportions between the incised-valley-fill deposits range from 78% to 96%. Also, shales were found to be longer (mean = 7.8 m, n = 460) than wider (mean = 5.1 m, n = 150). Statistical relationships obtained through the quantitative analysis of the sand and shale realizations have a potential to reduce uncertainty related to stochastic modeling of analogous subsurface systems such as the McMurray Formation of the Athabasca oil sands of Canada or the Frio Formation of the U.S. Gulf of Mexico.