Towards a More Quantitative Ichnological Approach: Use of Thin Sections and Large Thin Slices, an Example from Book Cliffs, Utah, USA
Nicola S. Tonkin, Duncan McIlroy, and Rudi Meyer
Department of Earth Sciences, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada;
E-mail: [email protected]
Knowledge of the lateral variability of bioturbation and application of a more quantitative ichnological methodology is required to make reliable predictions of reservoir properties. While many studies of bioturbation have been carried out, most of these have aimed at understanding changes in vertical profiles and are based on semi-quantitative and qualitative approaches. Data from both vertical and lateral profiles of bioturbated outcrops from nearshore marine environments in the Book Cliffs, Utah are utilized in this study. Upper Cretaceous age Blue Gate Member of the Mancos Shale and Neslen Formation are well exposed in cliff exposures at Garley Canyon and Sagers Canyon, respectively. Development of a more quantitative ichnological methodology involves collection of detailed sedimentological and ichnological field datasets complimented with laboratory analyses of samples, including petrological analysis using standard thin sections and large thin slices. In addition, porosity and permeability are measured around trace fossils in order to determine the role that organisms have on reservoir potential of these bioturbated facies. Understanding significance and scale of the lateral trends in ichnology—alongside physical and biological parameters—allows for reliable predictions about bioturbation on an inter-well scale in a range of different facies. In addition, the development of a quantitative approach to ichnology is the first step towards creation of an objective methodology that can be duplicated generating easily comparable ichnological datasets that can be correlated at a range of spatial and geographical scales. Once established, robust methodology for quantitative ichnological assessment can then be applied to analogous core samples to enable predictive reservoir characterization of subsurface reservoirs.
AAPG Search and Discovery Article #90070 © 2007 AAPG Foundation Grants in Aid