LAUSR

We have determined how stratigraphy and lithofacies control pore structures in the Mississippian limestone and chert reservoir of north-central Oklahoma. There are 17 lithofacies and 29 high-frequency cycles documented in the Mississippian interval of this study. The high-frequency cycles have thicknesses ranging from 0.3 to 30.5 m (1–100 ft) and are mainly asymmetric regressive phases. The pore characteristics, measured through digital-image analysis (DIA) of thin-sections photomicrographs ([Formula: see text]100), exhibit unique correlations with core porosity, permeability, and lithofacies within a sequence-stratigraphic framework. There are five fundamental correlations observed. First, porosity from DIA and laboratory core measurements has a strong positive relationship ([Formula: see text]). However, some values from DIA porosity yield relatively higher values, specifically in spiculitic mudstone wackestones and argillaceous spiculitic mudstone wackestones. The difference is hypothesized due to the presence of isolated nanopores that are not accessible by helium during measurement of core porosity. Second, the relationship between pore circularity and permeability is indeterminate. The indeterminate relationship is related to a complex internal pore network, intensive diagenetic alteration, an unconnected microfracture network, and isolated pores. Third, positive moderate to strong correlations ([Formula: see text]) between porosity and permeability are observed only in four lithofacies. Fourth, coarse-grained lithofacies within the uppermost depositional sequence of the Mississippian interval have a heterogeneous pore-size distribution, whereas fine-grained lithofacies tend to exhibit a homogeneous pore-size distribution. Fifth, higher reservoir quality is associated with the upper intervals of high-frequency shallowing-upward cycles. This confirms that the sequence-stratigraphic variability of lithofacies is important to predict reservoir quality and its distribution. An alternative graphical method of pore-size distribution is also developed. To be a useful “technique,” examples of the plot are demonstrated using samples in this study. The plot successfully provides simple identification of pore-size classes, quantitative percentage of pore-size class, dominant pore class, and approximate minimum and maximum pore size.