INTEGRATED RESERVOIR CHARACTERIZATION FOR ENHANCED OIL RECOVERY, TAR SPRINGS FORMATION, ILLINOIS BASIN

The Illinois basin contains many mature Mississippian aged reservoirs that are potential targets for enhanced oil recovery (EOR). In this study we integrate sedimentology, petrography, quantitative mineralogy (XRD), infrared analysis (FTIR), thermal analysis/evolved gas analysis (TGA/EGA), and scanning electron microscopy (SEM) to characterize the physical and chemical properties of the Tar Springs Formation in a producing field. Two cores comprising ~40 feet of reservoir were provided by Pioneer Oil Company for our reservoir characterization approach.

Reservoir cores were described, sampled, and analyzed on a foot-by-foot scale using sedimentology and petrography. Four distinct lithofacies serve to categorize the studied reservoir: F1 – fine- to medium-grained, horizontally-stratified sandstone with consistent porosity but large variations in permeability; F2 – very fine- to fine-grained flaser-bedded sandstone with consistent porosity and permeability; F3 – fine-grained sandstone and mudstone with little porosity and permeability; and F4 – medium-grained sandstone with calcite cement that occludes all porosity and permeability. Lithofacies F1 represents the highest quality reservoir interval but thin-section observations show millimeter-scale heterogeneity as a function of calcite cement and clay-rich horizons. XRD analyses confirm the presence of quartz and calcite but also identify illite, kaolinite, and chlorite as primary constituents in F1. SEM work has revealed pore mineralogy variations that can significantly influence flow distribution as it relates to porosity and permeability. TGA/EGA and FTIR results show large amounts of residual oil. Exposures of the Tar Springs Formation along the margins of the Illinois basin and core data from the Indiana Geological Survey have also been studied to provide a regional framework to better understand the expected variability within Mississippian aged reservoirs.

Collectively, our data sets show the importance of identifying mineral content, cement types, and clay minerals to help define flow parameters within a reservoir. We will also discuss how these integrated data sets are being used by other members of our research team to determine the optimal surfactant-polymer pairs and reservoir simulation modeling needed for EOR.